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How To Write The Methodology Chapter

The what, why & how explained simply (with examples).

By: Jenna Crossley (PhD) | Reviewed By: Dr. Eunice Rautenbach | September 2021 (Updated April 2023)

So, you’ve pinned down your research topic and undertaken a review of the literature – now it’s time to write up the methodology section of your dissertation, thesis or research paper . But what exactly is the methodology chapter all about – and how do you go about writing one? In this post, we’ll unpack the topic, step by step .

Overview: The Methodology Chapter

  • The purpose  of the methodology chapter
  • Why you need to craft this chapter (really) well
  • How to write and structure the chapter
  • Methodology chapter example
  • Essential takeaways

What (exactly) is the methodology chapter?

The methodology chapter is where you outline the philosophical underpinnings of your research and outline the specific methodological choices you’ve made. The point of the methodology chapter is to tell the reader exactly how you designed your study and, just as importantly, why you did it this way.

Importantly, this chapter should comprehensively describe and justify all the methodological choices you made in your study. For example, the approach you took to your research (i.e., qualitative, quantitative or mixed), who  you collected data from (i.e., your sampling strategy), how you collected your data and, of course, how you analysed it. If that sounds a little intimidating, don’t worry – we’ll explain all these methodological choices in this post .

Free Webinar: Research Methodology 101

Why is the methodology chapter important?

The methodology chapter plays two important roles in your dissertation or thesis:

Firstly, it demonstrates your understanding of research theory, which is what earns you marks. A flawed research design or methodology would mean flawed results. So, this chapter is vital as it allows you to show the marker that you know what you’re doing and that your results are credible .

Secondly, the methodology chapter is what helps to make your study replicable. In other words, it allows other researchers to undertake your study using the same methodological approach, and compare their findings to yours. This is very important within academic research, as each study builds on previous studies.

The methodology chapter is also important in that it allows you to identify and discuss any methodological issues or problems you encountered (i.e., research limitations ), and to explain how you mitigated the impacts of these. Every research project has its limitations , so it’s important to acknowledge these openly and highlight your study’s value despite its limitations . Doing so demonstrates your understanding of research design, which will earn you marks. We’ll discuss limitations in a bit more detail later in this post, so stay tuned!

Need a helping hand?

how to write a methodology for a qualitative research paper

How to write up the methodology chapter

First off, it’s worth noting that the exact structure and contents of the methodology chapter will vary depending on the field of research (e.g., humanities, chemistry or engineering) as well as the university . So, be sure to always check the guidelines provided by your institution for clarity and, if possible, review past dissertations from your university. Here we’re going to discuss a generic structure for a methodology chapter typically found in the sciences.

Before you start writing, it’s always a good idea to draw up a rough outline to guide your writing. Don’t just start writing without knowing what you’ll discuss where. If you do, you’ll likely end up with a disjointed, ill-flowing narrative . You’ll then waste a lot of time rewriting in an attempt to try to stitch all the pieces together. Do yourself a favour and start with the end in mind .

Section 1 – Introduction

As with all chapters in your dissertation or thesis, the methodology chapter should have a brief introduction. In this section, you should remind your readers what the focus of your study is, especially the research aims . As we’ve discussed many times on the blog, your methodology needs to align with your research aims, objectives and research questions. Therefore, it’s useful to frontload this component to remind the reader (and yourself!) what you’re trying to achieve.

In this section, you can also briefly mention how you’ll structure the chapter. This will help orient the reader and provide a bit of a roadmap so that they know what to expect. You don’t need a lot of detail here – just a brief outline will do.

The intro provides a roadmap to your methodology chapter

Section 2 – The Methodology

The next section of your chapter is where you’ll present the actual methodology. In this section, you need to detail and justify the key methodological choices you’ve made in a logical, intuitive fashion. Importantly, this is the heart of your methodology chapter, so you need to get specific – don’t hold back on the details here. This is not one of those “less is more” situations.

Let’s take a look at the most common components you’ll likely need to cover. 

Methodological Choice #1 – Research Philosophy

Research philosophy refers to the underlying beliefs (i.e., the worldview) regarding how data about a phenomenon should be gathered , analysed and used . The research philosophy will serve as the core of your study and underpin all of the other research design choices, so it’s critically important that you understand which philosophy you’ll adopt and why you made that choice. If you’re not clear on this, take the time to get clarity before you make any further methodological choices.

While several research philosophies exist, two commonly adopted ones are positivism and interpretivism . These two sit roughly on opposite sides of the research philosophy spectrum.

Positivism states that the researcher can observe reality objectively and that there is only one reality, which exists independently of the observer. As a consequence, it is quite commonly the underlying research philosophy in quantitative studies and is oftentimes the assumed philosophy in the physical sciences.

Contrasted with this, interpretivism , which is often the underlying research philosophy in qualitative studies, assumes that the researcher performs a role in observing the world around them and that reality is unique to each observer . In other words, reality is observed subjectively .

These are just two philosophies (there are many more), but they demonstrate significantly different approaches to research and have a significant impact on all the methodological choices. Therefore, it’s vital that you clearly outline and justify your research philosophy at the beginning of your methodology chapter, as it sets the scene for everything that follows.

The research philosophy is at the core of the methodology chapter

Methodological Choice #2 – Research Type

The next thing you would typically discuss in your methodology section is the research type. The starting point for this is to indicate whether the research you conducted is inductive or deductive .

Inductive research takes a bottom-up approach , where the researcher begins with specific observations or data and then draws general conclusions or theories from those observations. Therefore these studies tend to be exploratory in terms of approach.

Conversely , d eductive research takes a top-down approach , where the researcher starts with a theory or hypothesis and then tests it using specific observations or data. Therefore these studies tend to be confirmatory in approach.

Related to this, you’ll need to indicate whether your study adopts a qualitative, quantitative or mixed  approach. As we’ve mentioned, there’s a strong link between this choice and your research philosophy, so make sure that your choices are tightly aligned . When you write this section up, remember to clearly justify your choices, as they form the foundation of your study.

Methodological Choice #3 – Research Strategy

Next, you’ll need to discuss your research strategy (also referred to as a research design ). This methodological choice refers to the broader strategy in terms of how you’ll conduct your research, based on the aims of your study.

Several research strategies exist, including experimental , case studies , ethnography , grounded theory, action research , and phenomenology . Let’s take a look at two of these, experimental and ethnographic, to see how they contrast.

Experimental research makes use of the scientific method , where one group is the control group (in which no variables are manipulated ) and another is the experimental group (in which a specific variable is manipulated). This type of research is undertaken under strict conditions in a controlled, artificial environment (e.g., a laboratory). By having firm control over the environment, experimental research typically allows the researcher to establish causation between variables. Therefore, it can be a good choice if you have research aims that involve identifying causal relationships.

Ethnographic research , on the other hand, involves observing and capturing the experiences and perceptions of participants in their natural environment (for example, at home or in the office). In other words, in an uncontrolled environment.  Naturally, this means that this research strategy would be far less suitable if your research aims involve identifying causation, but it would be very valuable if you’re looking to explore and examine a group culture, for example.

As you can see, the right research strategy will depend largely on your research aims and research questions – in other words, what you’re trying to figure out. Therefore, as with every other methodological choice, it’s essential to justify why you chose the research strategy you did.

Methodological Choice #4 – Time Horizon

The next thing you’ll need to detail in your methodology chapter is the time horizon. There are two options here: cross-sectional and longitudinal . In other words, whether the data for your study were all collected at one point in time (cross-sectional) or at multiple points in time (longitudinal).

The choice you make here depends again on your research aims, objectives and research questions. If, for example, you aim to assess how a specific group of people’s perspectives regarding a topic change over time , you’d likely adopt a longitudinal time horizon.

Another important factor to consider is simply whether you have the time necessary to adopt a longitudinal approach (which could involve collecting data over multiple months or even years). Oftentimes, the time pressures of your degree program will force your hand into adopting a cross-sectional time horizon, so keep this in mind.

Methodological Choice #5 – Sampling Strategy

Next, you’ll need to discuss your sampling strategy . There are two main categories of sampling, probability and non-probability sampling.

Probability sampling involves a random (and therefore representative) selection of participants from a population, whereas non-probability sampling entails selecting participants in a non-random  (and therefore non-representative) manner. For example, selecting participants based on ease of access (this is called a convenience sample).

The right sampling approach depends largely on what you’re trying to achieve in your study. Specifically, whether you trying to develop findings that are generalisable to a population or not. Practicalities and resource constraints also play a large role here, as it can oftentimes be challenging to gain access to a truly random sample. In the video below, we explore some of the most common sampling strategies.

Methodological Choice #6 – Data Collection Method

Next up, you’ll need to explain how you’ll go about collecting the necessary data for your study. Your data collection method (or methods) will depend on the type of data that you plan to collect – in other words, qualitative or quantitative data.

Typically, quantitative research relies on surveys , data generated by lab equipment, analytics software or existing datasets. Qualitative research, on the other hand, often makes use of collection methods such as interviews , focus groups , participant observations, and ethnography.

So, as you can see, there is a tight link between this section and the design choices you outlined in earlier sections. Strong alignment between these sections, as well as your research aims and questions is therefore very important.

Methodological Choice #7 – Data Analysis Methods/Techniques

The final major methodological choice that you need to address is that of analysis techniques . In other words, how you’ll go about analysing your date once you’ve collected it. Here it’s important to be very specific about your analysis methods and/or techniques – don’t leave any room for interpretation. Also, as with all choices in this chapter, you need to justify each choice you make.

What exactly you discuss here will depend largely on the type of study you’re conducting (i.e., qualitative, quantitative, or mixed methods). For qualitative studies, common analysis methods include content analysis , thematic analysis and discourse analysis . In the video below, we explain each of these in plain language.

For quantitative studies, you’ll almost always make use of descriptive statistics , and in many cases, you’ll also use inferential statistical techniques (e.g., correlation and regression analysis). In the video below, we unpack some of the core concepts involved in descriptive and inferential statistics.

In this section of your methodology chapter, it’s also important to discuss how you prepared your data for analysis, and what software you used (if any). For example, quantitative data will often require some initial preparation such as removing duplicates or incomplete responses . Similarly, qualitative data will often require transcription and perhaps even translation. As always, remember to state both what you did and why you did it.

Section 3 – The Methodological Limitations

With the key methodological choices outlined and justified, the next step is to discuss the limitations of your design. No research methodology is perfect – there will always be trade-offs between the “ideal” methodology and what’s practical and viable, given your constraints. Therefore, this section of your methodology chapter is where you’ll discuss the trade-offs you had to make, and why these were justified given the context.

Methodological limitations can vary greatly from study to study, ranging from common issues such as time and budget constraints to issues of sample or selection bias . For example, you may find that you didn’t manage to draw in enough respondents to achieve the desired sample size (and therefore, statistically significant results), or your sample may be skewed heavily towards a certain demographic, thereby negatively impacting representativeness .

In this section, it’s important to be critical of the shortcomings of your study. There’s no use trying to hide them (your marker will be aware of them regardless). By being critical, you’ll demonstrate to your marker that you have a strong understanding of research theory, so don’t be shy here. At the same time, don’t beat your study to death . State the limitations, why these were justified, how you mitigated their impacts to the best degree possible, and how your study still provides value despite these limitations .

Section 4 – Concluding Summary

Finally, it’s time to wrap up the methodology chapter with a brief concluding summary. In this section, you’ll want to concisely summarise what you’ve presented in the chapter. Here, it can be a good idea to use a figure to summarise the key decisions, especially if your university recommends using a specific model (for example, Saunders’ Research Onion ).

Importantly, this section needs to be brief – a paragraph or two maximum (it’s a summary, after all). Also, make sure that when you write up your concluding summary, you include only what you’ve already discussed in your chapter; don’t add any new information.

Keep it simple

Methodology Chapter Example

In the video below, we walk you through an example of a high-quality research methodology chapter from a dissertation. We also unpack our free methodology chapter template so that you can see how best to structure your chapter.

Wrapping Up

And there you have it – the methodology chapter in a nutshell. As we’ve mentioned, the exact contents and structure of this chapter can vary between universities , so be sure to check in with your institution before you start writing. If possible, try to find dissertations or theses from former students of your specific degree program – this will give you a strong indication of the expectations and norms when it comes to the methodology chapter (and all the other chapters!).

Also, remember the golden rule of the methodology chapter – justify every choice ! Make sure that you clearly explain the “why” for every “what”, and reference credible methodology textbooks or academic sources to back up your justifications.

If you need a helping hand with your research methodology (or any other component of your research), be sure to check out our private coaching service , where we hold your hand through every step of the research journey. Until next time, good luck!

how to write a methodology for a qualitative research paper

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SciSpace Resources

Here's What You Need to Understand About Research Methodology

Deeptanshu D

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.

Analyze and understand research methodologies faster with SciSpace Copilot

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.

how to write a methodology for a qualitative research paper

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Chapter 1. Introduction

“Science is in danger, and for that reason it is becoming dangerous” -Pierre Bourdieu, Science of Science and Reflexivity

Why an Open Access Textbook on Qualitative Research Methods?

I have been teaching qualitative research methods to both undergraduates and graduate students for many years.  Although there are some excellent textbooks out there, they are often costly, and none of them, to my mind, properly introduces qualitative research methods to the beginning student (whether undergraduate or graduate student).  In contrast, this open-access textbook is designed as a (free) true introduction to the subject, with helpful, practical pointers on how to conduct research and how to access more advanced instruction.  

Textbooks are typically arranged in one of two ways: (1) by technique (each chapter covers one method used in qualitative research); or (2) by process (chapters advance from research design through publication).  But both of these approaches are necessary for the beginner student.  This textbook will have sections dedicated to the process as well as the techniques of qualitative research.  This is a true “comprehensive” book for the beginning student.  In addition to covering techniques of data collection and data analysis, it provides a road map of how to get started and how to keep going and where to go for advanced instruction.  It covers aspects of research design and research communication as well as methods employed.  Along the way, it includes examples from many different disciplines in the social sciences.

The primary goal has been to create a useful, accessible, engaging textbook for use across many disciplines.  And, let’s face it.  Textbooks can be boring.  I hope readers find this to be a little different.  I have tried to write in a practical and forthright manner, with many lively examples and references to good and intellectually creative qualitative research.  Woven throughout the text are short textual asides (in colored textboxes) by professional (academic) qualitative researchers in various disciplines.  These short accounts by practitioners should help inspire students.  So, let’s begin!

What is Research?

When we use the word research , what exactly do we mean by that?  This is one of those words that everyone thinks they understand, but it is worth beginning this textbook with a short explanation.  We use the term to refer to “empirical research,” which is actually a historically specific approach to understanding the world around us.  Think about how you know things about the world. [1] You might know your mother loves you because she’s told you she does.  Or because that is what “mothers” do by tradition.  Or you might know because you’ve looked for evidence that she does, like taking care of you when you are sick or reading to you in bed or working two jobs so you can have the things you need to do OK in life.  Maybe it seems churlish to look for evidence; you just take it “on faith” that you are loved.

Only one of the above comes close to what we mean by research.  Empirical research is research (investigation) based on evidence.  Conclusions can then be drawn from observable data.  This observable data can also be “tested” or checked.  If the data cannot be tested, that is a good indication that we are not doing research.  Note that we can never “prove” conclusively, through observable data, that our mothers love us.  We might have some “disconfirming evidence” (that time she didn’t show up to your graduation, for example) that could push you to question an original hypothesis , but no amount of “confirming evidence” will ever allow us to say with 100% certainty, “my mother loves me.”  Faith and tradition and authority work differently.  Our knowledge can be 100% certain using each of those alternative methods of knowledge, but our certainty in those cases will not be based on facts or evidence.

For many periods of history, those in power have been nervous about “science” because it uses evidence and facts as the primary source of understanding the world, and facts can be at odds with what power or authority or tradition want you to believe.  That is why I say that scientific empirical research is a historically specific approach to understand the world.  You are in college or university now partly to learn how to engage in this historically specific approach.

In the sixteenth and seventeenth centuries in Europe, there was a newfound respect for empirical research, some of which was seriously challenging to the established church.  Using observations and testing them, scientists found that the earth was not at the center of the universe, for example, but rather that it was but one planet of many which circled the sun. [2]   For the next two centuries, the science of astronomy, physics, biology, and chemistry emerged and became disciplines taught in universities.  All used the scientific method of observation and testing to advance knowledge.  Knowledge about people , however, and social institutions, however, was still left to faith, tradition, and authority.  Historians and philosophers and poets wrote about the human condition, but none of them used research to do so. [3]

It was not until the nineteenth century that “social science” really emerged, using the scientific method (empirical observation) to understand people and social institutions.  New fields of sociology, economics, political science, and anthropology emerged.  The first sociologists, people like Auguste Comte and Karl Marx, sought specifically to apply the scientific method of research to understand society, Engels famously claiming that Marx had done for the social world what Darwin did for the natural world, tracings its laws of development.  Today we tend to take for granted the naturalness of science here, but it is actually a pretty recent and radical development.

To return to the question, “does your mother love you?”  Well, this is actually not really how a researcher would frame the question, as it is too specific to your case.  It doesn’t tell us much about the world at large, even if it does tell us something about you and your relationship with your mother.  A social science researcher might ask, “do mothers love their children?”  Or maybe they would be more interested in how this loving relationship might change over time (e.g., “do mothers love their children more now than they did in the 18th century when so many children died before reaching adulthood?”) or perhaps they might be interested in measuring quality of love across cultures or time periods, or even establishing “what love looks like” using the mother/child relationship as a site of exploration.  All of these make good research questions because we can use observable data to answer them.

What is Qualitative Research?

“All we know is how to learn. How to study, how to listen, how to talk, how to tell.  If we don’t tell the world, we don’t know the world.  We’re lost in it, we die.” -Ursula LeGuin, The Telling

At its simplest, qualitative research is research about the social world that does not use numbers in its analyses.  All those who fear statistics can breathe a sigh of relief – there are no mathematical formulae or regression models in this book! But this definition is less about what qualitative research can be and more about what it is not.  To be honest, any simple statement will fail to capture the power and depth of qualitative research.  One way of contrasting qualitative research to quantitative research is to note that the focus of qualitative research is less about explaining and predicting relationships between variables and more about understanding the social world.  To use our mother love example, the question about “what love looks like” is a good question for the qualitative researcher while all questions measuring love or comparing incidences of love (both of which require measurement) are good questions for quantitative researchers. Patton writes,

Qualitative data describe.  They take us, as readers, into the time and place of the observation so that we know what it was like to have been there.  They capture and communicate someone else’s experience of the world in his or her own words.  Qualitative data tell a story. ( Patton 2002:47 )

Qualitative researchers are asking different questions about the world than their quantitative colleagues.  Even when researchers are employed in “mixed methods” research ( both quantitative and qualitative), they are using different methods to address different questions of the study.  I do a lot of research about first-generation and working-college college students.  Where a quantitative researcher might ask, how many first-generation college students graduate from college within four years? Or does first-generation college status predict high student debt loads?  A qualitative researcher might ask, how does the college experience differ for first-generation college students?  What is it like to carry a lot of debt, and how does this impact the ability to complete college on time?  Both sets of questions are important, but they can only be answered using specific tools tailored to those questions.  For the former, you need large numbers to make adequate comparisons.  For the latter, you need to talk to people, find out what they are thinking and feeling, and try to inhabit their shoes for a little while so you can make sense of their experiences and beliefs.

Examples of Qualitative Research

You have probably seen examples of qualitative research before, but you might not have paid particular attention to how they were produced or realized that the accounts you were reading were the result of hours, months, even years of research “in the field.”  A good qualitative researcher will present the product of their hours of work in such a way that it seems natural, even obvious, to the reader.  Because we are trying to convey what it is like answers, qualitative research is often presented as stories – stories about how people live their lives, go to work, raise their children, interact with one another.  In some ways, this can seem like reading particularly insightful novels.  But, unlike novels, there are very specific rules and guidelines that qualitative researchers follow to ensure that the “story” they are telling is accurate , a truthful rendition of what life is like for the people being studied.  Most of this textbook will be spent conveying those rules and guidelines.  Let’s take a look, first, however, at three examples of what the end product looks like.  I have chosen these three examples to showcase very different approaches to qualitative research, and I will return to these five examples throughout the book.  They were all published as whole books (not chapters or articles), and they are worth the long read, if you have the time.  I will also provide some information on how these books came to be and the length of time it takes to get them into book version.  It is important you know about this process, and the rest of this textbook will help explain why it takes so long to conduct good qualitative research!

Example 1 : The End Game (ethnography + interviews)

Corey Abramson is a sociologist who teaches at the University of Arizona.   In 2015 he published The End Game: How Inequality Shapes our Final Years ( 2015 ). This book was based on the research he did for his dissertation at the University of California-Berkeley in 2012.  Actually, the dissertation was completed in 2012 but the work that was produced that took several years.  The dissertation was entitled, “This is How We Live, This is How We Die: Social Stratification, Aging, and Health in Urban America” ( 2012 ).  You can see how the book version, which was written for a more general audience, has a more engaging sound to it, but that the dissertation version, which is what academic faculty read and evaluate, has a more descriptive title.  You can read the title and know that this is a study about aging and health and that the focus is going to be inequality and that the context (place) is going to be “urban America.”  It’s a study about “how” people do something – in this case, how they deal with aging and death.  This is the very first sentence of the dissertation, “From our first breath in the hospital to the day we die, we live in a society characterized by unequal opportunities for maintaining health and taking care of ourselves when ill.  These disparities reflect persistent racial, socio-economic, and gender-based inequalities and contribute to their persistence over time” ( 1 ).  What follows is a truthful account of how that is so.

