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Published by Nicolas at March 21st, 2024 , Revised On March 12, 2024

The Ultimate Guide To Research Methodology

Research methodology is a crucial aspect of any investigative process, serving as the blueprint for the entire research journey. If you are stuck in the methodology section of your research paper , then this blog will guide you on what is a research methodology, its types and how to successfully conduct one. 

Table of Contents

What Is Research Methodology?

Research methodology can be defined as the systematic framework that guides researchers in designing, conducting, and analyzing their investigations. It encompasses a structured set of processes, techniques, and tools employed to gather and interpret data, ensuring the reliability and validity of the research findings. 

Research methodology is not confined to a singular approach; rather, it encapsulates a diverse range of methods tailored to the specific requirements of the research objectives.

Here is why Research methodology is important in academic and professional settings.

Facilitating Rigorous Inquiry

Research methodology forms the backbone of rigorous inquiry. It provides a structured approach that aids researchers in formulating precise thesis statements , selecting appropriate methodologies, and executing systematic investigations. This, in turn, enhances the quality and credibility of the research outcomes.

Ensuring Reproducibility And Reliability

In both academic and professional contexts, the ability to reproduce research outcomes is paramount. A well-defined research methodology establishes clear procedures, making it possible for others to replicate the study. This not only validates the findings but also contributes to the cumulative nature of knowledge.

Guiding Decision-Making Processes

In professional settings, decisions often hinge on reliable data and insights. Research methodology equips professionals with the tools to gather pertinent information, analyze it rigorously, and derive meaningful conclusions.

This informed decision-making is instrumental in achieving organizational goals and staying ahead in competitive environments.

Contributing To Academic Excellence

For academic researchers, adherence to robust research methodology is a hallmark of excellence. Institutions value research that adheres to high standards of methodology, fostering a culture of academic rigour and intellectual integrity. Furthermore, it prepares students with critical skills applicable beyond academia.

Enhancing Problem-Solving Abilities

Research methodology instills a problem-solving mindset by encouraging researchers to approach challenges systematically. It equips individuals with the skills to dissect complex issues, formulate hypotheses , and devise effective strategies for investigation.

Understanding Research Methodology

In the pursuit of knowledge and discovery, understanding the fundamentals of research methodology is paramount. 

Basics Of Research

Research, in its essence, is a systematic and organized process of inquiry aimed at expanding our understanding of a particular subject or phenomenon. It involves the exploration of existing knowledge, the formulation of hypotheses, and the collection and analysis of data to draw meaningful conclusions. 

Research is a dynamic and iterative process that contributes to the continuous evolution of knowledge in various disciplines.

Types of Research

Research takes on various forms, each tailored to the nature of the inquiry. Broadly classified, research can be categorized into two main types:

• Quantitative Research: This type involves the collection and analysis of numerical data to identify patterns, relationships, and statistical significance. It is particularly useful for testing hypotheses and making predictions.
• Qualitative Research: Qualitative research focuses on understanding the depth and details of a phenomenon through non-numerical data. It often involves methods such as interviews, focus groups, and content analysis, providing rich insights into complex issues.

Components Of Research Methodology

To conduct effective research, one must go through the different components of research methodology. These components form the scaffolding that supports the entire research process, ensuring its coherence and validity.

Research Design

Research design serves as the blueprint for the entire research project. It outlines the overall structure and strategy for conducting the study. The three primary types of research design are:

• Exploratory Research: Aimed at gaining insights and familiarity with the topic, often used in the early stages of research.
• Descriptive Research: Involves portraying an accurate profile of a situation or phenomenon, answering the ‘what,’ ‘who,’ ‘where,’ and ‘when’ questions.
• Explanatory Research: Seeks to identify the causes and effects of a phenomenon, explaining the ‘why’ and ‘how.’

Data Collection Methods

Choosing the right data collection methods is crucial for obtaining reliable and relevant information. Common methods include:

• Surveys and Questionnaires: Employed to gather information from a large number of respondents through standardized questions.
• Interviews: In-depth conversations with participants, offering qualitative insights.
• Observation: Systematic watching and recording of behaviour, events, or processes in their natural setting.

Data Analysis Techniques

Once data is collected, analysis becomes imperative to derive meaningful conclusions. Different methodologies exist for quantitative and qualitative data:

• Quantitative Data Analysis: Involves statistical techniques such as descriptive statistics, inferential statistics, and regression analysis to interpret numerical data.
• Qualitative Data Analysis: Methods like content analysis, thematic analysis, and grounded theory are employed to extract patterns, themes, and meanings from non-numerical data.

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Choosing a Research Method

Selecting an appropriate research method is a critical decision in the research process. It determines the approach, tools, and techniques that will be used to answer the research questions. 

Quantitative Research Methods

Quantitative research involves the collection and analysis of numerical data, providing a structured and objective approach to understanding and explaining phenomena.

Experimental Research

Experimental research involves manipulating variables to observe the effect on another variable under controlled conditions. It aims to establish cause-and-effect relationships.

Key Characteristics:

• Controlled Environment: Experiments are conducted in a controlled setting to minimize external influences.
• Random Assignment: Participants are randomly assigned to different experimental conditions.
• Quantitative Data: Data collected is numerical, allowing for statistical analysis.

Applications: Commonly used in scientific studies and psychology to test hypotheses and identify causal relationships.

Survey Research

Survey research gathers information from a sample of individuals through standardized questionnaires or interviews. It aims to collect data on opinions, attitudes, and behaviours.

• Structured Instruments: Surveys use structured instruments, such as questionnaires, to collect data.
• Large Sample Size: Surveys often target a large and diverse group of participants.
• Quantitative Data Analysis: Responses are quantified for statistical analysis.

Applications: Widely employed in social sciences, marketing, and public opinion research to understand trends and preferences.

Descriptive Research

Descriptive research seeks to portray an accurate profile of a situation or phenomenon. It focuses on answering the ‘what,’ ‘who,’ ‘where,’ and ‘when’ questions.

• Observation and Data Collection: This involves observing and documenting without manipulating variables.
• Objective Description: Aim to provide an unbiased and factual account of the subject.
• Quantitative or Qualitative Data: T his can include both types of data, depending on the research focus.

Applications: Useful in situations where researchers want to understand and describe a phenomenon without altering it, common in social sciences and education.

Qualitative Research Methods

Qualitative research emphasizes exploring and understanding the depth and complexity of phenomena through non-numerical data.

A case study is an in-depth exploration of a particular person, group, event, or situation. It involves detailed, context-rich analysis.

• Rich Data Collection: Uses various data sources, such as interviews, observations, and documents.
• Contextual Understanding: Aims to understand the context and unique characteristics of the case.
• Holistic Approach: Examines the case in its entirety.

Applications: Common in social sciences, psychology, and business to investigate complex and specific instances.

Ethnography

Ethnography involves immersing the researcher in the culture or community being studied to gain a deep understanding of their behaviours, beliefs, and practices.

• Participant Observation: Researchers actively participate in the community or setting.
• Holistic Perspective: Focuses on the interconnectedness of cultural elements.
• Qualitative Data: In-depth narratives and descriptions are central to ethnographic studies.

Applications: Widely used in anthropology, sociology, and cultural studies to explore and document cultural practices.

Grounded Theory

Grounded theory aims to develop theories grounded in the data itself. It involves systematic data collection and analysis to construct theories from the ground up.

• Constant Comparison: Data is continually compared and analyzed during the research process.
• Inductive Reasoning: Theories emerge from the data rather than being imposed on it.
• Iterative Process: The research design evolves as the study progresses.

Applications: Commonly applied in sociology, nursing, and management studies to generate theories from empirical data.

Research design is the structural framework that outlines the systematic process and plan for conducting a study. It serves as the blueprint, guiding researchers on how to collect, analyze, and interpret data.

Exploratory, Descriptive, And Explanatory Designs

Exploratory design.

Exploratory research design is employed when a researcher aims to explore a relatively unknown subject or gain insights into a complex phenomenon.

• Flexibility: Allows for flexibility in data collection and analysis.
• Open-Ended Questions: Uses open-ended questions to gather a broad range of information.
• Preliminary Nature: Often used in the initial stages of research to formulate hypotheses.

Applications: Valuable in the early stages of investigation, especially when the researcher seeks a deeper understanding of a subject before formalizing research questions.

Descriptive Design

Descriptive research design focuses on portraying an accurate profile of a situation, group, or phenomenon.

• Structured Data Collection: Involves systematic and structured data collection methods.
• Objective Presentation: Aims to provide an unbiased and factual account of the subject.
• Quantitative or Qualitative Data: Can incorporate both types of data, depending on the research objectives.

Applications: Widely used in social sciences, marketing, and educational research to provide detailed and objective descriptions.

Explanatory Design

Explanatory research design aims to identify the causes and effects of a phenomenon, explaining the ‘why’ and ‘how’ behind observed relationships.

• Causal Relationships: Seeks to establish causal relationships between variables.
• Controlled Variables : Often involves controlling certain variables to isolate causal factors.
• Quantitative Analysis: Primarily relies on quantitative data analysis techniques.

Applications: Commonly employed in scientific studies and social sciences to delve into the underlying reasons behind observed patterns.

Cross-Sectional Vs. Longitudinal Designs

Cross-sectional design.

Cross-sectional designs collect data from participants at a single point in time.

• Snapshot View: Provides a snapshot of a population at a specific moment.
• Efficiency: More efficient in terms of time and resources.
• Limited Temporal Insights: Offers limited insights into changes over time.

Applications: Suitable for studying characteristics or behaviours that are stable or not expected to change rapidly.

Longitudinal Design

Longitudinal designs involve the collection of data from the same participants over an extended period.

• Temporal Sequence: Allows for the examination of changes over time.
• Causality Assessment: Facilitates the assessment of cause-and-effect relationships.
• Resource-Intensive: Requires more time and resources compared to cross-sectional designs.

Applications: Ideal for studying developmental processes, trends, or the impact of interventions over time.

Experimental Vs Non-experimental Designs

Experimental design.

Experimental designs involve manipulating variables under controlled conditions to observe the effect on another variable.

• Causality Inference: Enables the inference of cause-and-effect relationships.
• Quantitative Data: Primarily involves the collection and analysis of numerical data.

Applications: Commonly used in scientific studies, psychology, and medical research to establish causal relationships.

Non-Experimental Design

Non-experimental designs observe and describe phenomena without manipulating variables.

• Natural Settings: Data is often collected in natural settings without intervention.
• Descriptive or Correlational: Focuses on describing relationships or correlations between variables.
• Quantitative or Qualitative Data: This can involve either type of data, depending on the research approach.

Applications: Suitable for studying complex phenomena in real-world settings where manipulation may not be ethical or feasible.

Effective data collection is fundamental to the success of any research endeavour. 

Designing Effective Surveys

Objective Design:

• Clearly define the research objectives to guide the survey design.
• Craft questions that align with the study’s goals and avoid ambiguity.

Structured Format:

• Use a structured format with standardized questions for consistency.
• Include a mix of closed-ended and open-ended questions for detailed insights.

Pilot Testing:

• Conduct pilot tests to identify and rectify potential issues with survey design.
• Ensure clarity, relevance, and appropriateness of questions.

Sampling Strategy:

• Develop a robust sampling strategy to ensure a representative participant group.
• Consider random sampling or stratified sampling based on the research goals.

Conducting Interviews

Establishing Rapport:

• Build rapport with participants to create a comfortable and open environment.
• Clearly communicate the purpose of the interview and the value of participants’ input.

Open-Ended Questions:

• Frame open-ended questions to encourage detailed responses.
• Allow participants to express their thoughts and perspectives freely.

Active Listening:

• Practice active listening to understand areas and gather rich data.
• Avoid interrupting and maintain a non-judgmental stance during the interview.

Ethical Considerations:

• Obtain informed consent and assure participants of confidentiality.
• Be transparent about the study’s purpose and potential implications.

Observation

1. participant observation.

Immersive Participation:

• Actively immerse yourself in the setting or group being observed.
• Develop a deep understanding of behaviours, interactions, and context.

Field Notes:

• Maintain detailed and reflective field notes during observations.
• Document observed patterns, unexpected events, and participant reactions.

Ethical Awareness:

• Be conscious of ethical considerations, ensuring respect for participants.
• Balance the role of observer and participant to minimize bias.

2. Non-participant Observation

Objective Observation:

• Maintain a more detached and objective stance during non-participant observation.
• Focus on recording behaviours, events, and patterns without direct involvement.

Data Reliability:

• Enhance the reliability of data by reducing observer bias.
• Develop clear observation protocols and guidelines.

Contextual Understanding:

• Strive for a thorough understanding of the observed context.
• Consider combining non-participant observation with other methods for triangulation.

Archival Research

1. using existing data.

Identifying Relevant Archives:

• Locate and access archives relevant to the research topic.
• Collaborate with institutions or repositories holding valuable data.

Data Verification:

• Verify the accuracy and reliability of archived data.
• Cross-reference with other sources to ensure data integrity.

Ethical Use:

• Adhere to ethical guidelines when using existing data.
• Respect copyright and intellectual property rights.

2. Challenges and Considerations

Incomplete or Inaccurate Archives:

• Address the possibility of incomplete or inaccurate archival records.
• Acknowledge limitations and uncertainties in the data.

Temporal Bias:

• Recognize potential temporal biases in archived data.
• Consider the historical context and changes that may impact interpretation.

Access Limitations:

• Address potential limitations in accessing certain archives.
• Seek alternative sources or collaborate with institutions to overcome barriers.

Common Challenges in Research Methodology

Conducting research is a complex and dynamic process, often accompanied by a myriad of challenges. Addressing these challenges is crucial to ensure the reliability and validity of research findings.

Sampling Issues

Sampling bias:.

• The presence of sampling bias can lead to an unrepresentative sample, affecting the generalizability of findings.
• Employ random sampling methods and ensure the inclusion of diverse participants to reduce bias.

Sample Size Determination:

• Determining an appropriate sample size is a delicate balance. Too small a sample may lack statistical power, while an excessively large sample may strain resources.
• Conduct a power analysis to determine the optimal sample size based on the research objectives and expected effect size.

Data Quality And Validity

Measurement error:.

• Inaccuracies in measurement tools or data collection methods can introduce measurement errors, impacting the validity of results.
• Pilot test instruments, calibrate equipment, and use standardized measures to enhance the reliability of data.

Construct Validity:

• Ensuring that the chosen measures accurately capture the intended constructs is a persistent challenge.
• Use established measurement instruments and employ multiple measures to assess the same construct for triangulation.

Time And Resource Constraints

Timeline pressures:.

• Limited timeframes can compromise the depth and thoroughness of the research process.
• Develop a realistic timeline, prioritize tasks, and communicate expectations with stakeholders to manage time constraints effectively.

Resource Availability:

• Inadequate resources, whether financial or human, can impede the execution of research activities.
• Seek external funding, collaborate with other researchers, and explore alternative methods that require fewer resources.

Managing Bias in Research

Selection bias:.

• Selecting participants in a way that systematically skews the sample can introduce selection bias.
• Employ randomization techniques, use stratified sampling, and transparently report participant recruitment methods.

Confirmation Bias:

• Researchers may unintentionally favour information that confirms their preconceived beliefs or hypotheses.
• Adopt a systematic and open-minded approach, use blinded study designs, and engage in peer review to mitigate confirmation bias.

Tips On How To Write A Research Methodology

Conducting successful research relies not only on the application of sound methodologies but also on strategic planning and effective collaboration. Here are some tips to enhance the success of your research methodology:

Tip 1. Clear Research Objectives

Well-defined research objectives guide the entire research process. Clearly articulate the purpose of your study, outlining specific research questions or hypotheses.

Tip 2. Comprehensive Literature Review

A thorough literature review provides a foundation for understanding existing knowledge and identifying gaps. Invest time in reviewing relevant literature to inform your research design and methodology.

Tip 3. Detailed Research Plan

A detailed plan serves as a roadmap, ensuring all aspects of the research are systematically addressed. Develop a detailed research plan outlining timelines, milestones, and tasks.

Tip 4. Ethical Considerations

Ethical practices are fundamental to maintaining the integrity of research. Address ethical considerations early, obtain necessary approvals, and ensure participant rights are safeguarded.

Tip 5. Stay Updated On Methodologies

Research methodologies evolve, and staying updated is essential for employing the most effective techniques. Engage in continuous learning by attending workshops, conferences, and reading recent publications.

Tip 6. Adaptability In Methods

Unforeseen challenges may arise during research, necessitating adaptability in methods. Be flexible and willing to modify your approach when needed, ensuring the integrity of the study.

Tip 7. Iterative Approach

Research is often an iterative process, and refining methods based on ongoing findings enhance the study’s robustness. Regularly review and refine your research design and methods as the study progresses.

Frequently Asked Questions

What is the research methodology.

Research methodology is the systematic process of planning, executing, and evaluating scientific investigation. It encompasses the techniques, tools, and procedures used to collect, analyze, and interpret data, ensuring the reliability and validity of research findings.

What are the methodologies in research?

Research methodologies include qualitative and quantitative approaches. Qualitative methods involve in-depth exploration of non-numerical data, while quantitative methods use statistical analysis to examine numerical data. Mixed methods combine both approaches for a comprehensive understanding of research questions.

How to write research methodology?

To write a research methodology, clearly outline the study’s design, data collection, and analysis procedures. Specify research tools, participants, and sampling methods. Justify choices and discuss limitations. Ensure clarity, coherence, and alignment with research objectives for a robust methodology section.

How to write the methodology section of a research paper?

In the methodology section of a research paper, describe the study’s design, data collection, and analysis methods. Detail procedures, tools, participants, and sampling. Justify choices, address ethical considerations, and explain how the methodology aligns with research objectives, ensuring clarity and rigour.

What is mixed research methodology?

Mixed research methodology combines both qualitative and quantitative research approaches within a single study. This approach aims to enhance the details and depth of research findings by providing a more comprehensive understanding of the research problem or question.

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• What Is a Research Methodology? | Steps & Tips

What Is a Research Methodology? | Steps & Tips

Published on 25 February 2019 by Shona McCombes . Revised on 10 October 2022.

Your research methodology discusses and explains the data collection and analysis methods you used in your research. A key part of your thesis, dissertation, or research paper, the methodology chapter explains what you did and how you did it, allowing readers to evaluate the reliability and validity of your research.

It should include:

• The type of research you conducted
• How you collected and analysed your data
• Any tools or materials you used in the research
• Why you chose these methods
• Your methodology section should generally be written in the past tense .
• Academic style guides in your field may provide detailed guidelines on what to include for different types of studies.
• Your citation style might provide guidelines for your methodology section (e.g., an APA Style methods section ).

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Table of contents

How to write a research methodology, why is a methods section important, step 1: explain your methodological approach, step 2: describe your data collection methods, step 3: describe your analysis method, step 4: evaluate and justify the methodological choices you made, tips for writing a strong methodology chapter, frequently asked questions about methodology.

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Your methods section is your opportunity to share how you conducted your research and why you chose the methods you chose. It’s also the place to show that your research was rigorously conducted and can be replicated .

It gives your research legitimacy and situates it within your field, and also gives your readers a place to refer to if they have any questions or critiques in other sections.

You can start by introducing your overall approach to your research. You have two options here.

Option 1: Start with your “what”

What research problem or question did you investigate?

• Aim to describe the characteristics of something?
• Explore an under-researched topic?
• Establish a causal relationship?

And what type of data did you need to achieve this aim?

• Quantitative data , qualitative data , or a mix of both?
• Primary data collected yourself, or secondary data collected by someone else?
• Experimental data gathered by controlling and manipulating variables, or descriptive data gathered via observations?

Option 2: Start with your “why”

Depending on your discipline, you can also start with a discussion of the rationale and assumptions underpinning your methodology. In other words, why did you choose these methods for your study?

• Why is this the best way to answer your research question?
• Is this a standard methodology in your field, or does it require justification?
• Were there any ethical considerations involved in your choices?
• What are the criteria for validity and reliability in this type of research ?

Once you have introduced your reader to your methodological approach, you should share full details about your data collection methods .

Quantitative methods

In order to be considered generalisable, you should describe quantitative research methods in enough detail for another researcher to replicate your study.

Here, explain how you operationalised your concepts and measured your variables. Discuss your sampling method or inclusion/exclusion criteria, as well as any tools, procedures, and materials you used to gather your data.

Surveys Describe where, when, and how the survey was conducted.

• How did you design the questionnaire?
• What form did your questions take (e.g., multiple choice, Likert scale )?
• Were your surveys conducted in-person or virtually?
• What sampling method did you use to select participants?
• What was your sample size and response rate?

Experiments Share full details of the tools, techniques, and procedures you used to conduct your experiment.

• How did you design the experiment ?
• How did you recruit participants?
• How did you manipulate and measure the variables ?
• What tools did you use?

Existing data Explain how you gathered and selected the material (such as datasets or archival data) that you used in your analysis.

• Where did you source the material?
• How was the data originally produced?
• What criteria did you use to select material (e.g., date range)?

The survey consisted of 5 multiple-choice questions and 10 questions measured on a 7-point Likert scale.

The goal was to collect survey responses from 350 customers visiting the fitness apparel company’s brick-and-mortar location in Boston on 4–8 July 2022, between 11:00 and 15:00.

Here, a customer was defined as a person who had purchased a product from the company on the day they took the survey. Participants were given 5 minutes to fill in the survey anonymously. In total, 408 customers responded, but not all surveys were fully completed. Due to this, 371 survey results were included in the analysis.

Qualitative methods

In qualitative research , methods are often more flexible and subjective. For this reason, it’s crucial to robustly explain the methodology choices you made.

Be sure to discuss the criteria you used to select your data, the context in which your research was conducted, and the role you played in collecting your data (e.g., were you an active participant, or a passive observer?)

Interviews or focus groups Describe where, when, and how the interviews were conducted.

• How did you find and select participants?
• How many participants took part?
• What form did the interviews take ( structured , semi-structured , or unstructured )?
• How long were the interviews?
• How were they recorded?

Participant observation Describe where, when, and how you conducted the observation or ethnography .

• What group or community did you observe? How long did you spend there?
• How did you gain access to this group? What role did you play in the community?
• How long did you spend conducting the research? Where was it located?
• How did you record your data (e.g., audiovisual recordings, note-taking)?

Existing data Explain how you selected case study materials for your analysis.

• What type of materials did you analyse?
• How did you select them?

In order to gain better insight into possibilities for future improvement of the fitness shop’s product range, semi-structured interviews were conducted with 8 returning customers.

Here, a returning customer was defined as someone who usually bought products at least twice a week from the store.

Surveys were used to select participants. Interviews were conducted in a small office next to the cash register and lasted approximately 20 minutes each. Answers were recorded by note-taking, and seven interviews were also filmed with consent. One interviewee preferred not to be filmed.

Mixed methods

Mixed methods research combines quantitative and qualitative approaches. If a standalone quantitative or qualitative study is insufficient to answer your research question, mixed methods may be a good fit for you.

Mixed methods are less common than standalone analyses, largely because they require a great deal of effort to pull off successfully. If you choose to pursue mixed methods, it’s especially important to robustly justify your methods here.

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Next, you should indicate how you processed and analysed your data. Avoid going into too much detail: you should not start introducing or discussing any of your results at this stage.

In quantitative research , your analysis will be based on numbers. In your methods section, you can include:

• How you prepared the data before analysing it (e.g., checking for missing data , removing outliers , transforming variables)
• Which software you used (e.g., SPSS, Stata or R)
• Which statistical tests you used (e.g., two-tailed t test , simple linear regression )

In qualitative research, your analysis will be based on language, images, and observations (often involving some form of textual analysis ).

