**What is Grounded Theory, Anyway? An overview with examples from qualitative research on women Veterans**

>>Looks like we are just about at the top of the hour here.  I’m just going to take a moment to introduce our presenter today.  Dr. Alison Hamilton is a psychiatric anthropologist and research health scientist at the VA Greater Los Angeles Center of Excellence for the Study of Healthcare Provider behavior and the Desert Pacific MIRECC.  Affiliated with the GLA for over 9 years, Dr. Hamilton conducts implementation research, specializing in qualitative methods.  Currently Dr. Hamilton is PI of the SAMHSA funded evaluation of New Directions, the supportive employment program for homeless veterans, co-investigator on the HSR&D funded study of adoption and delivery of genomic medicine, and lead of the VISN 22 PACT demonstration lab’s implementation evaluation.  She’s also an investigator with the QUERI center for implementation practice and research support, and the HSR&D women’s health research consortium.  Under the auspiciousness of an NIMH VA QUERI Implementation Research Institute fellowship, Dr. Hamilton is studying services for co-occurring mental health conditions among women veterans.  She is also an associate research anthropologist in the UCLA Department of Psychiatry.  Dr. Hamilton, I would like to turn things over to you.

>>Thank you so much, Heidi.  And thank you everyone for joining this afternoon, or of course this morning for those of you on the west coast.  

The impetus behind this session came from exactly the question that’s posed in the title of the seminar, which is a question that I have often gotten.  What is Grounded Theory anyway?  I hope that after today’s session you will have more of an understanding of what grounded theory is, if you don’t already have that understanding. 

We will start with a couple of quick polls just to get a sense of who is joining us on the call today. The first one is, do you conduct qualitative research or plan to conduct qualitative research in the future? If you could just indicate whether you do it now, plan to do it, or do not do it at all. Looks like most of you so far do conduct qualitative research. Give that a minute to fill in. OK, great.  Thank you everyone, looks like about half of you so far do conduct qualitative research and about a third do not. So I hope all of you find this of interest. 

Our second poll is, are you familiar with grounded theory? So, very familiar?  Somewhat?  Maybe you’ve heard of it.  Or maybe you’re not familiar with it at all.  Okay so it looks like most people are falling into the “heard of it” or “are not familiar with it” territory so that is good for the purposes of this cyber seminar. 

I am going to get started in the presentation.  I just want to start with some quick thank yous, first of all to the HSR&D Women’s Health Research Consortium for sponsoring this cyber seminar.  Also to my colleagues Barbara Bokhour and Susan Zickmund for their ongoing collaboration.  And to several colleagues at the HSR&D center of excellence for providing their valuable feedback on an earlier version of this presentation.    Thank you to all the folks named there.

So what I’m going to do today is to provide a brief history on grounded theory and I'm going to go over some basic premises and key components, and then talk about approaching data analysis with grounded theory, discuss briefly when grounded theory may or may not be appropriate, and briefly talk about other approaches besides grounded theory. Then I will provide 2 examples of qualitative studies that use grounded theory, with both of these studies having a focus on women veterans.  I will make some suggestions for working with qualitative data and wrap up with just briefly discussing the importance of qualitative research in health services research on women veterans and then take your questions and comments. 

I thought I might start with talking about what grounded theory is not, rather than what it is.  So just to start, as many of you may know grounded theory is not defined in only one way by only one or two people.  So you may be familiar with Glaser and Strauss, who I’ll discuss in a minute, but there are many others who have defined and utilized grounded theory, in a number of different ways.  Grounded theory is also not only about data analysis.  It’s actually a method within research that you may use for your data analysis but that you may use for your entire research design. Grounded theory is also not the only way to approach qualitative data, there many other ways that you might approach your qualitative study and your qualitative data analysis, and I will mention some of these a little bit later. And finally grounded theory is not limited to qualitative research, so some grounded theory may incorporate findings and discoveries in quantitative research. 

So just to give a little bit of history and context for this, sorry about that, grounded theory was developed by two sociologists, Barney Glaser and Anselm Strauss.  The roots of grounded theory are in what’s called symbolic interactionism, which was coined by another sociologist named Herbert Blumer.  With the focus of symbolic interactionism is on how meaning is created during social interactions. Grounded theory actually originated in a constant comparison method which then became grounded theory with publication of the discovery of grounded theory in 1967 and it is important to note that grounded theory really developed at a time when qualitative research was seen as unscientific or non-systematic so much of grounded theory is in reaction to this perception and prevailing idea that qualitative research was not systematic, so is really an effort to systematize qualitative research and put in more within the scientific realm. Another important point about the development of grounded theory is that Glaser and Strauss came to disagree about grounded theory in several significant ways and I will come back to this point and its implications for the use of grounded theory.