Cory Abramson spent three years conducting his research in four different urban neighborhoods.  We call the type of research he conducted “comparative ethnographic” because he designed his study to compare groups of seniors as they went about their everyday business.  It’s comparative because he is comparing different groups (based on race, class, gender) and ethnographic because he is studying the culture/way of life of a group. [4]   He had an educated guess, rooted in what previous research had shown and what social theory would suggest, that people’s experiences of aging differ by race, class, and gender.  So, he set up a research design that would allow him to observe differences.  He chose two primarily middle-class (one was racially diverse and the other was predominantly White) and two primarily poor neighborhoods (one was racially diverse and the other was predominantly African American).  He hung out in senior centers and other places seniors congregated, watched them as they took the bus to get prescriptions filled, sat in doctor’s offices with them, and listened to their conversations with each other.  He also conducted more formal conversations, what we call in-depth interviews, with sixty seniors from each of the four neighborhoods.  As with a lot of fieldwork , as he got closer to the people involved, he both expanded and deepened his reach –

By the end of the project, I expanded my pool of general observations to include various settings frequented by seniors: apartment building common rooms, doctors’ offices, emergency rooms, pharmacies, senior centers, bars, parks, corner stores, shopping centers, pool halls, hair salons, coffee shops, and discount stores. Over the course of the three years of fieldwork, I observed hundreds of elders, and developed close relationships with a number of them. ( 2012:10 )

When Abramson rewrote the dissertation for a general audience and published his book in 2015, it got a lot of attention.  It is a beautifully written book and it provided insight into a common human experience that we surprisingly know very little about.  It won the Outstanding Publication Award by the American Sociological Association Section on Aging and the Life Course and was featured in the New York Times .  The book was about aging, and specifically how inequality shapes the aging process, but it was also about much more than that.  It helped show how inequality affects people’s everyday lives.  For example, by observing the difficulties the poor had in setting up appointments and getting to them using public transportation and then being made to wait to see a doctor, sometimes in standing-room-only situations, when they are unwell, and then being treated dismissively by hospital staff, Abramson allowed readers to feel the material reality of being poor in the US.  Comparing these examples with seniors with adequate supplemental insurance who have the resources to hire car services or have others assist them in arranging care when they need it, jolts the reader to understand and appreciate the difference money makes in the lives and circumstances of us all, and in a way that is different than simply reading a statistic (“80% of the poor do not keep regular doctor’s appointments”) does.  Qualitative research can reach into spaces and places that often go unexamined and then reports back to the rest of us what it is like in those spaces and places.

Example 2: Racing for Innocence (Interviews + Content Analysis + Fictional Stories)

Jennifer Pierce is a Professor of American Studies at the University of Minnesota.  Trained as a sociologist, she has written a number of books about gender, race, and power.  Her very first book, Gender Trials: Emotional Lives in Contemporary Law Firms, published in 1995, is a brilliant look at gender dynamics within two law firms.  Pierce was a participant observer, working as a paralegal, and she observed how female lawyers and female paralegals struggled to obtain parity with their male colleagues.

Fifteen years later, she reexamined the context of the law firm to include an examination of racial dynamics, particularly how elite white men working in these spaces created and maintained a culture that made it difficult for both female attorneys and attorneys of color to thrive. Her book, Racing for Innocence: Whiteness, Gender, and the Backlash Against Affirmative Action , published in 2012, is an interesting and creative blending of interviews with attorneys, content analyses of popular films during this period, and fictional accounts of racial discrimination and sexual harassment.  The law firm she chose to study had come under an affirmative action order and was in the process of implementing equitable policies and programs.  She wanted to understand how recipients of white privilege (the elite white male attorneys) come to deny the role they play in reproducing inequality.  Through interviews with attorneys who were present both before and during the affirmative action order, she creates a historical record of the “bad behavior” that necessitated new policies and procedures, but also, and more importantly , probed the participants ’ understanding of this behavior.  It should come as no surprise that most (but not all) of the white male attorneys saw little need for change, and that almost everyone else had accounts that were different if not sometimes downright harrowing.

I’ve used Pierce’s book in my qualitative research methods courses as an example of an interesting blend of techniques and presentation styles.  My students often have a very difficult time with the fictional accounts she includes.  But they serve an important communicative purpose here.  They are her attempts at presenting “both sides” to an objective reality – something happens (Pierce writes this something so it is very clear what it is), and the two participants to the thing that happened have very different understandings of what this means.  By including these stories, Pierce presents one of her key findings – people remember things differently and these different memories tend to support their own ideological positions.  I wonder what Pierce would have written had she studied the murder of George Floyd or the storming of the US Capitol on January 6 or any number of other historic events whose observers and participants record very different happenings.

This is not to say that qualitative researchers write fictional accounts.  In fact, the use of fiction in our work remains controversial.  When used, it must be clearly identified as a presentation device, as Pierce did.  I include Racing for Innocence here as an example of the multiple uses of methods and techniques and the way that these work together to produce better understandings by us, the readers, of what Pierce studied.  We readers come away with a better grasp of how and why advantaged people understate their own involvement in situations and structures that advantage them.  This is normal human behavior , in other words.  This case may have been about elite white men in law firms, but the general insights here can be transposed to other settings.  Indeed, Pierce argues that more research needs to be done about the role elites play in the reproduction of inequality in the workplace in general.

Example 3: Amplified Advantage (Mixed Methods: Survey Interviews + Focus Groups + Archives)

The final example comes from my own work with college students, particularly the ways in which class background affects the experience of college and outcomes for graduates.  I include it here as an example of mixed methods, and for the use of supplementary archival research.  I’ve done a lot of research over the years on first-generation, low-income, and working-class college students.  I am curious (and skeptical) about the possibility of social mobility today, particularly with the rising cost of college and growing inequality in general.  As one of the few people in my family to go to college, I didn’t grow up with a lot of examples of what college was like or how to make the most of it.  And when I entered graduate school, I realized with dismay that there were very few people like me there.  I worried about becoming too different from my family and friends back home.  And I wasn’t at all sure that I would ever be able to pay back the huge load of debt I was taking on.  And so I wrote my dissertation and first two books about working-class college students.  These books focused on experiences in college and the difficulties of navigating between family and school ( Hurst 2010a, 2012 ).  But even after all that research, I kept coming back to wondering if working-class students who made it through college had an equal chance at finding good jobs and happy lives,

What happens to students after college?  Do working-class students fare as well as their peers?  I knew from my own experience that barriers continued through graduate school and beyond, and that my debtload was higher than that of my peers, constraining some of the choices I made when I graduated.  To answer these questions, I designed a study of students attending small liberal arts colleges, the type of college that tried to equalize the experience of students by requiring all students to live on campus and offering small classes with lots of interaction with faculty.  These private colleges tend to have more money and resources so they can provide financial aid to low-income students.  They also attract some very wealthy students.  Because they enroll students across the class spectrum, I would be able to draw comparisons.  I ended up spending about four years collecting data, both a survey of more than 2000 students (which formed the basis for quantitative analyses) and qualitative data collection (interviews, focus groups, archival research, and participant observation).  This is what we call a “mixed methods” approach because we use both quantitative and qualitative data.  The survey gave me a large enough number of students that I could make comparisons of the how many kind, and to be able to say with some authority that there were in fact significant differences in experience and outcome by class (e.g., wealthier students earned more money and had little debt; working-class students often found jobs that were not in their chosen careers and were very affected by debt, upper-middle-class students were more likely to go to graduate school).  But the survey analyses could not explain why these differences existed.  For that, I needed to talk to people and ask them about their motivations and aspirations.  I needed to understand their perceptions of the world, and it is very hard to do this through a survey.

By interviewing students and recent graduates, I was able to discern particular patterns and pathways through college and beyond.  Specifically, I identified three versions of gameplay.  Upper-middle-class students, whose parents were themselves professionals (academics, lawyers, managers of non-profits), saw college as the first stage of their education and took classes and declared majors that would prepare them for graduate school.  They also spent a lot of time building their resumes, taking advantage of opportunities to help professors with their research, or study abroad.  This helped them gain admission to highly-ranked graduate schools and interesting jobs in the public sector.  In contrast, upper-class students, whose parents were wealthy and more likely to be engaged in business (as CEOs or other high-level directors), prioritized building social capital.  They did this by joining fraternities and sororities and playing club sports.  This helped them when they graduated as they called on friends and parents of friends to find them well-paying jobs.  Finally, low-income, first-generation, and working-class students were often adrift.  They took the classes that were recommended to them but without the knowledge of how to connect them to life beyond college.  They spent time working and studying rather than partying or building their resumes.  All three sets of students thought they were “doing college” the right way, the way that one was supposed to do college.   But these three versions of gameplay led to distinct outcomes that advantaged some students over others.  I titled my work “Amplified Advantage” to highlight this process.

These three examples, Cory Abramson’s The End Game , Jennifer Peirce’s Racing for Innocence, and my own Amplified Advantage, demonstrate the range of approaches and tools available to the qualitative researcher.  They also help explain why qualitative research is so important.  Numbers can tell us some things about the world, but they cannot get at the hearts and minds, motivations and beliefs of the people who make up the social worlds we inhabit.  For that, we need tools that allow us to listen and make sense of what people tell us and show us.  That is what good qualitative research offers us.

How Is This Book Organized?

This textbook is organized as a comprehensive introduction to the use of qualitative research methods.  The first half covers general topics (e.g., approaches to qualitative research, ethics) and research design (necessary steps for building a successful qualitative research study).  The second half reviews various data collection and data analysis techniques.  Of course, building a successful qualitative research study requires some knowledge of data collection and data analysis so the chapters in the first half and the chapters in the second half should be read in conversation with each other.  That said, each chapter can be read on its own for assistance with a particular narrow topic.  In addition to the chapters, a helpful glossary can be found in the back of the book.  Rummage around in the text as needed.

Chapter Descriptions

Chapter 2 provides an overview of the Research Design Process.  How does one begin a study? What is an appropriate research question?  How is the study to be done – with what methods ?  Involving what people and sites?  Although qualitative research studies can and often do change and develop over the course of data collection, it is important to have a good idea of what the aims and goals of your study are at the outset and a good plan of how to achieve those aims and goals.  Chapter 2 provides a road map of the process.

Chapter 3 describes and explains various ways of knowing the (social) world.  What is it possible for us to know about how other people think or why they behave the way they do?  What does it mean to say something is a “fact” or that it is “well-known” and understood?  Qualitative researchers are particularly interested in these questions because of the types of research questions we are interested in answering (the how questions rather than the how many questions of quantitative research).  Qualitative researchers have adopted various epistemological approaches.  Chapter 3 will explore these approaches, highlighting interpretivist approaches that acknowledge the subjective aspect of reality – in other words, reality and knowledge are not objective but rather influenced by (interpreted through) people.

Chapter 4 focuses on the practical matter of developing a research question and finding the right approach to data collection.  In any given study (think of Cory Abramson’s study of aging, for example), there may be years of collected data, thousands of observations , hundreds of pages of notes to read and review and make sense of.  If all you had was a general interest area (“aging”), it would be very difficult, nearly impossible, to make sense of all of that data.  The research question provides a helpful lens to refine and clarify (and simplify) everything you find and collect.  For that reason, it is important to pull out that lens (articulate the research question) before you get started.  In the case of the aging study, Cory Abramson was interested in how inequalities affected understandings and responses to aging.  It is for this reason he designed a study that would allow him to compare different groups of seniors (some middle-class, some poor).  Inevitably, he saw much more in the three years in the field than what made it into his book (or dissertation), but he was able to narrow down the complexity of the social world to provide us with this rich account linked to the original research question.  Developing a good research question is thus crucial to effective design and a successful outcome.  Chapter 4 will provide pointers on how to do this.  Chapter 4 also provides an overview of general approaches taken to doing qualitative research and various “traditions of inquiry.”

Chapter 5 explores sampling .  After you have developed a research question and have a general idea of how you will collect data (Observations?  Interviews?), how do you go about actually finding people and sites to study?  Although there is no “correct number” of people to interview , the sample should follow the research question and research design.  Unlike quantitative research, qualitative research involves nonprobability sampling.  Chapter 5 explains why this is so and what qualities instead make a good sample for qualitative research.

Chapter 6 addresses the importance of reflexivity in qualitative research.  Related to epistemological issues of how we know anything about the social world, qualitative researchers understand that we the researchers can never be truly neutral or outside the study we are conducting.  As observers, we see things that make sense to us and may entirely miss what is either too obvious to note or too different to comprehend.  As interviewers, as much as we would like to ask questions neutrally and remain in the background, interviews are a form of conversation, and the persons we interview are responding to us .  Therefore, it is important to reflect upon our social positions and the knowledges and expectations we bring to our work and to work through any blind spots that we may have.  Chapter 6 provides some examples of reflexivity in practice and exercises for thinking through one’s own biases.

Chapter 7 is a very important chapter and should not be overlooked.  As a practical matter, it should also be read closely with chapters 6 and 8.  Because qualitative researchers deal with people and the social world, it is imperative they develop and adhere to a strong ethical code for conducting research in a way that does not harm.  There are legal requirements and guidelines for doing so (see chapter 8), but these requirements should not be considered synonymous with the ethical code required of us.   Each researcher must constantly interrogate every aspect of their research, from research question to design to sample through analysis and presentation, to ensure that a minimum of harm (ideally, zero harm) is caused.  Because each research project is unique, the standards of care for each study are unique.  Part of being a professional researcher is carrying this code in one’s heart, being constantly attentive to what is required under particular circumstances.  Chapter 7 provides various research scenarios and asks readers to weigh in on the suitability and appropriateness of the research.  If done in a class setting, it will become obvious fairly quickly that there are often no absolutely correct answers, as different people find different aspects of the scenarios of greatest importance.  Minimizing the harm in one area may require possible harm in another.  Being attentive to all the ethical aspects of one’s research and making the best judgments one can, clearly and consciously, is an integral part of being a good researcher.

Chapter 8 , best to be read in conjunction with chapter 7, explains the role and importance of Institutional Review Boards (IRBs) .  Under federal guidelines, an IRB is an appropriately constituted group that has been formally designated to review and monitor research involving human subjects .  Every institution that receives funding from the federal government has an IRB.  IRBs have the authority to approve, require modifications to (to secure approval), or disapprove research.  This group review serves an important role in the protection of the rights and welfare of human research subjects.  Chapter 8 reviews the history of IRBs and the work they do but also argues that IRBs’ review of qualitative research is often both over-inclusive and under-inclusive.  Some aspects of qualitative research are not well understood by IRBs, given that they were developed to prevent abuses in biomedical research.  Thus, it is important not to rely on IRBs to identify all the potential ethical issues that emerge in our research (see chapter 7).

Chapter 9 provides help for getting started on formulating a research question based on gaps in the pre-existing literature.  Research is conducted as part of a community, even if particular studies are done by single individuals (or small teams).  What any of us finds and reports back becomes part of a much larger body of knowledge.  Thus, it is important that we look at the larger body of knowledge before we actually start our bit to see how we can best contribute.  When I first began interviewing working-class college students, there was only one other similar study I could find, and it hadn’t been published (it was a dissertation of students from poor backgrounds).  But there had been a lot published by professors who had grown up working class and made it through college despite the odds.  These accounts by “working-class academics” became an important inspiration for my study and helped me frame the questions I asked the students I interviewed.  Chapter 9 will provide some pointers on how to search for relevant literature and how to use this to refine your research question.

Chapter 10 serves as a bridge between the two parts of the textbook, by introducing techniques of data collection.  Qualitative research is often characterized by the form of data collection – for example, an ethnographic study is one that employs primarily observational data collection for the purpose of documenting and presenting a particular culture or ethnos.  Techniques can be effectively combined, depending on the research question and the aims and goals of the study.   Chapter 10 provides a general overview of all the various techniques and how they can be combined.

The second part of the textbook moves into the doing part of qualitative research once the research question has been articulated and the study designed.  Chapters 11 through 17 cover various data collection techniques and approaches.  Chapters 18 and 19 provide a very simple overview of basic data analysis.  Chapter 20 covers communication of the data to various audiences, and in various formats.

Chapter 11 begins our overview of data collection techniques with a focus on interviewing , the true heart of qualitative research.  This technique can serve as the primary and exclusive form of data collection, or it can be used to supplement other forms (observation, archival).  An interview is distinct from a survey, where questions are asked in a specific order and often with a range of predetermined responses available.  Interviews can be conversational and unstructured or, more conventionally, semistructured , where a general set of interview questions “guides” the conversation.  Chapter 11 covers the basics of interviews: how to create interview guides, how many people to interview, where to conduct the interview, what to watch out for (how to prepare against things going wrong), and how to get the most out of your interviews.

Chapter 12 covers an important variant of interviewing, the focus group.  Focus groups are semistructured interviews with a group of people moderated by a facilitator (the researcher or researcher’s assistant).  Focus groups explicitly use group interaction to assist in the data collection.  They are best used to collect data on a specific topic that is non-personal and shared among the group.  For example, asking a group of college students about a common experience such as taking classes by remote delivery during the pandemic year of 2020.  Chapter 12 covers the basics of focus groups: when to use them, how to create interview guides for them, and how to run them effectively.

Chapter 13 moves away from interviewing to the second major form of data collection unique to qualitative researchers – observation .  Qualitative research that employs observation can best be understood as falling on a continuum of “fly on the wall” observation (e.g., observing how strangers interact in a doctor’s waiting room) to “participant” observation, where the researcher is also an active participant of the activity being observed.  For example, an activist in the Black Lives Matter movement might want to study the movement, using her inside position to gain access to observe key meetings and interactions.  Chapter  13 covers the basics of participant observation studies: advantages and disadvantages, gaining access, ethical concerns related to insider/outsider status and entanglement, and recording techniques.

Chapter 14 takes a closer look at “deep ethnography” – immersion in the field of a particularly long duration for the purpose of gaining a deeper understanding and appreciation of a particular culture or social world.  Clifford Geertz called this “deep hanging out.”  Whereas participant observation is often combined with semistructured interview techniques, deep ethnography’s commitment to “living the life” or experiencing the situation as it really is demands more conversational and natural interactions with people.  These interactions and conversations may take place over months or even years.  As can be expected, there are some costs to this technique, as well as some very large rewards when done competently.  Chapter 14 provides some examples of deep ethnographies that will inspire some beginning researchers and intimidate others.

Chapter 15 moves in the opposite direction of deep ethnography, a technique that is the least positivist of all those discussed here, to mixed methods , a set of techniques that is arguably the most positivist .  A mixed methods approach combines both qualitative data collection and quantitative data collection, commonly by combining a survey that is analyzed statistically (e.g., cross-tabs or regression analyses of large number probability samples) with semi-structured interviews.  Although it is somewhat unconventional to discuss mixed methods in textbooks on qualitative research, I think it is important to recognize this often-employed approach here.  There are several advantages and some disadvantages to taking this route.  Chapter 16 will describe those advantages and disadvantages and provide some particular guidance on how to design a mixed methods study for maximum effectiveness.

Chapter 16 covers data collection that does not involve live human subjects at all – archival and historical research (chapter 17 will also cover data that does not involve interacting with human subjects).  Sometimes people are unavailable to us, either because they do not wish to be interviewed or observed (as is the case with many “elites”) or because they are too far away, in both place and time.  Fortunately, humans leave many traces and we can often answer questions we have by examining those traces.  Special collections and archives can be goldmines for social science research.  This chapter will explain how to access these places, for what purposes, and how to begin to make sense of what you find.

Chapter 17 covers another data collection area that does not involve face-to-face interaction with humans: content analysis .  Although content analysis may be understood more properly as a data analysis technique, the term is often used for the entire approach, which will be the case here.  Content analysis involves interpreting meaning from a body of text.  This body of text might be something found in historical records (see chapter 16) or something collected by the researcher, as in the case of comment posts on a popular blog post.  I once used the stories told by student loan debtors on the website studentloanjustice.org as the content I analyzed.  Content analysis is particularly useful when attempting to define and understand prevalent stories or communication about a topic of interest.  In other words, when we are less interested in what particular people (our defined sample) are doing or believing and more interested in what general narratives exist about a particular topic or issue.  This chapter will explore different approaches to content analysis and provide helpful tips on how to collect data, how to turn that data into codes for analysis, and how to go about presenting what is found through analysis.

Where chapter 17 has pushed us towards data analysis, chapters 18 and 19 are all about what to do with the data collected, whether that data be in the form of interview transcripts or fieldnotes from observations.  Chapter 18 introduces the basics of coding , the iterative process of assigning meaning to the data in order to both simplify and identify patterns.  What is a code and how does it work?  What are the different ways of coding data, and when should you use them?  What is a codebook, and why do you need one?  What does the process of data analysis look like?

Chapter 19 goes further into detail on codes and how to use them, particularly the later stages of coding in which our codes are refined, simplified, combined, and organized.  These later rounds of coding are essential to getting the most out of the data we’ve collected.  As students are often overwhelmed with the amount of data (a corpus of interview transcripts typically runs into the hundreds of pages; fieldnotes can easily top that), this chapter will also address time management and provide suggestions for dealing with chaos and reminders that feeling overwhelmed at the analysis stage is part of the process.  By the end of the chapter, you should understand how “findings” are actually found.

The book concludes with a chapter dedicated to the effective presentation of data results.  Chapter 20 covers the many ways that researchers communicate their studies to various audiences (academic, personal, political), what elements must be included in these various publications, and the hallmarks of excellent qualitative research that various audiences will be expecting.  Because qualitative researchers are motivated by understanding and conveying meaning , effective communication is not only an essential skill but a fundamental facet of the entire research project.  Ethnographers must be able to convey a certain sense of verisimilitude , the appearance of true reality.  Those employing interviews must faithfully depict the key meanings of the people they interviewed in a way that rings true to those people, even if the end result surprises them.  And all researchers must strive for clarity in their publications so that various audiences can understand what was found and why it is important.

The book concludes with a short chapter ( chapter 21 ) discussing the value of qualitative research. At the very end of this book, you will find a glossary of terms. I recommend you make frequent use of the glossary and add to each entry as you find examples. Although the entries are meant to be simple and clear, you may also want to paraphrase the definition—make it “make sense” to you, in other words. In addition to the standard reference list (all works cited here), you will find various recommendations for further reading at the end of many chapters. Some of these recommendations will be examples of excellent qualitative research, indicated with an asterisk (*) at the end of the entry. As they say, a picture is worth a thousand words. A good example of qualitative research can teach you more about conducting research than any textbook can (this one included). I highly recommend you select one to three examples from these lists and read them along with the textbook.

A final note on the choice of examples – you will note that many of the examples used in the text come from research on college students.  This is for two reasons.  First, as most of my research falls in this area, I am most familiar with this literature and have contacts with those who do research here and can call upon them to share their stories with you.  Second, and more importantly, my hope is that this textbook reaches a wide audience of beginning researchers who study widely and deeply across the range of what can be known about the social world (from marine resources management to public policy to nursing to political science to sexuality studies and beyond).  It is sometimes difficult to find examples that speak to all those research interests, however. A focus on college students is something that all readers can understand and, hopefully, appreciate, as we are all now or have been at some point a college student.

Recommended Reading: Other Qualitative Research Textbooks

I’ve included a brief list of some of my favorite qualitative research textbooks and guidebooks if you need more than what you will find in this introductory text.  For each, I’ve also indicated if these are for “beginning” or “advanced” (graduate-level) readers.  Many of these books have several editions that do not significantly vary; the edition recommended is merely the edition I have used in teaching and to whose page numbers any specific references made in the text agree.

