**Transcript of Cyberseminar**

**Spotlight on Women’s Health**

**Qualitative Methods in Rapid Turn-Around Health Services Research**

**Presenter: Alison B. Hamilton, PhD, MPH**

**December 11, 2013**

*This is an unedited transcript of this session. As such, it may contain omissions or errors due to sound quality or misinterpretation. For clarification or verification of any points in the transcript, please refer to the audio version posted at www.hsrd.research.va.gov/cyberseminars/catalog-archive.cfm or contact alison.hamilton@va.gov.*

Moderator:And we are at the top of the hour now so I would like to introduce our speaker. We have Dr. Alison Hamilton. She is a Research Health Scientist and Lead, Qualitative Methods Group at the HSR&D Center of the Study of Healthcare Innovation, Implementation & Policy at the VA Greater Los Angeles Healthcare System. So it is my pleasure to introduce Alison.

Dr. Hamilton:Thank you, Molly. Can you hear me okay?

Moderator:Yup, coming through.

Dr. Hamilton:Okay, great. Thank you and good morning, or good afternoon, depending on where you are in the country. Thank you very much for joining me for this session about qualitative methods in rapid turnaround health services research. 

Before I get started, it is very important that I thank a few key people who have been central to the development of these ideas; specifically, Dr. Ray Maietta and Barbara Bokhour and Susan Zickmund who have contributed quite a bit to the development of this work, as well as my VA Qualitative Research teams, which would take me a while to name but you know who you are. And also, participants who have taken this course from me before have really helped to refine and expand the methods, as well. So I appreciate all the input from these key people.

So we are going to start with a core question, which is how familiar are you with qualitative methods. If you could just let me know your level of familiarity, that would be great.

Moderator:Thank you. For our attendees, simply click the circle next to the answer that best corresponds with your familiarity. All right, looks like we are getting a great response rate and the answers are still streaming in so we will give people a few more seconds to reply. Okay, thank you for our respondents. It looks like we have a good mix—about thirty-seven percent say they are very familiar with qualitative methods, about fifty-one percent say somewhat, ten percent say not very, and about one percent say not at all. So thank you to our respondents.

Dr. Hamilton:Okay, thank you, Molly. So I have three main objectives today. First I want to provide a rationale for the tailoring of qualitative methods for rapid cycle projects and address some research design issues, and then some analysis strategies. And to illustrate the points that I would like to make, I am going to use examples from a one-year project that was funded by Women’s Health Services run by Connie Hayes.

First I am going to talk about why we need a tailored approach for rapid projects. So to start with some definitions, what do we mean by rapid? Much of what I am going to present this morning is not new. It is really a combination of information and strategies and approaches that have been used in many different fields by many different individuals. One of the main people who kind of pioneered the rapid assessment process was James Beebe in a book from 2001 where he defined rapid assessment process as “intensive, team-based, qualitative inquiry using triangulation, iterative data analysis, and additional data collection to quickly develop a *preliminary understanding* of a situation from the insider’s perspective.” The italics there are mine and what I really wanted to highlight was that this is a form of qualitative inquiry and also that it is a method designed to give you a preliminary understanding, not a thorough and comprehensive understanding. And I will come back to this point in a few minutes.

In that book, he defined “rapid” as a minimum of four days and a maximum of six weeks. I have adjusted this for the context of the types of health services research that many of us do to mean projects that are one year or less, so RRPs and other types of projects that may be funded through Central Office or other mechanisms that last a year or less.

But the point here is rapid does not mean rushed. So you may have a quick turnaround but you are still wanting to develop a systematic approach to your qualitative project, and that process should not be a rushed process.

Why would we need rapid methods? Well, since I have a fairly familiar audience, you probably have heard the critique of qualitative research that it takes too much time. It is one of the most common critiques that I hear a lot. But yet, we see that health services research, implementation research, and other areas are increasingly reliant on qualitative methods. And often, the demand for qualitative methods takes place within constricted timeframes with a frequent demand for products. So we need to come up with things pretty quickly. And we also are still under a very high expectation of rigor.

When might you need a rapid approach? This list seems to grow as I work with these methods. So things that I have encountered in my own work and then other people who have used this work, of course, you might have a specific timeframe with deliverables due on a certain date. You may have a particular need for products or progress; for example, competition or pressure to publish. You may need data for a preliminary studies section or you may need to provide your partners with some rapid feedback. 

The qualitative aspect of your study might be embedded or contiguous with other aspects of the study so you are informing different ways of data collection, maybe making real time modifications to an implementation strategy, using qualitative data to inform quantitative measures or data collection. And also, maybe you need to do a quick qualitative study in order to understand some unexpected discoveries or findings. 

Another time that rapid methods come into play is when you have got some type of time-sensitive issue or new development and you kind of want to strike when the iron is hot and use some methods that will get you to the understanding that you seek to achieve within a short timeframe. This is not an exhaustive list but these are just some of the reasons why people have turned to these types of methods.

So just to compare and contrast, my background is in anthropology so I am definitely steeped in the left column of traditional qualitative studies versus a more rapid approach. But the health services input into my work and others’ work has really caused us to think about what the differences and distinctions might be.

So for example, traditional studies might be more constructivist, more exploratory, and inductive whereas rapid studies may take a more positivist approach that would be more explanatory and more deductively oriented. Your data collection in that traditional project might be more continuous long-term, involve long-term engagement in a setting whereas in a rapid project, you might have multiple time point data collection and maybe minimal or time-limited engagement in the setting. The traditional approach might be more descriptive, broad-based, and interpretive whereas a rapid approach might be more targeted and explanatory, and that interpretive aspect could come later. 