Grounded theory has become the paradigm of choice in qualitative research, and there are several references to support that point. Why might that be the case? It offers a solution to what to do with what we might think of as a pile of non-numerical data. It provides a set of procedures and a means of generating theory.  So while there are many different theories of grounded theory, they all have rather concrete ideas about what one should do with non-numerical data and how one should handle the development of theory so it is a little bit of a hook to hang your hat on. When you’re faced with a problem with a considerable mound of data, that might be confusing or overwhelming at first. As I mentioned, Glaser and Strauss, while they are the pioneers of grounded theory, they are not the only ones who have worked on this concept. Kathy Charmaz has done quite a bit of work in grounded theory with an important book called Constructing Grounded Theory.  Corbin and Strauss have taken grounded theory in their own direction, with Corbin having been a student of Strauss's and they have written several books and articles about their own take on grounded theory.  There is actually an entire SAGE Handbook  devoted to grounded theory which is several hundred pages long.  And Adele Clark wrote a book about situational analysis which she calls a postmodern turn on grounded theory.  These are just a few of many different sources on grounded theory and different perspectives on grounded theory.  

Despite the fact that there are numerous theories and approaches to grounded theory I believe there are some fundamental premises of grounded theory that do cut across many of these different perspectives. So to get on to these basic premises of grounded theory, here are the most fundamental components of grounded theory.  Theory comes from data, so in other words, theory is “grounded” in the data instead of being imposed on the data, and I’ll come back to that.  In addition, within the grounded theory framework, everything related to the subject or study is data. So if you enter a study, all of your interactions, experiences related to that study would be considered data within the framework of that study.  Also in grounded theory one must approach data to find theory rather than approach data with a theory.  So the idea is that theory would emerge from the data and that you would not go in attempting to prove a theory, but rather to find a theory.  So in that sense your data might be moving toward a hypothesis, it might be hypothesis-generating, rather than starting with a hypothesis which you’re attempting to prove.  Grounded theory studies are typically trying to answer the question, “what is really going on, or what’s happening, and how is it happening?”  So if you stop this question at the “what’s really going on”, that’s limited to a description which is not really what’s at the core of grounded theory.  The “and how” or “and why” question that one might ask would be more consistent with the grounded theory approach, which is that you’re trying to explain what’s going on, not merely describe what’s going on.  And finally another very important core of grounded theory is that one would typically start data analysis very early on, in other words after the first data collection episode which might be an interview, a meeting, a participant observation encounter, that kind of thing.  So according to grounded theory there would be no break between data collection and analysis and your analysis in that iterative way would be informing your data collection all along the course of your study.

Excuse me.  Some other key components of grounded theory are these four aspects: fit, relevance, workability, and modifiability.  So in terms of fit, the question is do the concepts that you’re generating fit with what’s been described?  I’ve also heard this described as “fittingness”.  And the key is that it needs to be true to what participants have expressed in your data collection episodes.  Similarly to the findings and the theory potentially, they also need to have relevance.  So does the study and do the findings address something of concern to the people who are affected by the phenomenon that you’re studying?  So for theory, in terms of workability, explore how the phenomenon is being addressed/solved/managed or otherwise handled, so you’re always getting at the question of how or why.  And finally can the theory be modified upon the introduction of new data?  So if we stick with this idea that data collection and analysis is iterative and mutually informative, then theoretically, the theory that you’re developing would be modified as you go along because you’re constantly learning from the data you’re collecting and adding it to your analysis.

Now what I’m calling a hardcore grounded theory -- what might be sort of the old school grounded theory in Glaser’s terms not Strauss’s terms per se, would be an approach where one would ostensibly begin with no pre-existing knowledge about a topic.  So you would not conduct a literature review, for example, before going to conduct your study.  Some of you might be thinking, wow, we can’t do that in health services research because we have to know about our study in order to get it funded.  We have to have that literature review in our proposals in order to get it funded.  So this is not something that I’m ascribing or promoting within grounded theory but rather just pointing out these sort of early day or old school perspectives on grounded theory where the idea is really to exercise what the data was telling you rather than what you were bringing to the data.  Someone so far suggested that we shouldn’t even tape record or transcribe interviews, that that would somehow distance the researcher from the data that he or she was gathering.  And that there be no discussion of emergent theory with people outside of the project so the development of that theory wouldn’t be swayed or otherwise influenced by people who might have different perspectives, which again would take the theory away from the data itself.  Now most of these are not tenable in the types of work that we do in health services research, but it’s just important to think about those early roots and what was the thought behind these roots which was to stick to the data and not move away from the data into other peoples’ concepts or ideas. 