Barbour, Rosaline. 2014. Introducing Qualitative Research: A Student’s Guide. Thousand Oaks, CA: SAGE.  A good introduction to qualitative research, with abundant examples (often from the discipline of health care) and clear definitions.  Includes quick summaries at the ends of each chapter.  However, some US students might find the British context distracting and can be a bit advanced in some places.  Beginning .

Bloomberg, Linda Dale, and Marie F. Volpe. 2012. Completing Your Qualitative Dissertation . 2nd ed. Thousand Oaks, CA: SAGE.  Specifically designed to guide graduate students through the research process. Advanced .

Creswell, John W., and Cheryl Poth. 2018 Qualitative Inquiry and Research Design: Choosing among Five Traditions .  4th ed. Thousand Oaks, CA: SAGE.  This is a classic and one of the go-to books I used myself as a graduate student.  One of the best things about this text is its clear presentation of five distinct traditions in qualitative research.  Despite the title, this reasonably sized book is about more than research design, including both data analysis and how to write about qualitative research.  Advanced .

Lareau, Annette. 2021. Listening to People: A Practical Guide to Interviewing, Participant Observation, Data Analysis, and Writing It All Up .  Chicago: University of Chicago Press. A readable and personal account of conducting qualitative research by an eminent sociologist, with a heavy emphasis on the kinds of participant-observation research conducted by the author.  Despite its reader-friendliness, this is really a book targeted to graduate students learning the craft.  Advanced .

Lune, Howard, and Bruce L. Berg. 2018. 9th edition.  Qualitative Research Methods for the Social Sciences.  Pearson . Although a good introduction to qualitative methods, the authors favor symbolic interactionist and dramaturgical approaches, which limits the appeal primarily to sociologists.  Beginning .

Marshall, Catherine, and Gretchen B. Rossman. 2016. 6th edition. Designing Qualitative Research. Thousand Oaks, CA: SAGE.  Very readable and accessible guide to research design by two educational scholars.  Although the presentation is sometimes fairly dry, personal vignettes and illustrations enliven the text.  Beginning .

Maxwell, Joseph A. 2013. Qualitative Research Design: An Interactive Approach .  3rd ed. Thousand Oaks, CA: SAGE. A short and accessible introduction to qualitative research design, particularly helpful for graduate students contemplating theses and dissertations. This has been a standard textbook in my graduate-level courses for years.  Advanced .

Patton, Michael Quinn. 2002. Qualitative Research and Evaluation Methods . Thousand Oaks, CA: SAGE.  This is a comprehensive text that served as my “go-to” reference when I was a graduate student.  It is particularly helpful for those involved in program evaluation and other forms of evaluation studies and uses examples from a wide range of disciplines.  Advanced .

Rubin, Ashley T. 2021. Rocking Qualitative Social Science: An Irreverent Guide to Rigorous Research. Stanford : Stanford University Press.  A delightful and personal read.  Rubin uses rock climbing as an extended metaphor for learning how to conduct qualitative research.  A bit slanted toward ethnographic and archival methods of data collection, with frequent examples from her own studies in criminology. Beginning .

Weis, Lois, and Michelle Fine. 2000. Speed Bumps: A Student-Friendly Guide to Qualitative Research . New York: Teachers College Press.  Readable and accessibly written in a quasi-conversational style.  Particularly strong in its discussion of ethical issues throughout the qualitative research process.  Not comprehensive, however, and very much tied to ethnographic research.  Although designed for graduate students, this is a recommended read for students of all levels.  Beginning .

Patton’s Ten Suggestions for Doing Qualitative Research

The following ten suggestions were made by Michael Quinn Patton in his massive textbooks Qualitative Research and Evaluations Methods . This book is highly recommended for those of you who want more than an introduction to qualitative methods. It is the book I relied on heavily when I was a graduate student, although it is much easier to “dip into” when necessary than to read through as a whole. Patton is asked for “just one bit of advice” for a graduate student considering using qualitative research methods for their dissertation.  Here are his top ten responses, in short form, heavily paraphrased, and with additional comments and emphases from me:

  • Make sure that a qualitative approach fits the research question. The following are the kinds of questions that call out for qualitative methods or where qualitative methods are particularly appropriate: questions about people’s experiences or how they make sense of those experiences; studying a person in their natural environment; researching a phenomenon so unknown that it would be impossible to study it with standardized instruments or other forms of quantitative data collection.
  • Study qualitative research by going to the original sources for the design and analysis appropriate to the particular approach you want to take (e.g., read Glaser and Straus if you are using grounded theory )
  • Find a dissertation adviser who understands or at least who will support your use of qualitative research methods. You are asking for trouble if your entire committee is populated by quantitative researchers, even if they are all very knowledgeable about the subject or focus of your study (maybe even more so if they are!)
  • Really work on design. Doing qualitative research effectively takes a lot of planning.  Even if things are more flexible than in quantitative research, a good design is absolutely essential when starting out.
  • Practice data collection techniques, particularly interviewing and observing. There is definitely a set of learned skills here!  Do not expect your first interview to be perfect.  You will continue to grow as a researcher the more interviews you conduct, and you will probably come to understand yourself a bit more in the process, too.  This is not easy, despite what others who don’t work with qualitative methods may assume (and tell you!)
  • Have a plan for analysis before you begin data collection. This is often a requirement in IRB protocols , although you can get away with writing something fairly simple.  And even if you are taking an approach, such as grounded theory, that pushes you to remain fairly open-minded during the data collection process, you still want to know what you will be doing with all the data collected – creating a codebook? Writing analytical memos? Comparing cases?  Having a plan in hand will also help prevent you from collecting too much extraneous data.
  • Be prepared to confront controversies both within the qualitative research community and between qualitative research and quantitative research. Don’t be naïve about this – qualitative research, particularly some approaches, will be derided by many more “positivist” researchers and audiences.  For example, is an “n” of 1 really sufficient?  Yes!  But not everyone will agree.
  • Do not make the mistake of using qualitative research methods because someone told you it was easier, or because you are intimidated by the math required of statistical analyses. Qualitative research is difficult in its own way (and many would claim much more time-consuming than quantitative research).  Do it because you are convinced it is right for your goals, aims, and research questions.
  • Find a good support network. This could be a research mentor, or it could be a group of friends or colleagues who are also using qualitative research, or it could be just someone who will listen to you work through all of the issues you will confront out in the field and during the writing process.  Even though qualitative research often involves human subjects, it can be pretty lonely.  A lot of times you will feel like you are working without a net.  You have to create one for yourself.  Take care of yourself.
  • And, finally, in the words of Patton, “Prepare to be changed. Looking deeply at other people’s lives will force you to look deeply at yourself.”
  • We will actually spend an entire chapter ( chapter 3 ) looking at this question in much more detail! ↵
  • Note that this might have been news to Europeans at the time, but many other societies around the world had also come to this conclusion through observation.  There is often a tendency to equate “the scientific revolution” with the European world in which it took place, but this is somewhat misleading. ↵
  • Historians are a special case here.  Historians have scrupulously and rigorously investigated the social world, but not for the purpose of understanding general laws about how things work, which is the point of scientific empirical research.  History is often referred to as an idiographic field of study, meaning that it studies things that happened or are happening in themselves and not for general observations or conclusions. ↵
  • Don’t worry, we’ll spend more time later in this book unpacking the meaning of ethnography and other terms that are important here.  Note the available glossary ↵

An approach to research that is “multimethod in focus, involving an interpretative, naturalistic approach to its subject matter.  This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them.  Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives." ( Denzin and Lincoln 2005:2 ). Contrast with quantitative research .

In contrast to methodology, methods are more simply the practices and tools used to collect and analyze data.  Examples of common methods in qualitative research are interviews , observations , and documentary analysis .  One’s methodology should connect to one’s choice of methods, of course, but they are distinguishable terms.  See also methodology .

A proposed explanation for an observation, phenomenon, or scientific problem that can be tested by further investigation.  The positing of a hypothesis is often the first step in quantitative research but not in qualitative research.  Even when qualitative researchers offer possible explanations in advance of conducting research, they will tend to not use the word “hypothesis” as it conjures up the kind of positivist research they are not conducting.

The foundational question to be addressed by the research study.  This will form the anchor of the research design, collection, and analysis.  Note that in qualitative research, the research question may, and probably will, alter or develop during the course of the research.

An approach to research that collects and analyzes numerical data for the purpose of finding patterns and averages, making predictions, testing causal relationships, and generalizing results to wider populations.  Contrast with qualitative research .

Data collection that takes place in real-world settings, referred to as “the field;” a key component of much Grounded Theory and ethnographic research.  Patton ( 2002 ) calls fieldwork “the central activity of qualitative inquiry” where “‘going into the field’ means having direct and personal contact with people under study in their own environments – getting close to people and situations being studied to personally understand the realities of minutiae of daily life” (48).

The people who are the subjects of a qualitative study.  In interview-based studies, they may be the respondents to the interviewer; for purposes of IRBs, they are often referred to as the human subjects of the research.

The branch of philosophy concerned with knowledge.  For researchers, it is important to recognize and adopt one of the many distinguishing epistemological perspectives as part of our understanding of what questions research can address or fully answer.  See, e.g., constructivism , subjectivism, and  objectivism .

An approach that refutes the possibility of neutrality in social science research.  All research is “guided by a set of beliefs and feelings about the world and how it should be understood and studied” (Denzin and Lincoln 2005: 13).  In contrast to positivism , interpretivism recognizes the social constructedness of reality, and researchers adopting this approach focus on capturing interpretations and understandings people have about the world rather than “the world” as it is (which is a chimera).

The cluster of data-collection tools and techniques that involve observing interactions between people, the behaviors, and practices of individuals (sometimes in contrast to what they say about how they act and behave), and cultures in context.  Observational methods are the key tools employed by ethnographers and Grounded Theory .

Research based on data collected and analyzed by the research (in contrast to secondary “library” research).

The process of selecting people or other units of analysis to represent a larger population. In quantitative research, this representation is taken quite literally, as statistically representative.  In qualitative research, in contrast, sample selection is often made based on potential to generate insight about a particular topic or phenomenon.

A method of data collection in which the researcher asks the participant questions; the answers to these questions are often recorded and transcribed verbatim. There are many different kinds of interviews - see also semistructured interview , structured interview , and unstructured interview .

The specific group of individuals that you will collect data from.  Contrast population.

The practice of being conscious of and reflective upon one’s own social location and presence when conducting research.  Because qualitative research often requires interaction with live humans, failing to take into account how one’s presence and prior expectations and social location affect the data collected and how analyzed may limit the reliability of the findings.  This remains true even when dealing with historical archives and other content.  Who we are matters when asking questions about how people experience the world because we, too, are a part of that world.

The science and practice of right conduct; in research, it is also the delineation of moral obligations towards research participants, communities to which we belong, and communities in which we conduct our research.

An administrative body established to protect the rights and welfare of human research subjects recruited to participate in research activities conducted under the auspices of the institution with which it is affiliated. The IRB is charged with the responsibility of reviewing all research involving human participants. The IRB is concerned with protecting the welfare, rights, and privacy of human subjects. The IRB has the authority to approve, disapprove, monitor, and require modifications in all research activities that fall within its jurisdiction as specified by both the federal regulations and institutional policy.

Research, according to US federal guidelines, that involves “a living individual about whom an investigator (whether professional or student) conducting research:  (1) Obtains information or biospecimens through intervention or interaction with the individual, and uses, studies, or analyzes the information or biospecimens; or  (2) Obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens.”

One of the primary methodological traditions of inquiry in qualitative research, ethnography is the study of a group or group culture, largely through observational fieldwork supplemented by interviews. It is a form of fieldwork that may include participant-observation data collection. See chapter 14 for a discussion of deep ethnography. 

A form of interview that follows a standard guide of questions asked, although the order of the questions may change to match the particular needs of each individual interview subject, and probing “follow-up” questions are often added during the course of the interview.  The semi-structured interview is the primary form of interviewing used by qualitative researchers in the social sciences.  It is sometimes referred to as an “in-depth” interview.  See also interview and  interview guide .

A method of observational data collection taking place in a natural setting; a form of fieldwork .  The term encompasses a continuum of relative participation by the researcher (from full participant to “fly-on-the-wall” observer).  This is also sometimes referred to as ethnography , although the latter is characterized by a greater focus on the culture under observation.

A research design that employs both quantitative and qualitative methods, as in the case of a survey supplemented by interviews.

An epistemological perspective that posits the existence of reality through sensory experience similar to empiricism but goes further in denying any non-sensory basis of thought or consciousness.  In the social sciences, the term has roots in the proto-sociologist August Comte, who believed he could discern “laws” of society similar to the laws of natural science (e.g., gravity).  The term has come to mean the kinds of measurable and verifiable science conducted by quantitative researchers and is thus used pejoratively by some qualitative researchers interested in interpretation, consciousness, and human understanding.  Calling someone a “positivist” is often intended as an insult.  See also empiricism and objectivism.

A place or collection containing records, documents, or other materials of historical interest; most universities have an archive of material related to the university’s history, as well as other “special collections” that may be of interest to members of the community.

A method of both data collection and data analysis in which a given content (textual, visual, graphic) is examined systematically and rigorously to identify meanings, themes, patterns and assumptions.  Qualitative content analysis (QCA) is concerned with gathering and interpreting an existing body of material.    

A word or short phrase that symbolically assigns a summative, salient, essence-capturing, and/or evocative attribute for a portion of language-based or visual data (Saldaña 2021:5).

Usually a verbatim written record of an interview or focus group discussion.

The primary form of data for fieldwork , participant observation , and ethnography .  These notes, taken by the researcher either during the course of fieldwork or at day’s end, should include as many details as possible on what was observed and what was said.  They should include clear identifiers of date, time, setting, and names (or identifying characteristics) of participants.

The process of labeling and organizing qualitative data to identify different themes and the relationships between them; a way of simplifying data to allow better management and retrieval of key themes and illustrative passages.  See coding frame and  codebook.

A methodological tradition of inquiry and approach to analyzing qualitative data in which theories emerge from a rigorous and systematic process of induction.  This approach was pioneered by the sociologists Glaser and Strauss (1967).  The elements of theory generated from comparative analysis of data are, first, conceptual categories and their properties and, second, hypotheses or generalized relations among the categories and their properties – “The constant comparing of many groups draws the [researcher’s] attention to their many similarities and differences.  Considering these leads [the researcher] to generate abstract categories and their properties, which, since they emerge from the data, will clearly be important to a theory explaining the kind of behavior under observation.” (36).

A detailed description of any proposed research that involves human subjects for review by IRB.  The protocol serves as the recipe for the conduct of the research activity.  It includes the scientific rationale to justify the conduct of the study, the information necessary to conduct the study, the plan for managing and analyzing the data, and a discussion of the research ethical issues relevant to the research.  Protocols for qualitative research often include interview guides, all documents related to recruitment, informed consent forms, very clear guidelines on the safekeeping of materials collected, and plans for de-identifying transcripts or other data that include personal identifying information.

Introduction to Qualitative Research Methods Copyright © 2023 by Allison Hurst is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

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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.

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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  • How to Write Your Methods

how to write a methodology for a qualitative research paper

Ensure understanding, reproducibility and replicability

What should you include in your methods section, and how much detail is appropriate?

Why Methods Matter

The methods section was once the most likely part of a paper to be unfairly abbreviated, overly summarized, or even relegated to hard-to-find sections of a publisher’s website. While some journals may responsibly include more detailed elements of methods in supplementary sections, the movement for increased reproducibility and rigor in science has reinstated the importance of the methods section. Methods are now viewed as a key element in establishing the credibility of the research being reported, alongside the open availability of data and results.

A clear methods section impacts editorial evaluation and readers’ understanding, and is also the backbone of transparency and replicability.

For example, the Reproducibility Project: Cancer Biology project set out in 2013 to replicate experiments from 50 high profile cancer papers, but revised their target to 18 papers once they understood how much methodological detail was not contained in the original papers.

how to write a methodology for a qualitative research paper

What to include in your methods section

What you include in your methods sections depends on what field you are in and what experiments you are performing. However, the general principle in place at the majority of journals is summarized well by the guidelines at PLOS ONE : “The Materials and Methods section should provide enough detail to allow suitably skilled investigators to fully replicate your study. ” The emphases here are deliberate: the methods should enable readers to understand your paper, and replicate your study. However, there is no need to go into the level of detail that a lay-person would require—the focus is on the reader who is also trained in your field, with the suitable skills and knowledge to attempt a replication.

A constant principle of rigorous science

A methods section that enables other researchers to understand and replicate your results is a constant principle of rigorous, transparent, and Open Science. Aim to be thorough, even if a particular journal doesn’t require the same level of detail . Reproducibility is all of our responsibility. You cannot create any problems by exceeding a minimum standard of information. If a journal still has word-limits—either for the overall article or specific sections—and requires some methodological details to be in a supplemental section, that is OK as long as the extra details are searchable and findable .

Imagine replicating your own work, years in the future

As part of PLOS’ presentation on Reproducibility and Open Publishing (part of UCSF’s Reproducibility Series ) we recommend planning the level of detail in your methods section by imagining you are writing for your future self, replicating your own work. When you consider that you might be at a different institution, with different account logins, applications, resources, and access levels—you can help yourself imagine the level of specificity that you yourself would require to redo the exact experiment. Consider:

  • Which details would you need to be reminded of? 
  • Which cell line, or antibody, or software, or reagent did you use, and does it have a Research Resource ID (RRID) that you can cite?
  • Which version of a questionnaire did you use in your survey? 
  • Exactly which visual stimulus did you show participants, and is it publicly available? 
  • What participants did you decide to exclude? 
  • What process did you adjust, during your work? 

Tip: Be sure to capture any changes to your protocols

You yourself would want to know about any adjustments, if you ever replicate the work, so you can surmise that anyone else would want to as well. Even if a necessary adjustment you made was not ideal, transparency is the key to ensuring this is not regarded as an issue in the future. It is far better to transparently convey any non-optimal methods, or methodological constraints, than to conceal them, which could result in reproducibility or ethical issues downstream.

Visual aids for methods help when reading the whole paper

Consider whether a visual representation of your methods could be appropriate or aid understanding your process. A visual reference readers can easily return to, like a flow-diagram, decision-tree, or checklist, can help readers to better understand the complete article, not just the methods section.

Ethical Considerations

In addition to describing what you did, it is just as important to assure readers that you also followed all relevant ethical guidelines when conducting your research. While ethical standards and reporting guidelines are often presented in a separate section of a paper, ensure that your methods and protocols actually follow these guidelines. Read more about ethics .

Existing standards, checklists, guidelines, partners

While the level of detail contained in a methods section should be guided by the universal principles of rigorous science outlined above, various disciplines, fields, and projects have worked hard to design and develop consistent standards, guidelines, and tools to help with reporting all types of experiment. Below, you’ll find some of the key initiatives. Ensure you read the submission guidelines for the specific journal you are submitting to, in order to discover any further journal- or field-specific policies to follow, or initiatives/tools to utilize.

Tip: Keep your paper moving forward by providing the proper paperwork up front

Be sure to check the journal guidelines and provide the necessary documents with your manuscript submission. Collecting the necessary documentation can greatly slow the first round of peer review, or cause delays when you submit your revision.

Randomized Controlled Trials – CONSORT The Consolidated Standards of Reporting Trials (CONSORT) project covers various initiatives intended to prevent the problems of  inadequate reporting of randomized controlled trials. The primary initiative is an evidence-based minimum set of recommendations for reporting randomized trials known as the CONSORT Statement . 

Systematic Reviews and Meta-Analyses – PRISMA The Preferred Reporting Items for Systematic Reviews and Meta-Analyses ( PRISMA ) is an evidence-based minimum set of items focusing  on the reporting of  reviews evaluating randomized trials and other types of research.

Research using Animals – ARRIVE The Animal Research: Reporting of In Vivo Experiments ( ARRIVE ) guidelines encourage maximizing the information reported in research using animals thereby minimizing unnecessary studies. (Original study and proposal , and updated guidelines , in PLOS Biology .) 

Laboratory Protocols Protocols.io has developed a platform specifically for the sharing and updating of laboratory protocols , which are assigned their own DOI and can be linked from methods sections of papers to enhance reproducibility. Contextualize your protocol and improve discovery with an accompanying Lab Protocol article in PLOS ONE .

Consistent reporting of Materials, Design, and Analysis – the MDAR checklist A cross-publisher group of editors and experts have developed, tested, and rolled out a checklist to help establish and harmonize reporting standards in the Life Sciences . The checklist , which is available for use by authors to compile their methods, and editors/reviewers to check methods, establishes a minimum set of requirements in transparent reporting and is adaptable to any discipline within the Life Sciences, by covering a breadth of potentially relevant methodological items and considerations. If you are in the Life Sciences and writing up your methods section, try working through the MDAR checklist and see whether it helps you include all relevant details into your methods, and whether it reminded you of anything you might have missed otherwise.

Summary Writing tips

The main challenge you may find when writing your methods is keeping it readable AND covering all the details needed for reproducibility and replicability. While this is difficult, do not compromise on rigorous standards for credibility!

how to write a methodology for a qualitative research paper

  • Keep in mind future replicability, alongside understanding and readability.
  • Follow checklists, and field- and journal-specific guidelines.
  • Consider a commitment to rigorous and transparent science a personal responsibility, and not just adhering to journal guidelines.
  • Establish whether there are persistent identifiers for any research resources you use that can be specifically cited in your methods section.
  • Deposit your laboratory protocols in Protocols.io, establishing a permanent link to them. You can update your protocols later if you improve on them, as can future scientists who follow your protocols.
  • Consider visual aids like flow-diagrams, lists, to help with reading other sections of the paper.
  • Be specific about all decisions made during the experiments that someone reproducing your work would need to know.

how to write a methodology for a qualitative research paper

Don’t

  • Summarize or abbreviate methods without giving full details in a discoverable supplemental section.
  • Presume you will always be able to remember how you performed the experiments, or have access to private or institutional notebooks and resources.
  • Attempt to hide constraints or non-optimal decisions you had to make–transparency is the key to ensuring the credibility of your research.
  • How to Write a Great Title
  • How to Write an Abstract
  • How to Report Statistics
  • How to Write Discussions and Conclusions
  • How to Edit Your Work

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Organizing Your Social Sciences Research Paper

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The methods section describes actions taken to investigate a research problem and the rationale for the application of specific procedures or techniques used to identify, select, process, and analyze information applied to understanding the problem, thereby, allowing the reader to critically evaluate a study’s overall validity and reliability. The methodology section of a research paper answers two main questions: How was the data collected or generated? And, how was it analyzed? The writing should be direct and precise and always written in the past tense.