Specific methods might include:

• Content analysis : Categorising and discussing the meaning of words, phrases and sentences
• Thematic analysis : Coding and closely examining the data to identify broad themes and patterns
• Discourse analysis : Studying communication and meaning in relation to their social context

Mixed methods combine the above two research methods, integrating both qualitative and quantitative approaches into one coherent analytical process.

Above all, your methodology section should clearly make the case for why you chose the methods you did. This is especially true if you did not take the most standard approach to your topic. In this case, discuss why other methods were not suitable for your objectives, and show how this approach contributes new knowledge or understanding.

In any case, it should be overwhelmingly clear to your reader that you set yourself up for success in terms of your methodology’s design. Show how your methods should lead to results that are valid and reliable, while leaving the analysis of the meaning, importance, and relevance of your results for your discussion section .

• Quantitative: Lab-based experiments cannot always accurately simulate real-life situations and behaviours, but they are effective for testing causal relationships between variables .
• Qualitative: Unstructured interviews usually produce results that cannot be generalised beyond the sample group , but they provide a more in-depth understanding of participants’ perceptions, motivations, and emotions.
• Mixed methods: Despite issues systematically comparing differing types of data, a solely quantitative study would not sufficiently incorporate the lived experience of each participant, while a solely qualitative study would be insufficiently generalisable.

Remember that your aim is not just to describe your methods, but to show how and why you applied them. Again, it’s critical to demonstrate that your research was rigorously conducted and can be replicated.

1. Focus on your objectives and research questions

The methodology section should clearly show why your methods suit your objectives  and convince the reader that you chose the best possible approach to answering your problem statement and research questions .

2. Cite relevant sources

Your methodology can be strengthened by referencing existing research in your field. This can help you to:

• Show that you followed established practice for your type of research
• Discuss how you decided on your approach by evaluating existing research
• Present a novel methodological approach to address a gap in the literature

3. Write for your audience

Consider how much information you need to give, and avoid getting too lengthy. If you are using methods that are standard for your discipline, you probably don’t need to give a lot of background or justification.

Regardless, your methodology should be a clear, well-structured text that makes an argument for your approach, not just a list of technical details and procedures.

Methodology refers to the overarching strategy and rationale of your research. Developing your methodology involves studying the research methods used in your field and the theories or principles that underpin them, in order to choose the approach that best matches your objectives.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. interviews, experiments , surveys , statistical tests ).

In a dissertation or scientific paper, the methodology chapter or methods section comes after the introduction and before the results , discussion and conclusion .

Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

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What is research methodology?

The basics of research methodology

Why do you need a research methodology, what needs to be included, why do you need to document your research method, what are the different types of research instruments, qualitative / quantitative / mixed research methodologies, how do you choose the best research methodology for you, frequently asked questions about research methodology, related articles.

When you’re working on your first piece of academic research, there are many different things to focus on, and it can be overwhelming to stay on top of everything. This is especially true of budding or inexperienced researchers.

If you’ve never put together a research proposal before or find yourself in a position where you need to explain your research methodology decisions, there are a few things you need to be aware of.

Once you understand the ins and outs, handling academic research in the future will be less intimidating. We break down the basics below:

A research methodology encompasses the way in which you intend to carry out your research. This includes how you plan to tackle things like collection methods, statistical analysis, participant observations, and more.

You can think of your research methodology as being a formula. One part will be how you plan on putting your research into practice, and another will be why you feel this is the best way to approach it. Your research methodology is ultimately a methodological and systematic plan to resolve your research problem.

In short, you are explaining how you will take your idea and turn it into a study, which in turn will produce valid and reliable results that are in accordance with the aims and objectives of your research. This is true whether your paper plans to make use of qualitative methods or quantitative methods.

The purpose of a research methodology is to explain the reasoning behind your approach to your research - you'll need to support your collection methods, methods of analysis, and other key points of your work.

Think of it like writing a plan or an outline for you what you intend to do.

When carrying out research, it can be easy to go off-track or depart from your standard methodology.

Tip: Having a methodology keeps you accountable and on track with your original aims and objectives, and gives you a suitable and sound plan to keep your project manageable, smooth, and effective.

With all that said, how do you write out your standard approach to a research methodology?

As a general plan, your methodology should include the following information:

• Your research method.  You need to state whether you plan to use quantitative analysis, qualitative analysis, or mixed-method research methods. This will often be determined by what you hope to achieve with your research.
• Explain your reasoning. Why are you taking this methodological approach? Why is this particular methodology the best way to answer your research problem and achieve your objectives?
• Explain your instruments.  This will mainly be about your collection methods. There are varying instruments to use such as interviews, physical surveys, questionnaires, for example. Your methodology will need to detail your reasoning in choosing a particular instrument for your research.
• What will you do with your results?  How are you going to analyze the data once you have gathered it?
• Advise your reader.  If there is anything in your research methodology that your reader might be unfamiliar with, you should explain it in more detail. For example, you should give any background information to your methods that might be relevant or provide your reasoning if you are conducting your research in a non-standard way.
• How will your sampling process go?  What will your sampling procedure be and why? For example, if you will collect data by carrying out semi-structured or unstructured interviews, how will you choose your interviewees and how will you conduct the interviews themselves?
• Any practical limitations?  You should discuss any limitations you foresee being an issue when you’re carrying out your research.

In any dissertation, thesis, or academic journal, you will always find a chapter dedicated to explaining the research methodology of the person who carried out the study, also referred to as the methodology section of the work.

A good research methodology will explain what you are going to do and why, while a poor methodology will lead to a messy or disorganized approach.

You should also be able to justify in this section your reasoning for why you intend to carry out your research in a particular way, especially if it might be a particularly unique method.

Having a sound methodology in place can also help you with the following:

• When another researcher at a later date wishes to try and replicate your research, they will need your explanations and guidelines.
• In the event that you receive any criticism or questioning on the research you carried out at a later point, you will be able to refer back to it and succinctly explain the how and why of your approach.
• It provides you with a plan to follow throughout your research. When you are drafting your methodology approach, you need to be sure that the method you are using is the right one for your goal. This will help you with both explaining and understanding your method.
• It affords you the opportunity to document from the outset what you intend to achieve with your research, from start to finish.

A research instrument is a tool you will use to help you collect, measure and analyze the data you use as part of your research.

The choice of research instrument will usually be yours to make as the researcher and will be whichever best suits your methodology.

There are many different research instruments you can use in collecting data for your research.

Generally, they can be grouped as follows:

• Interviews (either as a group or one-on-one). You can carry out interviews in many different ways. For example, your interview can be structured, semi-structured, or unstructured. The difference between them is how formal the set of questions is that is asked of the interviewee. In a group interview, you may choose to ask the interviewees to give you their opinions or perceptions on certain topics.
• Surveys (online or in-person). In survey research, you are posing questions in which you ask for a response from the person taking the survey. You may wish to have either free-answer questions such as essay-style questions, or you may wish to use closed questions such as multiple choice. You may even wish to make the survey a mixture of both.
• Focus Groups.  Similar to the group interview above, you may wish to ask a focus group to discuss a particular topic or opinion while you make a note of the answers given.
• Observations.  This is a good research instrument to use if you are looking into human behaviors. Different ways of researching this include studying the spontaneous behavior of participants in their everyday life, or something more structured. A structured observation is research conducted at a set time and place where researchers observe behavior as planned and agreed upon with participants.

These are the most common ways of carrying out research, but it is really dependent on your needs as a researcher and what approach you think is best to take.

It is also possible to combine a number of research instruments if this is necessary and appropriate in answering your research problem.

There are three different types of methodologies, and they are distinguished by whether they focus on words, numbers, or both.

➡️ Want to learn more about the differences between qualitative and quantitative research, and how to use both methods? Check out our guide for that!

If you've done your due diligence, you'll have an idea of which methodology approach is best suited to your research.

It’s likely that you will have carried out considerable reading and homework before you reach this point and you may have taken inspiration from other similar studies that have yielded good results.

Still, it is important to consider different options before setting your research in stone. Exploring different options available will help you to explain why the choice you ultimately make is preferable to other methods.

If proving your research problem requires you to gather large volumes of numerical data to test hypotheses, a quantitative research method is likely to provide you with the most usable results.

If instead you’re looking to try and learn more about people, and their perception of events, your methodology is more exploratory in nature and would therefore probably be better served using a qualitative research methodology.

It helps to always bring things back to the question: what do I want to achieve with my research?

Once you have conducted your research, you need to analyze it. Here are some helpful guides for qualitative data analysis:

➡️  How to do a content analysis

➡️  How to do a thematic analysis

➡️  How to do a rhetorical analysis

Research methodology refers to the techniques used to find and analyze information for a study, ensuring that the results are valid, reliable and that they address the research objective.

Data can typically be organized into four different categories or methods: observational, experimental, simulation, and derived.

Writing a methodology section is a process of introducing your methods and instruments, discussing your analysis, providing more background information, addressing your research limitations, and more.

Your research methodology section will need a clear research question and proposed research approach. You'll need to add a background, introduce your research question, write your methodology and add the works you cited during your data collecting phase.

The research methodology section of your study will indicate how valid your findings are and how well-informed your paper is. It also assists future researchers planning to use the same methodology, who want to cite your study or replicate it.

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Here's What You Need to Understand About Research Methodology

Table of Contents

Research methodology involves a systematic and well-structured approach to conducting scholarly or scientific inquiries. Knowing the significance of research methodology and its different components is crucial as it serves as the basis for any study.

Typically, your research topic will start as a broad idea you want to investigate more thoroughly. Once you’ve identified a research problem and created research questions , you must choose the appropriate methodology and frameworks to address those questions effectively.

What is the definition of a research methodology?

Research methodology is the process or the way you intend to execute your study. The methodology section of a research paper outlines how you plan to conduct your study. It covers various steps such as collecting data, statistical analysis, observing participants, and other procedures involved in the research process

The methods section should give a description of the process that will convert your idea into a study. Additionally, the outcomes of your process must provide valid and reliable results resonant with the aims and objectives of your research. This thumb rule holds complete validity, no matter whether your paper has inclinations for qualitative or quantitative usage.

Studying research methods used in related studies can provide helpful insights and direction for your own research. Now easily discover papers related to your topic on SciSpace and utilize our AI research assistant, Copilot , to quickly review the methodologies applied in different papers.

The need for a good research methodology

While deciding on your approach towards your research, the reason or factors you weighed in choosing a particular problem and formulating a research topic need to be validated and explained. A research methodology helps you do exactly that. Moreover, a good research methodology lets you build your argument to validate your research work performed through various data collection methods, analytical methods, and other essential points.

Just imagine it as a strategy documented to provide an overview of what you intend to do.

While undertaking any research writing or performing the research itself, you may get drifted in not something of much importance. In such a case, a research methodology helps you to get back to your outlined work methodology.

A research methodology helps in keeping you accountable for your work. Additionally, it can help you evaluate whether your work is in sync with your original aims and objectives or not. Besides, a good research methodology enables you to navigate your research process smoothly and swiftly while providing effective planning to achieve your desired results.

What is the basic structure of a research methodology?

Usually, you must ensure to include the following stated aspects while deciding over the basic structure of your research methodology:

1. Your research procedure

Explain what research methods you’re going to use. Whether you intend to proceed with quantitative or qualitative, or a composite of both approaches, you need to state that explicitly. The option among the three depends on your research’s aim, objectives, and scope.

2. Provide the rationality behind your chosen approach

Based on logic and reason, let your readers know why you have chosen said research methodologies. Additionally, you have to build strong arguments supporting why your chosen research method is the best way to achieve the desired outcome.

3. Explain your mechanism

The mechanism encompasses the research methods or instruments you will use to develop your research methodology. It usually refers to your data collection methods. You can use interviews, surveys, physical questionnaires, etc., of the many available mechanisms as research methodology instruments. The data collection method is determined by the type of research and whether the data is quantitative data(includes numerical data) or qualitative data (perception, morale, etc.) Moreover, you need to put logical reasoning behind choosing a particular instrument.

4. Significance of outcomes

The results will be available once you have finished experimenting. However, you should also explain how you plan to use the data to interpret the findings. This section also aids in understanding the problem from within, breaking it down into pieces, and viewing the research problem from various perspectives.

5. Reader’s advice

Anything that you feel must be explained to spread more awareness among readers and focus groups must be included and described in detail. You should not just specify your research methodology on the assumption that a reader is aware of the topic.  

All the relevant information that explains and simplifies your research paper must be included in the methodology section. If you are conducting your research in a non-traditional manner, give a logical justification and list its benefits.

6. Explain your sample space

Include information about the sample and sample space in the methodology section. The term "sample" refers to a smaller set of data that a researcher selects or chooses from a larger group of people or focus groups using a predetermined selection method. Let your readers know how you are going to distinguish between relevant and non-relevant samples. How you figured out those exact numbers to back your research methodology, i.e. the sample spacing of instruments, must be discussed thoroughly.

For example, if you are going to conduct a survey or interview, then by what procedure will you select the interviewees (or sample size in case of surveys), and how exactly will the interview or survey be conducted.

7. Challenges and limitations

This part, which is frequently assumed to be unnecessary, is actually very important. The challenges and limitations that your chosen strategy inherently possesses must be specified while you are conducting different types of research.

The importance of a good research methodology

You must have observed that all research papers, dissertations, or theses carry a chapter entirely dedicated to research methodology. This section helps maintain your credibility as a better interpreter of results rather than a manipulator.

A good research methodology always explains the procedure, data collection methods and techniques, aim, and scope of the research. In a research study, it leads to a well-organized, rationality-based approach, while the paper lacking it is often observed as messy or disorganized.

You should pay special attention to validating your chosen way towards the research methodology. This becomes extremely important in case you select an unconventional or a distinct method of execution.

Curating and developing a strong, effective research methodology can assist you in addressing a variety of situations, such as:

• When someone tries to duplicate or expand upon your research after few years.
• If a contradiction or conflict of facts occurs at a later time. This gives you the security you need to deal with these contradictions while still being able to defend your approach.
• Gaining a tactical approach in getting your research completed in time. Just ensure you are using the right approach while drafting your research methodology, and it can help you achieve your desired outcomes. Additionally, it provides a better explanation and understanding of the research question itself.
• Documenting the results so that the final outcome of the research stays as you intended it to be while starting.

Instruments you could use while writing a good research methodology

As a researcher, you must choose which tools or data collection methods that fit best in terms of the relevance of your research. This decision has to be wise.

There exists many research equipments or tools that you can use to carry out your research process. These are classified as:

a. Interviews (One-on-One or a Group)

An interview aimed to get your desired research outcomes can be undertaken in many different ways. For example, you can design your interview as structured, semi-structured, or unstructured. What sets them apart is the degree of formality in the questions. On the other hand, in a group interview, your aim should be to collect more opinions and group perceptions from the focus groups on a certain topic rather than looking out for some formal answers.

In surveys, you are in better control if you specifically draft the questions you seek the response for. For example, you may choose to include free-style questions that can be answered descriptively, or you may provide a multiple-choice type response for questions. Besides, you can also opt to choose both ways, deciding what suits your research process and purpose better.

c. Sample Groups

Similar to the group interviews, here, you can select a group of individuals and assign them a topic to discuss or freely express their opinions over that. You can simultaneously note down the answers and later draft them appropriately, deciding on the relevance of every response.

d. Observations

If your research domain is humanities or sociology, observations are the best-proven method to draw your research methodology. Of course, you can always include studying the spontaneous response of the participants towards a situation or conducting the same but in a more structured manner. A structured observation means putting the participants in a situation at a previously decided time and then studying their responses.

Of all the tools described above, it is you who should wisely choose the instruments and decide what’s the best fit for your research. You must not restrict yourself from multiple methods or a combination of a few instruments if appropriate in drafting a good research methodology.

Types of research methodology

A research methodology exists in various forms. Depending upon their approach, whether centered around words, numbers, or both, methodologies are distinguished as qualitative, quantitative, or an amalgamation of both.

1. Qualitative research methodology

When a research methodology primarily focuses on words and textual data, then it is generally referred to as qualitative research methodology. This type is usually preferred among researchers when the aim and scope of the research are mainly theoretical and explanatory.

The instruments used are observations, interviews, and sample groups. You can use this methodology if you are trying to study human behavior or response in some situations. Generally, qualitative research methodology is widely used in sociology, psychology, and other related domains.

2. Quantitative research methodology

If your research is majorly centered on data, figures, and stats, then analyzing these numerical data is often referred to as quantitative research methodology. You can use quantitative research methodology if your research requires you to validate or justify the obtained results.

In quantitative methods, surveys, tests, experiments, and evaluations of current databases can be advantageously used as instruments If your research involves testing some hypothesis, then use this methodology.

3. Amalgam methodology

As the name suggests, the amalgam methodology uses both quantitative and qualitative approaches. This methodology is used when a part of the research requires you to verify the facts and figures, whereas the other part demands you to discover the theoretical and explanatory nature of the research question.

The instruments for the amalgam methodology require you to conduct interviews and surveys, including tests and experiments. The outcome of this methodology can be insightful and valuable as it provides precise test results in line with theoretical explanations and reasoning.

The amalgam method, makes your work both factual and rational at the same time.

Final words: How to decide which is the best research methodology?

If you have kept your sincerity and awareness intact with the aims and scope of research well enough, you must have got an idea of which research methodology suits your work best.

Before deciding which research methodology answers your research question, you must invest significant time in reading and doing your homework for that. Taking references that yield relevant results should be your first approach to establishing a research methodology.

Moreover, you should never refrain from exploring other options. Before setting your work in stone, you must try all the available options as it explains why the choice of research methodology that you finally make is more appropriate than the other available options.

You should always go for a quantitative research methodology if your research requires gathering large amounts of data, figures, and statistics. This research methodology will provide you with results if your research paper involves the validation of some hypothesis.

Whereas, if  you are looking for more explanations, reasons, opinions, and public perceptions around a theory, you must use qualitative research methodology.The choice of an appropriate research methodology ultimately depends on what you want to achieve through your research.

Frequently Asked Questions (FAQs) about Research Methodology

1. how to write a research methodology.

You can always provide a separate section for research methodology where you should specify details about the methods and instruments used during the research, discussions on result analysis, including insights into the background information, and conveying the research limitations.

2. What are the types of research methodology?

There generally exists four types of research methodology i.e.

• Observation
• Experimental
• Derivational

3. What is the true meaning of research methodology?

The set of techniques or procedures followed to discover and analyze the information gathered to validate or justify a research outcome is generally called Research Methodology.

4. Where lies the importance of research methodology?

Your research methodology directly reflects the validity of your research outcomes and how well-informed your research work is. Moreover, it can help future researchers cite or refer to your research if they plan to use a similar research methodology.

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What is Research Methodology? Definition, Types, and Examples

Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of the research. Several aspects must be considered before selecting an appropriate research methodology, such as research limitations and ethical concerns that may affect your research.

The research methodology section in a scientific paper describes the different methodological choices made, such as the data collection and analysis methods, and why these choices were selected. The reasons should explain why the methods chosen are the most appropriate to answer the research question. A good research methodology also helps ensure the reliability and validity of the research findings. There are three types of research methodology—quantitative, qualitative, and mixed-method, which can be chosen based on the research objectives.

What is research methodology ?

A research methodology describes the techniques and procedures used to identify and analyze information regarding a specific research topic. It is a process by which researchers design their study so that they can achieve their objectives using the selected research instruments. It includes all the important aspects of research, including research design, data collection methods, data analysis methods, and the overall framework within which the research is conducted. While these points can help you understand what is research methodology, you also need to know why it is important to pick the right methodology.

Why is research methodology important?

Having a good research methodology in place has the following advantages: 3

• Helps other researchers who may want to replicate your research; the explanations will be of benefit to them.
• You can easily answer any questions about your research if they arise at a later stage.
• A research methodology provides a framework and guidelines for researchers to clearly define research questions, hypotheses, and objectives.
• It helps researchers identify the most appropriate research design, sampling technique, and data collection and analysis methods.
• A sound research methodology helps researchers ensure that their findings are valid and reliable and free from biases and errors.
• It also helps ensure that ethical guidelines are followed while conducting research.
• A good research methodology helps researchers in planning their research efficiently, by ensuring optimum usage of their time and resources.

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Types of research methodology.

There are three types of research methodology based on the type of research and the data required. 1

• Quantitative research methodology focuses on measuring and testing numerical data. This approach is good for reaching a large number of people in a short amount of time. This type of research helps in testing the causal relationships between variables, making predictions, and generalizing results to wider populations.
• Qualitative research methodology examines the opinions, behaviors, and experiences of people. It collects and analyzes words and textual data. This research methodology requires fewer participants but is still more time consuming because the time spent per participant is quite large. This method is used in exploratory research where the research problem being investigated is not clearly defined.
• Mixed-method research methodology uses the characteristics of both quantitative and qualitative research methodologies in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method.

What are the types of sampling designs in research methodology?

Sampling 4 is an important part of a research methodology and involves selecting a representative sample of the population to conduct the study, making statistical inferences about them, and estimating the characteristics of the whole population based on these inferences. There are two types of sampling designs in research methodology—probability and nonprobability.

• Probability sampling

In this type of sampling design, a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are:

• Systematic —sample members are chosen at regular intervals. It requires selecting a starting point for the sample and sample size determination that can be repeated at regular intervals. This type of sampling method has a predefined range; hence, it is the least time consuming.
• Stratified —researchers divide the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized, and then a sample can be drawn from each group separately.
• Cluster —the population is divided into clusters based on demographic parameters like age, sex, location, etc.
• Convenience —selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.
• Purposive —participants are selected at the researcher’s discretion. Researchers consider the purpose of the study and the understanding of the target audience.
• Snowball —already selected participants use their social networks to refer the researcher to other potential participants.
• Quota —while designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.

What are data collection methods?

During research, data are collected using various methods depending on the research methodology being followed and the research methods being undertaken. Both qualitative and quantitative research have different data collection methods, as listed below.

Qualitative research 5

• One-on-one interviews: Helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event
• Document study/literature review/record keeping: Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.
• Focus groups: Constructive discussions that usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic.
• Qualitative observation : Researchers collect data using their five senses (sight, smell, touch, taste, and hearing).

Quantitative research 6

• Sampling: The most common type is probability sampling.
• Interviews: Commonly telephonic or done in-person.
• Observations: Structured observations are most commonly used in quantitative research. In this method, researchers make observations about specific behaviors of individuals in a structured setting.
• Document review: Reviewing existing research or documents to collect evidence for supporting the research.
• Surveys and questionnaires. Surveys can be administered both online and offline depending on the requirement and sample size.

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What are data analysis methods.

The data collected using the various methods for qualitative and quantitative research need to be analyzed to generate meaningful conclusions. These data analysis methods 7 also differ between quantitative and qualitative research.

Quantitative research involves a deductive method for data analysis where hypotheses are developed at the beginning of the research and precise measurement is required. The methods include statistical analysis applications to analyze numerical data and are grouped into two categories—descriptive and inferential.

Descriptive analysis is used to describe the basic features of different types of data to present it in a way that ensures the patterns become meaningful. The different types of descriptive analysis methods are:

• Measures of frequency (count, percent, frequency)
• Measures of central tendency (mean, median, mode)
• Measures of dispersion or variation (range, variance, standard deviation)
• Measure of position (percentile ranks, quartile ranks)

Inferential analysis is used to make predictions about a larger population based on the analysis of the data collected from a smaller population. This analysis is used to study the relationships between different variables. Some commonly used inferential data analysis methods are:

• Correlation: To understand the relationship between two or more variables.
• Cross-tabulation: Analyze the relationship between multiple variables.
• Regression analysis: Study the impact of independent variables on the dependent variable.
• Frequency tables: To understand the frequency of data.
• Analysis of variance: To test the degree to which two or more variables differ in an experiment.