So just to talk briefly about approaching analysis with grounded theory. Again, many different ideas and approaches to how to apply grounded theory to data analysis.  So I’m going to be putting some ideas up here but I do want to emphasize that there are many many different perspectives on this and we could look at any number of those authors I mentioned earlier, they have different ideas about how to do this and what these concepts mean.  So I’m going with sort of a general presentation of what some of the key concepts are in many of the different functions of grounded theory.  So there is this idea of “open coding” or “substantive coding”.  With open coding one would generally take an inductive approach to the data.  Take a data set and identify the substance of the data.  So we’re looking at what is the data telling you and then applying code accordingly.  This can be done at a local level, for example line-by-line coding, which at least in my work in health services research in VA, is too time-consuming and I actually can accomplish that with micro-level coding which leads to a better perspective on the data which I’ll get back to in a minute.  The idea behind codes is that they’re identifying these key points in the data and when you move on toward your analysis and your theory you would probably be engaged in the process of combining your codes to generate concepts.  But again because of the iterative nature of data collection and analysis, your codes are most likely going to change over time, and accordingly concepts will change over time.  And the key to these changes and this evolution of the analytic process is what’s called constant comparison.  It’s not only a comparison across your codes and within your dataset but across your data sources.  So you’re constantly comparing ideas that are raised by different people possibly or maybe in different focus groups, maybe in different meetings or settings and seeing what’s the range of possibility within these different ideas and then how can you capture that to then feed into a theory that explains why a phenomenon is operating or functioning or happening as it is.

This is a depiction from a recent article of the process that I’ve just explained.  So let me see if I can get my pointer to work here.  So you can see here that your research question and you begin the data collection process and immediately you’re moving up into this analysis process.  And going in a cyclical approach to collecting and analyzing your data.  With very early on, your initial analysis feeding into the development of grounded theory.  So you’ll see this particular depiction has sort of that old school perspective that your literature review wouldn’t happen until your grounded theory has emerged from your empirical data.  So at least in my experience I’ve found that this literature review has to happen back here, as much as there be some merit to having it over here, we just don’t typically have that luxury.  And moreover we tend to enter projects and start projects already having an idea of why we’re doing them, what we’re interested in, and what we need to find out.

Other concepts that you may have heard of in grounded theory that you may utilize in your own work in analyzing data, are axial coding and selective coding.  So axial coding was proposed by Strauss and Corbin in 1990 and it basically means that you’re creating axes across your codes, potentially across your categories and concepts. So if you can think of lines connecting different codes, that’s really the fundamental nature of axial coding where you want to be able to combine your data and put it back together so when you’re coding and pulling apart a piece of the data as part of this process of the drilling the data to find your themes and your concepts but then there needs to be some effort to put it back together and that’s where axial coding comes in.  Selective coding typically happens after open coding.  So you identify a theme or concept you want to pursue, you might then want to focus on that concept and revisit the data with that concept in mind and do additional selective coding.  You also may decide you need to revisit a subset of your data that pertains to that concept and that might move you toward some theoretical sampling.  It may be that you actually need to collect additional data to support the theory that you’re developing, and that too would fall within the realm of theoretical sampling.

One of the most important aspects of grounded theory, and I would argue one of the most important aspects of iterative and qualitative data with any given approach, is the writing of memos.  And I should add that pretty much all qualitative data analysis software packages that I’m aware of have some mechanism for writing memos.  It may not be called memos, but it’s some space that is separate from the data you collected where you’re going to document what you’re observing in your data.  So what happens with memos, is writing about what’s being observed in the data.  You may be keeping track of ideas, relationships between codes, emergent concepts.  You might be developing your theory within the body of the memo. The idea is generally speaking with a memo, is that there are no rules about how a memo should look. So if there is a rule it’s that there are no rules.  But memos should be free flowing, stream of consciousness if that’s the way you like to write and think, and most importantly the memo should be constant throughout your analysis.  So you’re constantly reflecting on what are you thinking, what are you seeing, what doesn’t make sense to you, what might make sense, you might be reminded of something from another project or another aspect of your data collection, all of these sort of potentially random or serendipitous stuff should be recorded in memos in whatever way makes sense for you in your own style.  The other important part of memos is that you might engage in reflecting on your own role in the research. So this reflectivity is another part of grounded theory and many other approaches to qualitative research, where you want to take account of what you’re doing to the picture and your table.  What’s your background?  What’s your perspective?  And things happen during data collection episodes.  Everyone brings something different to the table. And you might write about what your experiences were in the data collection episode and when you’re actually analyzing the data.