Kallet, Richard H. "How to Write the Methods Section of a Research Paper." Respiratory Care 49 (October 2004): 1229-1232.

Importance of a Good Methodology Section

You must explain how you obtained and analyzed your results for the following reasons:

  • Readers need to know how the data was obtained because the method you chose affects the results and, by extension, how you interpreted their significance in the discussion section of your paper.
  • Methodology is crucial for any branch of scholarship because an unreliable method produces unreliable results and, as a consequence, undermines the value of your analysis of the findings.
  • In most cases, there are a variety of different methods you can choose to investigate a research problem. The methodology section of your paper should clearly articulate the reasons why you have chosen a particular procedure or technique.
  • The reader wants to know that the data was collected or generated in a way that is consistent with accepted practice in the field of study. For example, if you are using a multiple choice questionnaire, readers need to know that it offered your respondents a reasonable range of answers to choose from.
  • The method must be appropriate to fulfilling the overall aims of the study. For example, you need to ensure that you have a large enough sample size to be able to generalize and make recommendations based upon the findings.
  • The methodology should discuss the problems that were anticipated and the steps you took to prevent them from occurring. For any problems that do arise, you must describe the ways in which they were minimized or why these problems do not impact in any meaningful way your interpretation of the findings.
  • In the social and behavioral sciences, it is important to always provide sufficient information to allow other researchers to adopt or replicate your methodology. This information is particularly important when a new method has been developed or an innovative use of an existing method is utilized.

Bem, Daryl J. Writing the Empirical Journal Article. Psychology Writing Center. University of Washington; Denscombe, Martyn. The Good Research Guide: For Small-Scale Social Research Projects . 5th edition. Buckingham, UK: Open University Press, 2014; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008.

Structure and Writing Style

I.  Groups of Research Methods

There are two main groups of research methods in the social sciences:

  • The e mpirical-analytical group approaches the study of social sciences in a similar manner that researchers study the natural sciences . This type of research focuses on objective knowledge, research questions that can be answered yes or no, and operational definitions of variables to be measured. The empirical-analytical group employs deductive reasoning that uses existing theory as a foundation for formulating hypotheses that need to be tested. This approach is focused on explanation.
  • The i nterpretative group of methods is focused on understanding phenomenon in a comprehensive, holistic way . Interpretive methods focus on analytically disclosing the meaning-making practices of human subjects [the why, how, or by what means people do what they do], while showing how those practices arrange so that it can be used to generate observable outcomes. Interpretive methods allow you to recognize your connection to the phenomena under investigation. However, the interpretative group requires careful examination of variables because it focuses more on subjective knowledge.

II.  Content

The introduction to your methodology section should begin by restating the research problem and underlying assumptions underpinning your study. This is followed by situating the methods you used to gather, analyze, and process information within the overall “tradition” of your field of study and within the particular research design you have chosen to study the problem. If the method you choose lies outside of the tradition of your field [i.e., your review of the literature demonstrates that the method is not commonly used], provide a justification for how your choice of methods specifically addresses the research problem in ways that have not been utilized in prior studies.

The remainder of your methodology section should describe the following:

  • Decisions made in selecting the data you have analyzed or, in the case of qualitative research, the subjects and research setting you have examined,
  • Tools and methods used to identify and collect information, and how you identified relevant variables,
  • The ways in which you processed the data and the procedures you used to analyze that data, and
  • The specific research tools or strategies that you utilized to study the underlying hypothesis and research questions.

In addition, an effectively written methodology section should:

  • Introduce the overall methodological approach for investigating your research problem . Is your study qualitative or quantitative or a combination of both (mixed method)? Are you going to take a special approach, such as action research, or a more neutral stance?
  • Indicate how the approach fits the overall research design . Your methods for gathering data should have a clear connection to your research problem. In other words, make sure that your methods will actually address the problem. One of the most common deficiencies found in research papers is that the proposed methodology is not suitable to achieving the stated objective of your paper.
  • Describe the specific methods of data collection you are going to use , such as, surveys, interviews, questionnaires, observation, archival research. If you are analyzing existing data, such as a data set or archival documents, describe how it was originally created or gathered and by whom. Also be sure to explain how older data is still relevant to investigating the current research problem.
  • Explain how you intend to analyze your results . Will you use statistical analysis? Will you use specific theoretical perspectives to help you analyze a text or explain observed behaviors? Describe how you plan to obtain an accurate assessment of relationships, patterns, trends, distributions, and possible contradictions found in the data.
  • Provide background and a rationale for methodologies that are unfamiliar for your readers . Very often in the social sciences, research problems and the methods for investigating them require more explanation/rationale than widely accepted rules governing the natural and physical sciences. Be clear and concise in your explanation.
  • Provide a justification for subject selection and sampling procedure . For instance, if you propose to conduct interviews, how do you intend to select the sample population? If you are analyzing texts, which texts have you chosen, and why? If you are using statistics, why is this set of data being used? If other data sources exist, explain why the data you chose is most appropriate to addressing the research problem.
  • Provide a justification for case study selection . A common method of analyzing research problems in the social sciences is to analyze specific cases. These can be a person, place, event, phenomenon, or other type of subject of analysis that are either examined as a singular topic of in-depth investigation or multiple topics of investigation studied for the purpose of comparing or contrasting findings. In either method, you should explain why a case or cases were chosen and how they specifically relate to the research problem.
  • Describe potential limitations . Are there any practical limitations that could affect your data collection? How will you attempt to control for potential confounding variables and errors? If your methodology may lead to problems you can anticipate, state this openly and show why pursuing this methodology outweighs the risk of these problems cropping up.

NOTE:   Once you have written all of the elements of the methods section, subsequent revisions should focus on how to present those elements as clearly and as logically as possibly. The description of how you prepared to study the research problem, how you gathered the data, and the protocol for analyzing the data should be organized chronologically. For clarity, when a large amount of detail must be presented, information should be presented in sub-sections according to topic. If necessary, consider using appendices for raw data.

ANOTHER NOTE: If you are conducting a qualitative analysis of a research problem , the methodology section generally requires a more elaborate description of the methods used as well as an explanation of the processes applied to gathering and analyzing of data than is generally required for studies using quantitative methods. Because you are the primary instrument for generating the data [e.g., through interviews or observations], the process for collecting that data has a significantly greater impact on producing the findings. Therefore, qualitative research requires a more detailed description of the methods used.

YET ANOTHER NOTE:   If your study involves interviews, observations, or other qualitative techniques involving human subjects , you may be required to obtain approval from the university's Office for the Protection of Research Subjects before beginning your research. This is not a common procedure for most undergraduate level student research assignments. However, i f your professor states you need approval, you must include a statement in your methods section that you received official endorsement and adequate informed consent from the office and that there was a clear assessment and minimization of risks to participants and to the university. This statement informs the reader that your study was conducted in an ethical and responsible manner. In some cases, the approval notice is included as an appendix to your paper.

III.  Problems to Avoid

Irrelevant Detail The methodology section of your paper should be thorough but concise. Do not provide any background information that does not directly help the reader understand why a particular method was chosen, how the data was gathered or obtained, and how the data was analyzed in relation to the research problem [note: analyzed, not interpreted! Save how you interpreted the findings for the discussion section]. With this in mind, the page length of your methods section will generally be less than any other section of your paper except the conclusion.

Unnecessary Explanation of Basic Procedures Remember that you are not writing a how-to guide about a particular method. You should make the assumption that readers possess a basic understanding of how to investigate the research problem on their own and, therefore, you do not have to go into great detail about specific methodological procedures. The focus should be on how you applied a method , not on the mechanics of doing a method. An exception to this rule is if you select an unconventional methodological approach; if this is the case, be sure to explain why this approach was chosen and how it enhances the overall process of discovery.

Problem Blindness It is almost a given that you will encounter problems when collecting or generating your data, or, gaps will exist in existing data or archival materials. Do not ignore these problems or pretend they did not occur. Often, documenting how you overcame obstacles can form an interesting part of the methodology. It demonstrates to the reader that you can provide a cogent rationale for the decisions you made to minimize the impact of any problems that arose.

Literature Review Just as the literature review section of your paper provides an overview of sources you have examined while researching a particular topic, the methodology section should cite any sources that informed your choice and application of a particular method [i.e., the choice of a survey should include any citations to the works you used to help construct the survey].

It’s More than Sources of Information! A description of a research study's method should not be confused with a description of the sources of information. Such a list of sources is useful in and of itself, especially if it is accompanied by an explanation about the selection and use of the sources. The description of the project's methodology complements a list of sources in that it sets forth the organization and interpretation of information emanating from those sources.

Azevedo, L.F. et al. "How to Write a Scientific Paper: Writing the Methods Section." Revista Portuguesa de Pneumologia 17 (2011): 232-238; Blair Lorrie. “Choosing a Methodology.” In Writing a Graduate Thesis or Dissertation , Teaching Writing Series. (Rotterdam: Sense Publishers 2016), pp. 49-72; Butin, Dan W. The Education Dissertation A Guide for Practitioner Scholars . Thousand Oaks, CA: Corwin, 2010; Carter, Susan. Structuring Your Research Thesis . New York: Palgrave Macmillan, 2012; Kallet, Richard H. “How to Write the Methods Section of a Research Paper.” Respiratory Care 49 (October 2004):1229-1232; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008. Methods Section. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Rudestam, Kjell Erik and Rae R. Newton. “The Method Chapter: Describing Your Research Plan.” In Surviving Your Dissertation: A Comprehensive Guide to Content and Process . (Thousand Oaks, Sage Publications, 2015), pp. 87-115; What is Interpretive Research. Institute of Public and International Affairs, University of Utah; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University; Methods and Materials. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College.

Writing Tip

Statistical Designs and Tests? Do Not Fear Them!

Don't avoid using a quantitative approach to analyzing your research problem just because you fear the idea of applying statistical designs and tests. A qualitative approach, such as conducting interviews or content analysis of archival texts, can yield exciting new insights about a research problem, but it should not be undertaken simply because you have a disdain for running a simple regression. A well designed quantitative research study can often be accomplished in very clear and direct ways, whereas, a similar study of a qualitative nature usually requires considerable time to analyze large volumes of data and a tremendous burden to create new paths for analysis where previously no path associated with your research problem had existed.

To locate data and statistics, GO HERE .

Another Writing Tip

Knowing the Relationship Between Theories and Methods

There can be multiple meaning associated with the term "theories" and the term "methods" in social sciences research. A helpful way to delineate between them is to understand "theories" as representing different ways of characterizing the social world when you research it and "methods" as representing different ways of generating and analyzing data about that social world. Framed in this way, all empirical social sciences research involves theories and methods, whether they are stated explicitly or not. However, while theories and methods are often related, it is important that, as a researcher, you deliberately separate them in order to avoid your theories playing a disproportionate role in shaping what outcomes your chosen methods produce.

Introspectively engage in an ongoing dialectic between the application of theories and methods to help enable you to use the outcomes from your methods to interrogate and develop new theories, or ways of framing conceptually the research problem. This is how scholarship grows and branches out into new intellectual territory.

Reynolds, R. Larry. Ways of Knowing. Alternative Microeconomics . Part 1, Chapter 3. Boise State University; The Theory-Method Relationship. S-Cool Revision. United Kingdom.

Yet Another Writing Tip

Methods and the Methodology

Do not confuse the terms "methods" and "methodology." As Schneider notes, a method refers to the technical steps taken to do research . Descriptions of methods usually include defining and stating why you have chosen specific techniques to investigate a research problem, followed by an outline of the procedures you used to systematically select, gather, and process the data [remember to always save the interpretation of data for the discussion section of your paper].

The methodology refers to a discussion of the underlying reasoning why particular methods were used . This discussion includes describing the theoretical concepts that inform the choice of methods to be applied, placing the choice of methods within the more general nature of academic work, and reviewing its relevance to examining the research problem. The methodology section also includes a thorough review of the methods other scholars have used to study the topic.

Bryman, Alan. "Of Methods and Methodology." Qualitative Research in Organizations and Management: An International Journal 3 (2008): 159-168; Schneider, Florian. “What's in a Methodology: The Difference between Method, Methodology, and Theory…and How to Get the Balance Right?” PoliticsEastAsia.com. Chinese Department, University of Leiden, Netherlands.

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Research Method

Home » Research Methodology – Types, Examples and writing Guide

Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

  • Provide an overview of the research problem and the need for a research methodology section
  • Outline the main research questions and objectives

II. Research Design

  • Explain the research design chosen and why it is appropriate for the research question(s) and objectives
  • Discuss any alternative research designs considered and why they were not chosen
  • Describe the research setting and participants (if applicable)

III. Data Collection Methods

  • Describe the methods used to collect data (e.g., surveys, interviews, observations)
  • Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
  • Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

  • Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
  • Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
  • Detail any procedures or software used for data analysis

V. Ethical Considerations

  • Discuss any ethical issues that may arise from the research and how they were addressed
  • Explain how informed consent was obtained (if applicable)
  • Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

  • Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

  • Summarize the key aspects of the research methodology section
  • Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

  • Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
  • Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
  • Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
  • Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
  • Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
  • Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
  • Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
  • Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

  • To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
  • To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
  • To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
  • To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
  • To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
  • To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
  • To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
  • To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
  • To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

  • To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
  • To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
  • To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
  • To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
  • To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

  • Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
  • Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
  • Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
  • Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
  • Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
  • Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
  • Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
  • Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

Research MethodologyResearch Methods
Research methodology refers to the philosophical and theoretical frameworks that guide the research process. refer to the techniques and procedures used to collect and analyze data.
It is concerned with the underlying principles and assumptions of research.It is concerned with the practical aspects of research.
It provides a rationale for why certain research methods are used.It determines the specific steps that will be taken to conduct research.
It is broader in scope and involves understanding the overall approach to research.It is narrower in scope and focuses on specific techniques and tools used in research.
It is concerned with identifying research questions, defining the research problem, and formulating hypotheses.It is concerned with collecting data, analyzing data, and interpreting results.
It is concerned with the validity and reliability of research.It is concerned with the accuracy and precision of data.
It is concerned with the ethical considerations of research.It is concerned with the practical considerations of research.

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How to Write Research Methodology

Last Updated: May 27, 2024 Approved

This article was co-authored by Alexander Ruiz, M.Ed. and by wikiHow staff writer, Jennifer Mueller, JD . Alexander Ruiz is an Educational Consultant and the Educational Director of Link Educational Institute, a tutoring business based in Claremont, California that provides customizable educational plans, subject and test prep tutoring, and college application consulting. With over a decade and a half of experience in the education industry, Alexander coaches students to increase their self-awareness and emotional intelligence while achieving skills and the goal of achieving skills and higher education. He holds a BA in Psychology from Florida International University and an MA in Education from Georgia Southern University. wikiHow marks an article as reader-approved once it receives enough positive feedback. In this case, several readers have written to tell us that this article was helpful to them, earning it our reader-approved status. This article has been viewed 524,394 times.

The research methodology section of any academic research paper gives you the opportunity to convince your readers that your research is useful and will contribute to your field of study. An effective research methodology is grounded in your overall approach – whether qualitative or quantitative – and adequately describes the methods you used. Justify why you chose those methods over others, then explain how those methods will provide answers to your research questions. [1] X Research source

Describing Your Methods

Step 1 Restate your research problem.

  • In your restatement, include any underlying assumptions that you're making or conditions that you're taking for granted. These assumptions will also inform the research methods you've chosen.
  • Generally, state the variables you'll test and the other conditions you're controlling or assuming are equal.

Step 2 Establish your overall methodological approach.

  • If you want to research and document measurable social trends, or evaluate the impact of a particular policy on various variables, use a quantitative approach focused on data collection and statistical analysis.
  • If you want to evaluate people's views or understanding of a particular issue, choose a more qualitative approach.
  • You can also combine the two. For example, you might look primarily at a measurable social trend, but also interview people and get their opinions on how that trend is affecting their lives.

Step 3 Define how you collected or generated data.

  • For example, if you conducted a survey, you would describe the questions included in the survey, where and how the survey was conducted (such as in person, online, over the phone), how many surveys were distributed, and how long your respondents had to complete the survey.
  • Include enough detail that your study can be replicated by others in your field, even if they may not get the same results you did. [4] X Research source

Step 4 Provide background for uncommon methods.

  • Qualitative research methods typically require more detailed explanation than quantitative methods.
  • Basic investigative procedures don't need to be explained in detail. Generally, you can assume that your readers have a general understanding of common research methods that social scientists use, such as surveys or focus groups.

Step 5 Cite any sources that contributed to your choice of methodology.

  • For example, suppose you conducted a survey and used a couple of other research papers to help construct the questions on your survey. You would mention those as contributing sources.

Justifying Your Choice of Methods

Step 1 Explain your selection criteria for data collection.

  • Describe study participants specifically, and list any inclusion or exclusion criteria you used when forming your group of participants.
  • Justify the size of your sample, if applicable, and describe how this affects whether your study can be generalized to larger populations. For example, if you conducted a survey of 30 percent of the student population of a university, you could potentially apply those results to the student body as a whole, but maybe not to students at other universities.

Step 2 Distinguish your research from any weaknesses in your methods.

  • Reading other research papers is a good way to identify potential problems that commonly arise with various methods. State whether you actually encountered any of these common problems during your research.

Step 3 Describe how you overcame obstacles.

  • If you encountered any problems as you collected data, explain clearly the steps you took to minimize the effect that problem would have on your results.

Step 4 Evaluate other methods you could have used.

  • In some cases, this may be as simple as stating that while there were numerous studies using one method, there weren't any using your method, which caused a gap in understanding of the issue.
  • For example, there may be multiple papers providing quantitative analysis of a particular social trend. However, none of these papers looked closely at how this trend was affecting the lives of people.

Connecting Your Methods to Your Research Goals

Step 1 Describe how you analyzed your results.

  • Depending on your research questions, you may be mixing quantitative and qualitative analysis – just as you could potentially use both approaches. For example, you might do a statistical analysis, and then interpret those statistics through a particular theoretical lens.

Step 2 Explain how your analysis suits your research goals.

  • For example, suppose you're researching the effect of college education on family farms in rural America. While you could do interviews of college-educated people who grew up on a family farm, that would not give you a picture of the overall effect. A quantitative approach and statistical analysis would give you a bigger picture.

Step 3 Identify how your analysis answers your research questions.

  • If in answering your research questions, your findings have raised other questions that may require further research, state these briefly.
  • You can also include here any limitations to your methods, or questions that weren't answered through your research.

Step 4 Assess whether your findings can be transferred or generalized.

  • Generalization is more typically used in quantitative research. If you have a well-designed sample, you can statistically apply your results to the larger population your sample belongs to.

Template to Write Research Methodology

how to write a methodology for a qualitative research paper

Community Q&A

AneHane

  • Organize your methodology section chronologically, starting with how you prepared to conduct your research methods, how you gathered data, and how you analyzed that data. [13] X Research source Thanks Helpful 0 Not Helpful 0
  • Write your research methodology section in past tense, unless you're submitting the methodology section before the research described has been carried out. [14] X Research source Thanks Helpful 0 Not Helpful 0
  • Discuss your plans in detail with your advisor or supervisor before committing to a particular methodology. They can help identify possible flaws in your study. [15] X Research source Thanks Helpful 0 Not Helpful 0

how to write a methodology for a qualitative research paper

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  • ↑ http://expertjournals.com/how-to-write-a-research-methodology-for-your-academic-article/
  • ↑ http://libguides.usc.edu/writingguide/methodology
  • ↑ https://www.skillsyouneed.com/learn/dissertation-methodology.html
  • ↑ https://uir.unisa.ac.za/bitstream/handle/10500/4245/05Chap%204_Research%20methodology%20and%20design.pdf
  • ↑ https://elc.polyu.edu.hk/FYP/html/method.htm

About This Article

Alexander Ruiz, M.Ed.

To write a research methodology, start with a section that outlines the problems or questions you'll be studying, including your hypotheses or whatever it is you're setting out to prove. Then, briefly explain why you chose to use either a qualitative or quantitative approach for your study. Next, go over when and where you conducted your research and what parameters you used to ensure you were objective. Finally, cite any sources you used to decide on the methodology for your research. To learn how to justify your choice of methods in your research methodology, scroll down! Did this summary help you? Yes No

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

Edward barroga.

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

Glafera Janet Matanguihan

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

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

INTRODUCTION

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

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

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

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

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

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

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

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

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

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

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

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

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

Quantitative research questionsQuantitative research hypotheses
Descriptive research questionsSimple hypothesis
Comparative research questionsComplex hypothesis
Relationship research questionsDirectional hypothesis
Non-directional hypothesis
Associative hypothesis
Causal hypothesis
Null hypothesis
Alternative hypothesis
Working hypothesis
Statistical hypothesis
Logical hypothesis
Hypothesis-testing
Qualitative research questionsQualitative research hypotheses
Contextual research questionsHypothesis-generating
Descriptive research questions
Evaluation research questions
Explanatory research questions
Exploratory research questions
Generative research questions
Ideological research questions
Ethnographic research questions
Phenomenological research questions
Grounded theory questions
Qualitative case study questions

Research questions in quantitative research

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

Quantitative research questions
Descriptive research question
- Measures responses of subjects to variables
- Presents variables to measure, analyze, or assess
What is the proportion of resident doctors in the hospital who have mastered ultrasonography (response of subjects to a variable) as a diagnostic technique in their clinical training?
Comparative research question
- Clarifies difference between one group with outcome variable and another group without outcome variable
Is there a difference in the reduction of lung metastasis in osteosarcoma patients who received the vitamin D adjunctive therapy (group with outcome variable) compared with osteosarcoma patients who did not receive the vitamin D adjunctive therapy (group without outcome variable)?
- Compares the effects of variables
How does the vitamin D analogue 22-Oxacalcitriol (variable 1) mimic the antiproliferative activity of 1,25-Dihydroxyvitamin D (variable 2) in osteosarcoma cells?
Relationship research question
- Defines trends, association, relationships, or interactions between dependent variable and independent variable
Is there a relationship between the number of medical student suicide (dependent variable) and the level of medical student stress (independent variable) in Japan during the first wave of the COVID-19 pandemic?