Also with the traditional approach, you might collect data for a very long time before analyzing it where oftentimes in rapid projects; you need to be conducting your analyses during the course of data collection. And finally, with a traditional approach, it may be difficult to fit in everything you want to do in a more traditional long-term qualitative project within a mixed methods study due to time constraints and design issues and that kind of thing whereas a rapid approach might be well-suited for a mixed methods study.

What is unique about rapid qualitative research? Well, a few things that characterize this approach. First of all, it is telescoped so it is targeted, it is focused, and it is action oriented. Also, there is a pragmatic need for the qualitative data. You might need to describe the environment where an intervention is being implemented or a process that occurs while the intervention is underway. You might be pressed to describe “usual” care, services, practices—many other reasons, especially for us working in VA, why we might have that pragmatic need.

Typically and preferably, a more rapid project should be conducted by teams because you want to have enough people available to do the work and also, to add legitimacy to your analysis by having multiple team members. 

You are probably going to need to draw data quickly from multiple sources and oftentimes, triangulate with quantitative data. And one of the drawbacks or sort of consequences of the more rapid approach is that there is going to be less time to critique, to reflect, to synthesize, to do more in-depth work in the analysis that you might want to do and that you might be used to doing. But as I will point out later, it does not mean that that cannot happen. It just might not happen within the timeframe that you have for your rapid project.

So how can we tailor qualitative methods for rapid-cycle projects? The questions that are on this slide are really not specific to rapid projects but they kind of take on a different flavor when it comes to working within a rapid timeframe. So again, because of that more telescoped approach, you really need to think about your key research questions. You may have five great research questions or four that have specific aims but within the time you have, you can only really answer one of those questions well, or achieve one of those aims. So you have to batch up, as I will show you in the next slide, to really match up the time you have with what you are able to accomplish. 

What guides your rapid study, what will be your sources of data, where are you going to get the data, from whom. What types of data, what is your timing of data collection and the logic behind that timing. That is a really important  piece that links back to your aims. What is the nature of the team that you have—their training, the size of the team? And what type of approach are you going to take to analyzing the data, which is really bulk of what I will be talking about during this cyber seminar. 

Also, I think what becomes a little bit more highlighted within a rapid project is thinking about product. So who is going to receive your results? When and how are they going to get those results? And how are you going to tell the story or stories of your data? So that really gets to the issue of product. What products do you have to develop? For whom? What is that audience? What is the nature of the audience? And that is often what distinguishes a rapid project is that your audience might be different and they might need and expect different products than, you know, a manuscript in a high-impact journal, for example. That might not be your audience’s priority.

So here is just another way of looking at this combination of factors. So think of it in terms of matching up the pieces with time being sort of the parameters that are guiding all of these factors. So your specific questions, your prepared team, a feasible amount of data collection and orientation toward data collection, as well as analysis, and specific targeted products. Again, it does not mean that all of your products have to be accomplished within the timeframe that you have but there may be very specific products that you are expected to generate. And that is what often happens in the type of work that we do in health services research.

So this is where methods come into play in terms of feasibility. If you think about qualitative methods existing along a spectrum from highly unstructured methods to more structured methods, the unstructured end of the spectrum really does not work well for rapid projects. Where you want to find yourself in terms of choosing methods is more on the semi-structured end of the spectrum because you want that more targeted approach to your project. And having a more maybe grounded theory or unstructured, highly ethnographic approach really is meant to allow you to go in many directions and that does not lend itself well to being done quickly. 

So in terms of methods that might work for your rapid project, you might choose focus groups or a combination of the methods that we are going to mention. But even within focus groups, you might want to select some activities that would give you a little bit more structured data within the context of the focus group. So for example, asking participants to prioritize their preferences for some aspect of care, and that could be done in a little bit more structured fashion, which helps to generate a nice concrete body of data from a focus group.

Also, in semi-structured interviews, you may want to include some ranking or rating questions such that you are generating some—again—more concrete targeted data to go along with the qualitative data that you would be obtaining in those interviews.

Also, in terms of sampling for your semi-structured interviews—and for that matter, for your focus groups—you really want to think about limiting the samples to people who are going to know what you are interested in learning, know about it. So for example, key informants or key stakeholders, really using some purposeful sampling techniques to get what you might think of as the biggest bang for your buck within the context of the time that you have. So in a more unstructured approach, you might talk to people who may or may not know what you are interested in learning about whereas probably in a rapid project, you will not have time to go beyond people who most likely do know about what you are interested in.

Observations can also work in rapid turnaround projects but there might be aspects of those observations that you would want to structure more than in a classic ethnographic study. So for example, you might want to use some templates or really limit what you are observing to the research questions at hand.

So the example I am going to talk about today to illustrate these points is a Women’s Health Services project that I will call the Telehealth Project, which took place in fiscal year ’12. The timeframe was really less than a year total, which included IRB submissions and I would imagine you all know how long that can take, the formation of the teams, in-person site visits, and analysis. So all those things had to take place within really less than a year. 

Our aim was to investigate VA Women’s Health telehealth efforts in order to inform next steps with these services at the central office level. We did have a fairly large team of nine individuals who had varying levels of qualitative methods experience, and some members of the team had no experience but were happy to have the opportunity to visit some sites and learn methods and also, learn quite a bit about the content. 

So our team was comprised of interview leads and observers. We did mostly in-person interviews with key stakeholders at selected Women’s Health Practice-Based Research Network sites across the United States. 

And just going back to this point about products, you will see here that the products noted are not manuscripts. There is a final report for Women’s Health Services and presentations that we needed to prepare to inform our Women’s Health CREATE. So we have projects within our CREATE that were sort of waiting to benefit, in a sense, from what we learned from these site visits. So we needed to turn the data around quickly in order to inform those projects, which are now underway.