So I’m just going to talk for a minute about where grounded theory might be appropriate and might not be appropriate.  So just to reiterate this point, grounded theory is often an appropriate approach to choose when the goal of your study is to generate concepts that explain a given phenomenon.  So to answer why or how something is happening, not just what is happening.  And also grounded theory might be appropriate of course if that is the research design approach that you have taken, and your data that you selected lends itself to the development of theory.  So not only is your design might be a grounded theory design, and that goes back to the point I was making earlier about how grounded theory is not limited to analysis, it’s actually an entire method, that we might compare to something like ethnography.  Grounded theory is a method just like ethnography is a method within qualitative research.

Some places it might not be appropriate ... when straight description of a phenomenon is the goal.  So you’re not looking at why, but what.  There is not really a need to get into grounded theory if what you want to do is describe, which is a perfectly legitimate goal within qualitative research, but grounded theory might not be the approach that you would need for a straight description.  Also when theory is not the goal of the project.  If you’re not trying to generate a new theory, then using an approach that’s all about generating theory probably would not be warranted.  And finally, when the project was not initially set up to explore a given phenomenon.  But I put “sometimes” there because as many of you may have found in the course of doing qualitative research, sometimes we end up with things that we don’t expect.  So you may not have set out to develop a theory or even collect data that would lend itself to a theory, but your data may end up being so rich that you find that actually you do want to use grounded theory to analyze your data.  So there’s a caveat there that you might end up with data that would work really well with the grounded theory approach.

So what else is there besides grounded theory?  I’ve mentioned before that grounded theory isn’t the only method to use.  So I’m just going to highlight a couple of different sources that present and compare different approaches.  So there is this recent book that just came out called Five Ways of Doing Qualitative Analysis, and the five ways that the book discusses are phenomenal logical psychology, grounded theory, discourse analysis, narrative research, and intuitive inquiry. What is really interesting about this book is that the authors not only describe each of the approaches but then reflect on the other approaches and how their approach differs from and is consistent with the other approaches.  So it’s very informative in the sense that you are getting not only getting an understanding of each approach but then its relationship to these other approaches.  Then there is John Creswell’s book, Qualitative Inquiry and Research Design and in that book he’s talking about five approaches which to some extent differ from the five approaches in this more recent book. So the five he addresses are narrative, phenomenology, grounded theory, ethnography, and case studies.  So his look at ethnography and case studies is different than the book I was talking about before but again he does a really fantastic job of explaining each of these approaches and comparing them to one another. 

Then there a really interesting article in qualitative health research called Choose Your Method: A Comparison of Phenomenology, Discourse Analysis, and Grounded Theory. Incidentally with the exception of the book the articles that I'm referring to are all listed at the end of his presentation in the reference list you'll be able to find them. This article, in qualitative health research, looks at phenomenology, discourse analysis and grounded theory.  Just briefly, the goal of phenomenology would be to study how people make meaning of their lived experience.  Phenomenology is a really useful approach when you have unstructured qualitative data or very minimally structured qualitative data. So you're going in with a very exploratory approach where maybe you’re asking people to tell you their life histories.  So then you really want to understand the meaning behind their lived experiences and phenomenology is an excellent approach in that case. Discourse analysis, the goal is to examine how language is used to accomplish personal, social and political projects. There is a very detailed examination of the deployment of language and it also potentially a very fruitful approach in much of the health services research we do where language and people's ways of constructing reality become very important. And finally grounded theory which I’ve already been talking about.  I just wanted to add the point that the author’s make in this article, a point that they pull from Strauss and Corbin, which is that grounded theory examines the “six C’s” of social processes: causes, context, contingencies, consequences, covariances, and conditions. Looking at all those aspects of social processes in order to understand patterns and relationships and to develop theory.

What is really nice about this paper is that they take all through the methods and apply them to a single data set which may sound somewhat similar to some of the work that maybe you do.  So they had this interview study, data from an interview study, with 25 primary care physicians that explored their use of informed decision making in the context of prostate cancer screening.  So this sounds like a study that might take place in the VA, but it’s really interesting to take a look at what happened in their analysis, applying each of these three approaches.  The same data sets but three different approaches resulting in different ways of looking at what they heard about in those interviews. Their conclusion is that when iterative approach shapes research questions but also how are you paying attention to the data and your conclusions and I would add, your product. So you might think well, it would be a discourse analysis might produce a different type of product for a different type of audience than a grounded theory study would produce.  So especially in the VA where we have multiple audiences and multiple stakeholders, it’s very important to think about which method is going to lend itself to the type of product you are expected to have at the end of your project. 

