Speaker 1: So, to do qualitative research, you need to take five steps and I'm going to walk you through each of those today. Number one, define your research question. Number two, identify the appropriate research method to answer that question. Number three, collect data. Number four, analyze the data. And number five, communicate, so write up or present your research findings. In this video, I'm going to walk you through each of these steps in a little bit more detail. Now, obviously, we're not going to get into absolutely everything, but you are at least going to feel comfortable with the ideas that underpin qualitative research. So let's get going. So the starting point in this video is that I'm assuming that people have a general understanding of what qualitative research is. But just in case you're watching this and you're not sure, let me give you a quick overview. Qualitative research, as distinct from quantitative research, looks for meaning in the world around us using non-numeric data. In other words, it's not using numbers. It's using other kinds of data, like speaking to people, getting people's opinions, getting to know what people think, for example. Okay, let me illustrate that. If I were to count up the number of patients that I have in one of the wards in a hospital, that number would be quantitative research. That number would be quantitative research. That number would be quantitative research. Right? We've counted it up. It's a quantity. If, however, I was interested in how those patients felt about their treatment, there's not a number there. I need to speak to them. I need to extract a different kind of data from them, and that is what we call qualitative research. And that is what we call qualitative research. Got it? Okay, let's keep going. So let's get into these five stages, or these five components of your qualitative research project. Now, let me just say this. I'm only going to get into the very basics of each of these stages right now. If you want to know more, go to my website, learnmore365.com, and there's a course there that will tell you a lot more, a lot more detail about each of these five stages. Now, the first thing you want to do is you want to generate a well-developed research question. Your starting point for generating a research question is some sort of interest, right? You're interested in, for example, mental health. Fantastic. Now you want to start adding details, and you want to be as precise as possible, and you want to start adding parameters around that interest so that somebody else reading your research question knows exactly what it is that you're trying to understand. Let me give you an example. You might want to understand the use of alcohol as a coping mechanism among small business owners in London during the COVID-19 pandemic. Now we've got a much clearer, objectable question. If you're not sure if you've got a good research question, look at the literature. Who's been writing? Who's been studying in this area? What questions did they ask? Look at the literature. Look at the literature. Has this question been asked before? Okay, so get the question right. Let's move on. Next, we're going to talk about methods, or what some people call methodology. Now, you've got to get this right for a few reasons. First of all, if you don't get the methods right, your actual research won't produce meaningful results. Right? Your results won't be valid or reliable. Secondly, you need to be able to describe your methods well so that other people, people reading your research, will understand how it is that you got to where you got. Your research should be replicatable, and of course, people need to understand that what you've done follows a scientific method. So there's three aspects to methods that we're going to talk about, and I'm not going to get into a lot of detail on all of them, but I want to give you this kind of synopsis. First of all, there are different kinds of research. Secondly, there are different ways that data can be collected, and then thirdly, there are different ways that data can be analyzed. Right, so let's talk about all three buckets. Firstly, types of qualitative research. Now, there are many, many types of qualitative research. We can't get into all of them in this video. The four main types, the four most commonly used types of research are case studies, ethnography, phenomenology, and grounded theory, and we're going to talk about each of these quickly. Case studies look at a single example of something in a lot of detail. So a case study might explore a process, or an event, or an individual, or an experience, but the point is it goes into a lot of detail for that single entity. So for example, you might do a case study into how a specific or particular hospital dealt with the COVID-19 pandemic. Next, ethnography. Ethnography studies people in their own setting, or sometimes people say in their natural setting, and it studies them over a period of time. So for example, you might want to look at healthcare workers in a hospital setting during the COVID-19 pandemic. Ethnography explores the human experience around a particular phenomenon, and that phenomenon could be an object, an experience, an event, or an idea. So for example, you might want to explore how patients experience and understand the care that they're given while they're in a hospital. And the last one I want to talk about is grounded theory. Now grounded theory is a little bit different in that the output of your research is a theory, is a generalizable or abstract theory about how the world works, and that theory as to how the world works is meant to be grounded in your data, usually the opinions and thoughts of your research subjects. So for example, you