So I am going to come back to this project. You will see as I go along when I get into analysis issues.

Just to mention what our interview guides look like, as I stated before, your semi-structured interview guide needs to probably be fairly brief and prioritized, targeted, of course, also still very flexible. The prioritized point is really important because you may have several questions that you want to ask but if you find yourself with even less time with a respondent than you thought you would have, you want to make sure to get those top three questions asked of everyone. So you want to set up your interview guide in order to have the key questions right at the front in case your time is limited in the field.

So in our study, one question that we asked was what kinds of services are available to women Veterans at this clinic. And we had a few different areas of interest. So we were interested in PACT and whether PACT was in place in the women’s clinic and then asked them to describe that and whether they have made any adjustments to meet women’s needs. We were also interested in integrated services such as primary care and mental health integration. And of course, the main point of the project was the telehealth aspect. So we asked about any services that are available via telehealth and saw that there is interest in developing these services, especially tele-gynecology, and we wanted to get their perspectives on that.

So as you can see, these are still fairly open questions but they have specific topics that we need to cover, all of which corresponded to both the interest of Women’s Health Services in central office, as well as our CREATE project.

So like I said, I will come back to the project but I just wanted to give you the overall sense of what we were doing and what we were looking at and then these points will come back again. 

So I am going to move into analysis. And just wanted to cover some ground upfront before I get into the details. So a rapid analysis, within this constrained timeframe, may need to be supported by people who have limited or no qualitative methods background. So one of the main reasons why we started to come up with this approach was to find a way to maximize the potential and capacity of the team without needing everyone on the team to have a deep level of familiarity with qualitative methods. 

I am of the school of thought that believes that data analysis is not limited to coding. So there are other things that you can do with your qualitative analysis that do not necessitate coding. And in fact, a rapid approach will often necessitate systematic approaches other than coding. What I am going to suggest is an approach toward data reduction, which is typically needed in order to turn preliminary analyses around quickly. So going back to that earlier point about a preliminary understanding of a phenomenon or setting from an insider’s point of view, this is a preliminary approach to your analysis. It is not going to be the be-all-and-end-all of your analysis. 

And finally, a really important point is that rapid analysis does not preclude future, more intensive, what you might think of as “formal” analysis. Maybe you want to engage in some inductive coding, for example. All of that can still be done. It just may not be able to be done within the timeframe that you have. So the data is still there. Hopefully, you have collected high quality data that will allow you to go deeper and more expansively into the data at some point. But for the time that you have, you may not be able to get into that process. But there are still things you can do to come up with the products that you need.

So in case you are worried that this may not have a grounding in core qualitative methods, Miles & Huberman are two of the main proponents in qualitative analysis and this quote comes from their book called *Qualitative Data Analysis*, where they state that “Data reduction is not something separate from analysis. It is part of analysis.” So, “The researcher’s decision which data charts to code, which to pull out, which story to tell, are all analytic choices. Data reduction is a form of analysis that sharpens, sorts, focuses, discards, and organizes data in such a way that ‘final’ conclusions can be drawn and verified.” That “final” is in quotes in that book but I think it is even more important within a rapid approach because you probably are not going to come to final conclusions with a more rapid approach but they will be to the point where you can present them and feel confident about them in your product.

One important point that Miles & Huberman make is not to lose the words. So even in the process of reducing data, you do not want to strip the data from the context in which they occurred.

So what I am going to do now is take you through steps of rapid analysis. I put them all here on one slide just so you have them all in one place but I am going to actually go through each one at length now. So I am not going to pause here but just so you know all the steps are in one place, and I do want to note that this is an evolving approach and we are constantly learning how to improve it and work with it and make it work for the different types of projects that we do. So while I am suggesting this according to steps, this should be considered a highly tailorable process and there may be things that you want to do that meet your team’s needs, styles, training, etc., on the goals of your project that do not line up with these steps. But hopefully, there is enough flexibility built in that you can make it your own for what you are trying to accomplish.

So what I am going to suggest is the first step toward reducing the data is to develop templated summaries. I mentioned Ray Maietta earlier. He has really pioneered this idea of an episode profile. And this is sort of an offshoot of that where you are developing a summary of each data collection episode but further, you are creating it by using a template so it is a much more structured approach to summarizing your data collection episode. And by “episode,” I mean an interview, a focus group, whatever your data collection approach is. It is one chunk of that data collection effort.

So these summaries are going to be designed according to a relatively small set of predetermined domains, always leaving space of the unexpected. And the domain should mostly line up with the interview guide, which I will show you.

So this is Step 1, which is to create a neutral domain name that corresponds with each interview question. So if you recall the questions from the interview guide that I presented a few minutes ago, we had the question about telehealth. So you see the question on the left and then the domain created for that is telehealth services, tele-gynecology, our PACT question relates to the domain we call PACT, and our integrated services questions relate to the domain we called Integrated Services. 

I just want to highlight the one point about it being a neutral domain name. So this is not a process where you are getting into whether people felt positively or negatively about something. It is not really meant to be a highly interpretive process. You want to keep it kind of broad and neutral and the time for characterizing that domain will come a little bit later.

And then you want to draft a summary template for use by the team. So here is a piece of the template that we used for our study. So you indicate who prepared it, maybe what site the respondent was from or if you have a multi-site study, what the respondent’s role was. You can tailor the top of that however makes sense for your project. And then you just simply list the domains that correspond mostly to your interview guide.