Just briefly I want to get into one important aspect of qualitative data analysis and this is the area of establishing trustworthiness.  This issue was really put forward most strongly by Lincoln and Guba in Naturalistic Inquiry.  They propose that in qualitative research we use a constructive approach to qualitative research instead of a positivist approach.  So this goes back to the idea of not using qualitative research to prove something but to demonstrate something and to shed light on a phenomenon that perhaps other methods can’t do as well as qualitative research.  So what you see in the brackets here are the positivist area on these other ideas.  So within the trustworthiness framework of Lincoln and Guba, they discuss credibility, transferability, dependability, and confirmability.  It is a little bit beyond the scope of what I’m doing today to get into each of these but you may have heard of them and I can provide more detail if you're interested in another seminar or something.  But the idea here is that you might engage in something called member checking where you are checking back with your participants to see if the findings you generated make sense to them, going back to that point of relevance in grounded theory.  That you want to see, is what I'm saying about this data even real for the people who gave me the data. You also would want to keep an audit trail which is a very clear and transparent documentation of the steps that you took in your analysis.  So that anyone can look at what you did in the analysis and understand what you did, not necessarily agree with it, but at least understand the steps that you took and why they should believe or trust the story that you’re telling at the end of your study.

So now I want to talk briefly about two studies that used a grounded theory approach.  The first was a study that I conducted with colleagues and we were looking at pathways to homelessness among women veterans.  This is a paper that’s going to be coming out in a special issue of Women’s Health Issues.  So Dr. Washington had conducted a survey to understand risk factors for homelessness among women veterans and the study was very successful in identifying numerous risk factors for homelessness but what a survey cannot really unearth is how the risk factors work in combination with one another. So then three focus groups were conducted to understand how these risk factors that were identified in the survey actually worked together to produce these pathways towards homelessness among women veterans.  A semi-structured interview guide was used.  So this paper will look specifically at women’s descriptions of how they became homeless, or their entry into homelessness. And we used a constant comparison approach which I will describe in a minute. Why did we use this approach?  Because we were explicitly interested in developing a theory about how women veterans become homeless in order to identify critical junctures for intervention and prevention. So we were definitely interested in theorizing about pathways to homelessness. Already one divergence from grounded theory in this study, however, was that the data was analyzed after the focus groups were conducted.  I actually didn’t conduct them, I analyzed them so there wasn't that completely iterative process although within the analysis we try to achieve the iterative nature of analysis as much as possible.

So I started in the analysis by a description of the constant comparison method in a Glaser article from the mid 60s which provides pretty concrete guidance for deploying the constant comparison method. So there are basically four iterative stages, the first being that one would compare what are called “incidents”. These might be thought of as discrete narratives of experiences. For example each woman describes her experience of pre--- not each woman, some women describe their expense of pre-military homelessness.  So some women had unstable housing prior to entering the military or actual homelessness and each of these narratives was considered to be an incident and was coded. Women who talked about this, each narrative was compared to each other to really get a feel for what is this category of what we call pre-military adversity so wasn't only pre-military homelessness but also potentially abuse, and violence, and other negative experiences prior to entering the military which became this category of pre-military adversity. Which ended up being one of our primary roots of homelessness.  This category of pre-military adversity was one of several categories that we developed to understand that multiple pathways that women seem to be on toward homelessness and in the integration of these categories we were looking for the relationship.  So it might be that across several categories such as pre-military adversity and post-military adversity some women describe both of those types of experiences.  And so we wanted to see how these different risk factors and pathways were interacting with one another. We worked hard to delimit a theory for how these categories related to one another. We came up with five “roots” of homelessness.  So there were five main pathways and instigating sets of factors that seem to put women on a pathway towards homelessness. And ultimately we depicted this in a schematic which we refer to as a “web of vulnerability” which was a resulting theory we used in the paper to describe how women veterans came to be homeless with all the contextual factors kind of surrounding these roots.

Mattocks recently published a paper on Women Veterans’ Reproductive Health Preference and Experiences, also using focus group data.  So she conducted five focus groups again using a semi-structured interview guide and these concepts from grounded theory to analyze their data. So for example they used open coding where the coders work independently to review the transcripts and come up with their own open codes about what they were seeing in the data which then they compared across coders and resolved discrepancies all the while maintaining definitions of the code they were developing, refining those definitions and potentially changing them, and ultimately coming to a coding structure that includes 25 codes which is in general a very good ballpark for a coding structure with any given data set where you want to keep your codes to about 25 or 30 codes. Codes were combined using axial coding, which I mentioned earlier, into broader categories which, in this paper, became themes and authors recorded on five major themes across the focus groups and across the participants. So it is another good example of how one can use concepts from grounded theory to develop an understanding of what might be a very unknown are underexplored phenomenon such as women veterans reproductive health experiences.