Qualitative research involves an inductive method for data analysis where hypotheses are developed after data collection. The methods include:

• Content analysis: For analyzing documented information from text and images by determining the presence of certain words or concepts in texts.
• Narrative analysis: For analyzing content obtained from sources such as interviews, field observations, and surveys. The stories and opinions shared by people are used to answer research questions.
• Discourse analysis: For analyzing interactions with people considering the social context, that is, the lifestyle and environment, under which the interaction occurs.
• Grounded theory: Involves hypothesis creation by data collection and analysis to explain why a phenomenon occurred.
• Thematic analysis: To identify important themes or patterns in data and use these to address an issue.

How to choose a research methodology?

Here are some important factors to consider when choosing a research methodology: 8

• Research objectives, aims, and questions —these would help structure the research design.
• Review existing literature to identify any gaps in knowledge.
• Check the statistical requirements —if data-driven or statistical results are needed then quantitative research is the best. If the research questions can be answered based on people’s opinions and perceptions, then qualitative research is most suitable.
• Sample size —sample size can often determine the feasibility of a research methodology. For a large sample, less effort- and time-intensive methods are appropriate.
• Constraints —constraints of time, geography, and resources can help define the appropriate methodology.

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How to write a research methodology .

A research methodology should include the following components: 3,9

• Research design —should be selected based on the research question and the data required. Common research designs include experimental, quasi-experimental, correlational, descriptive, and exploratory.
• Research method —this can be quantitative, qualitative, or mixed-method.
• Reason for selecting a specific methodology —explain why this methodology is the most suitable to answer your research problem.
• Research instruments —explain the research instruments you plan to use, mainly referring to the data collection methods such as interviews, surveys, etc. Here as well, a reason should be mentioned for selecting the particular instrument.
• Sampling —this involves selecting a representative subset of the population being studied.
• Data collection —involves gathering data using several data collection methods, such as surveys, interviews, etc.
• Data analysis —describe the data analysis methods you will use once you’ve collected the data.
• Research limitations —mention any limitations you foresee while conducting your research.
• Validity and reliability —validity helps identify the accuracy and truthfulness of the findings; reliability refers to the consistency and stability of the results over time and across different conditions.
• Ethical considerations —research should be conducted ethically. The considerations include obtaining consent from participants, maintaining confidentiality, and addressing conflicts of interest.

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The methods section is a critical part of the research papers, allowing researchers to use this to understand your findings and replicate your work when pursuing their own research. However, it is usually also the most difficult section to write. This is where Paperpal can help you overcome the writer’s block and create the first draft in minutes with Paperpal Copilot, its secure generative AI feature suite.  

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Frequently Asked Questions

Q1. What are the key components of research methodology?

A1. A good research methodology has the following key components:

• Research design
• Data collection procedures
• Data analysis methods
• Ethical considerations

Q2. Why is ethical consideration important in research methodology?

A2. Ethical consideration is important in research methodology to ensure the readers of the reliability and validity of the study. Researchers must clearly mention the ethical norms and standards followed during the conduct of the research and also mention if the research has been cleared by any institutional board. The following 10 points are the important principles related to ethical considerations: 10

• Participants should not be subjected to harm.
• Respect for the dignity of participants should be prioritized.
• Full consent should be obtained from participants before the study.
• Participants’ privacy should be ensured.
• Confidentiality of the research data should be ensured.
• Anonymity of individuals and organizations participating in the research should be maintained.
• The aims and objectives of the research should not be exaggerated.
• Affiliations, sources of funding, and any possible conflicts of interest should be declared.
• Communication in relation to the research should be honest and transparent.
• Misleading information and biased representation of primary data findings should be avoided.

Q3. What is the difference between methodology and method?

A3. Research methodology is different from a research method, although both terms are often confused. Research methods are the tools used to gather data, while the research methodology provides a framework for how research is planned, conducted, and analyzed. The latter guides researchers in making decisions about the most appropriate methods for their research. Research methods refer to the specific techniques, procedures, and tools used by researchers to collect, analyze, and interpret data, for instance surveys, questionnaires, interviews, etc.

Research methodology is, thus, an integral part of a research study. It helps ensure that you stay on track to meet your research objectives and answer your research questions using the most appropriate data collection and analysis tools based on your research design.

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• What is research methodology? Research and writing guides. Accessed August 14, 2023. https://paperpile.com/g/what-is-research-methodology/
• Ethical considerations. Business research methodology website. Accessed August 17, 2023. https://research-methodology.net/research-methodology/ethical-considerations/

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• Open access
• Published: 07 September 2020

A tutorial on methodological studies: the what, when, how and why

• Lawrence Mbuagbaw   ORCID: orcid.org/0000-0001-5855-5461 1 , 2 , 3 ,
• Daeria O. Lawson 1 ,
• Livia Puljak 4 ,
• David B. Allison 5 &
• Lehana Thabane 1 , 2 , 6 , 7 , 8  

BMC Medical Research Methodology volume  20 , Article number:  226 ( 2020 ) Cite this article

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Methodological studies – studies that evaluate the design, analysis or reporting of other research-related reports – play an important role in health research. They help to highlight issues in the conduct of research with the aim of improving health research methodology, and ultimately reducing research waste.

We provide an overview of some of the key aspects of methodological studies such as what they are, and when, how and why they are done. We adopt a “frequently asked questions” format to facilitate reading this paper and provide multiple examples to help guide researchers interested in conducting methodological studies. Some of the topics addressed include: is it necessary to publish a study protocol? How to select relevant research reports and databases for a methodological study? What approaches to data extraction and statistical analysis should be considered when conducting a methodological study? What are potential threats to validity and is there a way to appraise the quality of methodological studies?

Appropriate reflection and application of basic principles of epidemiology and biostatistics are required in the design and analysis of methodological studies. This paper provides an introduction for further discussion about the conduct of methodological studies.

Peer Review reports

The field of meta-research (or research-on-research) has proliferated in recent years in response to issues with research quality and conduct [ 1 , 2 , 3 ]. As the name suggests, this field targets issues with research design, conduct, analysis and reporting. Various types of research reports are often examined as the unit of analysis in these studies (e.g. abstracts, full manuscripts, trial registry entries). Like many other novel fields of research, meta-research has seen a proliferation of use before the development of reporting guidance. For example, this was the case with randomized trials for which risk of bias tools and reporting guidelines were only developed much later – after many trials had been published and noted to have limitations [ 4 , 5 ]; and for systematic reviews as well [ 6 , 7 , 8 ]. However, in the absence of formal guidance, studies that report on research differ substantially in how they are named, conducted and reported [ 9 , 10 ]. This creates challenges in identifying, summarizing and comparing them. In this tutorial paper, we will use the term methodological study to refer to any study that reports on the design, conduct, analysis or reporting of primary or secondary research-related reports (such as trial registry entries and conference abstracts).

In the past 10 years, there has been an increase in the use of terms related to methodological studies (based on records retrieved with a keyword search [in the title and abstract] for “methodological review” and “meta-epidemiological study” in PubMed up to December 2019), suggesting that these studies may be appearing more frequently in the literature. See Fig.  1 .

Trends in the number studies that mention “methodological review” or “meta-

epidemiological study” in PubMed.

The methods used in many methodological studies have been borrowed from systematic and scoping reviews. This practice has influenced the direction of the field, with many methodological studies including searches of electronic databases, screening of records, duplicate data extraction and assessments of risk of bias in the included studies. However, the research questions posed in methodological studies do not always require the approaches listed above, and guidance is needed on when and how to apply these methods to a methodological study. Even though methodological studies can be conducted on qualitative or mixed methods research, this paper focuses on and draws examples exclusively from quantitative research.

The objectives of this paper are to provide some insights on how to conduct methodological studies so that there is greater consistency between the research questions posed, and the design, analysis and reporting of findings. We provide multiple examples to illustrate concepts and a proposed framework for categorizing methodological studies in quantitative research.

What is a methodological study?

Any study that describes or analyzes methods (design, conduct, analysis or reporting) in published (or unpublished) literature is a methodological study. Consequently, the scope of methodological studies is quite extensive and includes, but is not limited to, topics as diverse as: research question formulation [ 11 ]; adherence to reporting guidelines [ 12 , 13 , 14 ] and consistency in reporting [ 15 ]; approaches to study analysis [ 16 ]; investigating the credibility of analyses [ 17 ]; and studies that synthesize these methodological studies [ 18 ]. While the nomenclature of methodological studies is not uniform, the intents and purposes of these studies remain fairly consistent – to describe or analyze methods in primary or secondary studies. As such, methodological studies may also be classified as a subtype of observational studies.

Parallel to this are experimental studies that compare different methods. Even though they play an important role in informing optimal research methods, experimental methodological studies are beyond the scope of this paper. Examples of such studies include the randomized trials by Buscemi et al., comparing single data extraction to double data extraction [ 19 ], and Carrasco-Labra et al., comparing approaches to presenting findings in Grading of Recommendations, Assessment, Development and Evaluations (GRADE) summary of findings tables [ 20 ]. In these studies, the unit of analysis is the person or groups of individuals applying the methods. We also direct readers to the Studies Within a Trial (SWAT) and Studies Within a Review (SWAR) programme operated through the Hub for Trials Methodology Research, for further reading as a potential useful resource for these types of experimental studies [ 21 ]. Lastly, this paper is not meant to inform the conduct of research using computational simulation and mathematical modeling for which some guidance already exists [ 22 ], or studies on the development of methods using consensus-based approaches.

When should we conduct a methodological study?

Methodological studies occupy a unique niche in health research that allows them to inform methodological advances. Methodological studies should also be conducted as pre-cursors to reporting guideline development, as they provide an opportunity to understand current practices, and help to identify the need for guidance and gaps in methodological or reporting quality. For example, the development of the popular Preferred Reporting Items of Systematic reviews and Meta-Analyses (PRISMA) guidelines were preceded by methodological studies identifying poor reporting practices [ 23 , 24 ]. In these instances, after the reporting guidelines are published, methodological studies can also be used to monitor uptake of the guidelines.

These studies can also be conducted to inform the state of the art for design, analysis and reporting practices across different types of health research fields, with the aim of improving research practices, and preventing or reducing research waste. For example, Samaan et al. conducted a scoping review of adherence to different reporting guidelines in health care literature [ 18 ]. Methodological studies can also be used to determine the factors associated with reporting practices. For example, Abbade et al. investigated journal characteristics associated with the use of the Participants, Intervention, Comparison, Outcome, Timeframe (PICOT) format in framing research questions in trials of venous ulcer disease [ 11 ].

How often are methodological studies conducted?

There is no clear answer to this question. Based on a search of PubMed, the use of related terms (“methodological review” and “meta-epidemiological study”) – and therefore, the number of methodological studies – is on the rise. However, many other terms are used to describe methodological studies. There are also many studies that explore design, conduct, analysis or reporting of research reports, but that do not use any specific terms to describe or label their study design in terms of “methodology”. This diversity in nomenclature makes a census of methodological studies elusive. Appropriate terminology and key words for methodological studies are needed to facilitate improved accessibility for end-users.

Why do we conduct methodological studies?

Methodological studies provide information on the design, conduct, analysis or reporting of primary and secondary research and can be used to appraise quality, quantity, completeness, accuracy and consistency of health research. These issues can be explored in specific fields, journals, databases, geographical regions and time periods. For example, Areia et al. explored the quality of reporting of endoscopic diagnostic studies in gastroenterology [ 25 ]; Knol et al. investigated the reporting of p -values in baseline tables in randomized trial published in high impact journals [ 26 ]; Chen et al. describe adherence to the Consolidated Standards of Reporting Trials (CONSORT) statement in Chinese Journals [ 27 ]; and Hopewell et al. describe the effect of editors’ implementation of CONSORT guidelines on reporting of abstracts over time [ 28 ]. Methodological studies provide useful information to researchers, clinicians, editors, publishers and users of health literature. As a result, these studies have been at the cornerstone of important methodological developments in the past two decades and have informed the development of many health research guidelines including the highly cited CONSORT statement [ 5 ].

Where can we find methodological studies?

Methodological studies can be found in most common biomedical bibliographic databases (e.g. Embase, MEDLINE, PubMed, Web of Science). However, the biggest caveat is that methodological studies are hard to identify in the literature due to the wide variety of names used and the lack of comprehensive databases dedicated to them. A handful can be found in the Cochrane Library as “Cochrane Methodology Reviews”, but these studies only cover methodological issues related to systematic reviews. Previous attempts to catalogue all empirical studies of methods used in reviews were abandoned 10 years ago [ 29 ]. In other databases, a variety of search terms may be applied with different levels of sensitivity and specificity.

Some frequently asked questions about methodological studies

In this section, we have outlined responses to questions that might help inform the conduct of methodological studies.

Q: How should I select research reports for my methodological study?

A: Selection of research reports for a methodological study depends on the research question and eligibility criteria. Once a clear research question is set and the nature of literature one desires to review is known, one can then begin the selection process. Selection may begin with a broad search, especially if the eligibility criteria are not apparent. For example, a methodological study of Cochrane Reviews of HIV would not require a complex search as all eligible studies can easily be retrieved from the Cochrane Library after checking a few boxes [ 30 ]. On the other hand, a methodological study of subgroup analyses in trials of gastrointestinal oncology would require a search to find such trials, and further screening to identify trials that conducted a subgroup analysis [ 31 ].

The strategies used for identifying participants in observational studies can apply here. One may use a systematic search to identify all eligible studies. If the number of eligible studies is unmanageable, a random sample of articles can be expected to provide comparable results if it is sufficiently large [ 32 ]. For example, Wilson et al. used a random sample of trials from the Cochrane Stroke Group’s Trial Register to investigate completeness of reporting [ 33 ]. It is possible that a simple random sample would lead to underrepresentation of units (i.e. research reports) that are smaller in number. This is relevant if the investigators wish to compare multiple groups but have too few units in one group. In this case a stratified sample would help to create equal groups. For example, in a methodological study comparing Cochrane and non-Cochrane reviews, Kahale et al. drew random samples from both groups [ 34 ]. Alternatively, systematic or purposeful sampling strategies can be used and we encourage researchers to justify their selected approaches based on the study objective.

Q: How many databases should I search?

A: The number of databases one should search would depend on the approach to sampling, which can include targeting the entire “population” of interest or a sample of that population. If you are interested in including the entire target population for your research question, or drawing a random or systematic sample from it, then a comprehensive and exhaustive search for relevant articles is required. In this case, we recommend using systematic approaches for searching electronic databases (i.e. at least 2 databases with a replicable and time stamped search strategy). The results of your search will constitute a sampling frame from which eligible studies can be drawn.

Alternatively, if your approach to sampling is purposeful, then we recommend targeting the database(s) or data sources (e.g. journals, registries) that include the information you need. For example, if you are conducting a methodological study of high impact journals in plastic surgery and they are all indexed in PubMed, you likely do not need to search any other databases. You may also have a comprehensive list of all journals of interest and can approach your search using the journal names in your database search (or by accessing the journal archives directly from the journal’s website). Even though one could also search journals’ web pages directly, using a database such as PubMed has multiple advantages, such as the use of filters, so the search can be narrowed down to a certain period, or study types of interest. Furthermore, individual journals’ web sites may have different search functionalities, which do not necessarily yield a consistent output.

Q: Should I publish a protocol for my methodological study?

A: A protocol is a description of intended research methods. Currently, only protocols for clinical trials require registration [ 35 ]. Protocols for systematic reviews are encouraged but no formal recommendation exists. The scientific community welcomes the publication of protocols because they help protect against selective outcome reporting, the use of post hoc methodologies to embellish results, and to help avoid duplication of efforts [ 36 ]. While the latter two risks exist in methodological research, the negative consequences may be substantially less than for clinical outcomes. In a sample of 31 methodological studies, 7 (22.6%) referenced a published protocol [ 9 ]. In the Cochrane Library, there are 15 protocols for methodological reviews (21 July 2020). This suggests that publishing protocols for methodological studies is not uncommon.

Authors can consider publishing their study protocol in a scholarly journal as a manuscript. Advantages of such publication include obtaining peer-review feedback about the planned study, and easy retrieval by searching databases such as PubMed. The disadvantages in trying to publish protocols includes delays associated with manuscript handling and peer review, as well as costs, as few journals publish study protocols, and those journals mostly charge article-processing fees [ 37 ]. Authors who would like to make their protocol publicly available without publishing it in scholarly journals, could deposit their study protocols in publicly available repositories, such as the Open Science Framework ( https://osf.io/ ).

Q: How to appraise the quality of a methodological study?

A: To date, there is no published tool for appraising the risk of bias in a methodological study, but in principle, a methodological study could be considered as a type of observational study. Therefore, during conduct or appraisal, care should be taken to avoid the biases common in observational studies [ 38 ]. These biases include selection bias, comparability of groups, and ascertainment of exposure or outcome. In other words, to generate a representative sample, a comprehensive reproducible search may be necessary to build a sampling frame. Additionally, random sampling may be necessary to ensure that all the included research reports have the same probability of being selected, and the screening and selection processes should be transparent and reproducible. To ensure that the groups compared are similar in all characteristics, matching, random sampling or stratified sampling can be used. Statistical adjustments for between-group differences can also be applied at the analysis stage. Finally, duplicate data extraction can reduce errors in assessment of exposures or outcomes.

Q: Should I justify a sample size?

A: In all instances where one is not using the target population (i.e. the group to which inferences from the research report are directed) [ 39 ], a sample size justification is good practice. The sample size justification may take the form of a description of what is expected to be achieved with the number of articles selected, or a formal sample size estimation that outlines the number of articles required to answer the research question with a certain precision and power. Sample size justifications in methodological studies are reasonable in the following instances:

Comparing two groups

Determining a proportion, mean or another quantifier

Determining factors associated with an outcome using regression-based analyses

For example, El Dib et al. computed a sample size requirement for a methodological study of diagnostic strategies in randomized trials, based on a confidence interval approach [ 40 ].

Q: What should I call my study?

A: Other terms which have been used to describe/label methodological studies include “ methodological review ”, “methodological survey” , “meta-epidemiological study” , “systematic review” , “systematic survey”, “meta-research”, “research-on-research” and many others. We recommend that the study nomenclature be clear, unambiguous, informative and allow for appropriate indexing. Methodological study nomenclature that should be avoided includes “ systematic review” – as this will likely be confused with a systematic review of a clinical question. “ Systematic survey” may also lead to confusion about whether the survey was systematic (i.e. using a preplanned methodology) or a survey using “ systematic” sampling (i.e. a sampling approach using specific intervals to determine who is selected) [ 32 ]. Any of the above meanings of the words “ systematic” may be true for methodological studies and could be potentially misleading. “ Meta-epidemiological study” is ideal for indexing, but not very informative as it describes an entire field. The term “ review ” may point towards an appraisal or “review” of the design, conduct, analysis or reporting (or methodological components) of the targeted research reports, yet it has also been used to describe narrative reviews [ 41 , 42 ]. The term “ survey ” is also in line with the approaches used in many methodological studies [ 9 ], and would be indicative of the sampling procedures of this study design. However, in the absence of guidelines on nomenclature, the term “ methodological study ” is broad enough to capture most of the scenarios of such studies.

Q: Should I account for clustering in my methodological study?

A: Data from methodological studies are often clustered. For example, articles coming from a specific source may have different reporting standards (e.g. the Cochrane Library). Articles within the same journal may be similar due to editorial practices and policies, reporting requirements and endorsement of guidelines. There is emerging evidence that these are real concerns that should be accounted for in analyses [ 43 ]. Some cluster variables are described in the section: “ What variables are relevant to methodological studies?”

A variety of modelling approaches can be used to account for correlated data, including the use of marginal, fixed or mixed effects regression models with appropriate computation of standard errors [ 44 ]. For example, Kosa et al. used generalized estimation equations to account for correlation of articles within journals [ 15 ]. Not accounting for clustering could lead to incorrect p -values, unduly narrow confidence intervals, and biased estimates [ 45 ].

Q: Should I extract data in duplicate?

A: Yes. Duplicate data extraction takes more time but results in less errors [ 19 ]. Data extraction errors in turn affect the effect estimate [ 46 ], and therefore should be mitigated. Duplicate data extraction should be considered in the absence of other approaches to minimize extraction errors. However, much like systematic reviews, this area will likely see rapid new advances with machine learning and natural language processing technologies to support researchers with screening and data extraction [ 47 , 48 ]. However, experience plays an important role in the quality of extracted data and inexperienced extractors should be paired with experienced extractors [ 46 , 49 ].

Q: Should I assess the risk of bias of research reports included in my methodological study?

A : Risk of bias is most useful in determining the certainty that can be placed in the effect measure from a study. In methodological studies, risk of bias may not serve the purpose of determining the trustworthiness of results, as effect measures are often not the primary goal of methodological studies. Determining risk of bias in methodological studies is likely a practice borrowed from systematic review methodology, but whose intrinsic value is not obvious in methodological studies. When it is part of the research question, investigators often focus on one aspect of risk of bias. For example, Speich investigated how blinding was reported in surgical trials [ 50 ], and Abraha et al., investigated the application of intention-to-treat analyses in systematic reviews and trials [ 51 ].

Q: What variables are relevant to methodological studies?

A: There is empirical evidence that certain variables may inform the findings in a methodological study. We outline some of these and provide a brief overview below:

Country: Countries and regions differ in their research cultures, and the resources available to conduct research. Therefore, it is reasonable to believe that there may be differences in methodological features across countries. Methodological studies have reported loco-regional differences in reporting quality [ 52 , 53 ]. This may also be related to challenges non-English speakers face in publishing papers in English.

Authors’ expertise: The inclusion of authors with expertise in research methodology, biostatistics, and scientific writing is likely to influence the end-product. Oltean et al. found that among randomized trials in orthopaedic surgery, the use of analyses that accounted for clustering was more likely when specialists (e.g. statistician, epidemiologist or clinical trials methodologist) were included on the study team [ 54 ]. Fleming et al. found that including methodologists in the review team was associated with appropriate use of reporting guidelines [ 55 ].

Source of funding and conflicts of interest: Some studies have found that funded studies report better [ 56 , 57 ], while others do not [ 53 , 58 ]. The presence of funding would indicate the availability of resources deployed to ensure optimal design, conduct, analysis and reporting. However, the source of funding may introduce conflicts of interest and warrant assessment. For example, Kaiser et al. investigated the effect of industry funding on obesity or nutrition randomized trials and found that reporting quality was similar [ 59 ]. Thomas et al. looked at reporting quality of long-term weight loss trials and found that industry funded studies were better [ 60 ]. Kan et al. examined the association between industry funding and “positive trials” (trials reporting a significant intervention effect) and found that industry funding was highly predictive of a positive trial [ 61 ]. This finding is similar to that of a recent Cochrane Methodology Review by Hansen et al. [ 62 ]

Journal characteristics: Certain journals’ characteristics may influence the study design, analysis or reporting. Characteristics such as journal endorsement of guidelines [ 63 , 64 ], and Journal Impact Factor (JIF) have been shown to be associated with reporting [ 63 , 65 , 66 , 67 ].

Study size (sample size/number of sites): Some studies have shown that reporting is better in larger studies [ 53 , 56 , 58 ].

Year of publication: It is reasonable to assume that design, conduct, analysis and reporting of research will change over time. Many studies have demonstrated improvements in reporting over time or after the publication of reporting guidelines [ 68 , 69 ].