In creating that templated summary, you do want to include space—we typically put it at the end—for other observations. So this is material that was important in the interview but that does not necessarily fit into a domain. And also, I would recommend including space at the end for important quotations, so the things that people say that just strike you as you could not possibly say it better yourself. You might want to stick those at the end. There are other things that people who are using this approach have mentioned to me that can be helpful to include in your templated summary. For example, some teams want to include a section on reflections on the data collection episode, a more sort of reflective component of your process. All of these things are certainly possible. It really depends on what you need in your project and the training of your team to be able to complete it consistently. 

Before you start using the summary template, you really need to test it. Make sure that it is working. So what we typically do is have at least a subset of team members use the template for the same subset of transcripts. So each of us takes two or three transcripts and attempts to use the summary template. And there are a few things that you would want to assess after you take it for a test drive. So first of all, you want to make sure that those domains are intuitively labeled and that they are actually findable in the data. It might be that you need to name them something else or something happened during the course of data selection that means that that particular domain really did not come up, although hopefully, you are catching that earlier than when you are summarizing twenty or thirty or forty interviews. 

You also want to see are any domains missing. And a really critical question to ask is, is it easy to use. These templates should be easy to use. That is very, very important. And also, how long does it take to complete it? We typically find that it takes about an hour to complete a summary template for maybe a forty-five minute interview versus at least a good three hours of a preliminary stab at coding. It may take less because your interview may be shorter. It should not really take longer, except maybe if you are summarizing a focus group, which are a little bit more complex to summarize. But if you have folks who are taking two and three and four hours to complete a summary template, you really want to ask yourself and ask your team why is it taking so long. So it might be that something is wrong with the template itself, or it might be that they are putting too much thought into it.

So you really want to compare people’s styles because people do this in different ways. And you want to try to achieve some consistency so that the batch of summaries is usable across the team and across the project. Some areas where we have found some difference are in the volume of information per domain so you might have some people who put three bullet points and some people who put twelve and you want to kind of get to a normative place with that. That really is up to the team in terms of volume but you want it to be similar across the team. 

The use of direct quotes should be fairly minimal because those are what is going to make the summaries very long. But you might want to use snippets of people’s quotations, and I will come back to this point.

Also, it is really important to note the absence of content. So if you have a domain and there is nothing under it, it is really hard for someone else to read that and know what happened. So it is helpful to add whether the question was asked and not answered, or whether the question was not asked. So you, as someone reading someone else’s summary, do not have to ask, “Well, why is there no data here? Why don’t I understand anything about what the person said on this particular topic?” 

Also, it is very helpful to note depths in a particular domain. So this is sort of a signal to your team that there might be a lot of great data in a particular interview. So we say something like, “This interview has a lot of data on this topic,” or, “There are great quotes in this transcript.” Or, “Go back to this one for lots of material on this domain.” So that you are not trying to capture all of that in the summary but you are letting your team members and yourself know, “Hey, we need to go back to this one for this particular topic.” 

After you have established that consistency and you feel confident that people are approaching it in the same way, you can divide up the transcripts across the team and summarize. And you can take any number of approaches to dividing it up. It might be by site, by role, many different ways that you can approach it, depending on your study. So here is a little bit of what a completed summary might look like. So you see in our study that we use bullet points, so it is points. You see here that I do have a few quotes. And the information that I am going to present from our project is aggregated so it is not specific to a site or a particular interview. But you can see I did quote the individual in a few cases because it evoked what occurred in the interview. So for example, I put, “The respondent said that she was happy with PACT but that it was stressful for her RN.” I could have put that in another way but actually, including her words really allowed me to remember her saying that. Or it allowed me to convey to a team member exactly how the words that the person used to express that particular perspective.

So in terms of what makes for a good summary, you want them to be brief. Typically, they should be no more than two pages. So again, if you are taking a long time, chances are it is going to be very long. And you want them to be bulleted highlights of what the respondent said in the interview. They should be organized, they should be thorough and readable. So the point is that anyone reading the summary should get a sense of what the respondent said. Even if you were not the interviewer, you should be able to read someone else’s summary and say, “Okay, I have a pretty good idea of what this person said.” And they should also be very useful. So as I mentioned, having pointers about what is in the transcript can be very helpful to move on and know where to go back to when you are trying to develop a product on a particular topic.

This is a handout that I have shared with teams. I am not going to go over it. The point is that there are some instructions that are prepared. Again, you can tailor these. We could actually probably put these on the HSR&D website as a handout if you want to use these and then revise them for your teams. But it is just helpful to hand them out, especially for people who have never done something like this before to give them a list of instructions. 

Now I am going to move into data display. So you are at the point now where you have prepared summaries and the question is, “Well, what do we do next?” And this is where we get into the issue of data display and using matrices. What you are doing in terms of technicalities is actually transferring the summary points into the matrix, which might be set up by respondent by domain or other structures that make sense for your project. So literally, you are copying and pasting the summary points into a matrix. 

Before I show you that, I just want to get into some more broad picture views of where your matrices fit into qualitative analysis. There is a really nice paper by Averill about matrix analysis where she says that the “matrices streamline the process of noting... similarities, differences, and trends in responses across groups of informants.” And I think this next point is very important, kind of getting back to the critiques of qualitative messages that we might hear, that these matrices make the “synthesis and summary of important findings accessible to audiences who might never otherwise take the time to examine the data generated by the interview  process.” So especially for folks who again are not necessarily going to want to get into the weeds of what you have in your qualitative data. The matrices allow for that accessible view of well, what did we learn, kind of in a nutshell. What are the main points of what we learned from this project?

And going back to Miles & Huberman again, they make a very similar point, which is that data displays are “designed to assemble organized information into an immediately accessible compact form so that the analyst can see what is happening and either draw justified conclusions or move on to the next step of analysis.” And similar to the process of data reduction, the process of creating data displays “is not separate from analysis, it is a part of analysis.” 