I am just going to go over a few gentle suggestions for working with qualitative data in light of the information that I just provided. As I mentioned, there are several different approaches that one could take to a qualitative research study.  So it is important to consider which approach best suits the goals of the project and establish the research design accordingly. So what I would advocate is not deciding how to approach your qualitative data after you’ve already collected it.  It is important to think up front about what you're going to want to be able to do with it because that informs how you collect the data and from whom you collect the data. If you do plan to use grounded theory it is important to specify whose version of grounded theory and read the sources.  So don’t just cite the discovery of grounded theory from 1967 because it may not actually reflect the approach you're going to take.  So it’s important to read the sources of your grounded theory approach and make sure they are consistent with what you're proposing. If you plan to diverge from or modify your version of grounded theory, it is important to be explicit about the changes you made.  It is not a bad thing to modify the approach but it is important to say how you changed and why you changed it. And during your analysis, especially if it’s an  iterative analysis, it may be important to check back to your original grounded theory sources to make sure you’re still using the version of grounded theory that you had originally intended.  It might be important to consider using more than one analytic approach to your data, for example as they did in the paper described earlier where they applied three different approaches to the same data set so it might be important to think about the product that you're interested in and then choose your analytic approach accordingly, staying open to the idea that your data may lend itself to more than one analytic approach. And you may decide that you’re going to use methods or aspects of grounded theory that are consistent with the grounded theory approach but it may be that they’re not necessarily true to what I had earlier as far as hard-core grounded theory or a more strict approach to grounded theory. So there are many ideas inherent to grounded theory that may work very well for your project without having to do, for example, line by line coding.

And then in general this is not specific to grounded theory but worth noting.  Most of us do work in teams in our health services research, and potentially if you have a team working on a qualitative analysis, it is important to make sure that everyone on the analytic team has a shared understanding of the analytic process. Of the sources, if you're taking a grounded theory approach, everyone is familiar with what that approach is, what the components of that approach are, and how to use those approaches. As I mentioned before, documenting and memos is absolutely critical to an analysis and it is important to document your own analytic process and your team’s analytic process. So if you have team meetings where you're looking at qualitative data together, documenting what happened in that meeting, decisions that are made, problems that arise, is all very important for keeping that audit trail that Lincoln and Guba described.  And finally in your manuscripts, it is important to spell out the process that you used in a way that non-qualitative audiences will understand.  So it’s coming back to that Lincoln and Guba idea of trustworthiness, so that you’re striving for transparency.  You want people to believe in the story that you are telling based on your qualitative study.  And for them to believe it they have to understand, I would argue, what steps you took to produce the theory, for example, that you produced.  It needs to be believable, compelling, and people need to trust that you took the steps necessary to produce the ideas and theory that you perhaps have produced. 

So in closing I just want to talk for a minute about the importance of qualitative research in health services research on women veterans.  In the Bean-Mayberry systematic review of women veterans health services research found that most studies on women have been observational or descriptive.  So there is definitely a trend in women veterans health services research toward more implementation research which I believe will increasingly involve qualitative methods.  So for those of us who do qualitative research, I think there are more and more demand for the work that we do and therefore for rigor that should be associated with this approach to research. And furthermore with large scale VA initiatives such as PACT, a more in-depth understanding of women veterans’ healthcare preferences and experiences is needed. And qualitative research can contribute to the development of services that are attuned to womens’  preferences and needs. 

So as I mentioned, I do provide a very limited set of references here most of which I referred to in the talk today, with a couple of additional references. 

And here is my contact information, I also put at the bottom of the slide there is an excellent cyber seminar that was conducted by Dr. Susan Zickmund in June of 2010 on Coding Qualitative Data 101, I think is what it’s called.  So if you need more nuts and bolts of analyzing qualitative data I would strongly recommend checking out this cyber seminar from this past June. 

And now I'm happy to take questions and comments and I would also be particularly interested in whether anyone in the audience has an interest in learning about any of the other methods that I have mentioned so we can do another cyber seminar on a different method or approach in qualitative research and I would like to know if there is interest in another method: discourse analysis, or maybe content analysis, ethnography, or some combination of those.  I'm happy to field questions and comments. 

>> We actually just have one pending question / comment out here so I just want to invite our audience at this time to submit your questions using the Q&A screen in live meeting. You can open up your Q&A screen near the upper left-hand corner of your live meeting screen.  Click on that, it will open that screen right up.  Please do not raise your hand, I’m actually not able to call on people.  You will need to just type your question in. And the question I have here, somebody suggested, “I think we should coin a word for a woman veteran.  How about a word like weteran?”  [ Laughter ] 

>> Very interesting idea.

>> I completely understand, but...  [ Laughter ]  OK.  I have received a question here.  “I’m a P.I. who employs a qualitative researcher. She has told me about the analytic process but I’m having trouble understanding the process.  I only have enough money for her alone.  How can I help support her analysis?”