Type of intervention: In a methodological study of reporting quality of weight loss intervention studies, Thabane et al. found that trials of pharmacologic interventions were reported better than trials of non-pharmacologic interventions [ 70 ].

Interactions between variables: Complex interactions between the previously listed variables are possible. High income countries with more resources may be more likely to conduct larger studies and incorporate a variety of experts. Authors in certain countries may prefer certain journals, and journal endorsement of guidelines and editorial policies may change over time.

Q: Should I focus only on high impact journals?

A: Investigators may choose to investigate only high impact journals because they are more likely to influence practice and policy, or because they assume that methodological standards would be higher. However, the JIF may severely limit the scope of articles included and may skew the sample towards articles with positive findings. The generalizability and applicability of findings from a handful of journals must be examined carefully, especially since the JIF varies over time. Even among journals that are all “high impact”, variations exist in methodological standards.

Q: Can I conduct a methodological study of qualitative research?

A: Yes. Even though a lot of methodological research has been conducted in the quantitative research field, methodological studies of qualitative studies are feasible. Certain databases that catalogue qualitative research including the Cumulative Index to Nursing & Allied Health Literature (CINAHL) have defined subject headings that are specific to methodological research (e.g. “research methodology”). Alternatively, one could also conduct a qualitative methodological review; that is, use qualitative approaches to synthesize methodological issues in qualitative studies.

Q: What reporting guidelines should I use for my methodological study?

A: There is no guideline that covers the entire scope of methodological studies. One adaptation of the PRISMA guidelines has been published, which works well for studies that aim to use the entire target population of research reports [ 71 ]. However, it is not widely used (40 citations in 2 years as of 09 December 2019), and methodological studies that are designed as cross-sectional or before-after studies require a more fit-for purpose guideline. A more encompassing reporting guideline for a broad range of methodological studies is currently under development [ 72 ]. However, in the absence of formal guidance, the requirements for scientific reporting should be respected, and authors of methodological studies should focus on transparency and reproducibility.

Q: What are the potential threats to validity and how can I avoid them?

A: Methodological studies may be compromised by a lack of internal or external validity. The main threats to internal validity in methodological studies are selection and confounding bias. Investigators must ensure that the methods used to select articles does not make them differ systematically from the set of articles to which they would like to make inferences. For example, attempting to make extrapolations to all journals after analyzing high-impact journals would be misleading.

Many factors (confounders) may distort the association between the exposure and outcome if the included research reports differ with respect to these factors [ 73 ]. For example, when examining the association between source of funding and completeness of reporting, it may be necessary to account for journals that endorse the guidelines. Confounding bias can be addressed by restriction, matching and statistical adjustment [ 73 ]. Restriction appears to be the method of choice for many investigators who choose to include only high impact journals or articles in a specific field. For example, Knol et al. examined the reporting of p -values in baseline tables of high impact journals [ 26 ]. Matching is also sometimes used. In the methodological study of non-randomized interventional studies of elective ventral hernia repair, Parker et al. matched prospective studies with retrospective studies and compared reporting standards [ 74 ]. Some other methodological studies use statistical adjustments. For example, Zhang et al. used regression techniques to determine the factors associated with missing participant data in trials [ 16 ].

With regard to external validity, researchers interested in conducting methodological studies must consider how generalizable or applicable their findings are. This should tie in closely with the research question and should be explicit. For example. Findings from methodological studies on trials published in high impact cardiology journals cannot be assumed to be applicable to trials in other fields. However, investigators must ensure that their sample truly represents the target sample either by a) conducting a comprehensive and exhaustive search, or b) using an appropriate and justified, randomly selected sample of research reports.

Even applicability to high impact journals may vary based on the investigators’ definition, and over time. For example, for high impact journals in the field of general medicine, Bouwmeester et al. included the Annals of Internal Medicine (AIM), BMJ, the Journal of the American Medical Association (JAMA), Lancet, the New England Journal of Medicine (NEJM), and PLoS Medicine ( n  = 6) [ 75 ]. In contrast, the high impact journals selected in the methodological study by Schiller et al. were BMJ, JAMA, Lancet, and NEJM ( n  = 4) [ 76 ]. Another methodological study by Kosa et al. included AIM, BMJ, JAMA, Lancet and NEJM ( n  = 5). In the methodological study by Thabut et al., journals with a JIF greater than 5 were considered to be high impact. Riado Minguez et al. used first quartile journals in the Journal Citation Reports (JCR) for a specific year to determine “high impact” [ 77 ]. Ultimately, the definition of high impact will be based on the number of journals the investigators are willing to include, the year of impact and the JIF cut-off [ 78 ]. We acknowledge that the term “generalizability” may apply differently for methodological studies, especially when in many instances it is possible to include the entire target population in the sample studied.

Finally, methodological studies are not exempt from information bias which may stem from discrepancies in the included research reports [ 79 ], errors in data extraction, or inappropriate interpretation of the information extracted. Likewise, publication bias may also be a concern in methodological studies, but such concepts have not yet been explored.

A proposed framework

In order to inform discussions about methodological studies, the development of guidance for what should be reported, we have outlined some key features of methodological studies that can be used to classify them. For each of the categories outlined below, we provide an example. In our experience, the choice of approach to completing a methodological study can be informed by asking the following four questions:

What is the aim?

Methodological studies that investigate bias

A methodological study may be focused on exploring sources of bias in primary or secondary studies (meta-bias), or how bias is analyzed. We have taken care to distinguish bias (i.e. systematic deviations from the truth irrespective of the source) from reporting quality or completeness (i.e. not adhering to a specific reporting guideline or norm). An example of where this distinction would be important is in the case of a randomized trial with no blinding. This study (depending on the nature of the intervention) would be at risk of performance bias. However, if the authors report that their study was not blinded, they would have reported adequately. In fact, some methodological studies attempt to capture both “quality of conduct” and “quality of reporting”, such as Richie et al., who reported on the risk of bias in randomized trials of pharmacy practice interventions [ 80 ]. Babic et al. investigated how risk of bias was used to inform sensitivity analyses in Cochrane reviews [ 81 ]. Further, biases related to choice of outcomes can also be explored. For example, Tan et al investigated differences in treatment effect size based on the outcome reported [ 82 ].

Methodological studies that investigate quality (or completeness) of reporting

Methodological studies may report quality of reporting against a reporting checklist (i.e. adherence to guidelines) or against expected norms. For example, Croituro et al. report on the quality of reporting in systematic reviews published in dermatology journals based on their adherence to the PRISMA statement [ 83 ], and Khan et al. described the quality of reporting of harms in randomized controlled trials published in high impact cardiovascular journals based on the CONSORT extension for harms [ 84 ]. Other methodological studies investigate reporting of certain features of interest that may not be part of formally published checklists or guidelines. For example, Mbuagbaw et al. described how often the implications for research are elaborated using the Evidence, Participants, Intervention, Comparison, Outcome, Timeframe (EPICOT) format [ 30 ].

Methodological studies that investigate the consistency of reporting

Sometimes investigators may be interested in how consistent reports of the same research are, as it is expected that there should be consistency between: conference abstracts and published manuscripts; manuscript abstracts and manuscript main text; and trial registration and published manuscript. For example, Rosmarakis et al. investigated consistency between conference abstracts and full text manuscripts [ 85 ].

Methodological studies that investigate factors associated with reporting

In addition to identifying issues with reporting in primary and secondary studies, authors of methodological studies may be interested in determining the factors that are associated with certain reporting practices. Many methodological studies incorporate this, albeit as a secondary outcome. For example, Farrokhyar et al. investigated the factors associated with reporting quality in randomized trials of coronary artery bypass grafting surgery [ 53 ].

Methodological studies that investigate methods

Methodological studies may also be used to describe methods or compare methods, and the factors associated with methods. Muller et al. described the methods used for systematic reviews and meta-analyses of observational studies [ 86 ].

Methodological studies that summarize other methodological studies

Some methodological studies synthesize results from other methodological studies. For example, Li et al. conducted a scoping review of methodological reviews that investigated consistency between full text and abstracts in primary biomedical research [ 87 ].

Methodological studies that investigate nomenclature and terminology

Some methodological studies may investigate the use of names and terms in health research. For example, Martinic et al. investigated the definitions of systematic reviews used in overviews of systematic reviews (OSRs), meta-epidemiological studies and epidemiology textbooks [ 88 ].

Other types of methodological studies

In addition to the previously mentioned experimental methodological studies, there may exist other types of methodological studies not captured here.

What is the design?

Methodological studies that are descriptive

Most methodological studies are purely descriptive and report their findings as counts (percent) and means (standard deviation) or medians (interquartile range). For example, Mbuagbaw et al. described the reporting of research recommendations in Cochrane HIV systematic reviews [ 30 ]. Gohari et al. described the quality of reporting of randomized trials in diabetes in Iran [ 12 ].

Methodological studies that are analytical

Some methodological studies are analytical wherein “analytical studies identify and quantify associations, test hypotheses, identify causes and determine whether an association exists between variables, such as between an exposure and a disease.” [ 89 ] In the case of methodological studies all these investigations are possible. For example, Kosa et al. investigated the association between agreement in primary outcome from trial registry to published manuscript and study covariates. They found that larger and more recent studies were more likely to have agreement [ 15 ]. Tricco et al. compared the conclusion statements from Cochrane and non-Cochrane systematic reviews with a meta-analysis of the primary outcome and found that non-Cochrane reviews were more likely to report positive findings. These results are a test of the null hypothesis that the proportions of Cochrane and non-Cochrane reviews that report positive results are equal [ 90 ].

What is the sampling strategy?

Methodological studies that include the target population

Methodological reviews with narrow research questions may be able to include the entire target population. For example, in the methodological study of Cochrane HIV systematic reviews, Mbuagbaw et al. included all of the available studies ( n  = 103) [ 30 ].

Methodological studies that include a sample of the target population

Many methodological studies use random samples of the target population [ 33 , 91 , 92 ]. Alternatively, purposeful sampling may be used, limiting the sample to a subset of research-related reports published within a certain time period, or in journals with a certain ranking or on a topic. Systematic sampling can also be used when random sampling may be challenging to implement.

What is the unit of analysis?

Methodological studies with a research report as the unit of analysis

Many methodological studies use a research report (e.g. full manuscript of study, abstract portion of the study) as the unit of analysis, and inferences can be made at the study-level. However, both published and unpublished research-related reports can be studied. These may include articles, conference abstracts, registry entries etc.

Methodological studies with a design, analysis or reporting item as the unit of analysis

Some methodological studies report on items which may occur more than once per article. For example, Paquette et al. report on subgroup analyses in Cochrane reviews of atrial fibrillation in which 17 systematic reviews planned 56 subgroup analyses [ 93 ].

This framework is outlined in Fig.  2 .

A proposed framework for methodological studies

Conclusions

Methodological studies have examined different aspects of reporting such as quality, completeness, consistency and adherence to reporting guidelines. As such, many of the methodological study examples cited in this tutorial are related to reporting. However, as an evolving field, the scope of research questions that can be addressed by methodological studies is expected to increase.

In this paper we have outlined the scope and purpose of methodological studies, along with examples of instances in which various approaches have been used. In the absence of formal guidance on the design, conduct, analysis and reporting of methodological studies, we have provided some advice to help make methodological studies consistent. This advice is grounded in good contemporary scientific practice. Generally, the research question should tie in with the sampling approach and planned analysis. We have also highlighted the variables that may inform findings from methodological studies. Lastly, we have provided suggestions for ways in which authors can categorize their methodological studies to inform their design and analysis.

Availability of data and materials

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Abbreviations

Consolidated Standards of Reporting Trials

Evidence, Participants, Intervention, Comparison, Outcome, Timeframe

Grading of Recommendations, Assessment, Development and Evaluations

Participants, Intervention, Comparison, Outcome, Timeframe

Preferred Reporting Items of Systematic reviews and Meta-Analyses

Studies Within a Review

Studies Within a Trial

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LM conceived the idea and drafted the outline and paper. DOL and LT commented on the idea and draft outline. LM, LP and DOL performed literature searches and data extraction. All authors (LM, DOL, LT, LP, DBA) reviewed several draft versions of the manuscript and approved the final manuscript.

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Mbuagbaw, L., Lawson, D.O., Puljak, L. et al. A tutorial on methodological studies: the what, when, how and why. BMC Med Res Methodol 20 , 226 (2020). https://doi.org/10.1186/s12874-020-01107-7

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• Research methods
• Research-on-research

BMC Medical Research Methodology

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Research Methodologies

• What are research designs?

What are research methodologies?

Quantitative research methodologies, qualitative research methodologies, mixed method methodologies, selecting a methodology.

• What are research methods?
• Additional Sources

According to Dawson (2019),a research methodology is the primary principle that will guide your research.  It becomes the general approach in conducting research on your topic and determines what research method you will use. A research methodology is different from a research method because research methods are the tools you use to gather your data (Dawson, 2019).  You must consider several issues when it comes to selecting the most appropriate methodology for your topic.  Issues might include research limitations and ethical dilemmas that might impact the quality of your research.  Descriptions of each type of methodology are included below.

Quantitative research methodologies are meant to create numeric statistics by using survey research to gather data (Dawson, 2019).  This approach tends to reach a larger amount of people in a shorter amount of time.  According to Labaree (2020), there are three parts that make up a quantitative research methodology:

• Sample population
• How you will collect your data (this is the research method)
• How you will analyze your data

Once you decide on a methodology, you can consider the method to which you will apply your methodology.

Qualitative research methodologies examine the behaviors, opinions, and experiences of individuals through methods of examination (Dawson, 2019).  This type of approach typically requires less participants, but more time with each participant.  It gives research subjects the opportunity to provide their own opinion on a certain topic.

Examples of Qualitative Research Methodologies

• Action research:  This is when the researcher works with a group of people to improve something in a certain environment.  It is a common approach for research in organizational management, community development, education, and agriculture (Dawson, 2019).
• Ethnography:  The process of organizing and describing cultural behaviors (Dawson, 2019).  Researchers may immerse themselves into another culture to receive in "inside look" into the group they are studying.  It is often a time consuming process because the researcher will do this for a long period of time.  This can also be called "participant observation" (Dawson, 2019).
• Feminist research:  The goal of this methodology is to study topics that have been dominated by male test subjects.  It aims to study females and compare the results to previous studies that used male participants (Dawson, 2019).
• Grounded theory:  The process of developing a theory to describe a phenomenon strictly through the data results collected in a study.  It is different from other research methodologies where the researcher attempts to prove a hypothesis that they create before collecting data.  Popular research methods for this approach include focus groups and interviews (Dawson, 2019).

A mixed methodology allows you to implement the strengths of both qualitative and quantitative research methods.  In some cases, you may find that your research project would benefit from this.  This approach is beneficial because it allows each methodology to counteract the weaknesses of the other (Dawson, 2019).  You should consider this option carefully, as it can make your research complicated if not planned correctly.

What should you do to decide on a research methodology?  The most logical way to determine your methodology is to decide whether you plan on conducting qualitative or qualitative research.  You also have the option to implement a mixed methods approach.  Looking back on Dawson's (2019) five "W's" on the previous page , may help you with this process.  You should also look for key words that indicate a specific type of research methodology in your hypothesis or proposal.  Some words may lean more towards one methodology over another.

Quantitative Research Key Words

• How satisfied

Qualitative Research Key Words

• Experiences
• Thoughts/Think
• Relationship
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• Last Updated: Aug 2, 2022 2:36 PM
• URL: https://library.tiffin.edu/researchmethodologies

How To Choose Your Research Methodology

Qualitative vs quantitative vs mixed methods.

By: Derek Jansen (MBA). Expert Reviewed By: Dr Eunice Rautenbach | June 2021

Without a doubt, one of the most common questions we receive at Grad Coach is “ How do I choose the right methodology for my research? ”. It’s easy to see why – with so many options on the research design table, it’s easy to get intimidated, especially with all the complex lingo!

In this post, we’ll explain the three overarching types of research – qualitative, quantitative and mixed methods – and how you can go about choosing the best methodological approach for your research.

Overview: Choosing Your Methodology

Understanding the options – Qualitative research – Quantitative research – Mixed methods-based research

Choosing a research methodology – Nature of the research – Research area norms – Practicalities

1. Understanding the options

Before we jump into the question of how to choose a research methodology, it’s useful to take a step back to understand the three overarching types of research – qualitative , quantitative and mixed methods -based research. Each of these options takes a different methodological approach.

Qualitative research utilises data that is not numbers-based. In other words, qualitative research focuses on words , descriptions , concepts or ideas – while quantitative research makes use of numbers and statistics. Qualitative research investigates the “softer side” of things to explore and describe, while quantitative research focuses on the “hard numbers”, to measure differences between variables and the relationships between them.

Importantly, qualitative research methods are typically used to explore and gain a deeper understanding of the complexity of a situation – to draw a rich picture . In contrast to this, quantitative methods are usually used to confirm or test hypotheses . In other words, they have distinctly different purposes. The table below highlights a few of the key differences between qualitative and quantitative research – you can learn more about the differences here.

• Uses an inductive approach
• Is used to build theories
• Takes a subjective approach
• Adopts an open and flexible approach
• The researcher is close to the respondents
• Interviews and focus groups are oftentimes used to collect word-based data.
• Generally, draws on small sample sizes
• Uses qualitative data analysis techniques (e.g. content analysis , thematic analysis , etc)
• Uses a deductive approach
• Is used to test theories
• Takes an objective approach
• Adopts a closed, highly planned approach
• The research is disconnected from respondents
• Surveys or laboratory equipment are often used to collect number-based data.
• Generally, requires large sample sizes
• Uses statistical analysis techniques to make sense of the data

Mixed methods -based research, as you’d expect, attempts to bring these two types of research together, drawing on both qualitative and quantitative data. Quite often, mixed methods-based studies will use qualitative research to explore a situation and develop a potential model of understanding (this is called a conceptual framework), and then go on to use quantitative methods to test that model empirically.

In other words, while qualitative and quantitative methods (and the philosophies that underpin them) are completely different, they are not at odds with each other. It’s not a competition of qualitative vs quantitative. On the contrary, they can be used together to develop a high-quality piece of research. Of course, this is easier said than done, so we usually recommend that first-time researchers stick to a single approach , unless the nature of their study truly warrants a mixed-methods approach.

The key takeaway here, and the reason we started by looking at the three options, is that it’s important to understand that each methodological approach has a different purpose – for example, to explore and understand situations (qualitative), to test and measure (quantitative) or to do both. They’re not simply alternative tools for the same job. 

Right – now that we’ve got that out of the way, let’s look at how you can go about choosing the right methodology for your research.

2. How to choose a research methodology

To choose the right research methodology for your dissertation or thesis, you need to consider three important factors . Based on these three factors, you can decide on your overarching approach – qualitative, quantitative or mixed methods. Once you’ve made that decision, you can flesh out the finer details of your methodology, such as the sampling , data collection methods and analysis techniques (we discuss these separately in other posts ).

The three factors you need to consider are:

• The nature of your research aims, objectives and research questions
• The methodological approaches taken in the existing literature
• Practicalities and constraints

Let’s take a look at each of these.

Factor #1: The nature of your research

As I mentioned earlier, each type of research (and therefore, research methodology), whether qualitative, quantitative or mixed, has a different purpose and helps solve a different type of question. So, it’s logical that the key deciding factor in terms of which research methodology you adopt is the nature of your research aims, objectives and research questions .

But, what types of research exist?

Broadly speaking, research can fall into one of three categories:

• Exploratory – getting a better understanding of an issue and potentially developing a theory regarding it
• Confirmatory – confirming a potential theory or hypothesis by testing it empirically
• A mix of both – building a potential theory or hypothesis and then testing it

As a rule of thumb, exploratory research tends to adopt a qualitative approach , whereas confirmatory research tends to use quantitative methods . This isn’t set in stone, but it’s a very useful heuristic. Naturally then, research that combines a mix of both, or is seeking to develop a theory from the ground up and then test that theory, would utilize a mixed-methods approach.

Let’s look at an example in action.

If your research aims were to understand the perspectives of war veterans regarding certain political matters, you’d likely adopt a qualitative methodology, making use of interviews to collect data and one or more qualitative data analysis methods to make sense of the data.

If, on the other hand, your research aims involved testing a set of hypotheses regarding the link between political leaning and income levels, you’d likely adopt a quantitative methodology, using numbers-based data from a survey to measure the links between variables and/or constructs .

So, the first (and most important thing) thing you need to consider when deciding which methodological approach to use for your research project is the nature of your research aims , objectives and research questions. Specifically, you need to assess whether your research leans in an exploratory or confirmatory direction or involves a mix of both.

The importance of achieving solid alignment between these three factors and your methodology can’t be overstated. If they’re misaligned, you’re going to be forcing a square peg into a round hole. In other words, you’ll be using the wrong tool for the job, and your research will become a disjointed mess.

If your research is a mix of both exploratory and confirmatory, but you have a tight word count limit, you may need to consider trimming down the scope a little and focusing on one or the other. One methodology executed well has a far better chance of earning marks than a poorly executed mixed methods approach. So, don’t try to be a hero, unless there is a very strong underpinning logic.

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Factor #2: The disciplinary norms

Choosing the right methodology for your research also involves looking at the approaches used by other researchers in the field, and studies with similar research aims and objectives to yours. Oftentimes, within a discipline, there is a common methodological approach (or set of approaches) used in studies. While this doesn’t mean you should follow the herd “just because”, you should at least consider these approaches and evaluate their merit within your context.

A major benefit of reviewing the research methodologies used by similar studies in your field is that you can often piggyback on the data collection techniques that other (more experienced) researchers have developed. For example, if you’re undertaking a quantitative study, you can often find tried and tested survey scales with high Cronbach’s alphas. These are usually included in the appendices of journal articles, so you don’t even have to contact the original authors. By using these, you’ll save a lot of time and ensure that your study stands on the proverbial “shoulders of giants” by using high-quality measurement instruments .

Of course, when reviewing existing literature, keep point #1 front of mind. In other words, your methodology needs to align with your research aims, objectives and questions. Don’t fall into the trap of adopting the methodological “norm” of other studies just because it’s popular. Only adopt that which is relevant to your research.

Factor #3: Practicalities

When choosing a research methodology, there will always be a tension between doing what’s theoretically best (i.e., the most scientifically rigorous research design ) and doing what’s practical , given your constraints . This is the nature of doing research and there are always trade-offs, as with anything else.

But what constraints, you ask?

When you’re evaluating your methodological options, you need to consider the following constraints:

• Data access
• Equipment and software
• Your knowledge and skills

Let’s look at each of these.

Constraint #1: Data access

The first practical constraint you need to consider is your access to data . If you’re going to be undertaking primary research , you need to think critically about the sample of respondents you realistically have access to. For example, if you plan to use in-person interviews , you need to ask yourself how many people you’ll need to interview, whether they’ll be agreeable to being interviewed, where they’re located, and so on.

If you’re wanting to undertake a quantitative approach using surveys to collect data, you’ll need to consider how many responses you’ll require to achieve statistically significant results. For many statistical tests, a sample of a few hundred respondents is typically needed to develop convincing conclusions.

So, think carefully about what data you’ll need access to, how much data you’ll need and how you’ll collect it. The last thing you want is to spend a huge amount of time on your research only to find that you can’t get access to the required data.

Constraint #2: Time

The next constraint is time. If you’re undertaking research as part of a PhD, you may have a fairly open-ended time limit, but this is unlikely to be the case for undergrad and Masters-level projects. So, pay attention to your timeline, as the data collection and analysis components of different methodologies have a major impact on time requirements . Also, keep in mind that these stages of the research often take a lot longer than originally anticipated.