Hypotheses in quantitative research

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

Quantitative research hypotheses
Simple hypothesis
- Predicts relationship between single dependent variable and single independent variable
If the dose of the new medication (single independent variable) is high, blood pressure (single dependent variable) is lowered.
Complex hypothesis
- Foretells relationship between two or more independent and dependent variables
The higher the use of anticancer drugs, radiation therapy, and adjunctive agents (3 independent variables), the higher would be the survival rate (1 dependent variable).
Directional hypothesis
- Identifies study direction based on theory towards particular outcome to clarify relationship between variables
Privately funded research projects will have a larger international scope (study direction) than publicly funded research projects.
Non-directional hypothesis
- Nature of relationship between two variables or exact study direction is not identified
- Does not involve a theory
Women and men are different in terms of helpfulness. (Exact study direction is not identified)
Associative hypothesis
- Describes variable interdependency
- Change in one variable causes change in another variable
A larger number of people vaccinated against COVID-19 in the region (change in independent variable) will reduce the region’s incidence of COVID-19 infection (change in dependent variable).
Causal hypothesis
- An effect on dependent variable is predicted from manipulation of independent variable
A change into a high-fiber diet (independent variable) will reduce the blood sugar level (dependent variable) of the patient.
Null hypothesis
- A negative statement indicating no relationship or difference between 2 variables
There is no significant difference in the severity of pulmonary metastases between the new drug (variable 1) and the current drug (variable 2).
Alternative hypothesis
- Following a null hypothesis, an alternative hypothesis predicts a relationship between 2 study variables
The new drug (variable 1) is better on average in reducing the level of pain from pulmonary metastasis than the current drug (variable 2).
Working hypothesis
- A hypothesis that is initially accepted for further research to produce a feasible theory
Dairy cows fed with concentrates of different formulations will produce different amounts of milk.
Statistical hypothesis
- Assumption about the value of population parameter or relationship among several population characteristics
- Validity tested by a statistical experiment or analysis
The mean recovery rate from COVID-19 infection (value of population parameter) is not significantly different between population 1 and population 2.
There is a positive correlation between the level of stress at the workplace and the number of suicides (population characteristics) among working people in Japan.
Logical hypothesis
- Offers or proposes an explanation with limited or no extensive evidence
If healthcare workers provide more educational programs about contraception methods, the number of adolescent pregnancies will be less.
Hypothesis-testing (Quantitative hypothesis-testing research)
- Quantitative research uses deductive reasoning.
- This involves the formation of a hypothesis, collection of data in the investigation of the problem, analysis and use of the data from the investigation, and drawing of conclusions to validate or nullify the hypotheses.

Research questions in qualitative research

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

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

Qualitative research questions
Contextual research question
- Ask the nature of what already exists
- Individuals or groups function to further clarify and understand the natural context of real-world problems
What are the experiences of nurses working night shifts in healthcare during the COVID-19 pandemic? (natural context of real-world problems)
Descriptive research question
- Aims to describe a phenomenon
What are the different forms of disrespect and abuse (phenomenon) experienced by Tanzanian women when giving birth in healthcare facilities?
Evaluation research question
- Examines the effectiveness of existing practice or accepted frameworks
How effective are decision aids (effectiveness of existing practice) in helping decide whether to give birth at home or in a healthcare facility?
Explanatory research question
- Clarifies a previously studied phenomenon and explains why it occurs
Why is there an increase in teenage pregnancy (phenomenon) in Tanzania?
Exploratory research question
- Explores areas that have not been fully investigated to have a deeper understanding of the research problem
What factors affect the mental health of medical students (areas that have not yet been fully investigated) during the COVID-19 pandemic?
Generative research question
- Develops an in-depth understanding of people’s behavior by asking ‘how would’ or ‘what if’ to identify problems and find solutions
How would the extensive research experience of the behavior of new staff impact the success of the novel drug initiative?
Ideological research question
- Aims to advance specific ideas or ideologies of a position
Are Japanese nurses who volunteer in remote African hospitals able to promote humanized care of patients (specific ideas or ideologies) in the areas of safe patient environment, respect of patient privacy, and provision of accurate information related to health and care?
Ethnographic research question
- Clarifies peoples’ nature, activities, their interactions, and the outcomes of their actions in specific settings
What are the demographic characteristics, rehabilitative treatments, community interactions, and disease outcomes (nature, activities, their interactions, and the outcomes) of people in China who are suffering from pneumoconiosis?
Phenomenological research question
- Knows more about the phenomena that have impacted an individual
What are the lived experiences of parents who have been living with and caring for children with a diagnosis of autism? (phenomena that have impacted an individual)
Grounded theory question
- Focuses on social processes asking about what happens and how people interact, or uncovering social relationships and behaviors of groups
What are the problems that pregnant adolescents face in terms of social and cultural norms (social processes), and how can these be addressed?
Qualitative case study question
- Assesses a phenomenon using different sources of data to answer “why” and “how” questions
- Considers how the phenomenon is influenced by its contextual situation.
How does quitting work and assuming the role of a full-time mother (phenomenon assessed) change the lives of women in Japan?
Qualitative research hypotheses
Hypothesis-generating (Qualitative hypothesis-generating research)
- Qualitative research uses inductive reasoning.
- This involves data collection from study participants or the literature regarding a phenomenon of interest, using the collected data to develop a formal hypothesis, and using the formal hypothesis as a framework for testing the hypothesis.
- Qualitative exploratory studies explore areas deeper, clarifying subjective experience and allowing formulation of a formal hypothesis potentially testable in a future quantitative approach.

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

Hypotheses in qualitative research

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

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

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

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

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

VariablesUnclear and weak statement (Statement 1) Clear and good statement (Statement 2) Points to avoid
Research questionWhich is more effective between smoke moxibustion and smokeless moxibustion?“Moreover, regarding smoke moxibustion versus smokeless moxibustion, it remains unclear which is more effective, safe, and acceptable to pregnant women, and whether there is any difference in the amount of heat generated.” 1) Vague and unfocused questions
2) Closed questions simply answerable by yes or no
3) Questions requiring a simple choice
HypothesisThe smoke moxibustion group will have higher cephalic presentation.“Hypothesis 1. The smoke moxibustion stick group (SM group) and smokeless moxibustion stick group (-SLM group) will have higher rates of cephalic presentation after treatment than the control group.1) Unverifiable hypotheses
Hypothesis 2. The SM group and SLM group will have higher rates of cephalic presentation at birth than the control group.2) Incompletely stated groups of comparison
Hypothesis 3. There will be no significant differences in the well-being of the mother and child among the three groups in terms of the following outcomes: premature birth, premature rupture of membranes (PROM) at < 37 weeks, Apgar score < 7 at 5 min, umbilical cord blood pH < 7.1, admission to neonatal intensive care unit (NICU), and intrauterine fetal death.” 3) Insufficiently described variables or outcomes
Research objectiveTo determine which is more effective between smoke moxibustion and smokeless moxibustion.“The specific aims of this pilot study were (a) to compare the effects of smoke moxibustion and smokeless moxibustion treatments with the control group as a possible supplement to ECV for converting breech presentation to cephalic presentation and increasing adherence to the newly obtained cephalic position, and (b) to assess the effects of these treatments on the well-being of the mother and child.” 1) Poor understanding of the research question and hypotheses
2) Insufficient description of population, variables, or study outcomes

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

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

VariablesUnclear and weak statement (Statement 1)Clear and good statement (Statement 2)Points to avoid
Research questionDoes disrespect and abuse (D&A) occur in childbirth in Tanzania?How does disrespect and abuse (D&A) occur and what are the types of physical and psychological abuses observed in midwives’ actual care during facility-based childbirth in urban Tanzania?1) Ambiguous or oversimplistic questions
2) Questions unverifiable by data collection and analysis
HypothesisDisrespect and abuse (D&A) occur in childbirth in Tanzania.Hypothesis 1: Several types of physical and psychological abuse by midwives in actual care occur during facility-based childbirth in urban Tanzania.1) Statements simply expressing facts
Hypothesis 2: Weak nursing and midwifery management contribute to the D&A of women during facility-based childbirth in urban Tanzania.2) Insufficiently described concepts or variables
Research objectiveTo describe disrespect and abuse (D&A) in childbirth in Tanzania.“This study aimed to describe from actual observations the respectful and disrespectful care received by women from midwives during their labor period in two hospitals in urban Tanzania.” 1) Statements unrelated to the research question and hypotheses
2) Unattainable or unexplorable objectives

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

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

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

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

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

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

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

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EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

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

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

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

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

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

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

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

Author Contributions:

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

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No dissertation or research paper is complete without the research methodology section. Since this is the chapter where you explain how you carried out your research, this is where all the meat is! Here’s where you clearly lay out the steps you have taken to test your hypothesis or research problem.

Through this blog, we’ll unravel the complexities and meaning of research methodology in academic writing , from its fundamental principles and ethics to the diverse types of research methodology in use today. Alongside offering research methodology examples, we aim to guide you on how to write research methodology, ensuring your research endeavors are both impactful and impeccably grounded!

Ensure your research methodology is foolproof. Learn more

Let’s first take a closer look at a simple research methodology definition:

Defining what is research methodology

Research methodology is the set of procedures and techniques used to collect, analyze, and interpret data to understand and solve a research problem. Methodology in research not only includes the design and methods but also the basic principles that guide the choice of specific methods.

Grasping the concept of methodology in research is essential for students and scholars, as it demonstrates the thorough and structured method used to explore a hypothesis or research question. Understanding the definition of methodology in research aids in identifying the methods used to collect data. Be it through any type of research method approach, ensuring adherence to the proper research paper format is crucial.

Now let’s explore some research methodology types:

Types of research methodology

1. qualitative research methodology.

Qualitative research methodology is aimed at understanding concepts, thoughts, or experiences. This approach is descriptive and is often utilized to gather in-depth insights into people’s attitudes, behaviors, or cultures. Qualitative research methodology involves methods like interviews, focus groups, and observation. The strength of this methodology lies in its ability to provide contextual richness.

2. Quantitative research methodology

Quantitative research methodology, on the other hand, is focused on quantifying the problem by generating numerical data or data that can be transformed into usable statistics. It uses measurable data to formulate facts and uncover patterns in research. Quantitative research methodology typically involves surveys, experiments, or statistical analysis. This methodology is appreciated for its ability to produce objective results that are generalizable to a larger population.

3. Mixed-Methods research methodology

Mixed-methods research combines both qualitative and quantitative research methodologies to provide a more comprehensive understanding of the research problem. This approach leverages the strengths of both methodologies to provide a deeper insight into the research question of a research paper .

Research methodology vs. research methods

The research methodology or design is the overall strategy and rationale that you used to carry out the research. Whereas, research methods are the specific tools and processes you use to gather and understand the data you need to test your hypothesis.

Research methodology examples and application

To further understand research methodology, let’s explore some examples of research methodology:

a. Qualitative research methodology example: A study exploring the impact of author branding on author popularity might utilize in-depth interviews to gather personal experiences and perspectives.

b. Quantitative research methodology example: A research project investigating the effects of a book promotion technique on book sales could employ a statistical analysis of profit margins and sales before and after the implementation of the method.

c. Mixed-Methods research methodology example: A study examining the relationship between social media use and academic performance might combine both qualitative and quantitative approaches. It could include surveys to quantitatively assess the frequency of social media usage and its correlation with grades, alongside focus groups or interviews to qualitatively explore students’ perceptions and experiences regarding how social media affects their study habits and academic engagement.

These examples highlight the meaning of methodology in research and how it guides the research process, from data collection to analysis, ensuring the study’s objectives are met efficiently.

Importance of methodology in research papers

When it comes to writing your study, the methodology in research papers or a dissertation plays a pivotal role. A well-crafted methodology section of a research paper or thesis not only enhances the credibility of your research but also provides a roadmap for others to replicate or build upon your work.

How to structure the research methods chapter

Wondering how to write the research methodology section? Follow these steps to create a strong methods chapter:

Step 1: Explain your research methodology

At the start of a research paper , you would have provided the background of your research and stated your hypothesis or research problem. In this section, you will elaborate on your research strategy. 

Begin by restating your research question and proceed to explain what type of research you opted for to test it. Depending on your research, here are some questions you can consider: 

a. Did you use qualitative or quantitative data to test the hypothesis? 

b. Did you perform an experiment where you collected data or are you writing a dissertation that is descriptive/theoretical without data collection? 

c. Did you use primary data that you collected or analyze secondary research data or existing data as part of your study? 

These questions will help you establish the rationale for your study on a broader level, which you will follow by elaborating on the specific methods you used to collect and understand your data. 

Step 2: Explain the methods you used to test your hypothesis 

Now that you have told your reader what type of research you’ve undertaken for the dissertation, it’s time to dig into specifics. State what specific methods you used and explain the conditions and variables involved. Explain what the theoretical framework behind the method was, what samples you used for testing it, and what tools and materials you used to collect the data. 

Step 3: Explain how you analyzed the results

Once you have explained the data collection process, explain how you analyzed and studied the data. Here, your focus is simply to explain the methods of analysis rather than the results of the study. 

Here are some questions you can answer at this stage: 

a. What tools or software did you use to analyze your results? 

b. What parameters or variables did you consider while understanding and studying the data you’ve collected? 

c. Was your analysis based on a theoretical framework? 

Your mode of analysis will change depending on whether you used a quantitative or qualitative research methodology in your study. If you’re working within the hard sciences or physical sciences, you are likely to use a quantitative research methodology (relying on numbers and hard data). If you’re doing a qualitative study, in the social sciences or humanities, your analysis may rely on understanding language and socio-political contexts around your topic. This is why it’s important to establish what kind of study you’re undertaking at the onset. 

Step 4: Defend your choice of methodology 

Now that you have gone through your research process in detail, you’ll also have to make a case for it. Justify your choice of methodology and methods, explaining why it is the best choice for your research question. This is especially important if you have chosen an unconventional approach or you’ve simply chosen to study an existing research problem from a different perspective. Compare it with other methodologies, especially ones attempted by previous researchers, and discuss what contributions using your methodology makes.  

Step 5: Discuss the obstacles you encountered and how you overcame them

No matter how thorough a methodology is, it doesn’t come without its hurdles. This is a natural part of scientific research that is important to document so that your peers and future researchers are aware of it. Writing in a research paper about this aspect of your research process also tells your evaluator that you have actively worked to overcome the pitfalls that came your way and you have refined the research process. 

Tips to write an effective methodology chapter

1. Remember who you are writing for. Keeping sight of the reader/evaluator will help you know what to elaborate on and what information they are already likely to have. You’re condensing months’ work of research in just a few pages, so you should omit basic definitions and information about general phenomena people already know.

2. Do not give an overly elaborate explanation of every single condition in your study. 

3. Skip details and findings irrelevant to the results.

4. Cite references that back your claim and choice of methodology. 

5. Consistently emphasize the relationship between your research question and the methodology you adopted to study it. 

To sum it up, what is methodology in research? It’s the blueprint of your research, essential for ensuring that your study is systematic, rigorous, and credible. Whether your focus is on qualitative research methodology, quantitative research methodology, or a combination of both, understanding and clearly defining your methodology is key to the success of your research.

Once you write the research methodology and complete writing the entire research paper, the next step is to edit your paper. As experts in research paper editing and proofreading services , we’d love to help you perfect your paper!

Here are some other articles that you might find useful: 

  • Essential Research Tips for Essay Writing
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  • The Essential Types of Editing Every Writer Needs to Know
  • Editing and Proofreading Academic Papers: A Short Guide
  • The Top 10 Editing and Proofreading Services of 2023

Frequently Asked Questions

What does research methodology mean, what types of research methodologies are there, what is qualitative research methodology, how to determine sample size in research methodology, what is action research methodology.

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This is very simplified and direct. Very helpful to understand the research methodology section of a dissertation

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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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Qualitative Research Methodologies

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What is qualitative research.

Qualitative research methodologies seek to capture information that often can't be expressed numerically. These methodologies often include some level of interpretation from researchers as they collect information via observation, coded survey or interview responses, and so on. Researchers may use multiple qualitative methods in one study, as well as a theoretical or critical framework to help them interpret their data.

Qualitative research methods can be used to study:

  • How are political and social attitudes formed? 
  • How do people make decisions?
  • What teaching or training methods are most effective?  

Qualitative Research Approaches

Action research.

In this type of study, researchers will actively pursue some kind of intervention, resolve a problem, or affect some kind of change. They will not only analyze the results but will also examine the challenges encountered through the process. 

Ethnography

Ethnographies are an in-depth, holistic type of research used to capture cultural practices, beliefs, traditions, and so on. Here, the researcher observes and interviews members of a culture — an ethnic group, a clique, members of a religion, etc. — and then analyzes their findings. 

Grounded Theory

Researchers will create and test a hypothesis using qualitative data. Often, researchers use grounded theory to understand decision-making, problem-solving, and other types of behavior.

Narrative Research

Researchers use this type of framework to understand different aspects of the human experience and how their subjects assign meaning to their experiences. Researchers use interviews to collect data from a small group of subjects, then discuss those results in the form of a narrative or story.

Phenomenology

This type of research attempts to understand the lived experiences of a group and/or how members of that group find meaning in their experiences. Researchers use interviews, observation, and other qualitative methods to collect data. 

Often used to share novel or unique information, case studies consist of a detailed, in-depth description of a single subject, pilot project, specific events, and so on. 

  • Hossain, M.S., Runa, F., & Al Mosabbir, A. (2021). Impact of COVID-19 pandemic on rare diseases: A case study on thalassaemia patients in Bangladesh. Public Health in Practice, 2(100150), 1-3.
  • Nožina, M. (2021). The Czech Rhino connection: A case study of Vietnamese wildlife trafficking networks’ operations across central Europe. European Journal on Criminal Policy and Research, 27(2), 265-283.

Focus Groups

Researchers will recruit people to answer questions in small group settings. Focus group members may share similar demographics or be diverse, depending on the researchers' needs. Group members will then be asked a series of questions and have their responses recorded. While these responses may be coded and discussed numerically (e.g., 50% of group members responded negatively to a question), researchers will also use responses to provide context, nuance, and other details. 

  • Dichabeng, P., Merat, N., & Markkula, G. (2021). Factors that influence the acceptance of future shared automated vehicles – A focus group study with United Kingdom drivers. Transportation Research: Part F, 82, 121–140.
  • Maynard, E., Barton, S., Rivett, K., Maynard, O., & Davies, W. (2021). Because ‘grown-ups don’t always get it right’: Allyship with children in research—From research question to authorship. Qualitative Research in Psychology, 18(4), 518–536.

Observational Study

Researchers will arrange to observe (usually in an unobtrusive way) a set of subjects in specific conditions. For example, researchers might visit a school cafeteria to learn about the food choices students make or set up trail cameras to collect information about animal behavior in the area. 

  • He, J. Y., Chan, P. W., Li, Q. S., Li, L., Zhang, L., & Yang, H. L. (2022). Observations of wind and turbulence structures of Super Typhoons Hato and Mangkhut over land from a 356 m high meteorological tower. Atmospheric Research, 265(105910), 1-18.
  • Zerovnik Spela, Kos Mitja, & Locatelli Igor. (2022). Initiation of insulin therapy in patients with type 2 diabetes: An observational study. Acta Pharmaceutica, 72(1), 147–157.

Open-Ended Surveys

Unlike quantitative surveys, open-ended surveys require respondents to answer the questions in their own words. 

  • Mujcic, A., Blankers, M., Yildirim, D., Boon, B., & Engels, R. (2021). Cancer survivors’ views on digital support for smoking cessation and alcohol moderation: a survey and qualitative study. BMC Public Health, 21(1), 1-13.
  • Smith, S. D., Hall, J. P., & Kurth, N. K. (2021). Perspectives on health policy from people with disabilities. Journal of Disability Policy Studies, 32(3), 224–232.

Structured or Semi-Structured Interviews

Researchers will recruit a small number of people who fit pre-determined criteria (e.g., people in a certain profession) and ask each the same set of questions, one-on-one. Semi-structured interviews will include opportunities for the interviewee to provide additional information they weren't asked about by the researcher.

  • Gibbs, D., Haven-Tang, C., & Ritchie, C. (2021). Harmless flirtations or co-creation? Exploring flirtatious encounters in hospitable experiences. Tourism & Hospitality Research, 21(4), 473–486.
  • Hongying Dai, Ramos, A., Tamrakar, N., Cheney, M., Samson, K., & Grimm, B. (2021). School personnel’s responses to school-based vaping prevention program: A qualitative study. Health Behavior & Policy Review, 8(2), 130–147.
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Publication Manual of the American Psychological Association, Seventh Edition (2020)

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Official source for APA Style The Publication Manual of the American Psychological Association, Seventh Edition is the official source for APA Style.

Widely adopted With millions of copies sold worldwide in multiple languages, it is the style manual of choice for writers, researchers, editors, students, and educators in the social and behavioral sciences, natural sciences, nursing, communications, education, business, engineering, and other fields.

Authoritative and easy to use Known for its authoritative, easy-to-use reference and citation system, the Publication Manual also offers guidance on choosing the headings, tables, figures, language, and tone that will result in powerful, concise, and elegant scholarly communication.

Scholarly writing It guides users through the scholarly writing process—from the ethics of authorship to reporting research through publication.