>> Well, I think there are a number of different ways that we can be creative about this, it is a great question I think it is a situation that often people find themselves in, in this day and age of limited funding and some smaller studies that thankfully do include qualitative research. So if the qualitative researcher is really strong in data analysis, one thing I have done in some studies and that I have recommended in others, is that the experts take a first pass at the data and meet very frequently with the P.I. to explain the steps that he or she has taken in looking at the data. So what I've done in some cases is develop a very preliminary code list and then go through the code list with the P.I. who may not be familiar with this approach or maybe even with the data and say, ok here are my open codes, for example. And that P.I. will have the opportunity to react to those, seeing if they are true to his or her understanding of the data or perhaps the issues and then the P.I. might want to see the content of those codes. So one approach would be to say OK well I want to understand more about these three codes, and let me see all of the data that was coded to these three codes. And then they could actually just read through the data so there are some technicalities of the data that the P.I. does not necessarily have to be involved in, but the substance of the process could be very much something that the P.I. engages in where it is really a process of reading what the data is. Now what that doesn’t allow for is the second pair of eyes on the data to ensure that the coding that the one person did, actually accurately captured all of the data that is relevant to a given code.  But there are limitations sometimes and that is just something to be acknowledged and documented, so the two people, the one more experienced person and the one less experienced person, might then talk through the data on those three or four codes and just talk to their observations, understandings, perceptions, and then the analyst might go back and look for the additional data on something.  They might go through the process of selective coding, where the P.I. says I am really interested in X, Y and Z aspects of those codes. Can you tell me more about those?  So the analyst could go back and look for additional data on those specific topics and engage in that constant back-and-forth with the P.I. on the content of those codes. So each step in the process where the analyst might get to the point of comparing the cross codes, maybe  doing some axial coding, if the person is using software, even if not, the ideal would be to continually share the data with the P.I. because that is really the important part of it is that there is some shared understanding and interpretation that is developed with the data with the technicalities of the analysis perhaps being less important if the resources are not there to house two or more people to collect the data.  So there are a lot of steps that can be taken without the P.I. or less experienced person being involved in the actual coding of the data. And the key is really just to make sure that P.I. is looking at the data with the analyst and helping the analyst to take particular approaches to the data based on a mutual understanding or perhaps even on some discrepancy where the analyst may identify something that the P.I. says, well I don’t really it that way.  And that may cause the analyst to go back through the data and consider an alternative perspective.  So there is a lot that can be done even when it is a team of two and one member of that team really doesn't know the nuts and bolts of qualitative data analysis, but it becomes even more important in that situation to document each step of the road and how these two individuals come up with the results and findings.

>> Great. Thank you. As we continue on with questions I'm actually going to bring our feedback form up for our attendees, so please take the time to fill these out.  We definitely take all of your comments under consideration in our current and upcoming sessions.  The next question that I have here is: “Do you have difficulty publishing health services research using GT approach in typical health service journals, for example HSR?  Maybe due to lack of knowledge among reviewers?”

>> I think it is changed a lot even in the last five or 10 years I think that there are more reviewers available who do have a good understanding of grounded theory, and other approaches to qualitative research, other methods. I think that one of the keys in publishing health services research is really thinking about the audience that would be tied into a particular journal, so I have found that depending on the Journal the reviews that I would get have different disciplinary perspectives and emphasize different aspects of what should be described in the data analysis section. So for example a nursing journal might expect different details in the data analysis section than a social work journal or an anthropological journal, for that matter.  So is really different, in my experience, really different disciplinary perspectives on what to highlight in your analysis.  And so I think that there is a certain amount of implements required when you're attempting to publish something or when you have papers that will set a number of different venues is you have to expect that the reviewers are going to have particular things that they want you to cover based on their own perspectives on what a qualitative data analysis endeavor would involve. So you may have to even reframe your description and -- if it is not too far afield from your original intent, you may have to reframe your description of your analysis to meet the particular needs of the reviewers, via their disciplinary perspectives and other expectations with regard to how your data analysis process should be described. So, I do not think that it is inherently difficult to get qualitative research published anymore and especially because it sort of emergence and implementation research, I think there is more and more attention to qualitative research and more and more onus on us as qualitative researchers to be really clear about what we’re doing with our data and why we have taken the steps we have taken. So if I was answering that question even five years ago I might have had a different answer more along the lines of, yes it is hard to get it published. Now I would say it’s not as hard to get published but it is not sort of a slamdunk, and certainly it’s not really working, at least in my experience of reviewing papers, to say we used grounded theory to analyze our data.  It can’t stop there.  Mmuch more description and explanation is needed to establish, again, that trustworthiness of the product. 

>> Great, thank you. The next question I have here is: “how would you compare writing fieldnotes to memoing?” 