Another practical implication of time limits is that it will directly impact which time horizon you can use – i.e. longitudinal vs cross-sectional . For example, if you’ve got a 6-month limit for your entire research project, it’s quite unlikely that you’ll be able to adopt a longitudinal time horizon. 

Constraint #3: Money

As with so many things, money is another important constraint you’ll need to consider when deciding on your research methodology. While some research designs will cost near zero to execute, others may require a substantial budget .

Some of the costs that may arise include:

• Software costs – e.g. survey hosting services, analysis software, etc.
• Promotion costs – e.g. advertising a survey to attract respondents
• Incentive costs – e.g. providing a prize or cash payment incentive to attract respondents
• Equipment rental costs – e.g. recording equipment, lab equipment, etc.
• Travel costs
• Food & beverages

These are just a handful of costs that can creep into your research budget. Like most projects, the actual costs tend to be higher than the estimates, so be sure to err on the conservative side and expect the unexpected. It’s critically important that you’re honest with yourself about these costs, or you could end up getting stuck midway through your project because you’ve run out of money.

Constraint #4: Equipment & software

Another practical consideration is the hardware and/or software you’ll need in order to undertake your research. Of course, this variable will depend on the type of data you’re collecting and analysing. For example, you may need lab equipment to analyse substances, or you may need specific analysis software to analyse statistical data. So, be sure to think about what hardware and/or software you’ll need for each potential methodological approach, and whether you have access to these.

Constraint #5: Your knowledge and skillset

The final practical constraint is a big one. Naturally, the research process involves a lot of learning and development along the way, so you will accrue knowledge and skills as you progress. However, when considering your methodological options, you should still consider your current position on the ladder.

Some of the questions you should ask yourself are:

• Am I more of a “numbers person” or a “words person”?
• How much do I know about the analysis methods I’ll potentially use (e.g. statistical analysis)?
• How much do I know about the software and/or hardware that I’ll potentially use?
• How excited am I to learn new research skills and gain new knowledge?
• How much time do I have to learn the things I need to learn?

Answering these questions honestly will provide you with another set of criteria against which you can evaluate the research methodology options you’ve shortlisted.

So, as you can see, there is a wide range of practicalities and constraints that you need to take into account when you’re deciding on a research methodology. These practicalities create a tension between the “ideal” methodology and the methodology that you can realistically pull off. This is perfectly normal, and it’s your job to find the option that presents the best set of trade-offs.

Recap: Choosing a methodology

In this post, we’ve discussed how to go about choosing a research methodology. The three major deciding factors we looked at were:

• Exploratory
• Confirmatory
• Combination
• Research area norms
• Hardware and software
• Your knowledge and skillset

If you have any questions, feel free to leave a comment below. If you’d like a helping hand with your research methodology, check out our 1-on-1 research coaching service , or book a free consultation with a friendly Grad Coach.

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This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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Choosing the Right Research Methodology: A Guide for Researchers

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Table of Contents

Choosing an optimal research methodology is crucial for the success of any research project. The methodology you select will determine the type of data you collect, how you collect it, and how you analyse it. Understanding the different types of research methods available along with their strengths and weaknesses, is thus imperative to make an informed decision.

Understanding different research methods:

There are several research methods available depending on the type of study you are conducting, i.e., whether it is laboratory-based, clinical, epidemiological, or survey based . Some common methodologies include qualitative research, quantitative research, experimental research, survey-based research, and action research. Each method can be opted for and modified, depending on the type of research hypotheses and objectives.

Qualitative vs quantitative research:

When deciding on a research methodology, one of the key factors to consider is whether your research will be qualitative or quantitative. Qualitative research is used to understand people’s experiences, concepts, thoughts, or behaviours . Quantitative research, on the contrary, deals with numbers, graphs, and charts, and is used to test or confirm hypotheses, assumptions, and theories. 

Qualitative research methodology:

Qualitative research is often used to examine issues that are not well understood, and to gather additional insights on these topics. Qualitative research methods include open-ended survey questions, observations of behaviours described through words, and reviews of literature that has explored similar theories and ideas. These methods are used to understand how language is used in real-world situations, identify common themes or overarching ideas, and describe and interpret various texts. Data analysis for qualitative research typically includes discourse analysis, thematic analysis, and textual analysis. 

Quantitative research methodology:

The goal of quantitative research is to test hypotheses, confirm assumptions and theories, and determine cause-and-effect relationships. Quantitative research methods include experiments, close-ended survey questions, and countable and numbered observations. Data analysis for quantitative research relies heavily on statistical methods.

Analysing qualitative vs quantitative data:

The methods used for data analysis also differ for qualitative and quantitative research. As mentioned earlier, quantitative data is generally analysed using statistical methods and does not leave much room for speculation. It is more structured and follows a predetermined plan. In quantitative research, the researcher starts with a hypothesis and uses statistical methods to test it. Contrarily, methods used for qualitative data analysis can identify patterns and themes within the data, rather than provide statistical measures of the data. It is an iterative process, where the researcher goes back and forth trying to gauge the larger implications of the data through different perspectives and revising the analysis if required.

When to use qualitative vs quantitative research:

The choice between qualitative and quantitative research will depend on the gap that the research project aims to address, and specific objectives of the study. If the goal is to establish facts about a subject or topic, quantitative research is an appropriate choice. However, if the goal is to understand people’s experiences or perspectives, qualitative research may be more suitable. 

Conclusion:

In conclusion, an understanding of the different research methods available, their applicability, advantages, and disadvantages is essential for making an informed decision on the best methodology for your project. If you need any additional guidance on which research methodology to opt for, you can head over to Elsevier Author Services (EAS). EAS experts will guide you throughout the process and help you choose the perfect methodology for your research goals.

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Home » Methodological Framework – Types, Examples and Guide

Methodological Framework – Types, Examples and Guide

Table of Contents

Methodological Framework

Definition:

Methodological framework is a set of procedures, methods, and tools that guide the research process in a systematic and structured manner. It provides a structure for conducting research, collecting and analyzing data, and drawing conclusions. The framework outlines the steps to be taken in a research project, including the research question, hypothesis, data collection methods, data analysis techniques, and the interpretation of the results.

Types of Methodological Framework

There are different types of methodological frameworks that researchers can use depending on the nature of their research question, the type of data they want to collect, and the research methodology they want to employ. Some common types of methodological frameworks include:

Quantitative Research Framework

This type of framework uses numerical data and statistical analysis to test hypotheses and draw conclusions. It involves the collection of structured data through surveys, experiments, or other quantitative methods.

Qualitative Research Framework

This framework is used to explore complex social phenomena and involves the collection of non-numerical data through methods such as interviews, observation, and document analysis. Qualitative research typically involves the use of open-ended questions and in-depth analysis of data.

Mixed Methods Research Framework

This framework combines quantitative and qualitative research methods to address research questions from multiple angles. It involves collecting both numerical and non-numerical data and using both statistical analysis and interpretive techniques to analyze the data.

Action Research Framework

This framework involves the collaboration between researchers and participants to identify and address practical problems in real-world settings. It involves a cyclical process of planning, action, reflection, and evaluation to improve a specific situation or practice.

Case Study Research Framework

This framework involves the in-depth investigation of a specific case or phenomenon, often using qualitative methods. It aims to understand the complexity of the case and draw generalizations from the findings.

How to Develop a Methodological Framework

Developing a methodological framework involves a series of steps that help to guide the research process in a systematic and structured manner. Here are the general steps involved in developing a methodological framework:

• Define the research problem: The first step is to clearly define the research problem or question. This involves identifying the purpose of the research, the research objectives, and the scope of the study.
• Select an appropriate research methodology: The research methodology selected should align with the research problem and research question. Common research methodologies include quantitative, qualitative, mixed-methods, case study, or action research.
• Develop the research design: Once the research methodology is selected, the research design should be developed. This involves identifying the data collection methods, sampling strategy, and data analysis techniques.
• Identify and justify the data collection methods: The data collection methods should be chosen based on the research methodology and research design. For example, if the research methodology is qualitative, data collection methods such as interviews, observation, or document analysis may be used.
• Identify and justify the data analysis techniques: The data analysis techniques should also be chosen based on the research methodology and research design. For quantitative research, this may include statistical analysis techniques, while for qualitative research, this may include interpretive techniques such as thematic analysis.
• Consider ethical considerations: Ethical considerations should be taken into account throughout the research process. This includes obtaining informed consent, ensuring confidentiality and privacy, and protecting the rights of participants.
• Identify potential limitations: It is important to identify potential limitations or biases that may affect the research findings. This includes discussing potential sources of error or bias in the research design, data collection methods, or data analysis techniques.
• Consider the significance and implications of the research: The significance and implications of the research findings should be considered, including their potential contributions to theory, practice, or policy.
• Refine the framework: The methodological framework should be refined based on feedback from peers, experts, or other stakeholders. This involves identifying any areas for improvement in the research design, data collection methods, or data analysis techniques.

Applications of Methodological Framework

Here are some examples of how a methodological framework can be applied in various fields:

• Social sciences: In social sciences, a methodological framework can be used to conduct research on various topics, such as psychology, sociology, and anthropology. For example, a researcher may use a qualitative research methodology to investigate the experiences and perceptions of individuals living in poverty.
• Natural sciences: In natural sciences, a methodological framework can be used to conduct research on various topics, such as biology, chemistry, and physics. For example, a researcher may use a quantitative research methodology to investigate the effects of different fertilizers on crop yield.
• Engineering : In engineering, a methodological framework can be used to design and test new technologies or systems. For example, a researcher may use a mixed-methods research methodology to investigate the usability and effectiveness of a new software application.
• Business : In business, a methodological framework can be used to conduct research on various topics, such as marketing, management, and finance. For example, a researcher may use a quantitative research methodology to investigate the relationship between customer satisfaction and customer loyalty.

When to use Methodological Framework

Here are some specific situations when a methodological framework can be particularly useful:

• When conducting original research: If you are conducting original research, a methodological framework can help ensure that your study is designed in a structured and systematic manner, which increases the reliability and validity of the findings.
• When conducting a literature review: A methodological framework can be used when conducting a literature review to ensure that the review is conducted in a structured and systematic manner. This helps to identify relevant studies and synthesize the findings from multiple studies.
• When replicating previous research: If you are replicating previous research, a methodological framework can help ensure that the replication is conducted in a rigorous and systematic manner. This helps to ensure that the findings are consistent with the original study.
• When developing a research proposal : A methodological framework can be used when developing a research proposal to ensure that the proposal is designed in a structured and systematic manner. This helps to convince reviewers that the study is well-designed and likely to produce valid and reliable findings.
• When teaching research methods: A methodological framework can be used when teaching research methods to provide students with a structured approach to designing and conducting research. This helps to ensure that students understand the research process and are able to conduct research in a rigorous and systematic manner.

Examples of Methodological Framework

Here are some real-time examples of how methodological frameworks are used in various fields:

• In healthcare research, a mixed-methods research framework can be used to evaluate the effectiveness of a new treatment approach. The quantitative component may involve measuring the changes in patient outcomes, while the qualitative component may involve interviewing patients and healthcare providers to understand their perspectives on the treatment.
• In engineering, a design science research framework can be used to develop and test a new software application. The researchers may identify a problem with existing software, develop a new solution, and test it in a real-world setting.
• In business, a case study research framework can be used to understand the impact of a new marketing strategy on a particular company. The researcher may analyze data from the company’s financial statements, conduct interviews with key stakeholders, and observe the implementation of the strategy in order to understand its effectiveness.
• In education, an action research framework can be used to improve teaching practices. A teacher may identify a problem in their classroom, develop a plan to address the problem, implement the plan, and reflect on the results in order to improve their teaching practices.
• In social science research, a grounded theory framework can be used to develop a theory from qualitative data. A researcher may collect data from interviews or observations and use that data to develop a theory about a particular phenomenon.

Purpose of Methodological Framework

The purpose of a methodological framework is to provide a structured and systematic approach to designing, conducting, and analyzing research. The framework serves as a guide for researchers to follow, ensuring that the research is conducted in a rigorous and transparent manner, and that the results are reliable, valid, and generalizable. Some key purposes of a methodological framework are:

• To provide a clear and concise description of the research process: The framework outlines the steps involved in conducting the research, including the research question, data collection methods, data analysis, and interpretation of results.
• To ensure that the research is conducted in a systematic and rigorous manner : The framework provides a structured approach to the research, helping to ensure that the research is conducted in a way that minimizes bias and maximizes the accuracy and reliability of the results.
• To improve the quality of the research: The framework helps to ensure that the research is of high quality and meets the standards of the field. This can help to increase the impact and relevance of the research.
• To increase transparency and replicability: The framework provides a clear and transparent description of the research process, making it easier for others to understand and replicate the research.
• To facilitate communication and collaboration: The framework provides a common language and structure for researchers to communicate their research findings and collaborate with others in the field.

Characteristics of Methodological Framework

Here are some common characteristics of a methodological framework:

• Systematic : A methodological framework is a systematic approach to research that provides a clear and structured guide for researchers to follow. It outlines the steps involved in conducting research, from developing a research question to analyzing and interpreting data.
• Transparent : A methodological framework promotes transparency in research by providing a clear and concise description of the research process. This helps to ensure that others can understand and replicate the research.
• Flexible : A methodological framework should be flexible enough to accommodate different research designs and methodologies. It should allow for modifications based on the specific research question, data collection methods, and analysis techniques.
• Contextual : A methodological framework should take into account the contextual factors that may impact the research. This includes the cultural, social, and historical context of the research, as well as the research setting and the characteristics of the participants.
• Rigorous : A methodological framework promotes rigor in research by ensuring that the research is conducted in a systematic and unbiased manner. It includes strategies for minimizing bias and ensuring the validity and reliability of the findings.
• Theory-driven: A methodological framework should be grounded in theoretical concepts and principles that guide the research. This helps to ensure that the research is relevant and meaningful, and that the findings can be applied to broader theoretical frameworks.

Advantages of Methodological Framework

There are several advantages to using a methodological framework in research:

• Structured approach: A methodological framework provides a clear and structured approach to conducting research, which helps to ensure that the research is conducted in a systematic and rigorous manner.
• Increased efficiency: A methodological framework can increase the efficiency of the research process by providing a clear roadmap for researchers to follow, reducing the time and resources required to conduct the research.
• Reproducibility: A methodological framework promotes reproducibility by providing a clear and transparent description of the research process, making it easier for others to replicate the research.
• Improved quality : A methodological framework can improve the quality of research by ensuring that the research is conducted in a rigorous and transparent manner, and that the results are reliable and valid.
• Standardization : A methodological framework promotes standardization in research, helping to ensure that the research meets the standards of the field and is comparable to other research studies.
• Better communication : A methodological framework provides a common language and structure for researchers to communicate their research findings, facilitating communication and collaboration among researchers.
• Theory development: A methodological framework can contribute to the development of theory by providing a structured approach to data collection and analysis that is grounded in theoretical concepts and principles.

Limitations of Methodological Framework

While there are many advantages to using a methodological framework in research, there are also some limitations to be aware of:

• Flexibility : While a methodological framework can provide a structured approach to research, it may also limit flexibility in the research process. Researchers may feel constrained by the framework and unable to deviate from the prescribed steps, which may limit their ability to adapt to unexpected findings or changes in the research context.
• Applicability : Methodological frameworks may not be equally applicable to all research questions and contexts. Some frameworks may be more suitable for certain types of research than others, and researchers may need to modify or adapt the framework to fit their specific research question and context.
• Complexity : Some methodological frameworks can be complex and difficult to understand, particularly for novice researchers. This may limit their usefulness in certain contexts or for certain types of research.
• Time and resource constraints : Using a methodological framework may require additional time and resources to fully implement, which may not be feasible for all researchers or research projects.
• Overemphasis on methodology: While a methodological framework can provide a structured approach to research methodology, it may overemphasize the importance of methodology over other aspects of research, such as theoretical frameworks or ethical considerations.

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FAQ: Research Design & Method

What is the difference between Research Design and Research Method?

Research design is a plan to answer your research question.  A research method is a strategy used to implement that plan.  Research design and methods are different but closely related, because good research design ensures that the data you obtain will help you answer your research question more effectively.

Which research method should I choose ?

It depends on your research goal.  It depends on what subjects (and who) you want to study.  Let's say you are interested in studying what makes people happy, or why some students are more conscious about recycling on campus.  To answer these questions, you need to make a decision about how to collect your data.  Most frequently used methods include:

• Observation / Participant Observation
• Focus Groups
• Experiments
• Secondary Data Analysis / Archival Study
• Mixed Methods (combination of some of the above)

One particular method could be better suited to your research goal than others, because the data you collect from different methods will be different in quality and quantity.   For instance, surveys are usually designed to produce relatively short answers, rather than the extensive responses expected in qualitative interviews.

What other factors should I consider when choosing one method over another?

Time for data collection and analysis is something you want to consider.  An observation or interview method, so-called qualitative approach, helps you collect richer information, but it takes time.  Using a survey helps you collect more data quickly, yet it may lack details.  So, you will need to consider the time you have for research and the balance between strengths and weaknesses associated with each method (e.g., qualitative vs. quantitative).

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Writing a Methodology for your Dissertation | Complete Guide & Steps

What is a methodology.

The methodology is perhaps the most challenging and laborious part of the dissertation . Essentially, the methodology helps in understanding the broad, philosophical approach behind the methods of research you chose to employ in your study. The research methodology elaborates on the ‘how’ part of your research.

This means that your methodology chapter should clearly state whether you chose to use quantitative or qualitative data collection techniques or a mix of both.

Your research methodology should explain the following:

• What was the purpose of your research?
• What type of research method was used?
• What were the data-collecting methods?
• How did you analyse the data?
• What kind of resources were used in your research?
• Why did you choose these methods?

You will be required to provide justifications as to why you preferred a certain method over the others. If you are trying to figure out exactly how to write methodology or the structure of a methodology for a dissertation, this article will point you in the right direction.

Students must be sure of why they chose a certain research method over another. “I figured out” or “In my opinion” statements will not be an acceptable justification. So, you will need to come up with concrete academic reasons for your selection of research methods.

What are the Standard Contents of a Research Methodology?

The methodology generally acts as a guideline or plan for exactly how you intend to carry out your research. This is especially true for students who must submit their methodology chapter before carrying out the research.

Your methodology should link back to the literature review and clearly state why you chose certain data collection and analysis methods for your research/dissertation project.

The methodology chapter consists of the following:

• Research Design
• Philosophical Approach
• Data Collection Methods
• Research Limitations
• Ethical Considerations (If Any)
• Data Analysis Methods

For those who are submitting their dissertation as a single paper, their methodology should also touch on any modifications they had to make as their work progressed.

However, it is essential to provide academic justifications for all choices made by the researcher.

How to Choose your Dissertation Methodology and Research Design?

The theme of your research methodology chapter should be related to your literature review and research question (s).

You can visit your college or university library to find textbooks and articles that provide information about the commonly employed research methods .

An intensive reading of such books can help you devise your research philosophy and choose the appropriate methods. Any limitations or weaknesses of your chosen research approach should also be explained, as well as the strategies to overcome them.

To research well, you should read well! Read as many research articles (from reputed journals) as you can. Seeing how other researchers use methods in their studies and why will help you justify, in the long run, your own research method(s).

Regardless of the chosen research approach, you will find researchers who either support it or don’t. Use the arguments for and against articulated in the literature to clarify why you decided to choose the selected research design and why the research limitations are irrelevant to your research.

How to Structure your Dissertation Methodology?

The typical structure of the methodology chapter is as follows:

• Research Design And Strategy
• Methods Of Data Collection And Data Analysis
• Ethical Considerations, Reliability , Limitations And Generalisability

In research jargon, generalisability is termed external validity . It means how generalisable your research findings are to other contexts, places, times, people, etc. External validity is expected to be significantly high, especially in quantitative studies.

According to USC-Research Guides (2017) , a research design’s primary function is to enable the researcher to answer the research questions through evidence effectively. Generally, this section will shed light on how you collected your data.

The researcher will have to justify their choice of data collection methods, such as the one that was reviewed, the use of data tools (interviews, phone surveys, questionnaires, observation, online surveys , etc.) and the like.

Moreover, data sampling choice should also be clearly explained with a focus on how you chose the ethnicity, group, profession and age of the participants.

• What type of questions do you intend to ask the respondents?
• How will they help to answer your research questions ?
• How will they help to test the hypothesis of the dissertation?

It is recommended to prepare these questions at the start of your research. You should develop your research problem and questions. This approach can allow the room to change or modify research questions if your data collection methods do not give the desired results.

It’s a good practice to keep referring to your research questions whilst planning or writing the research design section. This will help your reader recall what the research is about; why you have done what you did. Even though this technique is recommended to be applied at the start of every section within a dissertation, it’s especially beneficial in the methodology section.

In short, you will need to make sure that the data you are going to collect relates to the topic you are exploring. The complexity and length of the research design section will vary depending on your academic subject and the scope of your research, but a well-written research design will have the following characteristics:

• It sheds light on alternative research design options and justifies why your chosen design is the best to address the research problem.
• Clearly specifies the research questions that the research aims to address or the hypothesis to validate.
• Explain how the collected data will help address the research problem and discusses your research methodology to collect the data.

Philosophical Approach Behind Writing a Methodology

This will discuss your chosen philosophy to strengthen your research and the research model. Commonly employed philosophies in academia are

• Interpretivism,
• Positivism/Post-Positivism
• Constructivism

There are several other research philosophies that you could adopt.

The choice of philosophy will depend on many factors, including your academic subject and the type and complexity of the research study. Regardless of which philosophy is used, you will be required to make different assumptions about the world.

Once you have chosen your research philosophy, the next step will describe your research context to answer all the questions, including when, where, why, how and what of your research.

Essentially, as a researcher, you will be required to decide whether you will be using a qualitative method, a quantitative method or a mix of both.

Did you know?

Using both qualitative and quantitative methods leads to the use of a mixed-methods approach. This approach also goes by another seldom-used name: eclectic approach.

The process of data collection is different for each method. Typically, you would want to decide whether you will adopt the positivist approach, defining your hypothesis and testing it against reality.

If this is the case, you will be required to take the quantitative approach, collecting numerical data at a large scale (from 30 or more respondents) and testing your hypotheses with this data.

Collecting data from at least 30 respondents/participants ensures reliable statistical analysis . This is especially true for quantitative studies. If the data contains less than 30 responses, it won’t be enough to carry out reliable statistical analyses on such data.

The other option for you would be to base your research on a qualitative approach, which will point you in a direction where you will be investigating broader areas by identifying people’s emotions and perceptions of a subject.

With a qualitative approach, you will have to collect responses from respondents and look at them in all their richness to develop theories about the field you are exploring.

Finally, you can also use a mix of qualitative and quantitative methods (which is becoming increasingly popular among researchers these days). This method is beneficial if you are interested in putting quantitative data into a real-world context or reflecting different perspectives on a subject.

Research philosophy in the ‘research onion.’

Methods of Data Collection and Data Analysis

This section will require you to clearly specify how you gathered the data and briefly discuss the tools you used to analyse it. For example, you may choose to conduct surveys and/or interviews as part of the data collection process.

Similarly, if you used software such as Excel or SPSS to process the data , you will have to justify your software choice. In this section of your methodology chapter , you will also have to explain how you arrived at your findings and how reliable they are.

It is important to note that your readers or supervisor would want to see a correlation between your findings and the hypothesis/research questions you based your study on at the very beginning.

Your supervisor or dissertation research assistant can play a key role in helping you write the methodology chapter according to established research standards. So, keep your supervisor in the loop to get their contributions and recommendations throughout the process.

In this section, you should briefly describe the methods you’ve used to analyse the data you’ve collected.