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7th edition table of contents

  • Front Matter
  • 1. Scholarly Writing and Publishing Principles
  • 2. Paper Elements and Format
  • 3. Journal Article Reporting Standards
  • 4. Writing Style and Grammar
  • 5. Bias-Free Language Guidelines
  • 6. Mechanics of Style
  • 7. Tables and Figures
  • 8. Works Credited in the Text
  • 9. Reference List
  • 10. Reference Examples
  • 11. Legal References
  • 12. Publication Process
  • Back Matter

List of Tables and Figures

Editorial Staff and Contributors

Acknowledgments

Introduction (PDF, 94KB)

Types of Articles and Papers

1.1 Quantitative Articles 1.2 Qualitative Articles 1.3 Mixed Methods Articles 1.4 Replication Articles 1.5 Quantitative and Qualitative Meta-Analyses 1.6 Literature Review Articles 1.7 Theoretical Articles 1.8 Methodological Articles 1.9 Other Types of Articles 1.10 Student Papers, Dissertations, and Theses

Ethical, legal, and professional standards in publishing

Ensuring the Accuracy of Scientific Findings

1.11 Planning for Ethical Compliance 1.12 Ethical and Accurate Reporting of Research Results 1.13 Errors, Corrections, and Retractions After Publication 1.14 Data Retention and Sharing 1.15 Additional Data-Sharing Considerations for Qualitative Research 1.16 Duplicate and Piecemeal Publication of Data 1.17 Implications of Plagiarism and Self-Plagiarism

Protecting the Rights and Welfare of Research Participants and Subjects

1.18 Rights and Welfare of Research Participants and Subjects 1.19 Protecting Confidentiality 1.20 Conflict of Interest

Protecting Intellectual Property Rights

1.21 Publication Credit 1.22 Order of Authors 1.23 Authors’ Intellectual Property Rights During Manuscript Review 1.24 Authors’ Copyright on Unpublished Manuscripts 1.25 Ethical Compliance Checklist

Required Elements

2.1 Professional Paper Required Elements 2.2 Student Paper Required Elements

Paper Elements

2.3 Title Page 2.4 Title 2.5 Author Name (Byline) 2.6 Author Affiliation 2.7 Author Note 2.8 Running Head 2.9 Abstract 2.10 Keywords 2.11 Text (Body) 2.12 Reference List 2.13 Footnotes 2.14 Appendices 2.15 Supplemental Materials

2.16 Importance of Format 2.17 Order of Pages 2.18 Page Header 2.19 Font 2.20 Special Characters 2.21 Line Spacing 2.22 Margins 2.23 Paragraph Alignment 2.24 Paragraph Indentation 2.25 Paper Length

Organization

2.26 Principles of Organization 2.27 Heading Levels 2.28 Section Labels

Sample papers

Overview of Reporting Standards

3.1 Application of the Principles of JARS 3.2 Terminology Used in JARS

Common Reporting Standards Across Research Designs

3.3 Abstract Standards 3.4 Introduction Standards

Reporting Standards for Quantitative Research

3.5 Basic Expectations for Quantitative Research Reporting 3.6 Quantitative Method Standards 3.7 Quantitative Results Standards 3.8 Quantitative Discussion Standards 3.9 Additional Reporting Standards for Typical Experimental and Nonexperimental Studies 3.10 Reporting Standards for Special Designs 3.11 Standards for Analytic Approaches 3.12 Quantitative Meta-Analysis Standards

Reporting Standards for Qualitative Research

3.13 Basic Expectations for Qualitative Research Reporting 3.14 Qualitative Method Standards 3.15 Qualitative Findings or Results Standards 3.16 Qualitative Discussion Standards 3.17 Qualitative Meta-Analysis Standards

Reporting Standards for Mixed Methods Research

3.18 Basic Expectations for Mixed Methods Research Reporting

Effective scholarly writing

Continuity and Flow

4.1 Importance of Continuity and Flow 4.2 Transitions 4.3 Noun Strings

Conciseness and Clarity

4.4 Importance of Conciseness and Clarity 4.5 Wordiness and Redundancy 4.6 Sentence and Paragraph Length 4.7 Tone 4.8 Contractions and Colloquialisms 4.9 Jargon 4.10 Logical Comparisons 4.11 Anthropomorphism

Grammar and usage

4.12 Verb Tense 4.13 Active and Passive Voice 4.14 Mood 4.15 Subject and Verb Agreement

4.16 First- Versus Third-Person Pronouns 4.17 Editorial “We” 4.18 Singular “They” 4.19 Pronouns for People and Animals (“Who” vs. “That”) 4.20 Pronouns as Subjects and Objects (“Who” vs. “Whom”) 4.21 Pronouns in Restrictive and Nonrestrictive Clauses (“That” vs. “Which”)

Sentence Construction

4.22 Subordinate Conjunctions 4.23 Misplaced and Dangling Modifiers 4.24 Parallel Construction

Strategies to Improve Your Writing

4.25 Reading to Learn Through Example 4.26 Writing From an Outline 4.27 Rereading the Draft 4.28 Seeking Help From Colleagues 4.29 Working With Copyeditors and Writing Centers 4.30 Revising a Paper

General Guidelines for Reducing Bias

5.1 Describe at the Appropriate Level of Specificity 5.2 Be Sensitive to Labels

Reducing Bias by Topic

5.3 Age 5.4 Disability 5.5 Gender 5.6 Participation in Research 5.7 Racial and Ethnic Identity 5.8 Sexual Orientation 5.9 Socioeconomic Status 5.10 Intersectionality

Punctuation

6.1 Spacing After Punctuation Marks 6.2 Period 6.3 Comma 6.4 Semicolon 6.5 Colon 6.6 Dash 6.7 Quotation Marks 6.8 Parentheses 6.9 Square Brackets 6.10 Slash

6.11 Preferred Spelling 6.12 Hyphenation

Capitalization

6.13 Words Beginning a Sentence 6.14 Proper Nouns and Trade Names 6.15 Job Titles and Positions 6.16 Diseases, Disorders, Therapies, Theories, and Related Terms 6.17 Titles of Works and Headings Within Works 6.18 Titles of Tests and Measures 6.19 Nouns Followed by Numerals or Letters 6.20 Names of Conditions or Groups in an Experiment 6.21 Names of Factors, Variables, and Effects

6.22 Use of Italics 6.23 Reverse Italics

Abbreviations

6.24 Use of Abbreviations 6.25 Definition of Abbreviations 6.26 Format of Abbreviations 6.27 Unit of Measurement Abbreviations 6.28 Time Abbreviations 6.29 Latin Abbreviations 6.30 Chemical Compound Abbreviations 6.31 Gene and Protein Name Abbreviations

6.32 Numbers Expressed in Numerals 6.33 Numbers Expressed in Words 6.34 Combining Numerals and Words to Express Numbers 6.35 Ordinal Numbers 6.36 Decimal Fractions 6.37 Roman Numerals 6.38 Commas in Numbers 6.39 Plurals of Numbers

Statistical and Mathematical Copy

6.40 Selecting Effective Presentation 6.41 References for Statistics 6.42 Formulas 6.43 Statistics in Text 6.44 Statistical Symbols and Abbreviations 6.45 Spacing, Alignment, and Punctuation for Statistics

Presentation of Equations

6.46 Equations in Text 6.47 Displayed Equations 6.48 Preparing Statistical and Mathematical Copy for Publication

6.49 List Guidelines 6.50 Lettered Lists 6.51 Numbered Lists 6.52 Bulleted Lists

General Guidelines for Tables and Figures

7.1 Purpose of Tables and Figures 7.2 Design and Preparation of Tables and Figures 7.3 Graphical Versus Textual Presentation 7.4 Formatting Tables and Figures 7.5 Referring to Tables and Figures in the Text 7.6 Placement of Tables and Figures 7.7 Reprinting or Adapting Tables and Figures

7.8 Principles of Table Construction 7.9 Table Components 7.10 Table Numbers 7.11 Table Titles 7.12 Table Headings 7.13 Table Body 7.14 Table Notes 7.15 Standard Abbreviations in Tables and Figures 7.16 Confidence Intervals in Tables 7.17 Table Borders and Shading 7.18 Long or Wide Tables 7.19 Relation Between Tables 7.20 Table Checklist 7.21 Sample Tables

Sample tables

7.22 Principles of Figure Construction 7.23 Figure Components 7.24 Figure Numbers 7.25 Figure Titles 7.26 Figure Images 7.27 Figure Legends 7.28 Figure Notes 7.29 Relation Between Figures 7.30 Photographs 7.31 Considerations for Electrophysiological, Radiological, Genetic, and Other Biological Data 7.32 Electrophysiological Data 7.33 Radiological (Imaging) Data 7.34 Genetic Data 7.35 Figure Checklist 7.36 Sample Figures

Sample figures

General Guidelines for Citation

8.1 Appropriate Level of Citation 8.2 Plagiarism 8.3 Self-Plagiarism 8.4 Correspondence Between Reference List and Text 8.5 Use of the Published Version or Archival Version 8.6 Primary and Secondary Sources

Works Requiring Special Approaches to Citation

8.7 Interviews 8.8 Classroom or Intranet Sources 8.9 Personal Communications

In-Text Citations

8.10 Author–Date Citation System 8.11 Parenthetical and Narrative Citations 8.12 Citing Multiple Works 8.13 Citing Specific Parts of a Source 8.14 Unknown or Anonymous Author 8.15 Translated, Reprinted, Republished, and Reissued Dates 8,16 Omitting the Year in Repeated Narrative Citations 8.17 Number of Authors to Include in In-Text Citations 8.18 Avoiding Ambiguity in In-Text Citations 8.19 Works With the Same Author and Same Date 8.20 Authors With the Same Surname 8.21 Abbreviating Group Authors 8.22 General Mentions of Websites, Periodicals, and Common Software and Apps

Paraphrases and Quotations

8.23 Principles of Paraphrasing 8.24 Long Paraphrases 8.25 Principles of Direct Quotation 8.26 Short Quotations (Fewer Than 40 Words) 8.27 Block Quotations (40 Words or More) 8.28 Direct Quotation of Material Without Page Numbers 8.29 Accuracy of Quotations 8.30 Changes to a Quotation Requiring No Explanation 8.31 Changes to a Quotation Requiring Explanation 8.32 Quotations That Contain Citations to Other Works 8.33 Quotations That Contain Material Already in Quotation Marks 8.34 Permission to Reprint or Adapt Lengthy Quotations 8.35 Epigraphs 8.36 Quotations From Research Participants

Reference Categories

9.1 Determining the Reference Category 9.2 Using the Webpages and Websites Reference Category 9.3 Online and Print References

Principles of Reference List Entries

9.4 Four Elements of a Reference 9.5 Punctuation Within Reference List Entries 9.6 Accuracy and Consistency in References

Reference elements

9.7 Definition of Author 9.8 Format of the Author Element 9.9 Spelling and Capitalization of Author Names 9.10 Identification of Specialized Roles 9.11 Group Authors 9.12 No Author

9.13 Definition of Date 9.14 Format of the Date Element 9.15 Updated or Reviewed Online Works 9.16 Retrieval Dates 9.17 No Date

9.18 Definition of Title 9.19 Format of the Title Element 9.20 Series and Multivolume Works 9.21 Bracketed Descriptions 9.22 No Title

9.23 Definition of Source 9.24 Format of the Source Element 9.25 Periodical Sources 9.26 Online Periodicals With Missing Information 9.27 Article Numbers 9.28 Edited Book Chapter and Reference Work Entry Sources 9.29 Publisher Sources 9.30 Database and Archive Sources 9.31 Works With Specific Locations 9.32 Social Media Sources 9.33 Website Sources 9.34 When to Include DOIs and URLs 9.35 Format of DOIs and URLs 9.36 DOI or URL Shorteners 9.37 No Source

Reference Variations

9.38 Works in Another Language 9.39 Translated Works 9.40 Reprinted Works 9.41 Republished or Reissued Works 9.42 Religious and Classical Works

Reference List Format and Order

9.43 Format of the Reference List 9.44 Order of Works in the Reference List 9.45 Order of Surname and Given Name 9.46 Order of Multiple Works by the Same First Author 9.47 Order of Works With the Same Author and Same Date 9.48 Order of Works by First Authors With the Same Surname 9.49 Order of Works With No Author or an Anonymous Author 9.50 Abbreviations in References 9.51 Annotated Bibliographies 9.52 References Included in a Meta-Analysis

Author Variations

Date Variations

Title Variations

Source Variations

Textual Works

10.1 Periodicals 10.2 Books and Reference Works 10.3 Edited Book Chapters and Entries in Reference Works 10.4 Reports and Gray Literature 10.5 Conference Sessions and Presentations 10.6 Dissertations and Theses 10.7 Reviews 10.8 Unpublished Works and Informally Published Works

Data Sets, Software, and Tests

10.9 Data Sets 10.10 Computer Software, Mobile Apps, Apparatuses, and Equipment 10.11 Tests, Scales, and Inventories

Audiovisual Media

10.12 Audiovisual Works 10.13 Audio Works 10.14 Visual Works

Online Media

10.15 Social Media 10.16 Webpages and Websites

General Guidelines for Legal References

11.1 APA Style References Versus Legal References 11.2 General Forms 11.3 In-Text Citations of Legal Materials

Legal Reference Examples

11.4 Cases or Court Decisions 11.5 Statutes (Laws and Acts) 11.6 Legislative Materials 11.7 Administrative and Executive Materials 11.8 Patents 11.9 Constitutions and Charters 11.10 Treaties and International Conventions

Preparing for Publication

12.1 Adapting a Dissertation or Thesis Into a Journal Article 12.2 Selecting a Journal for Publication 12.3 Prioritizing Potential Journals 12.4 Avoiding Predatory Journals

Understanding the Editorial Publication Process

12.5 Editorial Publication Process 12.6 Role of the Editors 12.7 Peer Review Process 12.8 Manuscript Decisions

Manuscript Preparation

12.9 Preparing the Manuscript for Submission 12.10 Using an Online Submission Portal 12.11 Writing a Cover Letter 12.12 Corresponding During Publication 12.13 Certifying Ethical Requirements

Copyright and Permission Guidelines

12.14 General Guidelines for Reprinting or Adapting Materials 12.15 Materials That Require Copyright Attribution 12.16 Copyright Status 12.17 Permission and Fair Use 12.18 Copyright Attribution Formats

During and After Publication

12.19 Article Proofs 12.20 Published Article Copyright Policies 12.21 Open Access Deposit Policies 12.22 Writing a Correction Notice 12.23 Sharing Your Article Online 12.24 Promoting Your Article

Credits for Adapted Tables, Figures, and Papers

  • DOI: 10.1002/acr2.11662
  • Corpus ID: 268273719

A Novel Approach for Mixed‐Methods Research Using Large Language Models: A Report Using Patients’ Perspectives on Barriers to Arthroplasty

  • I. Mannstadt , Susan M Goodman , +4 authors Bella Mehta
  • Published in ACR Open Rheumatology 7 March 2024

6 References

Interviewing the investigator: strategies for addressing instrumentation and researcher bias concerns in qualitative research., thematic analysis of qualitative data: amee guide no. 131, gpt-4 is here: what scientists think, nonhuman "authors" and implications for the integrity of scientific publication and medical knowledge., related papers.

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Methodology

  • What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

A research design is a strategy for answering your   research question  using empirical data. Creating a research design means making decisions about:

  • Your overall research objectives and approach
  • Whether you’ll rely on primary research or secondary research
  • Your sampling methods or criteria for selecting subjects
  • Your data collection methods
  • The procedures you’ll follow to collect data
  • Your data analysis methods

A well-planned research design helps ensure that your methods match your research objectives and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, other interesting articles, frequently asked questions about research design.

  • Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative approach Quantitative approach
and describe frequencies, averages, and correlations about relationships between variables

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

  • How much time do you have to collect data and write up the research?
  • Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
  • Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
  • Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types.

  • Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships
  • Descriptive and correlational designs allow you to measure variables and describe relationships between them.
Type of design Purpose and characteristics
Experimental relationships effect on a
Quasi-experimental )
Correlational
Descriptive

With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analyzing the data.

Type of design Purpose and characteristics
Grounded theory
Phenomenology

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

  • Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalize your results to the population as a whole.

Probability sampling Non-probability sampling

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study , your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question .

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews .

Questionnaires Interviews
)

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Quantitative observation

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

Field Examples of data collection methods
Media & communication Collecting a sample of texts (e.g., speeches, articles, or social media posts) for data on cultural norms and narratives
Psychology Using technologies like neuroimaging, eye-tracking, or computer-based tasks to collect data on things like attention, emotional response, or reaction time
Education Using tests or assignments to collect data on knowledge and skills
Physical sciences Using scientific instruments to collect data on things like weight, blood pressure, or chemical composition

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

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As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.

Operationalization

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.

Reliability Validity
) )

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method , you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

  • How many participants do you need for an adequate sample size?
  • What inclusion and exclusion criteria will you use to identify eligible participants?
  • How will you contact your sample—by mail, online, by phone, or in person?

If you’re using a probability sampling method , it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method , how will you avoid research bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organizing and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarize your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarize your sample data in terms of:

  • The distribution of the data (e.g., the frequency of each score on a test)
  • The central tendency of the data (e.g., the mean to describe the average score)
  • The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

  • Make estimates about the population based on your sample data.
  • Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

Approach Characteristics
Thematic analysis
Discourse analysis

There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

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.

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

 Statistics

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

Research bias

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

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

  • Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
  • Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

  • Your research questions and/or hypotheses
  • Your overall approach (e.g., qualitative or quantitative )
  • The type of design you’re using (e.g., a survey , experiment , or case study )
  • Your data collection methods (e.g., questionnaires , observations)
  • Your data collection procedures (e.g., operationalization , timing and data management)
  • Your data analysis methods (e.g., statistical tests  or thematic analysis )

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.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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  • Systematic Review
  • Open access
  • Published: 13 June 2024

Infant feeding experiences among Indigenous communities in Canada, the United States, Australia, and Aotearoa: a scoping review of the qualitative literature

  • Hiliary Monteith 1 ,
  • Carly Checholik 2 ,
  • Tracey Galloway 2 ,
  • Hosna Sahak 1 ,
  • Amy Shawanda 3 ,
  • Christina Liu 1 &
  • Anthony J. G. Hanley 1 , 4 , 5  

BMC Public Health volume  24 , Article number:  1583 ( 2024 ) Cite this article

277 Accesses

Metrics details

Although exclusive breastfeeding is recommended for the first six months of life, research suggests that breastfeeding initiation rates and duration among Indigenous communities differ from this recommendation. Qualitative studies point to a variety of factors influencing infant feeding decisions; however, there has been no collective review of this literature published to date. Therefore, the objective of this scoping review was to identify and summarize the qualitative literature regarding Indigenous infant feeding experiences within Canada, the United States, Australia, and Aotearoa.

Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses- Scoping Reviews and the Joanna Briggs Institute Guidelines, in October 2020, Medline, Embase, CINAHL, PsycINFO, and Scopus were searched for relevant papers focusing on Indigenous infant feeding experiences. Screening and full-text review was completed by two independent reviewers. A grey literature search was also conducted using country-specific Google searches and targeted website searching. The protocol is registered with the Open Science Framework and published in BMJ Open.

Forty-six papers from the five databases and grey literature searches were included in the final review and extraction. There were 18 papers from Canada, 11 papers in the US, 9 studies in Australia and 8 studies conducted in Aotearoa. We identified the following themes describing infant feeding experiences through qualitative analysis: colonization, culture and traditionality, social perceptions, family, professional influences, environment, cultural safety, survivance, establishing breastfeeding, autonomy, infant feeding knowledge , and milk substitutes , with family and culture having the most influence on infant feeding experiences based on frequency of themes.

Conclusions

This review highlights key influencers of Indigenous caregivers’ infant feeding experiences, which are often situated within complex social and environmental contexts with the role of family and culture as essential in supporting caregivers. There is a need for long-term follow-up studies that partner with communities to support sustainable policy and program changes that support infant and maternal health.

Peer Review reports

Introduction

Nutritional status is a key aspect of infant health with recommendations for exclusive breastfeeding for the first six months of life, which can also influence and be influenced by maternal health and wellbeing [ 1 , 2 ]. Breastfeeding has several benefits for the health and development of infants, including a reduced risk of ear and respiratory infections, obesity, asthma, skin conditions, childhood leukemia, and gastroenteritis [ 3 , 4 , 5 ]. It also supports bonding between the child and parent with improved intimacy [ 3 ]. Additionally, breastfeeding has several maternal physical and mental health benefits, including a reduced risk of breast and ovarian cancer, depression, and type 2 diabetes due to immunoprotective antibodies in breastmilk [ 3 ]. The World Health Organization (WHO) recommends exclusive breastfeeding for the first 6 months of life and initiation within the first hour after birth; however, less than half of infants 0–6 months old are exclusively breastfed worldwide [ 6 ]. Many countries are not meeting the WHO recommendations, with notable differences between low, middle, and high-income countries [ 2 ]. Differences in breastfeeding initiation rates and duration have been observed between Indigenous and non-Indigenous groups, with 6–10% lower breastfeeding initiation rates and shorter duration for Indigenous peoples [ 7 , 8 , 9 ].

Despite the many benefits of breastfeeding, bottle feeding with milk substitutes is a common form of infant nutrition and its common usage is related to a multi-dimensional set of factors influencing infant feeding decision-making. Breastfeeding is considered a traditional practice within many Indigenous cultures; however, disruptions to traditional lifeways through colonization have influenced intergenerational knowledge sharing, particularly within high-income, settler states like Canada, the US, Australia, and Aotearoa (New Zealand) [ 10 ]. Rollins et al. [ 1 ] summarize factors that influence the global breastfeeding environment including the sociocultural and market contexts, the healthcare system and services, family and community settings, employment, and individual determinants like the mother and infant attributes. However, these core breastfeeding environments for general populations overlook key considerations for Indigenous communities given the unique historical, cultural, and socio-economic contexts specific to Indigenous groups [ 11 ].

Many studies to date have focused on quantitative infant feeding data, incorporating structured questionnaires that have provided some insight into breastfeeding barriers and enablers for Indigenous caregivers [ 7 , 12 , 13 , 14 ]. However, these studies are informed by specific research questions and do not capture important nuances that caregivers experience related to infant feeding. Qualitative research can enhance our understanding of phenomena by providing flexible means for participants to engage in the research topic of interest without the constraints of structured instruments, and can even transform the research by highlighting community needs [ 15 , 16 ]. Qualitative research can also have synergy with Indigenous methodologies, supporting the use of qualitative research with Indigenous communities [ 17 ]. Given the value of qualitative inquiry and breastfeeding as traditional practice for many Indigenous cultures, disrupted by colonial influences and the burden of conditions that breastfeeding has been shown to mitigate [ 3 , 5 , 10 , 11 , 16 , 17 ], it is imperative that we consider Indigenous caregiver infant feeding experiences and perspectives to understand what needs exist as defined by communities and caregivers. Therefore, the overall aim of this scoping review was to identify and summarize the qualitative literature on infant nutrition experiences to inform needs as expressed qualitatively by Indigenous caregivers in Canada, the US, Australia, and Aotearoa. These regions are included given the shared colonial influences on Indigenous peoples with overlapping outcomes on health [ 10 , 18 ]. This review will also assess the qualitative methodologies used to understand what can be learned to inform Indigenous infant feeding services, policies, and research gaps.

Protocol and registration

This scoping review adheres to guidelines from Tricco and colleagues’ [ 19 ] Preferred Reporting Items for Systematic Reviews and Meta-Analyses ( PRISMA) extension for scoping reviews , the Joanna Briggs Institute’s Reviewer’s Manual Chap. 11 [ 20 ], as well as Arksey & O’Malley’s [ 21 ] foundational article on scoping studies. The protocol for the review is registered with the Open Science Framework ( https://doi.org/10.17605/OSF.IO/J8ZW2 ) and published with BMJ Open [ 22 ].