might want to interview people to get a general theory as to how it is that people react in a crisis. Right, let's talk about data, right? Three kinds of data or three sources of data, it's going to be something you hear, so it could be an interview, right, or a focus group. It could be something you see, so observational data, or it could be something you read, so content analysis or document analysis. Those are our three main sources of data in qualitative research. Interviews are conversations that we have with one or more of our participants, and we explore their thoughts, their feelings, their opinions about a particular phenomenon. Now usually when we do an interview, we record that interview, so we have an audio recording of that interview, and then we'll transcribe it so that we've got a written transcript that we can use for our analysis. We're going to talk more about that in just a minute. Interviews can be structured, semi-structured, or unstructured, and what we mean by that is the extent to which the interview follows a very prescribed order, a very predefined set of questions, and for some qualitative research, that's appropriate. Most of the time, however, most of the qualitative research that I've done is you allow the interview to take on a little bit of a life of its own within certain parameters. In other words, we want it to go in a certain direction, we've got certain big themes and headings that we want to cover, but we're not going to prescribe every single second of the interview and tell the person what questions to answer. We allow them to guide a little bit of how things unfold. Does that make sense? Focus groups are very much like interviews, but now you've got more than one person in the room. Now, the nice thing about focus groups is it allows people to interact with each other, so you can have a really rich source of ideas, you can have ideas develop, unfold, change, merge, it's all quite interesting. The whole thing is moderated by the researcher, and again, it could be structured, semi-structured, or unstructured. The next type of data is observations, or observational data. This is where we observe people directly, and the researcher would then take field notes or have some other way of recording what it is that they've observed. With this kind of research, with observations, the researcher, him or herself, may be a participant in the activity that's being observed, but they don't need to be. And the subjects may or may not know that they're being observed. And finally, document or content analysis, this is any recorded communication that can be analysed. Now, you might have more than one source of data, and believe me, that's not a bad thing. Very often, that's a very good thing. In other words, you, for example, might be looking at documents, be doing content analysis on documents, and you get a lot of facts and figures straight out of the documents. You complement that with interview data, right? You speak to people, you get their thoughts, their opinions, their insights into these facts and figures. Can you see how different methods can be mixed together, different sources of data can be thrown into the pot? You can even add in a bit of numbers, get some quantitative research in there. The point is, what you need to do is make sure that you're very transparent about your methodology, about the methods that you use. Make sure that a person reading your research understands how it is that you got there and why it is that you chose the sources of data that you did. Now, let's talk about collecting the data itself. The first thing that you want to get right is you want to select the right participants, right? You want to get the right people into the study. You want to get people with a perspective, with the opinions, with the thoughts, with the knowledge, with the insights that are going to give you a rich understanding of the phenomenon that you're studying. Of course, you want to get consent from the participants or in the case of document analysis and content analysis, you might want to get permission to use and analyze those documents. If you're going to be doing an interview or you're going to be doing focus groups, you might want to develop an interview guide. This is basically a document that outlines the general themes that you're going to explore and sometimes, depending on the kind of research that you're going to be doing, it might actually delineate what the actual questions are that you're going to ask. Now, as well as the information that you're going to extract from the participants with respect to their thoughts and feelings, etc., etc., about the phenomenon that you're studying, you might want additional information about them. In other words, you might want to, in your study, be able to say, we spoke to people within this age group and they were mostly males or mostly females or they were people from South Africa or these were people from Europe. There might be metadata about them that you want to identify as important that'll give context to the answers that they give. You also want to understand and describe the cohort of people who decided not to or declined to participate in your study. That might be important. There might be some sort of systematic difference between the people that did and the people that did not participate in your study and that's important in terms of interpreting the results that you get and the information and the data that you extract from the interviews or from the focus groups that you undertook. Then from a practical point of view, you want to find a time that works for them, a time that works for you so nobody feels rushed during this interview or during the focus group. You want to find a place or a