Qualitative Methods

The qualitative method includes analysing language, images, audio, videos, or any textual data (textual analysis). The following types of methods are used in textual analysis .

Discourse analysis:

Discourse analysis is an essential aspect of studying a language and its uses in day-to-day life.

Content analysis:

It is a method of studying and retrieving meaningful information from documents Thematic analysis:

It’s a method of identifying patterns of themes in the collected information, such as face-to-face interviews, texts, and transcripts.

Example: After collecting the data, it was checked thoroughly to find the missing information. The interviews were transcribed, and textual analysis was conducted. The repetitions of the text, types of colours displayed, and the tone of the speakers was measured.

Quantitative Methods

Quantitative data analysis is used for analysing numerical data. Include the following points:

• The methods of preparing data before analysing it.
• Which statistical test you have used? (one-ended test, two-ended test)
• The type of software you’ve used.

Ethical Considerations, Reliability and Limitations of a Dissertation Methodology

Other important sections of your methodology are:

Ethical Considerations

Always consider how your research will influence other individuals who are beyond the scope of the study. This is especially true for human subjects. As a researcher, you are always expected to make sure that your research and ideas do not harm anyone in any way.Discussion concerning data protection, data handling and data confidentiality will also be included in this brief segment.

• How did you ensure your participants’/respondents’ anonymity and/or confidentiality?
• Did you remove any identifiable markers after conducting the study (post-test stage) so that readers wouldn’t be able to guess the identity of the participant/respondent?
• Was personal information collected according to the purpose of the research? (For instance, asking respondents their age when it wasn’t even relevant in the study). All such ethical considerations need to be mentioned.

Even though there is no established rule to include ethical considerations and limitations within the methodology section, it’s generally recommended to include it in this section, as it makes more sense than including it, say, after the discussions section or within the conclusion.

This is mainly because limitations almost always occur in the methodology stage of research. And ethical considerations need to be taken while sampling, an important aspect of the research methodology.

Here are some examples of ethical issues that you should be mindful of

• Does your research involve participants recalling episodes of suffering and pain?
• Are you trying to find answers to questions considered culturally sensitive either by participants or the readers?
• Are your research, analysis and findings based on a specific location or a group of people?

All such issues should be categorically addressed and a justification provided for your chosen research methodology by highlighting the study’s benefits.

Reliability

Is your research study and findings reliable for other researchers in your field of work? To establish yourself as a reliable researcher, your study should be both authentic and reliable.

Reliability means the extent to which your research can yield similar results if it was replicated in another setting, at a different time, or under different circumstances. If replication occurs and different findings come to light, your (original) research would be deemed unreliable.

Limitations

Good dissertation writers will always acknowledge the limitations of their research study. Limitations in data sampling can decrease your results’ reliability.

A classic example of research limitation is collecting responses from people of a certain age group when you could have targeted a more representative cross-section of the population.Be humble and admit to your own study’s limitations. Doing so makes your referees, editors, supervisors, readers and anyone else involved in the research enterprise aware that you were also aware of the things that limited your study.

Limitations are NOT the same as implications. Sometimes, the two can be confused. Limitations lead to implications, that is, due to a certain factor being absent in the study (limitation) for instance, future research could be carried out in a setting where that factor is present (implication).

Dissertation Methodology Example

At this point, you might have a basic understanding of how to craft a well-written, organised, accurate methodology section for your dissertation. An example might help bring all the aforementioned points home. Here is a dissertation methodology example in pdf to better understand how to write methodology for a dissertation.

Sample Dissertation Methodology

Does your Research Methodology Have the Following?

• Great Research/Sources
• Perfect Language
• Accurate Sources

If not, we can help. Our panel of experts makes sure to keep the 3 pillars of Research Methodology strong.

Types of Methodologies

A scientific or lab-based study.

A methodology section for a scientific study will need to elaborate on reproducibility and meticulousness more than anything else. If your methods have obvious flaws, the readers are not going to be impressed. Therefore, it is important to ensure that your chosen research methodology is vigorous in nature.

Any information related to the procedure, setup and equipment should be clearly stated so other researchers in your field of study can work with the same method in the future if needed.

Variables that are likely to falsify your data must be taken into the equation to avoid ambiguities. It is recommended to present a comprehensive strategy to deal with these variables when gathering and analysing the data and drawing conclusions.

Statistical models employed as part of your scientific study will have to be justified, and so your methodology should include details of those statistical models.

Another scholar in the future might use any aspect of your methodology as the starting point for their research. For example, they might base their research on your methodology but analyse the data using other statistical models. Hence, this is something you should be mindful of.

Behavioural or Social Sciences-Based Dissertation

Like scientific or lab-based research, a behavioural and social sciences methodology needs to be built along the same lines. The chosen methodology should demonstrate reproducibility and firmness so other scholars can use your whole dissertation methodology or a part of it based on their research needs.

But there are additional issues that the researcher must take into consideration when working with human subjects. As a starting point, you will need to decide whether your analysis will be based on qualitative data, quantitative data or mixed-method of research, where qualitative data is used to provide contextual background to quantitative data or the other way around.

Here are some questions for you to consider:

• Will you observe the participants undertaking some activity, ask them to fill out a questionnaire, or record their responses during the interviews ?
• Will you base your research on existing evidence and datasets and avoid working with human subjects?
• What are the length, width, and reach of your data? Define its scope.
• Is the data highly explicit to the location or cultural setting you carried your study in, or can it be generalised to other situations and frameworks (reliability)? What are your reasons and justifications?

While you will be required to demonstrate that you have taken care of the above questions, it is equally important to make sure that you address your research study’s ethical issues side-by-side.

Of course, the first step in that regard will be to obtain formal approval for your research design from the ethics bodies (such as IRBs – institutional review boards), but still, there will be many more issues that could trigger a sense of grief and discomfort among some of the readers.

Humanities and Arts Dissertation Project

The rigour and dependability of the methods of research employed remain undisputed and unquestionable for humanities and arts-based dissertations as well. However, the way you convince your readers of your dissertation’s thoroughness is slightly different.

Unlike social science dissertation or a scientific study, the methodology of dissertations in arts and humanities subjects needs to be directly linked to the literature review regardless of how innovative your dissertation’s topic might be.

For example, you could demonstrate the relationship between A and B to discover a new theoretical background or use existing theories in a new framework.

The methodology section of humanities and arts-based dissertations is less complex, so there might be no need to justify it in detail. Students can achieve a seamless transition from the literature review to the analysis section.

However, like with every other type of research methodology, it is important to provide a detailed justification of your chosen methodology and relate it to the research problem.

Failing to do so could leave some readers unconvinced of your theoretical foundations’ suitability, which could potentially jeopardise your whole research.

Make sure that you are paying attention to and giving enough information about the social and historical background of the theoretical frameworks your research methodology is based on. This is especially important if there is an essential difference of opinion between your research and the research done on the subject in the past.

A justification of why opposing schools of thought disagree and why you still went ahead to use aspects of these schools of thought in your methodology should be clearly presented for the readers to understand how they would support your readings.

A Dissertation in Creative Arts

Some degree programs in the arts allow students to undertake a portfolio of artworks or creative writing rather than produce an extended dissertation research project.However, in practice, your creative research will be required to be submitted along with a comprehensive evaluative paper, including background information and an explanation that hypothesises your innovative exercise.

While this might seem like an easy thing to do, critical evaluation of someone’s work is highly complex and notorious in nature. This further reinforces the argument of developing a rigorous methodology and adhering to it.

As a scholar, you will be expected to showcase the ability to critically analyse your methodology and show that you are capable of critically evaluating your own creative work.Such an approach will help you justify your method of creating the work, which will give the readers the impression that your research is grounded in theory.

What to Avoid in Methodology?

All chapters of a dissertation paper are interconnected. This means that there will undoubtedly be some information that would overlap between the different chapters of the dissertation .

For example, some of the text material may seem appropriate to both the literature review and methodology sections; you might even end up moving information from pillar to post between different chapters as you edit and improve your dissertation .

However, make sure that you are not making the following a part of your dissertation methodology, even though it may seem appropriate to fit them in there:

A Long Review of Methods Employed by Previous Researchers

It might seem relevant to include details of the models your dissertation methodology is based on. However, a detailed review of models and precedents used by other scholars and theorists will better fit in the literature review chapter, which you can link back to. This will help the readers understand why you decided to go in favour of or against a certain tactic.

Unnecessary Details Readers Might Not be Interested In

There is absolutely no need to provide extensive details of things like lab equipment and experiment procedures. Having such information in the methodology chapter would discourage some readers who might not be interested in your equipment, setup, lab environment, etc.

Your aim as the author of the document will be to retain the readers’ interest and make the methodology chapter as readable as possible.

While it is important to get all the information relating to how others can reproduce your experiment, it is equally important to ensure your methodology section isn’t unnecessarily long. Again, additional information is better to be placed within the appendices chapter.

The methodology is not the section to provide raw data, even if you are only discussing the data collection process. All such information should be moved to the appendices section.

Even if you feel some finding or numerical data is crucial to be presented within the methodology section, you can, at most, make brief comments about such data. Its discussion, however, is only allowed in the discussions section .

What Makes your Methodology Stand Out?

The factors which can determine if your dissertation methodology is ‘great’ depend on many factors, including the level of study you are currently enrolled in.

Undergraduate dissertations are, of course, less complex and less demanding. At most universities in the UK, undergraduate students are required to exhibit the ability to conduct thorough research as they engage for the first time with theoretical and conceptual frameworks in their chosen research area.

As an undergraduate student, you will be expected to showcase the capacity to reproduce what you have learnt from theorists in your academic subject, transform your leanings into a methodology that would help you address the research problem, and test the research hypothesis, as mentioned in the introduction chapter.

A great undergraduate-level dissertation will incorporate different schools of thought and make a valuable contribution to existing knowledge. However, in general, undergraduate-level dissertations’ focus should be to show thorough desk-based and independent research skills.

Postgraduate dissertation papers are much more compound and challenging because they are expected to make a substantial contribution to existing knowledge.

Depending on the academic institute, some postgraduate students are even required to develop a project published by leading academic journals as an approval of their research skills.

It is important to recognise the importance of a postgraduate dissertation towards building your professional career, especially if your work is considered impactful in your area of study and receives citations from multiple scholars, enhancing your reputation in academic communities.

Even if some academics cite your literature review and conclusion in their own work, it is a well-known fact that your methodology framework will result in many more citations regardless of your academic subject.

Other scholars and researchers in your area of study are likely to give much more value to a well-crafted methodology, especially one they can use as the starting point for their own research.

Of course, they can alter, refine and enhance your methodology in one way or another. They can even apply your methodological framework to a new data set or apply it in a completely new situation that is irrelevant to your work.

Finally, postgraduate dissertations are expected to be highly convincing and demonstrate in-depth engagement. They should be reproducible and show rigour, so the findings and conclusions can be regarded as authentic and reliable among scientific and academic communities.

The methodology is the door to success when it comes to dissertation projects. An original methodology that takes into consideration all aspects of research is likely to have an impact on the field of study.

As a postgraduate student, you should ask yourself, Is my dissertation methodology reproducible and transferable? Producing a methodology that others can reproduce in the future is as important as answering research questions .

The methodology chapter can either make or break the grade of your research/dissertation paper. It’s one of the research elements that leave a memorable impression on your readers. So, it would help if you took your time when it comes to choosing the right design and philosophical approach for your research.

Always use authentic academic sources and discuss your plans in detail with your supervisor if you believe your research design or approach has flaws in it.

Did this article help you learn how to write a dissertation methodology and how to structure a dissertation methodology? Let us know in your comments.

Are you struggling to create a thorough and well-rounded dissertation methodology?

Avail of our dissertation writing services ! At ResearchProspect, we have Master’s and PhD qualified dissertation writers for all academic subjects, so you can be confident that the writer we will assign to your dissertation order will be an expert in your field of study. They can help you with your whole dissertation or just a part of it. You decide how much or how little help you need.

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Are you looking for intriguing and trending dissertation topics? Get inspired by our list of free dissertation topics on all subjects.

Looking for an easy guide to follow to write your essay? Here is our detailed essay guide explaining how to write an essay and examples and types of an essay.

Learn about the steps required to successfully complete their research project. Make sure to follow these steps in their respective order.

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Home Market Research

What is Research: Definition, Methods, Types & Examples

The search for knowledge is closely linked to the object of study; that is, to the reconstruction of the facts that will provide an explanation to an observed event and that at first sight can be considered as a problem. It is very human to seek answers and satisfy our curiosity. Let’s talk about research.

Content Index

What is Research?

What are the characteristics of research.

• Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, “research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.”

Inductive methods analyze an observed event, while deductive methods verify the observed event. Inductive approaches are associated with qualitative research , and deductive methods are more commonly associated with quantitative analysis .

Research is conducted with a purpose to:

• Identify potential and new customers
• Understand existing customers
• Set pragmatic goals
• Develop productive market strategies
• Address business challenges
• Put together a business expansion plan
• Identify new business opportunities
• Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.
• The analysis is based on logical reasoning and involves both inductive and deductive methods.
• Real-time data and knowledge is derived from actual observations in natural settings.
• There is an in-depth analysis of all data collected so that there are no anomalies associated with it.
• It creates a path for generating new questions. Existing data helps create more research opportunities.
• It is analytical and uses all the available data so that there is no ambiguity in inference.
• Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.

What is the purpose of research?

There are three main purposes:

• Exploratory: As the name suggests, researchers conduct exploratory studies to explore a group of questions. The answers and analytics may not offer a conclusion to the perceived problem. It is undertaken to handle new problem areas that haven’t been explored before. This exploratory data analysis process lays the foundation for more conclusive data collection and analysis.

LEARN ABOUT: Descriptive Analysis

• Descriptive: It focuses on expanding knowledge on current issues through a process of data collection. Descriptive research describe the behavior of a sample population. Only one variable is required to conduct the study. The three primary purposes of descriptive studies are describing, explaining, and validating the findings. For example, a study conducted to know if top-level management leaders in the 21st century possess the moral right to receive a considerable sum of money from the company profit.

LEARN ABOUT: Best Data Collection Tools

• Explanatory: Causal research or explanatory research is conducted to understand the impact of specific changes in existing standard procedures. Running experiments is the most popular form. For example, a study that is conducted to understand the effect of rebranding on customer loyalty.

Here is a comparative analysis chart for a better understanding:

It begins by asking the right questions and choosing an appropriate method to investigate the problem. After collecting answers to your questions, you can analyze the findings or observations to draw reasonable conclusions.

When it comes to customers and market studies, the more thorough your questions, the better the analysis. You get essential insights into brand perception and product needs by thoroughly collecting customer data through surveys and questionnaires . You can use this data to make smart decisions about your marketing strategies to position your business effectively.

To make sense of your study and get insights faster, it helps to use a research repository as a single source of truth in your organization and manage your research data in one centralized data repository .

Types of research methods and Examples

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods .

Qualitative research is a method that collects data using conversational methods, usually open-ended questions . The responses collected are essentially non-numerical. This method helps a researcher understand what participants think and why they think in a particular way.

Types of qualitative methods include:

• One-to-one Interview
• Focus Groups
• Ethnographic studies
• Text Analysis

Quantitative methods deal with numbers and measurable forms . It uses a systematic way of investigating events or data. It answers questions to justify relationships with measurable variables to either explain, predict, or control a phenomenon.

Types of quantitative methods include:

• Survey research
• Descriptive research
• Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

Remember, it is only valuable and useful when it is valid, accurate, and reliable. Incorrect results can lead to customer churn and a decrease in sales.

It is essential to ensure that your data is:

• Valid – founded, logical, rigorous, and impartial.
• Accurate – free of errors and including required details.
• Reliable – other people who investigate in the same way can produce similar results.
• Timely – current and collected within an appropriate time frame.
• Complete – includes all the data you need to support your business decisions.

Gather insights

• Identify the main trends and issues, opportunities, and problems you observe. Write a sentence describing each one.
• Keep track of the frequency with which each of the main findings appears.
• Make a list of your findings from the most common to the least common.
• Evaluate a list of the strengths, weaknesses, opportunities, and threats identified in a SWOT analysis .
• Prepare conclusions and recommendations about your study.
• Act on your strategies
• Look for gaps in the information, and consider doing additional inquiry if necessary
• Plan to review the results and consider efficient methods to analyze and interpret results.

Review your goals before making any conclusions about your study. Remember how the process you have completed and the data you have gathered help answer your questions. Ask yourself if what your analysis revealed facilitates the identification of your conclusions and recommendations.

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Principles of Social Research Methodology

• © 2022
• M. Rezaul Islam 0 ,
• Niaz Ahmed Khan 1 ,
• Rajendra Baikady 2

Centre for Family and Child Studies, Research Institute of Humanities and Social Sciences, University of Sharjah, Sharjah, United Arab Emirates

You can also search for this editor in PubMed   Google Scholar

Department of Development Studies, University of Dhaka, Dhaka, Bangladesh

Department of social work, school of humanities, university of johannesburg, johannesburg, south africa.

• Emphasizes the essentials and fundamentals of research methodologies
• Covers the entire research process, beginning with the conception of the research problem
• Combines theory and practical application to familiarize the reader with the logic of research design

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About this book

This book is a definitive, comprehensive understanding to social science research methodology. It covers both qualitative and quantitative approaches. The book covers the entire research process, beginning with the conception of the research problem to publication of findings. The text combines theory and practical application to familiarize the reader with the logic of research design, the logic and techniques of data analysis, and the fundamentals and implications of various data collection techniques. Organized in seven sections and easy to read chapters, the text emphasizes the importance of clearly defined research questions and well-constructed practical explanations and illustrations. A key contribution to the methodology literature, the book is an authoritative resource for policymakers, practitioners, graduate and advanced research students, and educators in all social science disciplines.

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Introduction

The potential of working hypotheses for deductive exploratory research

Research Design and Methodology

• Social Science Research
• Social Research Methods
• Qualitative Research
• Quantitative Research
• Mixed Method Research
• Research Design

Table of contents (35 chapters)

Front matter, introduction to social research, inquiry: a fundamental concept for scientific investigation.

M. Rezaul Islam

Research: Meaning and Purpose

• Kazi Abusaleh, Akib Bin Anwar

Social Research: Definitions, Types, Nature, and Characteristics

• Kanamik Kani Khan, Md. Mohsin Reza

Theory in Social Research

• Mumtaz Ali, Maya Khemlani David, Kuang Ching Hei

Philosophy of Social Science and Research Paradigms

Inductive and/or deductive research designs.

• Md. Shahidul Haque
• Premalatha Karupiah

Critical Theory in Social Research: A Theoretical and Methodological Outlook

• Ashek Mahmud, Farhana Zaman

Narrative Inquiry, Phenomenology, and Grounded Theory in Qualitative Research

• Rabiul Islam, Md. Sayeed Akhter
• Md. Rafiqul Islam

Quantitative Research Approach

Designing research proposal in quantitative approach.

• Md. Rezaul Karim

Experimental Method

• Syed Tanveer Rahman, Md. Rabiul Islam

Social Survey Method

• Isahaque Ali, Azlinda Azman, Shahid Mallick, Tahmina Sultana, Zulkarnain A. Hatta

Survey Questionnaire

• Shofiqur Rahman Chowdhury, Mohammad Ali Oakkas, Faisal Ahmmed

Interview Method

• Hazreena Hussein

Sampling Techniques for Quantitative Research

• Moniruzzaman Sarker, Mohammed Abdulmalek AL-Muaalemi

Data Analysis Techniques for Quantitative Study

Editors and affiliations.

Niaz Ahmed Khan

Rajendra Baikady

About the editors

Bibliographic information.

Book Title : Principles of Social Research Methodology

Editors : M. Rezaul Islam, Niaz Ahmed Khan, Rajendra Baikady

DOI : https://doi.org/10.1007/978-981-19-5441-2

Publisher : Springer Singapore

eBook Packages : Social Sciences

Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022

Hardcover ISBN : 978-981-19-5219-7 Published: 27 October 2022

Softcover ISBN : 978-981-19-5524-2 Published: 28 October 2023

eBook ISBN : 978-981-19-5441-2 Published: 26 October 2022

Edition Number : 1

Number of Pages : XXXI, 508

Number of Illustrations : 24 b/w illustrations, 45 illustrations in colour

Topics : Social Work , Education, general

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• Open access
• Published: 01 July 2024

Using community-based participatory research methods to build the foundation for an equitable integrated health data system within a Canadian urban context

• Dianne Fierheller 1 ,
• Casey Chu   ORCID: orcid.org/0000-0001-8942-3939 1 ,
• Chelsea D’Silva 1 ,
• Arvind Krishendeholl 1 , 8 ,
• Abdul Arham 3 ,
• Angela Carter 2 ,
• Keddone Dias 4 ,
• Isaac Francis 5 ,
• Marcia Glasgow 6 ,
• Gurpreet Malhotra 7 ,
• Ian Zenlea 1 , 8 &
• Laura C. Rosella 1 , 8  

International Journal for Equity in Health volume  23 , Article number:  131 ( 2024 ) Cite this article

Metrics details

Health inequalities amplified by the COVID-19 pandemic have disproportionately affected racialized and equity-deserving communities across Canada. In the Municipality of Peel, existing data, while limited, illustrates that individuals from racialized and equity-deserving communities continue to suffer, receive delayed care, and die prematurely. In response to these troubling statistics, grassroots community advocacy has called on health systems leaders in Peel to work with community and non-profit organizations to address the critical data and infrastructure gaps that hinder addressing the social determinants of health in the region. To support these advocacy efforts, we used a community-based participatory research approach to understand how we might build a data collection ecosystem across sectors, alongside community residents and service providers, to accurately capture the data about the social determinants of health. This approach involved developing a community engagement council, defining the problem with the community, mapping what data is actively collected and what is excluded, and understanding experiences of sociodemographic data collection from community members and service providers. Guided by community voices, our study focused on sociodemographic data collection in the primary care context and identified which service providers use and collect these data, how data are used in their work, the facilitators and barriers to data use and collection. Additionally, we gained insight into how sociodemographic data collection could be respectful, safe, and properly governed from the perspectives of community members. From this study, we identify a set of eight recommendations for sociodemographic data collection and highlight limitations. This foundational community-based work will inform future research in establishing data governance in partnership with diverse and equity-deserving communities.

Systemic discrimination is ingrained within social systems and institutions worldwide, reaching all sectors, including healthcare [ 1 , 2 ]. Health system design, delivery and evaluation have a long history of systemic racism and discrimination, often targeting, harming, and further marginalizing racialized and equity-deserving communities [ 1 , 3 ]. In Canada, these practices can lead to delayed care and premature death among individuals from racialized and equity-deserving communities [ 4 , 5 ]. The lack of appropriate sociodemographic data collection (that encompasses socioeconomic and identity-related information) contributes to widening health inequities by hindering health systems’ and community organizations’ abilities to understand and act on health disparities associated with sociodemographic factors. Intersectional data that capture an individual’s unique health and social needs, such as race, ethnicity, language, gender identity, age, employment, and housing, are required to create meaningful and culturally specific service provision and support for diverse communities [ 6 ].