So now getting into the technicalities for a few minutes, again, you want to set up the matrix in a format that makes sense for the purpose of your analysis. It might be that you want to look at site level information, role level information, you may have multiple waves of data collection. So this is something that you need to make your own according to the research questions and the aims that you have.

So going back to the project again that I mentioned, up at the top you see on the X axis, you see the domains that came up in the summary template. And then we have got along the Y axis, we have Site 1 and then Interview 1, Interview 2, and literally, the points from the summary template have been copied and pasted into this matrix. So when you are looking at this, you can read down and see what all you have about a particular domain. Of course, you can read across and see what the person talked about in the interview within each of the domains. You can do many things with the matrix, which I will bring up in a minute. But I just also wanted to note that you could, again, tailor this so that you—let me see if I can find my drawing tools. You may want to summarize the domain here so you can build on what you create in the matrix to have it serve the needs of your project. And this is especially helpful maybe toward the end of your project. Where you feel like you have a good handle on a particular topic, you might want to put those summary points into your matrix.

So there are several things that the matrix can do for you. First of all, as I mentioned, you can quickly peruse the content of any given domain. What you can start to get a sense of the variation. So I had mentioned before that the domains tend to work better if they are neutral. And this is where in the matrix analysis where you can start to look at okay, what is the nature of the data that I have? What is the variation? Are there positive and negative aspects to this? Are there barriers of facilitators? It really depends again on your questions but you can get a sense of the lay of the land of that particular topic.

You can also assess gaps in information. So just going back to the matrix for a minute, if one of these cells is empty, then you could ask yourself—now it may be empty but it says the question was not asked. But if you start to observe patterns in terms of empty cells, it might give you directions for questions to ask. For example, why might one site have a lot of empty cells on a particular topic or one role? And it can give you directions for your later interpretation.

Also, you can use your matrix analysis to develop memos so you can think about what themes are you noticing, what variations, what trends in the data, what directions you want to go in next, etc. And finally, you can develop summaries of summaries. So you can develop summaries of the domain, of the site, the types of respondents, etc. You can use that matrix analysis to get you a pretty good distance in terms of your understanding of what people talked about in your data collection episodes.

So in terms of where you can go with your rapid analysis, there are a couple of advantages that we have noticed in using this. First of all, you can divide up the labor of reviewing transcripts. And this is where that issue of training of the team is really important to come back to because the process of summarizing your transcripts or your data can be done by individuals who do not have qualitative training, who do not know software, who do not how to code. What the individuals on the team need to know how to do is read and faithfully summarize what was brought up in the interview. And that does not require the qualitative training per se but rather a careful reading—and a sensitive reading—of what came up in the interview. So that can be really helpful when you have teams that are comprised of individuals who do not have qualitative backgrounds but who want to dive into the data and particular in the process of reducing the data down to a manageable form for the purpose of your rapid project.

You can also assess the quality of data collection across your team. So you might even set up matrices by interviewers and see if there are interviewers who are doing more or less with asking particular questions. This would probably have to be done by someone with a pretty high level of qualitative training in order to assess quality. But the matrix does give you a pretty quick view of consistency of data collection and you can look at that by individuals who are collecting the data.

One of the main advantages of this is that it allows you to obtain a quick understanding of the major findings. And this can be especially helpful if you were not the person who collected all of the data, which is often the case in the rapid projects. So you may not have time to read hundreds and hundreds of pages of transcripts but you may have time to read some summaries or to look at a matrix. And again, going back to Miles & Huberman and Averill, it gives you that quick snapshot of what was learned during the course of data collection.

What we have been doing a lot in some current projects is using our summaries to inform subsequent waves of data collection. So we summarize the data after each wave and then when we go back to individuals to do followup interviews, we review the summaries from their prior interviews and are able to go into the subsequent interview in a very informed manner. And that means, you know, not reading the twenty-five page transcript but reading a two-page summary of the key points that the respondents had made the first time and said, “Well, you know, when we talked to you a year ago, you had mentioned this. Is this still an issue?” etc. So it is very, very helpful to use when you have multiple waves of data collection. And of course, that can help to inform subsequent waves of data collection in terms of setting up your interview guides and the data collection itself.

So rapid analysis can definitely facilitate the preparation of reports and presentations. And finally, they can help with developing a codebook. So when you are looking at a matrix that  has the key points from the interview, it should be giving you a sense of codes that would be relevant to develop for the data. So you can use that information from the summary within the matrix to identify the depth and breadth of the data that you have and then start to think about what the codes will look like. Typically, the domain names are too broad for code names but based on your investigation of what you have in each domain, you could start to think about what those codes might look like.

So just to give you a sample of what we were able to generate based on a matrix, this is a sample slide from a presentation that we gave to our partners and we were able to give all this information about PACT. And again, this was not based on a careful reading of hundreds and hundreds of pages of transcript but rather each person’s careful reading and then summarizing of the transcript and then a synthesis of those summaries on the matrix to develop this sample slide. So we were able to talk about what the team looked like at the site, what some of the concerns are, the role of the pharmacist. We were able to really touch on many of the key points about PACT without getting too far into the weeds. Of course, all that information is there for us to mine later. What we really need is this overall flavor of PACT in order to inform our partners.

And this was created, I should note, these slides, this presentation and several other presentations were created without any coding having taken place.

So I was trying to get through to the end just so there is time for questions. So there is not too much left in my part but just now that you have heard sort of the overall approach, I am curious to know if you are using a similar approach. If not, do you think you might try it? Or do you think, “No, it is not going to work?” So if you could just answer the poll, that would be great. Molly, are you with us?