>> This is just my take on it, so others might disagree or have other perspectives on this. I think of fieldnotes as an endeavor that occurs in the field so to speak. When you're actually collecting the data, I typically think of them as something that is done very proximal to the data collection episode.  Either it constitutes the data collection episode so if you’re conducting participant observation, for example, fieldnotes is what you would be doing while you're engaging in that particular method. Or if you maybe had done a series of interviews you might debrief with your colleagues afterwards or if you've done them alone take your own notes as close to that episode as possible to document what your experience and perceptions were. You may also take fieldnotes during meetings, if it is allowed according to parameters etc. Fieldnotes, in my experience and from my training, would occur pretty much simultaneous to or they would actually constitute the data collection episode. For me in my own work, memos are more activities that occurred during the course of data analysis, so they contain my reflections on the data that I am analyzing. So it is after the data collection episode when I am actually a little bit distant from that episode and working through the data and reflecting on the transcript. You could even, and I've done this many times, you would potentially write memos about your fieldnotes. So your fieldnotes become a source of data just like your interview transcripts and you would write memos that incorporate the experiences and reflections that you documented and your fieldnotes. You may find that you have memos on your fieldnotes as well as your interviews and your minutes and everything else that comprises your qualitative data.

>> Great. Thank you. Now Alison I do want to check with you, I don’t know if you spoke with Molly about this.  We do have quite a few questions here and we only have about five minutes left in our session. We are not going to get through all the questions. I am wondering do you have time to answer these questions off-line and I can forward our responses to the  attendees for the questions we do not get to? 

>> Absolutely. 

>> Ok.  Fantastic.  We’ll get through what we can here and I will forward to you what we have remaining.  The next question I have here: “Are you using the term theory synonymously with the term explanation? Meaning, are you not creating theory in the sense of developing, for instance, something like the health belief model?”

>> I think that is a really good question. I think that there are different perspectives on what theory means and there could be a very project specific or study specific theory that not reach the heights of something widely accepted like the health belief model which has been studied and tested and validated in numerous ways and used as an approach to multiple, too-many-to-name studies. The beginning of the question is, am I using theories as the same as explanations, right Heidi?

>> Yes, exactly.

>> OK.  So I think that I probably have to think about it for a minute, but I think that at the core of a theory is some type of explanation. Whether one decides that the explanation fits within their own idea of what a theory should be, I think is sort of a personal and possibly again a disciplinary-based choice, where you may be from a discipline that defines theory in one way and I may be from a discipline that defines it in another way.  So for example in anthropology, a theory would be, like what I described in our study of homeless women veterans, would be a theory that is very specific to that data.  So even for example in our web of vulnerability theory that we developed there are many connections that we could have made in the web based on understanding of the literature and other studies of homeless women but we tried to limit our theory to what we learned from the data.  So one could argue that maybe it doesn't rise to the status of a theory until and unless it incorporates perspectives from other data sources, other sources of literature. I think that there is no hard and fast rule about that but I think that in essence, a theory does provide some type of explanation for how or why a phenomenon is as it is. I hope that addresses the question. 

>> One of the nice things about getting the questions over the Q&A is that the questioner cannot come back and say, “no that is not what I meant at all”. [ laughter] Okay let's try to sneak one more question in here. The question I have is: “could you please say more about what theory means in the context of GT?”

>> I think it is similar to the last question that was sent.  But within grounded theory and the idea is that the data should move, for lack of a better term, from the description that your participants have provided for you, and other sources of data provided for you, it should move from that description to some explanation of the relationship between the patterns and interactions that are found in the data and the theory would reflect the nature of those relationships, associations, and potentially interactional dynamics. So again with grounded theory having its roots in  social interactionism and constructivism, that that of idea of where meaning happens, particularly in social interactions.  The idea in grounded theory anyway is that would want to develop some explanation to why things are as they are. So it is not merely saying here is what I observed in this setting or in this set of interactions but I want to explain why I think it is the way it is and the why I think it is the way it is, at least how I interpret it, is the theory that you’re attempting to develop.  So it is going beyond what you are seeing to move to an explanation of why you believe it to be that way. And making a case for it, so providing the empirical foundation for the case that you’re making given the interpretation or explanation of the phenomenon you are studying.

>> Fantastic, thank you so much. I do still have plenty more questions so for our attendees whose questions did not get asked in today’s session, I will be forwarding them to Dr. Hamilton and we will do our best to get a response back to you. Alison, I want to thank you so much for taking the time to prepare and present for today’s cyber seminar.  We really appreciate the time you put into it. 

>> My pleasure.

>> And our next session in the Spotlight on Women’s Health series is scheduled for June 2.  Martin Lee will be presenting “Hierarchical Research Designs: Design Strategies and Statistical” so hopefully we'll be able to see all of you at that upcoming session. Thank you for attending today's session and we hope to see you next time.  Thank you so much.