Within the primary care setting, collecting sociodemographic data has been cited as a feasible and worthwhile process valued by patients [ 7 , 8 , 9 ]. However, many individuals, particularly those from racialized and equity-deserving communities, have reported experiencing vulnerability and discomfort when having their personal information collected [ 10 ]. Some individuals worry that the data collected could be misused or used in a discriminatory way to negatively impact their care [ 10 ]. Therefore, it is necessary to develop ethical and safer sociodemographic data collection processes that reduce harm. This action requires drawing on the principles of the data justice movement, which believes “historical (and ongoing) ways of collecting and sharing data […] erase, invisiblize, misrepresent, or harm marginalized communities” [ 11 ] and emphasizes prioritizing community interest and participation to prevent further harm and marginalization [ 12 ]. Data justice principles recommend that data are intentionally collected to serve individuals and communities and promote community self-determination. The principles advocate that collection processes be mindful of the emotional impact experienced by those providing personal and sensitive information, that data are centred around community needs, preferences and priorities and that once provided, personal data requires ethical care, which includes ensuring privacy and security [ 3 , 13 , 14 , 15 , 16 , 17 ].

Internationally, the World Health Organization recommends conceptualizing data and data collection from social justice and human rights perspectives with principles of participation, data disaggregation, self-identification, transparency, privacy, and accountability to address racial discrimination, promote intercultural health services and reduce health inequities [ 2 , 18 ]. In Canada, there have been repeated calls for the collection of race-based data as a way to address health and social disparities resulting from systemic discrimination. Such standards include the Black Health Equity Working Group’s Engagement, Governance, Access, and Protection (EGAP) framework, the First Nations Information Governance Centre’s Ownership, Control, Access, and Possession (OCAP) principles, the Canadian Institute for Health Information (CIHI)’s guidelines related to race-based data collection in healthcare settings, and British Columbia’s Office of the Human Rights Commissioner’s framework for the collection of race-based, Indigenous and other disaggregated data for addressing systemic discrimination, from their report: “Disaggregated demographic data collection in British Columbia: The grandmother perspective”. Each of these highlight the importance of governance, community engagement, safety, individual and collective ownership, respectful relationships, and proper training for collecting data [ 19 , 20 , 21 ]. While there have been numerous calls to action and recommendations to transform data collection in healthcare, there have been few reported examples of how these recommendations have been developed at a regional level within the health system and alongside the diverse communities from which data are collected.

Our team of health system researchers, community organization leaders and community members began this project with the understanding that community members needed to be involved in co-designing the development of safe and culturally sensitive data collection processes and tools. Drawing on data justice principles, we wanted to ensure that historically excluded voices of diverse communities in the regional municipality of Peel, Ontario, Canada, were included. Therefore, we used a community-based participatory research (CBPR) approach – a model of research that partners with communities on all phases of research – and population health analytics to understand current gaps and opportunities in sociodemographic data collection in Peel. This approach ensured meaningful community engagement and integrated academic and community-based knowledge throughout the research process [ 22 , 23 ]. CBPR emphasizes community-driven and social-action-oriented principles [ 24 ] and allows the project to continue honouring and incorporating community knowledge, experiences and voices through shared learning, co-creating knowledge and capacity building [ 25 ].

In this study, the community is centred within every step of the research process, including defining the aims and methodologies used and interpreting, sharing and acting on findings. Our project aimed to identify the factors needed to operationalize community and healthcare data collection and to understand the barriers and facilitators of culturally safe, trauma-informed and effective sociodemographic data collection. This paper demonstrates the successful application of CBPR principles to explore the gaps and opportunities for building a system for collecting sociodemographic information in the health system.

Setting and context

This study takes place in the regional municipality of Peel (consisting of the municipalities of Mississauga, Brampton, and Caledon) in Ontario, Canada. Peel has approximately 1.38 million residents, with 52.2% and 43.0% of the population living in the suburban cities of Mississauga and Brampton, respectively, and 4.8% residing in the rural Town of Caledon [ 26 ]. The Peel region is one of the most diverse in Canada, with approximately 60% of the population identifying as a visible minority – 81% in Brampton, 61% in Mississauga, and 33% in Caledon [ 27 ]. This diversity makes Peel a microcosm for other urban Canadian communities and the ideal setting for innovative approaches that could be replicated in other communities across Canada and globally. Peel region faces serious health inequities that disproportionately affect marginalized communities. Existing research and limited data from the region reveal a greater burden of chronic conditions and premature mortality among neighbourhoods with lower socioeconomic status, as well as severe challenges for managing chronic conditions among marginalized groups [ 29 , 30 , 31 ]. These were amplified by the COVID-19 pandemic. At one point during the pandemic, Brampton reportedly had one of the highest rates of COVID-19 in Ontario; in one neighbourhood, nearly one in five tests were positive – Peel was considered one of the hardest-hit areas in the country [ 28 ].

In February 2021, the Anti-Black Racism & Systemic Discrimination Healthcare Collective (ABR-SDHC), a group of community and health service providers from local organizations, committed to meeting the health and social service needs of racialized communities in Peel, Halton and the Greater Toronto Area, made a call to action to health system leaders through a position paper entitled “ The Outcomes of Oppressive Systems and a Collective Call to Co-Design an Equitable and Inclusive Health System in Peel ” [ 4 ]. The report aimed to engage with health systems leaders, including Trillium Health Partners (THP), Canada’s largest community hospital system, serving over one million of Canada’s most ethnically diverse communities. In a dialogue about anti-Black racism and systemic discrimination with THP leadership and Peel community leaders, one of the most pressing issues raised was the critical data and infrastructure gaps that severely hindered Peel’s action to address the social determinants of health (SDOH). In the context of the pandemic, while there was some data on communities that tested positive for COVID-19, little was known about which communities were hardest hit by outcomes such as hospitalizations and deaths [ 29 ]. This gap in race-based data made it challenging to develop specialized public health initiatives and resources. To address the sociodemographic data gap, Peel community leaders advocated to the Ministry of Health and the regional public health unit to collect race-based data that they believed was vital to identifying and supporting impacted communities in the region [ 4 , 30 ].

We describe the steps of our CBPR project, including (1) Developing a Community Engagement Council (CEC) (2) Defining the Problem with the Community (3) Mapping What Data is Actively Collected and What is Excluded (4) Understanding Experiences of Sociodemographic Data Collection (5) Analysis and Results (6) Acting on Findings.

Study steps

Step 1: Developing a Community Engagement Council. We established a CEC comprising community members, organizational leaders, and researchers. The CEC represented diverse perspectives from across the Peel region, including those identified from racialized and non-racialized communities, newcomers and long-term residents, youth and seniors. The CEC established a project governance structure and principles of collaboration to address power differentials within the team based on individual identities such as profession, education, health, gender, race, ethnicity, age, poverty, and ability [ 22 , 23 , 31 ]. An output of this process was a Terms of Reference that outlined the role and responsibilities of the CEC and project members [see Additional file 1 ]. The CEC met virtually once a month for one hour to guide all project activities, including: refining the objectives and scope of the project, co-designing the survey and workshops, analysis, and interpretation; identifying critical issues for action and strategies for the next steps; planning the dissemination of project findings, and evaluating study processes and knowledge translation.

Step 2: Defining the Problem with the Community. As the project’s objectives were conceptualized broadly, early conversations with the CEC focused on co-identifying the key health inequity priorities in Peel that built on the existing work related to data and health equity. Through ongoing discussions, the members collectively identified issues related to Peel residents’ access to primary care providers as the project’s focus. Access to primary care services has been a point of discussion in the Peel region for decades [ 32 ] and community partners were concerned about residents’ access to primary care providers during the COVID-19 pandemic. The problem statement for the project, therefore, became: How can sociodemographic data inform who is and who is not accessing primary care services in the Peel region? Once primary care services were identified as the healthcare setting of focus, the study team engaged with multiple primary care networks, including family practice organizations (e.g., the Family Health Teams model in Ontario) and research teams working on primary care data collection, to understand the current state of sociodemographic data collection in primary care and gain insight on how this project can engage with primary care providers to collect data.

Step 3: Survey to Map the Data Collected and Excluded. To work towards building a more equitable data system for primary healthcare in Peel, we first needed to understand what the data system currently looked like, what data exist, how data are collected, what data are being collected and what data are missing. To answer these questions about the current data system, we worked with members of the CEC to co-develop and conduct a data gaps survey. This survey served to gather information about the current landscape of sociodemographic data collection in community organizations, health systems, and primary care settings. In addition, the survey was used to gather information on what specific variables were being collected, their format and their use. The United Nations Development Programme’s Guide to Data Innovation [ 33 ] was used as a framework for survey design in discussions between the study team and the CEC. The online survey took 10–15 min to complete and contained multiple-choice, checkboxes, and open-ended questions [see Additional file 2 for survey questions]. The CEC, community organizational leaders, primary care leaders and provider networks (from step 2) helped disseminate the survey to providers. Leaders from community organizations, health systems and primary care settings were asked to complete the survey on behalf of their practice or organization. The survey started by recording the participant’s role and workplace. Then, it contained general questions about how they collect sociodemographic information, in what format the data are recorded, the method of data collection, and which sociodemographic indicators are collected. The study team and CEC disseminated the survey throughout primary care and community organization leader networks.

Step 4: Understanding experiences of sociodemographic data collection. To continue building our understanding of the current data system, we conducted workshops with community members and service providers to understand their experiences with sociodemographic data gathering. The CEC and research team co-designed several virtual workshops to engage service providers and community members in discussing sociodemographic data collection in primary care settings. Both workshops were designed to encourage engagement through group discussion, using a Mentimeter© (an online interactive polling tool), break-out rooms with a facilitator and note taker, and reporting back to the larger group. Informed by the CEC, it was decided that we would not audio-record workshop sessions to create a safe space for participants to share their experiences. Participants were recruited by the CEC and research team by emailing workshop registration details to primary care and community organizational networks in the Peel region.

Service Provider Workshops. We invited community organization leaders, primary care leaders, health system leaders and service providers working in primary care in Peel to two 90-minute workshops. The main objectives were to (1) validate the problem statement and (2) discuss the barriers and facilitators to collecting sociodemographic data in primary care. The CEC and research team members facilitated the workshops and note-takers were also assigned to each break-out room discussion to capture the discussion. Community Member Workshop. We invited Peel community members to one 90-minute workshop. The workshop’s main objective was to ask community members about their preferences and experiences of being asked about sociodemographic data. Similar to the service provider workshops, facilitators included members of the research team and CEC members representing community voices and perspectives. Note-takers were also assigned to each break-out room discussion to capture the discussion.

Step 5: Analysis and Results. The results from the survey and workshops were analyzed separately, with the involvement of the CEC and their input, and findings were synthesized at the end. First, the survey responses were analyzed descriptively, looking at the proportions of participants who chose an option or summarizing content from free-text form response. These results were presented to the CEC and their reactions and feedback were noted. Second, the workshop notes were analyzed using conventional content analysis by two members of the research team and one CEC member [ 34 ]. Data were reviewed word by word to derive codes that captured critical thoughts or concepts. Excerpts from the notes were grouped and organized under the codes that best represented the data. After reading the excerpts within codes, related codes were organized to create meaningful categories [ 35 ]. These preliminary categories were presented and refined by the CEC and ABR-SDHC, some of whom also attended the workshops and were able to ensure that the categories represented the workshops. This iterative and participatory approach allowed for further refinement of the category descriptions. Lastly, the research team, the CEC and the ABR-SDHC discussed the categories and survey results to co-design recommendations for action.

Step 6: Acting on Findings. An essential aspect of CBPR is collaboratively deciding how to act on the findings [ 36 ]. Through an integrated knowledge exchange approach, the objectives, methods, and knowledge translation outputs were co-developed with members of the ABR-SDHC, researchers, community organizations and community members through ongoing CEC meetings. This included co-writing a report for the community on findings and recommendations titled: We Are All Accountable: Collective Action Through Data to Co-design a More Equitable and Integrated Health System in Peel Region to share with the community and serve as an advocacy tool ( https://familyandchildhealth.ca/wp-content/uploads/2023/08/Study-Final-Report-2023-1.pdf ). Through ongoing discussions with the CEC and ABR-SDHC, we decided to organize a Peel Health Equity forum, which served as a platform to workshop findings and establish plans of action emerging from recommendations with health systems and community leaders.

We successfully established a CEC that included six community members, three community organizational leaders, and three research team members. The CEC represented diversity across agencies and within the community to ensure a variety of perspectives were incorporated throughout the project. Findings from our project are summarized below.

The survey was distributed to 150 people through members of the CEC, primary care and community organizational leaders, and provider workshop participants. We received a total of 21 responses for the survey, each representing separate community organizations, health systems and primary care settings. Out of all respondents, 16 used sociodemographic data in their day-to-day work. Of the respondents, 13 were from community organizations or the health system/hospital (11 using sociodemographic data). Eight respondents were primary care providers (5 using sociodemographic data). Most respondents reported using an electronic medical record (EMR) to collect sociodemographic data, with only a few using paper to collect this information.

Most respondents reported collecting sociodemographic data during patient interviews and while taking a history. Only one of the five primary care provider respondents who reported using sociodemographic data collected gender identity, ethnicity, religion, income and preferred language. To some degree, all community organization respondents collected the sociodemographic data types listed on the survey. Specifically, all respondents collected sex, age, gender identity, ethnicity, race and preferred language ( n  = 10 for each). To a slightly lesser extent, respondents collected address ( n  = 9), email address ( n  = 9), immigrant status ( n  = 9) and marital status ( n  = 8). Additional data that respondents filled in included child custody, who lives with the child (from pediatrics provider respondents) and dietary requirements and restrictions.

For primary care providers, sociodemographic data were mainly used by clinicians and, to a lesser degree, nurses, allied health professionals, practice managers and administrative staff. For community organizations, sociodemographic data were used by case workers, intake workers and client navigators, service or organization managers, social workers and counsellors or therapists (less often by healthcare professionals or administrative staff).

Community and provider workshops

We held three workshops, with 44 community members, six primary care providers, and 20 community service providers. Participants highlighted three key considerations for sociodemographic data collection.

Safety and governance. Participants emphasized the importance of having a clear and justified purpose for data collection and sharing this information with service users when collecting data. This would encourage providers to collect data and service users to provide data. Participants also suggested that the community should govern data usage and storage; data protection must be transparent. Tailoring approaches . Participants noted that data collection approaches should be tailored to who is collecting data and the preferences of whom data are being collected from. Factors to consider include the timing of data collection (i.e., longitudinal data collection rather than trying to collect all the data at a single time point and asking at appropriate time points) and using appropriate language (i.e., accessible and respectful language). How should data be used? We also asked about desired reasons for collection to both community members and providers. Both groups agreed that data should be used to inform clinical care. Providers underscored the importance of using these data to inform program or service delivery and to be used to report to the government or funders. On the other hand, community members were comfortable with their sociodemographic data being used for quality improvement, research, and health service planning.

Co-designed recommendations for building sociodemographic data infrastructure

Throughout the survey and community workshops, participants directly offered suggestions on proper sociodemographic data collection. These included: having staff with training to collect the data; acknowledging and creating funding for the time it takes to collect sociodemographic data and training needed; analytic resources to collect, clean, and extract data for use; standardized electronic medical record classifications to enable data sharing and linkage; leadership buy-in; a community-driven and transparent purpose for the collected data; accurate ethnicity data that contributes to health equity for racialized and marginalized people.

High-level recommendations based on the survey and workshop results, as well as input from the CEC and ABR-SDHC, are shown in Table  1 .

We applied a CBPR approach to understanding how we could collect sociodemographic data for the health system in a large urban Canadian region by incorporating feedback from multiple stakeholders. A critical aspect of this approach involved recruiting a CEC to work alongside the research team at each stage of the research process. Ongoing community engagement and participation allowed us to focus on a community-identified priority area – data collection in primary care – which the research team may not have considered in isolation. We collaborated at regular monthly CEC meetings to co-design two data collection methods. First, we designed and administered a survey to gain insight into the current landscape of sociodemographic data collection in Peel. We then designed and hosted workshops with community members and service providers to understand critical considerations surrounding sociodemographic data collection, which could impact how we design a data ecosystem in primary care. We found that primary care providers seldom collect sociodemographic data from service users and rarely from an intersectional perspective. In contrast, community organizations collect various sociodemographic data from service users, and providers use this information to deliver tailored support and services. Community input collected throughout the project suggests that if primary care providers were to expand sociodemographic data collection, several factors need to be accounted for, including transparency around the purpose of data collection, data use, and data storage. Additionally, it is critical to appropriately match the mode of data to the setting and individuals’ level of comfort. Our results also noted several appropriate ways to use these data (e.g., clinical care and quality improvement).

The barriers we discovered in our results related to sociodemographic data collection are supported by a previous study by Yoon & Copeland (2020), which found that while data collection is helpful to community-based organizations, there are numerous challenges in accessing the data [ 37 ]. Our findings also align with Canadian sociodemographic data collection guidelines, such as the Engagement, Governance, Access, and Protection (EGAP) framework, the Ownership, Control, Access, and Possession (OCAP) principles, and the Canadian Institute for Health Information (CIHI)’s guidelines for race-based data collection [ 19 , 20 ], where there was strong emphasis on themes of data governance, community engagement, safety, individual and collective ownership, and proper training. Our results also reveal the importance of transparency in data collection, which echoes British Columbia’s Office of the Human Rights Commissioner framework stressing that data collection should serve as a tool for making systemic inequities more visible and be done with a clearly defined process and purpose [ 22 ]. Additionally, we expand on existing work that outlines potential harms and ethical considerations when collecting sociodemographic data in a healthcare setting [ 10 ] by moving beyond highlighting concerns such as privacy and misuse to creating a deeper understanding of how we can support trust-building within the sociodemographic data collection process. For example, we found that community members would feel more comfortable sharing sociodemographic information if it was clear how the data would be used and if the mode of data collection was tailored to individuals’ preferences. Lastly, we gained an understanding of the current state of sociodemographic data collection in primary care in the Peel region (i.e., who collects it and how), which provides a framework in which we can apply our findings to design a suitable data collection infrastructure in Peel that integrates community data into primary care data.

There is a long history of sociodemographic data being collected and used in harmful ways within health research and systems [ 3 ]. Building on the advocacy of data justice scholars and community leaders, we argue that bringing CBPR methodology alongside data science is vital to ensuring community needs and priorities are centred on building and maintaining data collection processes and systems [ 38 ]. Engaging diverse community perspectives in health system design can increase validity, support the implementation of services through partnerships and help design effective and meaningful systems and services [ 22 , 23 , 24 , 25 ]. Community members of the ABR-SDHC in Peel argued in their position paper for health system leaders to re-evaluate how and why data are collected within the current health system and how data are used to inform decision-making [ 4 ]. The collective also advocated for community voices to be included in co-designing data collection processes. This project was the first step in learning about how sociodemographic data could be collected more safely and builds on the work of data justice scholars, which draws on various fields, including Indigenous data sovereignty [ 3 ] and Black feminism [ 38 ]. A CBPR approach allowed the project to include ongoing community engagement as we worked to centre and prioritize the needs and experiences of equity-deserving community members. Shah & Sekalala (2023) further argue the importance of “equitable participation” that is required when building and organizing data systems within and across health spaces [ 38 ]. Our CBPR methodological approach allowed us to practically apply the recommendations of health data justice scholars alongside diverse communities in Peel. Throughout each project stage, opportunities were created for individuals from diverse communities across Peel to be central to the project through CEC participation, workshop engagement, analysis of findings and knowledge translation.

Limitations

We want to note three main limitations of our research. First, we recognize that the response rate for our data gaps survey may appear to be low, but the aim of our dissemination plan was to have a representative from each entity (community organization, health system, or primary care organization) complete the survey. This plan was informed by our engagement meetings with primary care leaders in our region before and during our project, who notified our team that primary care providers were overburdened, and few had the bandwidth to participate in research activities. Our survey respondents were representatives and leaders of provider organizations, which have extensive and holistic knowledge of the critical barriers to sociodemographic data collection in primary care delivery. Second, we acknowledge that while we strived to include diverse representation and perspectives, more work is needed to ensure that we continue to centre those who identify from Indigenous, Black, African and Caribbean, South Asian and racialized communities as we move into the future phases of our work. To do this, we argue that future research in building an integrated data ecosystem that includes community and healthcare data must use CBPR approaches that position diverse community voices at the centre. Lastly, we note that CBPR approaches are inherently context-specific, and our work may be limited in generalizability to other contexts. However, we argue that the steps we took can be applied to work on health data infrastructure development in many contexts, especially among urban and diverse municipalities.

Conclusions

Historically, healthcare systems, including data collection processes, have been influenced by systemic racism, inflicting harm on racialized and equity-deserving communities [ 3 ]. Many healthcare institutions are trying to understand how they might redesign institutional practices, tools and infrastructures through anti-racist and anti-oppressive ways. Yet, these institutions continue to fall short when trying to move these social justice and health equity frameworks into practice. While there are many calls to collect sociodemographic and, specifically, race-based, data to improve equity and health system accountability, more advocacy is needed on its value and importance by health care institutions and providers. There also needs to be more meaningful engagement with diverse communities on how best to do this to minimize harm and maximize benefit in terms of reducing health inequities. This study fills an important gap in understanding the perspectives of the communities impacted and whose data would be collected and used. This CBPR project exemplifies how data justice recommendations can be carried out alongside community partners in meaningful and ethical ways. It also demonstrates that ongoing community engagement and co-design are possible. Future work will explore co-designing data governance and standardizing the data ecosystem with community residents and partners in the region of Peel.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

Community–Based Participatory Research

Engagement, Governance, Access, and Protection

Canadian Institute for Health Information

SDHC–Anti–Black Racism & Systemic Discrimination Healthcare Collective

Social Determinants of Health

Community Engagement Council

Electronic Medical Record

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Acknowledgements

We would like to thank Peel community residents who participated and contributed their experiences and knowledge to the project through membership on the community engagement council and participation in the workshops. We would like to thank the Anti-Black Racism & Systemic Discrimination Healthcare Collective for their support at critical junctures of this project and for their advocacy work to hold healthcare institutions and systems accountable for addressing systemic racism and discrimination. We want to thank the Family and Child Health Initiative (FCHI) research team, many of whom are part of this project, for leading the engagement and research activities alongside the community. We would also like to thank the Health Equity Table at Trillium Health Partners for their strong support in the initial planning stages for this project and for being committed to taking action on our findings in the Peel. We would like to thank the Temerty Faculty of Medicine at the University of Toronto for funding this project through their Knowledge Translation Grant. Lastly, we would like to thank all the primary care leaders and providers who helped scope out this project at the initial stages and participated in workshops.

Funding for this project was provided by the Temerty Faculty of Medicine at the University of Toronto.

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Authors and affiliations.

The Institute for Better Health, Trillium Health Partners, Mississauga, ON, Canada

Dianne Fierheller, Casey Chu, Chelsea D’Silva, Arvind Krishendeholl, Ian Zenlea & Laura C. Rosella

Roots Community Services Inc, Brampton, ON, Canada

Angela Carter

UMass Chan-Baystate Medical Centre, Springfield, MA, USA

Abdul Arham

LAMP Community Health Centre, Etobicoke, ON, Canada

Keddone Dias

University of Toronto, Mississauga, ON, Canada

Isaac Francis

William Osler Health System, Brampton, ON, Canada

Marcia Glasgow

Indus Community Services, Mississauga, ON, Canada

Gurpreet Malhotra

University of Toronto, Toronto, ON, Canada

Arvind Krishendeholl, Ian Zenlea & Laura C. Rosella

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Contributions

All authors made substantial contributions to the conception or design of the work. The research team (DF, CC, CD, AK, IF, IZ, and LR) mainly took on the role of managing the research project. Both the research team and the CEC (AA, AC, KD, GM, and MG) shared equal responsibility in collecting, interpreting, and analyzing data, as well as critically reviewing the manuscript.

Corresponding author

Correspondence to Dianne Fierheller .

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Not applicable (the Trillium Health Partners Research Ethics Board exempted this study from ethical review as it was not classified as human subjects research).