venue that's quiet, that there's not going to be interruptions or distractions and you want to make sure that your recording device, if you're going to record the interviews, is ready and working and you've tested it and then you're good to go. Now let's talk about the analysis. The first step with the analysis is you want to prepare your data. Very often that'll involve, for example, you take your recordings, your recorded interviews or your recorded focus groups and you transcribe them. You want to get all of that transcribed and then quite often we'll take those transcripts and it'll be in electronic form and we'll upload them into software that helps us do the thematic analysis. Now, you don't have to do that. People sometimes just do it in Microsoft Excel. Some people just do it old school with paper and pen and highlighters on a desk. There's nothing wrong with that. There's no rules. The most important thing is that you're transparent about the method that you used and how it is that you got to the conclusions that you draw from the data that you've got. Once your data is prepared, a popular method of analyzing qualitative data is something that we call thematic analysis. So the first thing we do with thematic analysis is we code our data and I'm not going to get into the details of how to do this, but very briefly what it means is you're reading through your data, you read it again and again and again and again, you identify meanings that are common in different places and you apply labels or codes to that bit of text. So the same idea starts emerging in different places and we start seeing that. And the same bit of text may have more than one code applied to it, right? Once we've done that, once we've coded the data, we then extract all of the data that has the same code and we look at it separately and we start seeing different themes emerging. Now depending on the kind of research you're doing, your starting point even before you start looking at the data might be that you've got a set of codes and a set of themes that you're going to use and when you look at the data, you basically want to stick the right ideas into the right buckets or you might have those codes and those themes emerge from the data itself, right? So both methods are absolutely valid. Once you've analyzed your data, you want to communicate your findings either in a presentation or quite commonly you want to write a paper. Depending on the discipline within which you might find yourself, there may be different styles and formats that papers written in that discipline follow. I'm going to talk you through how a typical medical paper is written in the sort of medical sciences but the principles apply and I'm sure what it is that I'm going to say is more or less applicable no matter what discipline you're from. The first part of your paper is the introduction and background. This is where you talk about your question. Why is this an important question? What do we already know? What's in the literature? What are the gaps in the literature? And how will it be that by answering the question you're asking, those gaps will be filled? Next is going to be your method section. Now in the method section, you're going to describe in detail what it is that you did, how you identified people, how you collected your data, where did you keep your data, how did you analyze the data, etc, etc. Not only what you did but why you did it, what was the rationale, why did you do it this way instead of that way so that a person reading the paper understands your thought process completely. And your method section needs to describe how it is that you ensured scientific integrity, how it is that you ensured the validity and the reliability of your results. Next the result section. Now in as much as possible, keep the result section about your results, the data that you collected, the output of your analysis. Don't make the result section about what other people said in other research and interpreting your results and extrapolating, etc, etc. All of that can come into the discussion. Now the discussion section. Now this is where things really get interesting. First of all, in your discussion, you want to make sure that you address the fact that your results have addressed your original research question. So reiterate your research question. This is what we asked. This is what we found. This is how that answer relates to the question firstly. Secondly, address how it is that your results relate to the gaps in knowledge that you found in the literature. So when you looked at the literature, this is what the literature didn't address. This was the gap in knowledge that I identified and that's now been filled by the results that I've identified, by the outcomes of this piece of research. You can also talk about the extent to which what it is that you found is consistent or maybe at odds with other findings in the literature. So that's a great thing to bring into your discussion. The discussion is also a great place for you to interpret your results a little bit, speculate, extrapolate, talk about where the research might be going, what additional questions should be asked, what additional research could be done because of what it is that you've found and of course, importantly, also talk about the limitations of your study. And the conclusion section is usually short and punchy. What can we conclude? What are our actual take-home messages? What do we know now that we didn't know before? And importantly, what are the practical implications of your findings? If you want to learn more about qualitative research, then go to learnmore365.com. I've got a few courses there on research methods. I hope you enjoy. Take care. Please hang up and try again.