Moderator:Thank you, yes. We have got the poll up and running and it looks like the answers are streaming in. We have got a very responsive group with us today so that is great. So for those of you that might have joined us a little bit later in the session, simply click the circle next to your corresponding response and we will have those aggregated in just a second. All right, it looks like the answers have stopped streaming in. We have roughly twenty-nine percent that say yes, they are using a similar approach, about fifteen percent say I think so, fifty-one percent said no but I plan on trying it, and four percent said no, I do not think it will work for my projects. Thanks to our respondents.

Dr. Hamilton:Great, I am so glad that so many of you think you will try it. We are always trying to make it better and so I will be really interested to hear your questions.

So just to wrap up, I want to come back to what we might think of as hallmarks of credible qualitative analysis—and I added “rapid” there in parentheses. Because these are  hallmarks of what we would want to see in any analysis with a few little tweaks for a rapid approach. So typically, a credible traditional approach would have involved prolonged engagement with the data. And I just changed that to say systematic engagement because in the rapid context, you do not have time for a prolonged engagement. There may be a time later in your work where you want to engage in that prolonged approach to the data and certainly, that opportunity has not gone away. It just may not be feasible within your timeframe. 

You want the presentation of clear evidence grounded in the data. That is what the matrix can give you, as well as the summaries themselves. And you want to be able to identify cross-cutting themes and by reducing and displaying your data, you are able to identify those themes and also, to identify some more rare themes that are important to note but may not have cut across the majority of your data.

And finally, another final hallmark of a credible approach would be a team-based approach with discussion and consensus and preliminary conclusions and that is one of the hallmarks of a rapid approach, as well, that it does take place with a team. It may be that your team is two people. So I am not saying—you know, the team of nine that we had on this project was really quite a luxury. But what I am hearing about mostly in the field is teams of two, teams of three, and maybe the teams do not have—are comprised of all the people with that intensive level of familiarity with qualitative methods.

So I just want to acknowledge the team that selected the data, that created the summaries, and worked on the presentations with me and also, to acknowledge the support of Becky Yano and Britney and Jennifer, who helped us make all of this happen. So thank you to the team. I would also like to thank Women’s Health Services for funding the project and sending Drs. Patty Hayes and Sally Haskell for supporting our efforts, Dr. Susan Frayne for facilitating our relationships with the practice-based research network sites. And of course, the individuals who participated in our study.

Here are some references that either get at some of the broader methodological issues or that actually give examples of rapid approaches in a number of different formulations. So you can take a look at some of the project-oriented references here and see how they did it—what their timeframes were, how they approached analysis. They are not all using exactly what I just presented but some variation. And then I actually drew from many of these references to develop this presentation for today.

And finally, there is my contact information so hopefully, I have left enough time for at least a few questions, Molly. But thank you very much for listening and I look forward to your feedback. 

Moderator:Excellent, thank you. We do have several pending questions. For those of you that joined us after the top of the hour, simply submit your question in the upper right hand corner using the Q&A box. And the first one that came in. Very helpful information. If we plan to use this approach for an RRP/pilot project, do you suggest using BB 2001 as a reference for the general approach and Miles & Huberman for data analysis? [Interruption] Or Averill for data analysis?

Dr. Hamilton:Yeah, you could use any of the references that I have given. Probably the BB would not be the best reference just because it is a really specific process that he is describing that does not get into these analytic issues as much. You could maybe use this cyber seminar as a reference until I actually [laugh] get my paper out there, which I am working on very hard right now. But the Averill would work for the matrix analysis and definitely Miles & Huberman. There is actually a new version of that book with Johnny Saldana out now but certainly, that would be a good reference for the reduction and the display aspects of the approach.

Moderator:Thank you. You may have answered this question already. When doing template summaries, do you go ahead and paste in related quotes to save time later in having to go back and find them?

Dr. Hamilton:We typically do not. We might cut and paste in some little pieces of quotes but not the full quotes because they tend to make it very long and then it takes longer to read and make your way through it. We do put those important quotes at the end and sometimes we will put in the template itself, “See below for some great quotes on this.” But in the actual body of the template, we tend not to paste a lot of full quotes because again, they take up a lot of space and then your process of trying to read it and get those highlights begins to take longer. So the more data you put in, the more it starts to look like you are moving toward coding and then they actually are longer in terms of page length and also longer to read. So I would recommend not putting a whole lot of full quotes into the template itself. But again, if that works for your project and you want four-page summaries instead of two-page, then there is no reason not to do it. It really kind of depends on what you want to achieve with the summaries.

Moderator:Thank you for that response. We do have several great questions streaming in. The next person has several questions. We will tackle them one at a time. You emphasize this approach is not for peer review manuscripts. Does this mean that the audience of this work will be okay with this level of rigor analytic approach? Or do they have questions on it?

Dr. Hamilton:I am really glad that that question was raised because I did not actually mean to say that but I can see how I did say that [laugh]. So I think that this approach can be used for peer review manuscripts and the references that I provided in one of the later slides are examples of when a more rapid approach has been used. And of course, those are peer review publications. 

I think the point that I was making—and I should have made it better—is that the manuscript might not be the end goal of your rapid project and you may not be able to accomplish it within the parameters of your rapid project. Also, the type of journal that you are targeting may not find that t his approach is substantial enough for what they would want to see. So for example, if you are going toward a journal like *Qualitative Health Research* that reviewers might find that this is not an in-depth enough approach to analysis. Because it is really designed to give you that more preliminary understanding of what you have in the data. 