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Supplementary Material 1. Additional file 1.Pdf: Community Engagement Council – Project Terms of Reference.

Supplementary material 2. additional file 2.pdf: data gaps survey., rights and permissions.

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Fierheller, D., Chu, C., D’Silva, C. et al. Using community-based participatory research methods to build the foundation for an equitable integrated health data system within a Canadian urban context. Int J Equity Health 23 , 131 (2024). https://doi.org/10.1186/s12939-024-02179-3

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Facility for Rare Isotope Beams

At michigan state university, investigating the conditions for a new stellar process.

A scientific research team studied how the barium-139 nucleus captures  neutrons in the stellar environment in an experiment at  Argonne National Laboratory ’s (ANL)  CARIBU facility using FRIB’s Summing Nal (SuN) detector . The team’s goal was to lessen uncertainties related to lanthanum production. Lanthanum is a rare earth element sensitive to intermediate neutron capture process (i process) conditions. Uncovering the conditions of the i process allows scientists to determine its required neutron density and reveal potential sites where it might occur. The team recently published its findings in  Physical Review Letters   (“First Study of the 139Ba(𝑛,𝛾)140Ba Reaction to Constrain the Conditions for the Astrophysical i Process”).

Artemis Spyrou , professor of physics at FRIB and in the Department of Physics and Astronomy at Michigan State University (MSU), and Dennis Mücher , professor of physics at the  University of Cologne in Germany, led the experiment. MSU is home to FRIB, the only accelerator-based U.S. Department of Energy Office of Science (DOE-SC) user facility on a university campus. FRIB is operated by MSU to support the mission of the DOE-SC Office of Nuclear Physics as one of 28 DOE-SC user facilities.

Combining global collaboration and world-class educational experiences

The experiment was a collaborative effort involving more than 30 scientists and students from around the world. Participating institutions included the  University of Victoria in Canada, the  University of Oslo in Norway, and the  University of Jyväskyla in Finland. 

“The collaboration is essential because everyone comes from different backgrounds with different areas of expertise,” Spyrou said. “Together, we’re much stronger. It’s really an intellectual sharing of that knowledge and bringing new ideas to the experiment.”

The international collaboration also included five FRIB graduate and two FRIB undergraduate students. FRIB is an educational resource for the next generation of science and technical talent. Students enrolled in nuclear physics at MSU can work with scientific researchers from around the world to conduct groundbreaking research in accelerator science, cryogenic engineering, and astrophysics. 

“Our students contribute to every aspect of the experiment, from transporting the instrumentation to unpacking and setting it up, then testing and calibrating it to make sure everything works,” Spyrou said. “Then, we all work together to identify what’s in the beam. Is it reasonable? Do we accept it? Once everything is set up and ready, we all take shifts.”

Measuring the i process 

Producing some of the heaviest elements found on Earth, like platinum and gold, requires stellar environments rich in neutrons. Inside stars, neutrons combine with an atomic nucleus to create a heavier nucleus. These nuclear reactions, called neutron capture processes, are what create these heavy elements. Two neutron capture processes are known to occur in stars: the rapid neutron capture process ( r process) and the slow neutron capture process ( s process). Yet, neither process can explain some astronomic observations, such as unusual abundance patterns found on very old stars. A new stellar process—the i process—may help. The i process represents neutron densities that fall between those of the r and s processes.

“Through this reaction we are constraining, we discovered that compared to what theory predicted, the amount of lanthanum is actually less,” said Spyrou. 

Spyrou said that combining lanthanum with other elements, like barium and europium, helps provide a signature of the i process. 

“It’s a new process, and we don’t know the conditions where the i process is happening. It’s all theoretical, so unless we constrain the nuclear physics, we will never find out,” Spyrou said. “This was the first strong constraint from the nuclear physics point of view that validates that yes, the i process should be making these elements under these conditions.”

Neutron capture processes are difficult to measure directly, Spyrou said. Indirect techniques, like the beta-Oslo and shape methods, help constrain neutron capture reaction rates in exotic  nuclei . These two methods formed the basis of the barium-139 nucleus experiment.

To measure the data, beams provided by ANL’s CARIBU facility produced a high-intensity beam and delivered it to the center of the SuN detector, a device that measures gamma rays emitted from decaying  isotope beams. This tool was pivotal in producing strong data constraints during the study.

“I developed SuN with my group at the National Superconducting Cyclotron Laboratory, the predecessor to FRIB,” Spyrou said. “It’s a very efficient and large detector. Basically, every gamma ray that comes out, we can detect. This is an advantage compared to other detectors, which are smaller.”

The first i process constraint paves the way for more research

Studying the barium-139 neutron capture was only the first step in discovering the conditions of the i  process. Mücher is starting a new program at the University of Cologne that aims to measure some significant i  process reactions directly. Spyrou said that she and her FRIB team plan to continue studying the i process through different reactions that can help constrain the production of different elements or neutron densities. They recently conducted an experiment at ANL to study the neodymium-151 neutron capture. This neutron capture is the dominant reaction for europium production.

This material is based upon work supported by the National Science Foundation.

Michigan State University operates the Facility for Rare Isotope Beams (FRIB) as a user facility for the U.S. Department of Energy Office of Science (DOE-SC), supporting the mission of the DOE-SC Office of Nuclear Physics. Hosting what is designed to be the most powerful heavy-ion accelerator, FRIB enables scientists to make discoveries about the properties of rare isotopes in order to better understand the physics of nuclei, nuclear astrophysics, fundamental interactions, and applications for society, including in medicine, homeland security, and industry.

The U.S. Department of Energy Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of today’s most pressing challenges. For more information, visit  energy.gov/science .

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• How to Write a Research Proposal | Examples & Templates

How to Write a Research Proposal | Examples & Templates

Published on October 12, 2022 by Shona McCombes and Tegan George. Revised on November 21, 2023.

A research proposal describes what you will investigate, why it’s important, and how you will conduct your research.

The format of a research proposal varies between fields, but most proposals will contain at least these elements:

Introduction

Literature review.

• Research design

Reference list

While the sections may vary, the overall objective is always the same. A research proposal serves as a blueprint and guide for your research plan, helping you get organized and feel confident in the path forward you choose to take.

Table of contents

Research proposal purpose, research proposal examples, research design and methods, contribution to knowledge, research schedule, other interesting articles, frequently asked questions about research proposals.

Academics often have to write research proposals to get funding for their projects. As a student, you might have to write a research proposal as part of a grad school application , or prior to starting your thesis or dissertation .

In addition to helping you figure out what your research can look like, a proposal can also serve to demonstrate why your project is worth pursuing to a funder, educational institution, or supervisor.

Research proposal length

The length of a research proposal can vary quite a bit. A bachelor’s or master’s thesis proposal can be just a few pages, while proposals for PhD dissertations or research funding are usually much longer and more detailed. Your supervisor can help you determine the best length for your work.

One trick to get started is to think of your proposal’s structure as a shorter version of your thesis or dissertation , only without the results , conclusion and discussion sections.

Download our research proposal template

Prevent plagiarism. Run a free check.

Writing a research proposal can be quite challenging, but a good starting point could be to look at some examples. We’ve included a few for you below.

• Example research proposal #1: “A Conceptual Framework for Scheduling Constraint Management”
• Example research proposal #2: “Medical Students as Mediators of Change in Tobacco Use”

Like your dissertation or thesis, the proposal will usually have a title page that includes:

• The proposed title of your project
• Your supervisor’s name
• Your institution and department

The first part of your proposal is the initial pitch for your project. Make sure it succinctly explains what you want to do and why.

Your introduction should:

• Introduce your topic
• Give necessary background and context
• Outline your  problem statement  and research questions

To guide your introduction , include information about:

• Who could have an interest in the topic (e.g., scientists, policymakers)
• How much is already known about the topic
• What is missing from this current knowledge
• What new insights your research will contribute
• Why you believe this research is worth doing

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As you get started, it’s important to demonstrate that you’re familiar with the most important research on your topic. A strong literature review  shows your reader that your project has a solid foundation in existing knowledge or theory. It also shows that you’re not simply repeating what other people have already done or said, but rather using existing research as a jumping-off point for your own.

In this section, share exactly how your project will contribute to ongoing conversations in the field by:

• Comparing and contrasting the main theories, methods, and debates
• Examining the strengths and weaknesses of different approaches
• Explaining how will you build on, challenge, or synthesize prior scholarship

Following the literature review, restate your main  objectives . This brings the focus back to your own project. Next, your research design or methodology section will describe your overall approach, and the practical steps you will take to answer your research questions.

To finish your proposal on a strong note, explore the potential implications of your research for your field. Emphasize again what you aim to contribute and why it matters.

For example, your results might have implications for:

• Improving best practices
• Informing policymaking decisions
• Strengthening a theory or model
• Challenging popular or scientific beliefs
• Creating a basis for future research

Last but not least, your research proposal must include correct citations for every source you have used, compiled in a reference list . To create citations quickly and easily, you can use our free APA citation generator .

Some institutions or funders require a detailed timeline of the project, asking you to forecast what you will do at each stage and how long it may take. While not always required, be sure to check the requirements of your project.

Here’s an example schedule to help you get started. You can also download a template at the button below.

Download our research schedule template

If you are applying for research funding, chances are you will have to include a detailed budget. This shows your estimates of how much each part of your project will cost.

Make sure to check what type of costs the funding body will agree to cover. For each item, include:

• Cost : exactly how much money do you need?
• Justification : why is this cost necessary to complete the research?
• Source : how did you calculate the amount?

To determine your budget, think about:

• Travel costs : do you need to go somewhere to collect your data? How will you get there, and how much time will you need? What will you do there (e.g., interviews, archival research)?
• Materials : do you need access to any tools or technologies?
• Help : do you need to hire any research assistants for the project? What will they do, and how much will you pay them?

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

Methodology

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

 Statistics

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

Research bias

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

Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement .

Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.

I will compare …

A research aim is a broad statement indicating the general purpose of your research project. It should appear in your introduction at the end of your problem statement , before your research objectives.

Research objectives are more specific than your research aim. They indicate the specific ways you’ll address the overarching aim.

A PhD, which is short for philosophiae doctor (doctor of philosophy in Latin), is the highest university degree that can be obtained. In a PhD, students spend 3–5 years writing a dissertation , which aims to make a significant, original contribution to current knowledge.

A PhD is intended to prepare students for a career as a researcher, whether that be in academia, the public sector, or the private sector.

A master’s is a 1- or 2-year graduate degree that can prepare you for a variety of careers.

All master’s involve graduate-level coursework. Some are research-intensive and intend to prepare students for further study in a PhD; these usually require their students to write a master’s thesis . Others focus on professional training for a specific career.

Critical thinking refers to the ability to evaluate information and to be aware of biases or assumptions, including your own.

Like information literacy , it involves evaluating arguments, identifying and solving problems in an objective and systematic way, and clearly communicating your ideas.

The best way to remember the difference between a research plan and a research proposal is that they have fundamentally different audiences. A research plan helps you, the researcher, organize your thoughts. On the other hand, a dissertation proposal or research proposal aims to convince others (e.g., a supervisor, a funding body, or a dissertation committee) that your research topic is relevant and worthy of being conducted.

Cite this Scribbr article

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McCombes, S. & George, T. (2023, November 21). How to Write a Research Proposal | Examples & Templates. Scribbr. Retrieved June 27, 2024, from https://www.scribbr.com/research-process/research-proposal/

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Money blog: 'Bleak' new security measure seen in Tesco store

Welcome to the Money blog, your place for personal finance and consumer news and tips. Leave a comment on any of the stories we're covering below.

Tuesday 2 July 2024 02:17, UK

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Olive oil has become the latest staple to undergo "bleak" anti-theft measures.

The cooking product was spotted encased in netting and tagged with an alarm in an unspecified Tesco store, leading one customer to ask: "What has the world come to?"

It is just the latest product to be subject to supermarket security measures that have surprised customers, after an out-of-hours smoke machine was introduced in another Tesco store last month.

Neither security features are part of a universal policy and have been implemented only in individual stores, Sky News understands.

"All 'anti-shoplifting' measures are theatre," said one shopper on X, beneath a photo of the olive oil.

"This is so bleak," said another, while a third joked the oil "has to wear fishnets now".

We revealed earlier this year that there had been a 110.5% increase in the price of olive oil since January 2021.

High temperatures and droughts in Spain, the world's leading producer and exporter, have dented the harvest - a problem only worsened by global inflationary pressures.

Separately, a bacterial disease called Xylella Fastidiosa has attacked and killed century-old olive trees, severely diminishing yields in southern Europe.

And heightened prices have led organised criminal gangs to steal the "liquid gold".

Read more on what's behind exploding olive oil prices here...

We feature a lot of data on the changing prices of houses in the UK, but how do they compare to the rest of the world?

New data shows the UK ranked 37th for house price growth out of 56 countries analysed by Knight Frank for the Global House Price Index.

At 1.6% up over the year to the end of March, the UK underperformed (with the global average at 3.6%) but outstripped its European neighbours.

Only 11 countries saw prices fall, eight of which were European, with France (-5.2%) and Germany (-3.9%) feeling the effects of slower economic growth and high recent inflation.

Across all 56 markets, 82% saw annual price growth in the first quarter of the year - the strongest showing since the last quarter of 2022.

"Many markets are suffering from a lack of properties to sell as well as slow new-build delivery, leading to relatively healthy demand pushing prices to new highs," said Liam Bailey, Knight Frank's global head of research.

"In the longer term, however, only lower debt costs will sustain price growth."

With a 52% price increase, Turkey was at the top of the table by a huge margin - 36 percentage points - but there's more to this figure than meets the eye.

Consumer Price Index inflation in Turkey has risen 50% in the year to March, meaning in real terms house prices have actually fallen by 9.9%.

Recently we reported on how Barcelona had cracked down on tourism by planning to abolish short-term holiday lets . 

The Spanish city has now gone further in its war on overtourism by banning the display and sale of "offensive" souvenirs. 

It says sexist and homophobic messages on some souvenirs are tarnishing Barcelona's image. 

The ERC's deputy spokesperson Jordi Coronas said the ban included products such as "penises with the Barcelona brand, T-shirts with sexist or homophobic comments, or simply comments that, when displayed on these products, devalue Barcelona". 

Ahead of our Q&A, switching service Uswitch provided us with a list of what it considers the cheapest energy tariffs on the market right now.

It's worth reading the advice from Which? in our Q&A below (see 15.02 post) before deciding to switch from a standard variable tariff (that's what most households are on) - but if you're aware of the risks, then cheaper energy is available...

A big thanks to all those who submitted a question for our Q&A on the day the energy price cap fell - and sorry if we didn't get to yours.

A big thanks also to Emily Seymour, Which? energy editor, and Kate Mulvany, a principal consultant at Cornwall Insight, for tackling 10 of your questions so thoroughly.

Scroll down to read through their answers.

Does the UK have a secure enough energy supply in your view and what would it take for blackouts to occur this or any other winter?

Kate Mulvany, a principal consultant at Cornwall Insight, says..

The outlook for the upcoming winter appears promising, with strong gas reserves across Europe providing a healthy buffer to seasonal demand. 

While a very cold winter would increase the need for gas for heating across Europe, the UK's ability to secure gas and electricity from multiple sources keeps the risk of disruption to the flow of energy relatively low. 

Quite a few things would need to go wrong at the same time for there to be an increased risk of a widespread blackout. 

However, short-term blackouts would still be possible - as indeed at any time of year - due to storms or other weather incidents, as well as through localised network issues. 

It's worth mentioning that ministers have claimed the UK faces blackouts without new gas-fired power stations...

The bigger risk for homes in the UK is the pressure on energy bills. Although electricity and gas supplies appear healthy, affordability remains a concern, as seen in recent winters - particularly 2022-23.

Edward Morgan:

What's the best deal currently on the market in your view and does it come with any risks?

Emily Seymour, Which? energy editor, says...

As we said in one of our previous answers, there isn't a "one size fits all" for the best deals out there as it will all depend on individual circumstances. 

However, there are some tariffs available that are cheaper than the current price cap and might be worth considering. 

When Which? last checked, Ecotricity and Ovo both had fixed deals available for cheaper than the July price cap. 

However, Ecotricity's deal requires a smart meter - or you to agree to have one fitted - and Ovo's is only available if you also buy annual boiler cover, so you'll need to weigh up if this is right for you. Both also come with exit fees if you want to leave early. 

Tracker tariffs change in price relative to the price cap every three months when the price cap is reset to offer slightly cheaper rates than you'd be paying otherwise, and could be worth considering. They're currently available from E.ON Next , Scottish Power and Fuse Energy .

Consumers can use switching services - like Which? Switch Energy - to keep an eye on the best fixed deals available and compare deals to see what's cheapest for them. 

We'd always recommend checking the exit fees on fixed deals so you're not tied into a tariff if something better becomes available.

Why doesn't the government de-link the price of fossil fuel-generated electricity from that generated from renewable sources? Surely cheaper energy would be the result?

The current government has explored various methods to decouple wholesale gas and electricity prices through a programme called the Review of Electricity Market Arrangements (REMA). 

However, each option identified presented potential drawbacks for customers, as well as benefits. 

For example, one proposed solution was to set different prices for electricity generated by renewable sources compared to that generated by more carbon-intensive methods, such as burning gas. 

A significant challenge is that the country cannot yet generate all its electricity from renewable sources 24/7. 

During shortfalls, such as on a winter evening with low wind, non-variable renewable generation methods would still need to be used, meaning customers would still see the impacts of gas prices in those of electricity.

If I do not qualify for pension credit but receive housing benefit on top of my state pension, will I qualify for extra heating allowance/cold weather payment?

For the Warm Home Discount, Cold Weather Payment and Winter Heating payment, you should receive any discounts automatically if you're eligible. 

For the Warm Home Discount, each energy supplier also has its own eligibility criteria, which are approved by the energy regulator Ofgem, so you should check with your provider to see whether you meet its requirements.

If you were born before 25 September 1957, it's also likely you'll be able to get Winter Fuel Payments of between £100 and £300 for winter 2023-24. 

The payments are to help pay for your gas or electric heating in winter. You should get this automatically and should contact the Winter Fuel Payment Centre if you think you're eligible but haven't received anything. 

Energy companies are obliged to help you if you tell them you are struggling to pay and will not disconnect you if you miss a bill payment. 

If you are struggling with your bills, let your provider know and explain that you want to establish a payment plan that you can afford. 

Discuss your options with them, as they may include a review of your payments, a reduction in your payments or a payment break, more time to pay, and access to hardship funds.

Will energy prices ever return to levels seen before COVID - if not, why not?

Kate Mulvany, a principal consultant at Cornwall Insight, says...

At this point in time, we are not expecting a return to pre-COVID prices.

This is primarily due to the significant rise in the wholesale prices of electricity and gas following the Russian invasion of Ukraine. 

The cost of the fuel - the wholesale cost or the commodity cost - is the largest part of the energy bill. 

Although some non-wholesale components of energy bills may decrease, the main factor driving prices is the cost of commodities. 

The UK's heavy reliance on imported electricity and natural gas exacerbates this issue. 

Therefore, increasing investment in domestic renewable and low-carbon energy sources is crucial to reduce this dependency.

Additionally, implementing measures to decouple electricity and gas prices in the wholesale market could help lower bills.

Why does Ofgem allow the price cap to be so high when we know how high the profits of energy companies are which in turn causes so much hardship for UK families?

The price cap limits the unit rates and standing charge levels that suppliers can charge domestic customers across many circumstances. 

Some parts of the energy price cap are directly regulated by Ofgem, while others, such as wholesale energy costs, reflect market conditions. 

The price cap includes various elements such as wholesale energy costs, network costs (the cost of moving gas and electricity around the country), operating costs, environmental and social policy costs, and the allowable profit for suppliers.

The role of energy suppliers is to purchase electricity from generators and sell it to customers, managing customer service, billing and other retail functions. 

Ofgem's formula for the price cap includes an allowance for suppliers to make a profit, which is overall a relatively small percentage of the total price cap amount. 

Headlines about energy companies' profits can refer to companies involved throughout the energy industry, not just suppliers. 

For example, companies that extract and transport gas or which generate electricity might not have prices directly regulated by Ofgem. 

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Physical Review Research

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High harmonic generation from an atom in a squeezed-vacuum environment

Shijun wang, shaogang yu, xuanyang lai, and xiaojun liu, phys. rev. research 6 , 033010 – published 1 july 2024.

• No Citing Articles
• INTRODUCTION
• THEORETICAL METHOD
• RESULTS AND DISCUSSION
• CONCLUSIONS AND OUTLOOK
• ACKNOWLEDGMENTS

We investigate high harmonic generation (HHG) of an atom in the presence of squeezed vacuum of a single harmonic mode. Based on a fully quantum time-dependent Schrödinger equation, we derive an analytical formula for the harmonic amplitude. Our simulations of the HHG spectrum with this formula show that the harmonic amplitude of the corresponding squeezed mode can undergo significant changes with different parameters of the squeezed vacuum. Using the time-frequency analysis method, the physics underlying the effects of the vacuum quantum fluctuation (VQF) on the harmonic generation is revealed, which is found to be consistent with the explanation of Fermi's golden rule. Our work establishes a profound connection between harmonic generation and VQF, and may provide an unconventional approach to manipulating harmonic emission.

• Received 12 June 2023
• Revised 25 March 2024
• Accepted 5 June 2024

DOI: https://doi.org/10.1103/PhysRevResearch.6.033010

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

Published by the American Physical Society

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Authors & Affiliations

• 1 State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics , Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430071, China
• 2 School of Physical Sciences, University of Chinese Academy of Sciences , Beijing 100049, China
• 3 Wuhan Institute of Quantum Technology, Wuhan 430206, China
• * Contact author: [email protected]
• † Contact author: [email protected]

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Vol. 6, Iss. 3 — July - September 2024

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Schematic view of HHG from intense laser-atom interaction in a squeezed vacuum of a harmonic mode. The motion of an electron in a strong driving laser field (red curve) is depicted by the green curve [ 25, 26 ], and the emission of harmonics resulting from the electron's transition back to the atomic core is represented by the blue curve. Due to the influence of the quantum fluctuation of the squeezed vacuum (gray shadow) on the electron transition probability, the harmonic amplitude of the corresponding squeezed mode emitted at time t r is weak but becomes strong at t r ′ .

(a), (b) TDSE simulations of the HHG spectra of an atom in a squeezed vacuum of the first-order harmonic mode with the squeezing angle θ k = 0.9 π and the ninth-order harmonic mode with θ k = 0.27 π , respectively, as a function of the squeezing parameter r k . Considering a realistic scenario, the wavelengths of the driving light are 800 nm and 3600 nm, respectively. For more details, see the text. In (b), to better illustrate the change of the amplitude of the ninth-order harmonic, only a part of the harmonic orders are shown. (c) and (d) The amplitude of the first- and ninth-order harmonics in the corresponding single-mode squeezed vacuum state with different r k as a function of θ k . In our simulation, the driving light has a peak intensity of I = 1.15 × 10 14 W / cm 2 with a trapezoidal profile (up- and down-ramped over two cycles, constant over six cycles).

The wavelet time-frequency profile of the harmonic of the corresponding squeezed mode with r k = 0 (solid black curve) and r k = 0.5 (dashed red curve). The gray dashed curves with respect to the right axis denote the | μ k ( t ) | of the squeezed mode. (a) and (b) present the squeezed vacuum of the first-order harmonic mode with θ k = 0.9 π and 1.9 π , respectively. (c) and (d) present the squeezed vacuum of the ninth-order harmonic mode with θ k = 0.27 π and 1.27 π , respectively.

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