Eligibility criteria

Works included in this review must have focused on Indigenous populations in Canada, the United States, Australia, and/or Aotearoa. These four countries share commonalities in that they are colonial countries in which Indigenous peoples face inequitable health outcomes [ 10 , 18 , 23 ]. The topic of interest for this review was caregivers’ experiences of infant feeding within one or more of these regions. “Caregivers” refer to individuals in the infants’ immediate familial and social circles who are directly responsible for the regular care of the infant. A broad definition of those involved in caregiving was used, recognizing that within many Indigenous communities, traditional adoption practices occur, or biological parents may not be the primary caregivers in part related to complex socio-ecological challenges. The experiences of healthcare professionals were not included as they were not considered “caregivers” by this definition. Works that discussed breastfeeding, as well as alternative forms of infant feeding, such as formula and cow’s milk, were included. Works that only focused on the introduction of solid foods were excluded. To capture caregivers’ experiences of infant feeding, qualitative and mixed-method studies that discussed experiences, perspectives, and/or practices as described by caregivers were included. Studies that used exclusively quantitative methods or that only described an outsider perspective (e.g. health professional) were excluded. Peer-reviewed journal articles and grey literature were included if they met the above criteria, were published in the English language, and were published after 1969 [ 22 ].

Various types of grey literature such as government documents, dissertations, and research reports by academic and non-academic institutions, including Indigenous organizations, were included. Media reports (including videos, news, and blogs) were excluded from the grey literature as they did not follow a research design with results that could be considered alongside the studies included in the review, hindering our ability to compare and critically analyze the results. Similarly, publications that consisted of only an abstract were excluded from both grey and database publications during full-text review as not enough information was present for analysis.

Information sources

The search strategy was created with guidance from a research librarian at the Gerstein Science Information Centre, University of Toronto. The complete search strategy can be found as supplementary material in our published protocol [ 22 ]. Search terms primarily included broad terminology for Indigenous peoples (e.g. Native American) rather than specific Nation names (e.g. Ojibwe) as this would have significantly extended the search term list while not resulting in additional sources given how sources are indexed within Library systems. A database and grey literature search were conducted for this scoping review, completed independently from one another until final data extraction when the data were combined for analysis. For both searches, the reviewers followed a step-by-step process of title and abstract screening, followed by full-text screening, and then data extraction.

The database search planning and calibration occurred in August and September of 2020, and all data were exported in English on October 20, 21, and 22 of 2020. Exportation occurred over three days given feasibility of exporting the high number of citations and time capacity of the reviewers. A total of 16734 relevant sources available in the following databases were included: Medline, Embase, CINAHL, PsycINFO, and Scopus. These databases were selected to ensure a broad range of research given the multidisciplinary nature of research on this topic. The grey literature search consisted of a targeted search of a variety of Indigenous focused websites specific to the four countries and a thorough Google search with each of the country-specific Google versions (Google.com.au, Google.co.nz, Google.ca, and Google.com) where the first 10 pages of results were reviewed (Supplementary File 1 ). Lastly, Indigenous Studies Portal (I-Portal) was searched as part of the grey literature as this database uses a different indexing system than other research databases. The Canadian Agency for Drugs and Technologies in Health (CADTH)’s “Grey Matters” checklist [ 24 ] was used in the planning and tracking of grey literature searches and findings.

The results of the database search including 16734 citations were uploaded to Covidence (Veritas Health Innovation Ltd., Melbourne, Australia), a data management platform for systematic and scoping reviews, where 3928 duplicates were automatically removed. The 284 results of the grey literature search were recorded on Google Sheets (Alphabet Inc. California, USA) and 146 duplicates were manually removed by the reviewers. Due to the large number of results retrieved in the database and grey literature search, a hand-search of reference lists was not conducted.

A list of key words developed by HM were searched on each site and can be found in Supplementary File 1 . The grey literature search was completed by HM, CC, and HS with all reviewers assigned to search a Country-specific Google database for one of the included countries. Using a template created by Stapleton [ 25 ] at the University of Waterloo based on methods described by Godin et al. [ 26 ], the reviewers kept track of which search terms were searched on the websites, the number of results retrieved, and the number of items screened and saved for further full-text analysis. If a website did not have a search bar, relevant tabs were examined for research, resources, and other publications. I-Portal was originally searched on August 15th, 2021 (yielding 10 results), however the search was revised to remove Indigenous search terms as the database was already Indigenous-specific. The search was repeated on August 18th, 2021, and yielded 77 additional results. The grey literature search was completed between May 25, 2021 – August 18, 2021. No search limitations or filters were used for the grey literature search or the database search.

The database abstract screening was initially completed by HM and CC starting in October 2020. They were then joined by HS and CL in February 2021. To ensure all reviewers had a shared understanding of the eligibility criteria, two search results were screened together and each reviewer discussed their reasoning for inclusion or exclusion. HM also hosted an introductory meeting to review the screening process using Covidence Software [ 27 ] in detail. All 12806 database results were saved in Covidence [ 27 ].

Abstract and full-text screening was completed in Covidence by two independent reviewers. Any conflicts at the screening stage were resolved by AH after all the results had been screened by two reviewers. Full-text screening was completed by HM, AH, and CC, and when conflicts arose, the reviewers met to discuss the difference in opinion until a consensus was reached. A third reviewer joined to offer impartial opinions for full-text conflicts.

Grey literature results were not imported to Covidence. Instead, the team used Google Sheets to organize the publications. Similar to the database review process, each study was screened by two independent reviewers and conflicts were resolved by a third party and discussed for consensus. Full-text review of the grey literature was completed by HM, AH, CC, and HS.

Data extraction and analysis

HM compiled a list of variables to extract (Supplementary File 2 ), and the data extraction was completed by HM, AH, and CC in Covidence for database results and Google Sheets for the grey literature. The extraction template was reviewed and tested by all three reviewers using the same two articles. Discussion about any areas of confusion followed by minor edits to the data extraction template were completed prior to extraction.

Only one reviewer extracted data from most publications, however in circumstances where an article was complex or data extraction was not clear given the format of the article, two reviewers extracted data from the publication. An additional subset of five publications were also randomly double-reviewed by HM to ensure consistency in data extraction. There were an additional two articles that were excluded at this step after review and discussion by AH and HM.

Review findings using the extraction template (supplementary file 2 ) were exported into Microsoft Excel (Microsoft Corporation, Washington, USA) and reviewed by HM. HM compiled all data and completed summary figures for variables of interest. The primary analysis consisted of a qualitative review of the included papers’ results and recommendations using a thematic synthesis informed by grounded theory and meta-ethnography, where the included papers are synthesized together, and interpreted using descriptive and analytical themes [ 28 ]. Similar to grounded theory, this process was inductive and identifies themes through comparisons. HM reviewed all extracted data from the excel files, coding for overlapping themes and taking notes throughout. The full-text of the extracted papers were then revisited to identify overall concepts, followed by descriptive themes. Categorization of descriptive themes was completed based on the results and interpretations of included papers. Descriptive themes were refined through additional comparisons between papers. The same analytical process was used for both database and grey literature results, and final analysis involved the integration of themes from the database and grey literature papers. Supplementary file 3 provides a summary table of the included papers in this scoping review.

Characteristics of included articles

Of the final sample of 46 articles from which data was extracted (Fig.  1 ), there were studies from each of the four countries, with the most studies (39%) published from Canada. In addition, this qualitative literature on infant feeding included several Indigenous groups within the four countries. The studies retained in this review included authors who identified as either Indigenous or non-Indigenous, and several did not mention positionality (Fig.  2 ). 13% more grey literature studies discussed positionality and had Indigenous sole authorship compared to the database papers. Regarding methodologies utilized, several described Indigenous methodologies and used thematic analysis as an analytic tool (Figs.  3 and 4 ). However, a third of the studies did not describe their theoretical foundations for the qualitative inquiry. Over 60% of the studies were published in the fields of public health and/or nursing as per the authors stated fields of study and/or the Journal’s field, and although there were studies published from 1984 to 2019, 50% of the retained papers were published after 2010.

figure 1

PRISMA flow diagram for studies identified, screened, and included in this review from both database and grey literature searches. Note that records not retrived are those in which the full-text was not accessible. This diagram was created from the PRISMA 2020 statement [ 29 ]

figure 2

Author positionality as described in the retained papers

figure 3

Summary of analytic tools used in the retained studies

figure 4

Summary of theoretical foundations informing the retained studies’ methodologies

Analysis revealed a variety of important themes that aligned with Indigenous and public health perspectives on health, including the socioecological model. There were twelve final overarching themes including colonization, social perceptions, family, professional influences, culture and traditionality , environment (i.e. built environment) , autonomy, survivance, infant feeding knowledge, cultural safety , milk substitutes , and establishing breastfeeding with evidence of connections among these themes. These themes are shown in Fig.  5 in a circular pattern where the themes intersect with the infant and caregiver represented at the centre. This model is conceptually aligned with that of Dodgson et al. [ 30 ], who considered the “contextual influences within the social structures of family and community, Ojibwe culture, and mainstream culture.”

figure 5

Scoping review research model of themes

The twelve final themes are shown as the main influences on infant feeding experiences. The themes are arranged in a circular pattern with the infant and caregiver represented at the centre, emphasizing the connection between all of the themes

Theme one: colonization

There were 14 papers that discussed colonization of Indigenous peoples as a key factor influencing infant feeding decisions and experiences (Fig.  6 ) [ 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ]. Colonization has meant the dispossession of land and limited access to culturally safe healthcare, malnutrition, and loss of language through residential schools, loss of culture and traditional knowledge through assimilation and separation of families, disrupting breastfeeding practices and limiting income for infant formula. Eni et al. [ 36 ] described the policies leading to evacuation from communities to tertiary-care hospitals for birthing as the medicalization of birthing practices, which creates various challenges for First Nations women in Canada. One participant also shared about the impacts of intergenerational trauma related to colonization on breastfeeding, ‘‘You can’t teach about breastfeeding technique and think things will change. It’s the spirit that’s been affected, our experience with trauma. Our women need to relearn how to bond with their children.’’.

A qualitative study with Aboriginal Australian first-time mothers noted the disruptions to breastfeeding practices over time, providing a historical chart detailing how infant feeding practices changed as a result of colonial influences [ 38 ]. Brittany Luby [ 39 ] described how hydroelectric flooding from 1900 to 1975 in Northwestern Ontario reduced breastfeeding practices for Anishinabek mothers and their infants. Although not all studies specifically discussed history and colonization, those that considered the broader historical context highlighted how important this issue is in understanding the factors that lead to infant feeding decisions, particularly those that do not align with breastfeeding as a traditional feeding practice.

figure 6

Frequency of identified themes in the database papers and the grey literature

Theme two: culture and traditionality

Culture , including traditionality, was the second most described theme throughout all papers, identified both directly and indirectly in 31 papers (Fig.  6 ) [ 30 , 31 , 32 , 34 , 35 , 37 , 38 , 39 , 40 , 41 , 42 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 ]. The Navajo Infant Feeding Project focused on cultural beliefs influencing infant feeding practices within three Navajo communities in the United States [ 48 ] and emphasized breastfeeding’s significance for nutritional, physical, and psychological health where mothers not only pass along physical health benefits, but also their wellbeing to their children. The Baby Teeth Talk Study in Cree communities in Northern Manitoba, Canada, has identified breastfeeding as a cultural intervention for the prevention of early childhood caries [ 52 ]. Several studies included a variety of generations in data collection, contributing to rich discussion of how breastfeeding rates and connection to traditionality has changed in some communities [ 48 , 57 , 64 , 65 ]. For example, grandmothers living on the Fort Peck Reservation in Montana, US, were interviewed about their perspectives on infant feeding [ 65 ]. In one of the ethnographic studies, there was a specific focus on the Ojibwe culture relating to infant feeding practices from the perspective of mothers, professionals who were also community members, and Elders [ 35 ]. This study emphasized the holistic and collective worldview of the community, influencing women’s roles within the family and how teachings were passed on from generation to generation [ 35 ]. This was considered to be important in influencing effective and culturally safe breastfeeding promotion. Within the Northwest Territories, Canada, Moffitt and Dickinson [ 53 ] supported breastfeeding knowledge translation tools for Tłı̨chǫ women with one of the themes focused on factors that “pull to breastfeeding,” including breastfeeding as a traditional feeding method. In general, Indigenous communities described breastfeeding as a cultural practice; however, how this is supported and the traditional knowledge surrounding this practice may differ from community to community. Therefore, health providers must be aware of community-specific protocols and support these within programs and recommendations.

Theme three: social perceptions

Societal influences are often considered alongside cultural perspectives of infant feeding; therefore, this theme was also commonly discussed in the papers retained in this scoping review (Fig.  6 ) [ 30 , 32 , 33 , 36 , 37 , 38 , 40 , 42 , 49 , 50 , 52 , 54 , 57 , 58 , 59 , 61 , 64 , 66 , 67 , 68 , 69 , 70 , 71 ]. In New South Wales, Australia, Aboriginal mothers and key informants noted the need for “a safe place to feed,” including concerns about the social acceptability to breastfeed in public [ 32 ]. Broader social “norms” are also discussed as influencing maternal behavior [ 68 ], and respondents in some studies expressed concern about judgements from others [ 32 , 36 ]. Tapera et al. [ 40 ] described concerns about social pressures and a lack of support with one grandparent sharing, “well here in New Zealand, I know we have a problem with this [breast-feeding], especially when mothers go out and they breast-feed their babies in public. There’s a lot of people that moan and groan about this.” Similarly, regarding social norms, a grandmother living in the US shared,

“a long time ago that, it [breastfeeding] was acceptable and nobody had any qualms about it but today, I mean you read continually about, people, mother’s tryin’ ta breastfeed and they’re being chased out a places or stores or people are rude about it […]. Society’s changed, you know, it’s […] society, has come to the point where it’s […] trying to tell us what’s the right way ta live what’s the right way ta raise our kids” [ 65 ].

Dodgson et al. [ 30 ] described how in an Ojibwe community in Minnesota, US, participants noted the dominant societal influences in contrast to community traditions, with women making an effort to engage in traditional practices. The sexualization of breasts in mainstream society sometimes influenced Indigenous mothers’ infant feeding experiences [ 36 ], although Ojibwe caregivers in Minnesota attributed shyness with breastfeeding to traditional value opposed to sexualization of breasts [ 30 ]. Eni et al. [ 36 ] included sexual objectification of the feminine body as a subtheme in their study, describing how this social perception damages maternal mental health, creating a barrier to breastfeeding. While shifting social norms is a significant challenge, breastfeeding supports can address concerns about the sexual objectification of breasts by creating safe spaces for parents to talk about the challenges and ensure that parents have access to mental health resources.

Theme four: family

Dodgson et al. [ 30 ] described family as a pattern that influences breastfeeding intersecting with the social structures of the community, culture, and the broader society. There were 33 other papers that described the influence of family on infant feeding practices making this the most discussed theme (Fig.  6 ) [ 30 , 31 , 32 , 33 , 36 , 38 , 39 , 40 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 53 , 54 , 55 , 57 , 58 , 59 , 60 , 61 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 ]. Native American mothers living in six communities highlighted the importance of family as a key theme [ 47 ]. One mother shared, “For me, it’s my mom definitely [whose advice is most important] because she has had three kids and I lived with her or near her for all of my kids. So I’ve always gone to her first for advice.” This was echoed by many other participants with a paraprofessional adding, “family [advice is most important], because they are around their family most. And they always hear from their aunties, or from grandma, baby’s fussing, baby must be hungry, baby needs this and baby needs that.” The Baby Basket Program in Cape York, Australia identified that empowering families was the foundation of the program to ensure that mothers and their partners were equipped for the arrival of their babies [ 50 ]. Family often plays an integral role in supporting mothers in infant feeding practices. Bauer and Wright [ 45 ] note that even when mothers don’t have other supports or conditions in place to support breastfeeding, they may still choose to breastfeed if their family is supportive. However, when this support is lacking, mothers find it challenging to breastfeed [ 31 , 36 ]. Some studies identified the significance of family in the study design, integrating family caregiver perspectives in data collection [ 64 , 65 ]. Therefore, health programs and research studies should consider the role and experience of non-primary caregivers within family networks for infant and maternal health and nutrition.

Theme five: professional influences

This theme represents the influence of formal systems including healthcare professionals, health and social programs, child services, and the legal system. In total, there were 26 papers that referenced professional influences on infant feeding experiences (Fig.  6 ) [ 30 , 31 , 33 , 38 , 41 , 42 , 43 , 45 , 47 , 48 , 50 , 51 , 52 , 54 , 58 , 59 , 61 , 62 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 ]. Some studies incorporate health workers as participants in data collection [ 47 , 50 , 65 ]. One health paraprofessional shares about some of the pressures experienced by mothers to formula feed, “sometimes hospitals and doctors want to push formula in bottles on moms [ 47 ].” One of the main themes in a study with Sioux and Assiniboine Nations in the US was the ‘ Overburdened Healthcare System’ , describing a lack of resources and infrastructure to support breastfeeding, including a subtheme of mistrust in the healthcare system due to previous negative experiences such as forced sterilization of Indigenous women [ 65 ]. However, some caregivers also expressed positive healthcare supports, “when I was at home, [clinic midwife] and [lactation consultant made home visits] … they encouraged me … And then it started getting a little bit better, but it was still a bit hard. Now he feeds pretty all right [ 73 ].” Professional influences on infant feeding are nuanced and may differ significantly within various contexts and individuals; therefore, tailored interventions are needed.

Theme six: environment

This theme represents the external variables within the built environment that influence decision making including work, school, remoteness, and cost of formula. Eighteen papers addressed this theme [ 30 , 31 , 44 , 45 , 46 , 47 , 48 , 49 , 51 , 53 , 58 , 59 , 66 , 67 , 68 , 70 , 71 , 72 ]. Wright et al. [ 74 ] specifically considered the challenge of breastfeeding with maternal employment among the Navajo population in the US. In Bauer and Wright’s [ 45 ] study that explored infant feeding decision models, they identified that work and school are part of the decision-making process on whether to breastfeeding or to use formula, but even when these environmental challenges are present they can be further influenced by other factors, like family . For example, a mother may choose to breastfeed and use a breast pump to navigate work/school schedules, but family members may recommend that they can incorporate formula; decision-making is not only about the main caregiver’s desires but can involve various decision-makers.

Theme seven: autonomy

This theme describes parents’ freedom to make infant feeding decisions that fit for them and their priorities. Maternal desire to breast- or bottle-feed was discussed in select papers in this review [ 45 , 51 ]. In addition, other papers describe parents’ freedom to do activities outside of infant feeding in the early months of baby’s life with discussion of time required to breastfeed or prepare bottles for feeding [ 31 , 58 , 72 , 74 ]. A key informant in a study with an Aboriginal community in Northern New South Wales, Australia, shares, “they want to breastfeed, but then it comes down to when they want to go out, or keep up with their man [ 32 ].” Some parents report that they experienced judgements from others or feel forced into making a specific decision on infant feeding method, highlighting a desire to have support and freedom to make their own decisions [ 36 , 56 ].

Theme eight: infant feeding knowledge

Several studies emphasize the importance of knowledge on infant feeding experiences, highlighting the value of infant feeding education, both within the overall healthcare system and from traditional teachings [ 30 , 32 , 35 , 40 , 42 , 43 , 47 , 52 , 57 , 58 , 62 , 64 , 66 , 67 , 68 , 69 , 70 , 71 , 72 ]. Within the theme of addressing feeding challenges in one study [ 66 ], a caregiver shared how knowledge helped her to work through a challenge,

“He did start fussing at about 6 weeks and that was kind of hard because I thought, ‘No, I have got this perfect now, and he has started to muck up’. But then I read, because I had those booklets and I read that sometimes they — at a certain point — they get a bit fussy and you just have to work through it. [Ml7]” [ 66 ].

Traditional breastfeeding knowledge is important for many communities; one Anishinaabe community knowledge keeper shared that “breast milk is a gift and a medicine a mother gives her child” [ 35 ]. This study also discusses feeding patterns as shared by Elders and traditional teachers. Traditional knowledge considers holistic perspectives of health where caregivers are also focused on the baby’s spiritual wellbeing [ 48 , 56 ].

Theme nine: milk substitutes

Bottle feeding (formula or canned milk) and solid foods are described in several papers as alternatives or complements to breastfeeding [ 31 , 33 , 34 , 37 , 39 , 47 , 48 , 49 , 51 , 52 , 53 , 58 , 66 , 67 , 74 , 75 ]. In Neander and Morse’s [ 37 ] study with a Cree community in Alberta, Canada, bottle feedings were offered particularly when mothers felt that they were not producing adequate milk supply to meet the baby’s nutritional needs. Insufficient milk supply is echoed as a concern in several other papers resulting in complementary bottle feeding or weaning [ 48 , 51 , 56 , 66 , 67 ]. A Māori father shares,

“about the second week, baby just wanted more food. She (partner) would end her day and baby was just hungry. We had to [give her] the bottle and then she would be finally satisfied. It wasn’t that she made a choice. Baby was actually demanding more and more and she couldn’t produce it. (First-time father, mid 20’s) [ 56 ].”

This theme particularly overlaps with autonomy as parents balance infant feeding decisions with breastmilk supply, work, school, and other personal commitments.

Theme ten: cultural safety

Indigenous caregivers interact with a variety of health services postnatally; however, there is a need to address cultural safety within the healthcare system. Twelve retained papers highlighted this theme either directly as one of their themes or as part of another theme (Fig.  6 ) [ 30 , 31 , 44 , 47 , 50 , 64 , 66 , 67 , 69 , 71 , 73 , 74 ]. One health worker in Victoria, Australia, shared,

“I can’t say often enough or long enough, loud enough the ideal for children 0–8 is to have access to maternal and child health. You might say ‘oh yes, they’ve got access to mainstream and they’re culturally going to put up a few Indigenous prints in their rooms’ It’s not the same. Our families are telling us with their feet it’s not the same.”

Mothers expressed a desire for more traditional infant feeding knowledge within services and culturally relevant supports [ 47 , 64 ]. A study that focused on a baby basket program to support families in a Murri (Local Australian Aboriginal Group) Way identified how important culturally safe language and relationships are for families,

“…the nurse is also learning what the best way is to approach a family and what the wording has to be, what the languaging is around things, what the traditional words are for Indigenous language and are appropriate for use in certain circumstances” [ 50 ].