I cannot say that for sure because you know, of course it depends on the reviewers, etc. But there are certainly many journals that would accept an approach like this and that have accepted an approach like this. The key is to describe what you did systematically and the steps that you took to make it legitimate and valid. So what steps did the team take in really highlighting the systematic approach and how that yielded findings that are credible.

So it is definitely possible to use this approach for a manuscript but again, it really depends on what type of manuscript you are targeting and what type of analysis you need to achieve. So the examples in the references will give you that sense of what types of projects matched up with analytic approaches yielded findings that were accepted for the types of journals that are listed there.

Moderator:Thank you very much for that reply. And our submitted just said you answered all the subsequent questions with your response.

Dr. Hamilton:Oh, yeah.

Moderator:Great. The next one—let’s see. What, if any, software do they use for this rapid analysis? For example, the matrix display.

Dr. Hamilton:We just use Excel. So I think Excel gives you enough tools to play with the matrix and again, that might be software that folks on the team who do not have qualitative experience can use. So it is really nice to be able to build on the strengths of your team and not have to worry about everyone knowing ATLAS or NVivo or some of the more sophisticated qualitative  data analysis software packages.

Moderator:Thank you. And are you using the process you described in place of coding or in addition to?

Dr. Hamilton:Both. So we have some projects where—I mean, I think ultimately, you know, my hope is that in any project where I am using this, we would ultimately code. But oftentimes, the time is just not available. So I like  knowing that the option is there to code and the goal is typically still to move towards coding. But we have several projects where this is the main approach for many of the products that we need to generate and then we have coding in addition. So like for example, our PACT demonstrate lab, we use this approach that is not a rapid project but we have multiple waves of data collection. And so we use this approach for each wave but we are also coding but that is a much more lengthy aspect of what we are doing with the analysis. And it is fairly specific to the types of paper that we want to generate. But the products that we need in the interim for the demo lab are facilitated by this more rapid approach.

Moderator:Thank you for that reply. Looks like we have got about a dozen pending questions. The next one—do you have a sense of the maximum number of topics for a matrix? Or if it is, say, more than five, just do multiple matrices?

Dr. Hamilton:I would say that the average number of domains is about six to eight. And if you have got a lot more than that, I would want to think about what that semi-structured interview guide looks like. Because that means you have got, you know, ten, twelve, fifteen questions, which is a very long interview guide, especially for a rapid project. So if there seems to be a lot of domains, it might be that the domains are getting too specific. Or it might be that there are many, many questions that would be difficult to consistently ask in the course of a rapid project or in the course of interviews that have to take place within thirty minutes or something like that. So I would kind of go back to methods and to data collection instruments and see why do I have, you know, a lot of domains. 

Now in terms of the second part of that question, the development of the matrices, you really might want to have matrices for different aspects of your data. So you may not want all of the domains in one matrix. Maybe you have, for example, a two-part interview and you want a matrix on part one and then a matrix on part two. So by any means, you do not have to put all the domains into one matrix. But if you are finding that you have tons of domains, then there might be something that you need to look at in terms of your approach to data collection.

Moderator:Great, thank you. And if you are relying on data that has been mapped to the matrix, how do you ensure reliability of what you chose to put in the matrix? It seems like cherry-picking of findings would be much more possible.

Dr. Hamilton:I agree that there is that possibility. I mean, I think there is that possibility in coding, as well. What we try to emphasize in this process is pretty faithfully documenting what the person said and all the points that the person raised in response to the question. So if you are kind of sticking with that orientation, then it should not be a matter of picking out the things that sound good or look good or that are consistent with what you believe to be the case. Because there should not be a lot of judgement calls as to what to include but rather the key points, you know, whether or not you agree with them.

But this is definitely something that the lead of the team would want to assess. It could be really helpful to do this by having someone else summarize an interview that you conducted and then looking at the summary and seeing if all the key points are in the summary and you know, if you feel that it is an accurate reflection of what occurred in the data collection episode. Or, you know, yourself, do a check on the summary. 

You know, really, that is the test drive step of all of this is really important in terms of assessing the extent to which that cherry-picking might be occurring. So there really does need to be someone who is taking a look at the correspondence between the summary and the transcripts and making sure that there is not sort of a selective process going on whereby much of the data is left out of the summary. Because that of course, does not benefit anyone on the team where only certain points are included and others are not. 

But if you are really just documenting the points as they were stated by the respondents, there should hopefully be less of a tendency to select out the things that you liked the most. But it is a great point and certainly a possibility.

Moderator:Thank you for that response. Alison, are you able to stay on past the top of the hour to get the rest of the answers on tape?

Dr. Hamilton:Yeah, sure.

Moderator:Great, thank you. So the next question. What are the downsides of this approach? For example, can envision data use taking a different path than what was originally envisioned and being in the situation of having to defend methods in high stakes situations.

Dr. Hamilton:I think there are definitely some downsides because you know, this is sort of an overview type of approach. It is not really getting at synthesis. I mean, you could get at that in a preliminary fashion by working with the matrix. But in terms of the nuances of an analysis, that is really not going to be very possible within this approach. So that is one of the limitations, I would say. 

But I have come to terms with that in my own mind by just thinking okay, well, I can get into those nuances later. And most likely, my audience does not need to—is not so concerned with the nuances unless they make a point that really needs to be made.

In terms of the—can you repeat the high stakes part of that, Molly?

Moderator:Yes, just one second. Sorry about that, it will take just a second to pull it back up. All right, the high stakes part. Something about—okay, here we go. So can envision data use taking on a different path than what was originally envisioned and being in the situation of having to defend methods in high stakes situations.