Theme eleven: survivance

Indigenous caregivers experience a variety of hardships; however, through resistance and survival, they practice cultural revitalization [ 76 ]. This theme is discussed in 15 papers and is often described through a lens of maternal mental health (Fig.  6 ) [ 30 , 31 , 33 , 43 , 53 , 54 , 57 , 58 , 59 , 63 , 64 , 66 , 68 , 36 , 74 ]. Some parents express feelings of guilt for the challenges they encounter, which can further contribute to negative emotions [ 58 ]. Maternal mental and emotional health can impact infant feeding experiences,

“…sometimes people’s psychological health, mental health is more of a risk factor, you know if you’re not sleeping and you’re bordering on depression and you’re not coping well and you can’t get the baby to latch and you’re constantly feeling like a failure and you can’t get out of that rut, is it worth it?…People have to decide that for themselves. (Key Informant #5)” [ 33 ].

A grandmother in the Northwest Territories of Canada noted the disembodiment caused by residential schools as expressed as a disconnection between physical experiences and relationships,

“You know in those days, I mean residential school. In those days, they never did talk about their body parts because I think they were too ashamed [of your body] to say to your kids. I never did hear it [breastfeeding] from my sisters or nobody in the family. They were so private (L151-156)” [ 57 ].

Traumatic experiences, like residential schools, can have a lasting impact on how caregivers navigate motherhood and infant feeding, and the support they receive from family members.

Theme twelve: establishing breastfeeding

There are several practical challenges that mothers encounter while breastfeeding like pain, latching issues, and low milk supply, discussed in 11 of the studies (Fig.  6 ) [ 48 , 51 , 54 , 56 , 58 , 61 , 66 , 68 , 71 , 72 ]. A mother shared,

“He wouldn’t latch on all the time, like, the nurses and stuff tried to help me but then it would be all frustrating…. He didn’t really know what to do. He tried and then they gave him formula. He really loved it. [MI5]” [ 66 ].

Although these challenges are most discussed at the beginning of breastfeeding, sometimes concerns arise when babies are older.

“Yeah it was 8 or 9 months after she was born. After a while there was too much pressure on me. She was getting up all through the night and she would eat and eat and eat and not get full…” [ 33 ].

Overall, many caregivers reported that breastfeeding is difficult; therefore, supports that consider the variety of challenges that can arise are needed.

Study recommendations

The studies included in this review were published over three decades starting in 1984 until 2019 and were completed with various Indigenous communities in four countries. We anticipated that earlier work would demonstrate markedly different infant feeding recommendations than more recent research; however, this was not necessarily the case. For example, cultural safety is a more recent discussion within the health literature; however, although we see some discussion of this in more recent studies, studies in the 80’s and 90’s also highlight the importance of incorporating traditional teaching and consulting community members [ 37 , 48 ]. Therefore, supporting Indigenous self-determination where health professionals provide culturally appropriate care is essential.

In addition to topics related to cultural safety, various studies highlight a need for community-driven and local knowledge to inform programs and policies related to infant nutrition [ 31 , 47 , 57 , 64 , 75 ]. Several studies also focus on infant feeding specific programs and behavioral changes in their recommendations [ 47 , 50 , 65 ]; however, many of these studies also highlight the need to expand beyond the individual’s role in decision making and address the broader social and environmental factors such as the workplace, healthcare infrastructure, social perceptions, among others, that influence infant feeding decisions. For example, Eni et al. [ 36 ] note that there are a complexity of factors resulting in various breastfeeding environments. These structural, social and cultural contexts are discussed throughout several of the grey literature texts as well [ 32 , 33 ]. It is also important to note that in the most recently published database paper, maternal mental health is directly addressed in the recommendations and this is the only paper with this focus for next steps [ 65 ]. Interventions that target socio-ecological factors based on the included papers’ recommendations for infant feeding are summarized in Fig.  7 .

figure 7

(Adapted from Rollins et al. 2016)

The components of Indigenous infant feeding environments informed by community-based interventions

This scoping review presents and summarizes the findings reporting Indigenous infant feeding experiences within the qualitative literature in Canada, the US, Australia, and Aotearoa. Twelve themes were identified which summarize the literature including culture and traditionality , colonization, family, environment, social perceptions, professional influences, milk substitutes, breastfeeding initiation, cultural safety, survivance, infant feeding knowledge, and autonomy. The most prevalent themes discussed by caregivers and researchers in the included papers were family and culture/traditionality . The frequency of these two themes highlight the significant impact of family and culture/traditionality on infant nutrition decision-making for Indigenous caregivers and overlaps with components of the socio-ecological model [ 77 ]. This focus on family and culture/traditionality also emphasizes the importance of familial relationships and a collective mentality within traditional life ways for many Indigenous communities in these regions on infant nutrition and care practices.

In their informative global breastfeeding paper, Rollins and colleagues’ [ 1 ] conceptualize the components that contribute to the breastfeeding environment at multiple levels, overlapping with the social determinants of health. In this review, we observed that caregivers report similar components of the breastfeeding environment; however, these components seem to be described collectively, rather than as separate contexts. This is evident in the recommendations proposed by authors with a large focus on local and community-specific leadership, multidisciplinary interventions, and cultural safety in response to historical traumas, particularly within the healthcare system (Fig.  7 ). This aligns with Indigenous epistemology with an emphasis on the collective and interconnectedness of all things where power is manifested together, not over one another, and is based in local land-based knowledge [ 78 , 79 ].

A primary recommendation echoed within many of these studies was the need for community engagement in program and policy development [ 34 , 47 , 50 , 64 ]. This may need to be expanded upon to support Indigenous self-determination of policy and programs related to infant feeding where community members are not only engaged but leading the way forward in maternal and infant health. It is important to note that there have been changes over time in how these recommendations and perspectives are discussed and the role of the health professional, particularly related to cultural safety. For example, although similar concepts are discussed in Neander and Morse’s paper published in 1989, ‘cultural safety’ is not used as the terminology, which has been expanded upon in recent years by Indigenous and non-Indigenous scholars [ 37 , 80 , 81 ].

Related to this focus on health professionals and cultural safety, it’s important to distinguish that in many of the positive experiences expressed by participants in the studies, these interactions seemed to be primarily with professionals interacting closely with families. For example, midwives, who make home visits, were often included as part of positive experiences. In the literature, there is an emphasis on including practitioners who can build strong relationships with families through home visits and regular community engagement in routine services, which supports cultural safety within the healthcare system [ 82 , 83 ]. Health professional regulatory bodies should consider implementing practice competencies that support professionals to build and navigate strong and ethical relationships with clients/patients. Similarly, healthcare settings that serve Indigenous peoples should consider processes and therefore, facility infrastructures that enable close family-client-professional interactions. An example of this implementation with positive client experiences is the Toronto Birthing Centre, which uses an Indigenous framework and has birthing rooms with space for family [ 84 ].

The studies in this review are written within various fields of research; therefore, there were differences in methodological reporting. Future qualitative work should be thorough in reporting theoretical foundations to provide clarity of how the analyses and overall projects are approached (Fig.  4 ) [ 85 ]. Given the limited studies that report author/researcher positionality (Fig.  2 ), this may be an important addition in forthcoming work as a means of respecting Indigenous and qualitative literature conventions where we recognize that positionality influences ontological origins [ 86 ]. We challenge the academy to recognize that Indigenous and local knowledges are required within Indigenous health research and dissemination practices, while acknowledging our own limitation in this review of a single country authorship team.

This systematic scoping review utilized a rigorous search strategy that limited the possibility of missing relevant publications; however, it was time intensive. PRISMA-ScR guidelines were followed with two independent reviewers at each stage, enabling reproducibility of this review. The inclusion of the grey literature is a strength in this study as it captured important papers that were not published in peer-reviewed journals, often from Indigenous authors and communities (many of which were graduate dissertations), which was a priority in this review. A possible limitation is the exclusion of work that only discussed the introduction to solid foods; it is possible that this excluded an important conversation about the differences of introducing solids, like traditional foods from an Indigenous group’s perspective. In addition, the topic of this review is multidisciplinary; therefore, it is possible that although effort was made to include a broad range of research field databases in the search, relevant sources may have been missed.

In conclusion, this scoping review highlights important considerations for infant feeding environments within Indigenous communities with a focus on family and culture. Based on caregiver experiences, Indigenous breastfeeding supports must be community led with a focus on local capacity and traditional teachings. An emphasis on an intergenerational perspective that considers structural and systems approaches including cultural safety within healthcare, addressing maternal mental health, and consideration of sustainability over time is encouraged. Future work should focus on these key areas through strength-based research approaches, grounded in strong relationships and long-term follow-up.

Data availability

All data generated or analysed during this study are available from the corresponding author on reasonable request.

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Acknowledgements

We wish to acknowledge the important contribution of Halima Abubakar in the review process. Given the knowledge specific to Indigenous communities discussed in this scoping review and out of respect for Indigenous research conventions, the authors position themselves within the research to explain the lens from which they approach and understand the research process. TG and AH are non-Indigenous scholars and faculty members based at the University of Toronto, which rests on lands that are the traditional home of the Huron-Wendat, the Seneca, and the Mississaugas of the Credit. All other authors have had student or supporting roles throughout this work and situate themselves as follows: HM is a settler of Scottish, Irish, French, German, and English ancestry residing in Haudenosaunee and Anishinaabe territory, which is part of the dish with one spoon agreement; CC is a settler living in Treaty 7 Territory, with ancestral roots in Germany, Scotland, and the Ukraine; AS is an Odawa Kwe from Wikwemikong, Manitoulin Island, Ontario. Currently, residing in the Tiohtià:ke in Kanien’kéha unceded territory; and HS is living in Treaty 13 territory with ancestral roots in Afghanistan. The remaining co-authors identify as non-Indigenous scholars.

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

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As the first author, HM conceptualized this work and provided leadership throughout. She participated in every aspect of this review, wrote the initial manuscript, and completed revisions. CC contributed to the screening and full text review of this work. She also contributed to the analysis, and the writing and review of the manuscript. TG supported the protocol of this review and provided guidance throughout analysis. She also contributed to the final manuscript. HS supported screening and full text review. She also provided edits for the manuscript. AS provided feedback on the analysis for this review and contributed to the writing of the manuscript. CL supported screening of papers and provided edits to the final manuscript. AH provided guidance throughout the duration of this review, supported decision making, and provided edits on the manuscript. All authors approved the final manuscript.

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Monteith, H., Checholik, C., Galloway, T. et al. Infant feeding experiences among Indigenous communities in Canada, the United States, Australia, and Aotearoa: a scoping review of the qualitative literature. BMC Public Health 24 , 1583 (2024). https://doi.org/10.1186/s12889-024-19060-1

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1. Introduction

2. formulation of the proposed framework, 3. formulation of a multicomponent monodisperse spheres model, 4. numerical experiments, 5. discussion, 6. conclusions.

how to write a methodology for a qualitative research paper

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research papers \(\def\hfill{\hskip 5em}\def\hfil{\hskip 3em}\def\eqno#1{\hfil {#1}}\)

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Open Access

Qu­antitative selection of sample structures in small-angle scattering using Bayesian methods

a Graduate School of Frontier Sciences, University of Tokyo, Kashiwa, Chiba 277-8561, Japan, b Japan Synchrotron Radiation Research Institute, Sayo, Hyogo 679-5198, Japan, c National Institute for Materials Science, Tsukuba, Ibaraki 305-0047, Japan, and d Facalty of Advanced Science and Technology, Kumamoto University, Kumamoto 860-8555, Japan * Correspondence e-mail: [email protected]

Small-angle scattering (SAS) is a key experimental technique for analyzing nanoscale structures in various materials. In SAS data analysis, selecting an appropriate mathematical model for the scattering intensity is critical, as it generates a hypothesis of the structure of the experimental sample. Traditional model selection methods either rely on qualitative approaches or are prone to overfitting. This paper introduces an analytical method that applies Bayesian model selection to SAS measurement data, enabling a quantitative evaluation of the validity of mathematical models. The performance of the method is assessed through numerical experiments using artificial data for multicomponent spherical materials, demonstrating that this proposed analysis approach yields highly accurate and interpretable results. The ability of the method to analyze a range of mixing ratios and particle size ratios for mixed components is also discussed, along with its precision in model evaluation by the degree of fitting. The proposed method effectively facilitates quantitative analysis of nanoscale sample structures in SAS, which has traditionally been challenging, and is expected to contribute significantly to advancements in a wide range of fields.

Keywords: small-angle X-ray scattering ; small-angle neutron scattering ; nanostructure analysis ; model selection ; Bayesian inference .

SAS measurement data are expressed in terms of scattering intensity that corresponds to a scattering vector, a physical quantity representing the scattering angle. Data analysis requires selection and parameter estimation of a mathematical model of the scattering intensity that contains information about the structure of the specimen. This selection process is critical as it involves assumptions about the structure of the specimen.

We conducted numerical experiments to assess the effectiveness of our proposed method. These experiments are based on synthetic data used to estimate the number of distinct components in a specimen, which was modeled as a mixture of monodisperse spheres of varying radii, scattering length densities and volume fractions. The results demonstrate the high accuracy, interpretability and stability of our method, even in the presence of measurement noise. To discuss the utility of the proposed method, we compare our approach with traditional model selection methods based on the reduced χ -squared error.

In this section, we present a detailed formulation of our algorithm for selecting mathematical models for SAS specimens using Bayesian model selection. The pseudocode for this algorithm is provided in Algorithm 1.

2.1. Bayesian model selection

The likelihood is thus expressed as

Let φ ( K ) be the prior distribution of the parameter K that characterizes the model, and φ ( Ξ | K ) be the prior distribution of the model parameters Ξ . Then, from Bayes' theorem, the posterior distribution of the parameters given the measurement data can be written as

2.2. Calculation of marginal likelihood

Sampling from the joint probability distribution at each inverse temperature gives

2.3. Estimation of model parameters

In this paper, we consider isotropic scattering and focus on the scattering vector's magnitude q , defined as

Monodisperse spheres are spherical particles of uniform radius. The scattering intensity I ( q ,  ξ ) of a specimen composed of sufficiently dilute monodisperse spheres of a single type for the scattering vector magnitude q is given by

To formulate the scattering intensity of a specimen composed of K types of monodisperse sphere, we assume a dilute system and denote the particle size of the k th component in the sample as R k and the scale as S k . The scattering intensity of a sample composed of K types of monodisperse sphere is then given by


An illustration of a mixture of two types of spherical specimen. This shows scenarios with two components ( = 2), including mixtures of spherical particles of different sizes or volume fractions, and aggregates from a single particle type approximated as a large sphere.

The numerical experiments reported in this section were conducted with a burn-in period of 10 5 and a sample size of 10 5 for the REMC. We set the number of replicas for REMC, the values of inverse temperature and the step size of the Metropolis method taking into consideration the state exchange rate and the acceptance rate.

4.1. Generation of synthetic data

(i) Set the number of data points to N = 400 and define the scattering vector magnitudes at N equally spaced points within the interval [0.1, 3] to obtain { q i } i =1 N =400 (nm −1 ).

In this section, we consider cases with pseudo-measurement times of T = 1 and T = 0.1. Generally, smaller values of T indicate greater effects from measurement noise.

4.2. Setting the prior distributions

In the Bayesian model selection framework, prior knowledge concerning the parameters Ξ and the model-characterizing parameter K is set as their prior distributions.

In this numerical experiment, the prior distributions for the parameters Ξ were set as Gamma distributions based on the pseudo-measurement time T used during data generation, while the prior for K was a discrete uniform distribution over the interval [1, 4].


Plots of the prior distributions for various parameters. ( ) Prior distribution of , φ( ). ( ) Prior distribution of ) Prior distribution of , φ( ). ( ) Prior distribution of , φ( ).

4.3. Results for two-component monodisperse spheres based on scale ratio

The ratio of the scale parameters S 1 and S 2 for spheres 1 and 2 during data generation, denoted r S , is defined as


Parameter values used for data generation with varying

  Sphere 1 Sphere 2
Radius (nm) 2 10
Scale 250 {250, 100, 20, 0.5, 0.1, 0.05}
Background (cm ) 0.01
Pseudo-measurement time {1, 0.1}

Fitting to synthetic data generated at various values and residual plots. Panels and show cases for pseudo-measurement times of = 1 and = 0.1, respectively. In plots ( )–( ) and ( )–( ), the scale ratio is displayed in descending order for = 1 and = 0.1, respectively. Black circles represent the generated data and the black dotted lines indicate the true scattering intensity curves. For models = 1, = 2, = 3 and = 4, the fitting curves and residual plots are represented by blue dashed–dotted lines, red dashed lines, orange solid lines and green dotted lines, respectively. Fitting curves were plotted using 1000 parameter samples that were randomly selected from the posterior probability distributions for each model. The width of the distribution of these fitting curves reflects the confidence level at each point.

Results of Bayesian model selection among models = 1–4 for varying values. Panel shows the posterior probability for each model using data generated with a pseudo-measurement time of = 1, and panel shows results for = 0.1. In cases ( )–( ) and ( )–( ), the scale ratio is displayed in descending order for = 1 and = 0.1, respectively. The height of each bar corresponds to the average values calculated for ten data sets generated with different random seeds, with maximum and minimum values shown as error bars. Areas highlighted in red indicate cases where, on average, the highest probability was found for the true model with = 2, while blue backgrounds indicate that models other than = 2 were associated with the highest probability on average.


The number of times each model was associated with the highest probability in numerical experiments for ten data sets generated with different random seeds at each value

) = 1

 
1 2 3 4
( ) 1.0 0 0 0
( ) 0.4 0 0 0
( ) 0.08 0 0 0
( ) 0.002 0 0 0
( ) 0.0004 0 0 0
( ) 0.0002 2 0 0
) = 0.1

 
1 2 3 4
( ) 1.0 0 0 0
( ) 0.4 0 0 0
( ) 0.08 0 0 0
( ) 0.002 0 0 0
( ) 0.0004 1 0 0
( ) 0.0002 0 0 0

4.4. Results for two-component monodisperse spheres based on radius ratio

During synthetic data generation, the ratio of the radii R 1 and R 2 of spheres 1 and 2, denoted r R , was defined as

In this setup, we generated seven types of data by varying the value of r R for pseudo-measurement times of T = 1 and T  = 0.1.


Parameter values used for data generation when varying

  Sphere 1 Sphere 2
Radius (nm) {9.9, 9.7, 9.5, 0.5, 0.5, 0.4, 0.3} 10
Scale 250 100
Background (cm ) 0.01  
Pseudo-measurement time {1, 0.1}  

Fitting to synthetic data generated at various values and residual plots. Panels and show cases for pseudo-measurement times of = 1 and = 0.1, respectively. In plots ( )–( ) and ( )–( ), the radius ratio is displayed in descending order for = 1 and = 0.1, respectively. Black circles represent the generated data and the black dotted lines indicate the true scattering intensity curves. For models = 1, = 2, = 3 and = 4, the fitting curves and residual plots are represented by blue dashed–dotted lines, red dashed lines, orange solid lines and green dotted lines, respectively. Fitting curves were plotted using 1000 parameter samples that were randomly selected from the posterior probability distributions for each model. The width of the distribution of these fitting curves reflects the confidence level at each point.

Results of Bayesian model selection among models = 1–4 for varying values. Panel shows the posterior probability of each model using data generated with a pseudo-measurement time of = 1, and panel shows results for = 0.1. In cases ( )–( ) and ( )–( ), the radius ratio is displayed in descending order for = 1 and = 0.1, respectively. The height of each bar corresponds to the average values calculated for ten data sets generated with different random seeds, with the maximum and minimum values shown as error bars. Areas highlighted in red indicate cases where the true model = 2 was most highly supported, while the blue backgrounds indicate that the likelihood of a model other than = 2 was the highest.


The number of times each model was most highly supported in numerical experiments for ten data sets generated by varying values

) = 1

 
1 2 3 4
( ) 0.99 1 0 0
( ) 0.97 0 0 0
( ) 0.95 0 0 0
( ) 0.5 0 0 0
( ) 0.05 0 0 0
( ) 0.04 1 0 0
( ) 0.03 0 0 0
) = 0.1

 
1 2 3 4
( ) 0.99 0 0 0
( ) 0.97 2 0 0
( ) 0.95 0 0 0
( ) 0.5 0 0 0
( ) 0.05 1 0 0
( ) 0.04 3 0 0
( ) 0.03 0 0 0

5.1. Limitations of the proposed method

5.2. model selection based on χ -squared error.

In SAS data analysis, selecting an appropriate mathematical model for the analysis is a crucial but challenging process. In this subsection, we compare the conventional model selection method based on the χ -squared error with the results of model selection using our proposed method.


The fitting results and residual plots for the data shown in Fig. 3 ( ) were derived using parameters that minimize the χ-squared error from the posterior probability distributions for models ranging from = 1 to = 4. For each of these models, the fitting curves and their corresponding residual plots are represented by blue dashed–dotted lines, red dashed lines, orange solid lines and green dotted lines, respectively. The legend indicates the reduced χ-squared values for each model ( = 1 to = 4).


Model selection results based on reduced χ-squared values

-squared value to 1 for ten data sets generated with different random seeds for each setting = 1. Labels ( ) to ( ) refer to the settings in Figs. 3–4 and Table 2. The cases with the highest level of support for each data set are shown in bold.

 
1 2 3 4
( ) 1.0 0 2 0\sim
( ) 0.4 0 0 1
( ) 0.08 0 0 1
( ) 0.002 0 0 0
( ) 0.0004 0 4 1
( ) 0.0002 0 2 0

In this paper, we have introduced a Bayesian model selection framework for SAS data analysis that quantitatively evaluates model validity through posterior probabilities. We have conducted numerical experiments using synthetic data for a two-component system of monodisperse spheres to assess the performance of the proposed method.

We have identified the analytical limits of the proposed method, under the settings of this study, with respect to the scale and radius ratios of two-component spherical particles, and compared the performance of traditional model selection methods based on the reduced χ -squared.

The numerical experiments and subsequent discussion reveal the range of parameters that can be analyzed using the proposed method. Within that range, our method provides stable and highly accurate model selection, even for data with significant noise or in situations in which qualitative model determination is challenging. In comparison with the traditional method of selecting models based on fitting curves and data residuals, it was found that the proposed method offers greater accuracy and stability.

SAS is used to study specimens with a variety of structures other than spheres, including cylinders, core–shell structures, lamellae and more. The proposed method should be applied to other sample models to determine the feasibility of expanding the analysis beyond the case examined here to broader experimental settings. Future work could benefit from using the proposed method to conduct real data analysis, which is expected to yield new insights through our more efficient analysis approach.

Funding information

This work was supported by JST CREST (grant Nos. PMJCR1761 and JPMJCR1861) from the Japan Science and Technology Agency (JST) and by a JSPS KAKENHI Grant-in-Aid for Scientific Research (A) (grant No. 23H00486).

This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) Licence , which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.

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