Dr. Hamilton:Oh, okay. So that even this process of a more rapid approach might lead you down a road that you were maybe not funded to go down—or at least this is what I am interpreting. Forgive me if I am wrong to whomever asked the question. But that you might, you know, go in a direction that was not intended or that was not consistent with the original aims of the project. I do not see that as a danger of this approach, per se. I see that as an issue related to the overall endeavor of qualitative inquiry and probably, that is something that you would have picked up on earlier rather than later in your data collection effort to see well, we thought we should ask this question which has ended up not being as relevant. You know, we thought we should ask Question A but instead we find that Question B is really the more relevant question to ask. I think that is more of an inquiry related discovery, and a very important discovery, than one that if you pick up on it soon enough, you might be able to inform your funders or your audience why you are taking a different direction.

I mean, we do not tend to wait to create these summaries until the end. As soon as we have transcripts in hand, we start creating these, if possible, within the time that we have. So when you can do sort of simultaneous summarizing and initial reflections on the data during the course of data collection, you might pick up on that change in direction sooner than if you wait until the end to engage in this.

So I might not be getting the question right but my take on it is if you have gone in a different direction, it would not be because of this analytic approach. It might be because you found something different in the field that really made you think hey, we have got to go in a different direction with data collection.

Moderator:Thank you for that reply. The submitter is still in the audience so they can write in for further clarification if they need to. 

Dr. Hamilton:Okay.

Moderator:Would you ever later code the summaries and the matrices as field notes?

Dr. Hamilton:Oh, that is a great question. I have not done that but it could be done. I had a couple of students decide that they wanted to go in that direction. Now there were some kind of technical reasons for that because they were using ATLAS and they wanted to be able to link up their summaries with other aspects of their analysis. So I could definitely see why one might want to do that. I just personally have not done that. So I have had the summaries available, the matrices available, and the coding but I have not actually connected them by coding the matrices or the summaries. But I do not see why it could not be done.

Moderator:Thank you. How is rapid qualitative data analysis that you discussed today any different from the deductive approach qualitative data analysis?

Dr. Hamilton:I think it is consistent with a deductive approach to data analysis. What I have seen in terms of a deductive approach is more often related to deductive coding so that you are kind of getting into coding at a fairly early stage and from a deductive standpoint. And what we wanted to do within this approach was say well, what could we do without getting into the coding—without getting into software potentially, with having a team that may not be at all familiar with coding. But I think it is very consistent—it is a deductive approach, for sure. It just does not involve coding.

So I do not think of them as different, I think of them as consistent and compatible with the difference being that oftentimes that deductive approach takes the form of coding and this approach does not go in that direction, you know, from the outset.

Moderator:Thank you. The next person writes, “I am a graduate student interested in using qualitative research for my dissertation. Is this method appropriate for dissertation?”

Dr. Hamilton:I would say it probably would not be sufficient for a dissertation because of the expectations for what you are supposed to generate in a dissertation. It really depends on what field you are in because each field has different standards for what a “good” qualitative analysis looks like. I personally think that the summaries are helpful no matter what type of project you are doing because you can always go back to them and remind yourself of what someone said. So I think even not in a rapid project—in the context of a rapid project you would still benefit from having summaries of every data collection episode. But that would not be even the—that would not comprise even half of, or a quarter of your analytic process but rather serve as a resource for you as you proceed through the analysis. 

If you are using the matrix to help you develop a codebook, it could definitely be an important part of your process. But I do not think—again, depending on what type of field the person is in—I do not think it would be enough for a dissertation. I think you would need to be more immersed in the weeds. Because of course, part of what you are expected to do in that doctoral work is really know how to work your way through very complex data in very sophisticated ways. And this is not really kind of taking you all the way down that road.

Moderator:Great. She wrote back and said, “This has been very helpful.” 

Dr. Hamilton:Thanks.

Moderator:Can you speak a little bit more about how these rapid assessments have been used to inform implementation of programs as they are being implemented?

Dr. Hamilton:Yes. So in a large project called EQUIP, which we have done cyber seminars on before led by Alex Young and Amy Cohen, this was enhancing quality in Veterans with psychosis—quality of care in Veterans with psychosis. In that project, which was a hybrid implementation effectiveness study, we had multiple waves of qualitative and quantitative data collection among key stakeholders in our sites. It was a multisite study. And so, for example, at pre-implementation, we did a baseline assessment of organizational readiness via some quantitative measures and also, key stakeholders interviews. And we used that slice of data collection to inform our implementation strategy at each of the sites. 

So what that means, especially in the context of implementation research, is that you are analyzing the data fairly rapidly for the purposes that you need. So in other words, to inform the strategy that you might take at any given site. Again, it is not going to be the most thorough analysis of the data that you might want to do or perhaps feed into a more longitudinal type of analysis. But if you want to get a sense of what is going on at the site, where are the sites in terms of their readiness for different aspects of the intervention that you have in mind, it can be really helpful to use a rapid approach pretty proximal to the time of data collection in order to decide what steps to take next in a project. And we have published on that so if the person wants citations for that, they can contact me. But especially like in that study, we did pre, mid, and post implementation interviews, and we used the pre and the mid in a formative fashion to really inform what was going on with the implementation strategy throughout the course of the project.

Moderator:Thank you. The writer asks, “Do you have the citation?”

Dr. Hamilton:Yeah, there is a paper that I wrote in *JGIM* about organizational readiness in specialty mental health clinics, I think it is called, and I am the first author in that.

Operator:Your conference is scheduled to end in ten minutes.

Dr. Hamilton:That paper describes our use of some of the pre-implementation data and also there is a recent paper that I wrote in *Health Services Research* about our findings related to supportive employment in that project. And that goes through what we learned at each wave of data collection and how we used that information to tailor implementation of strategy. So if you have any trouble finding those references, there are others, too. But those are the two that come to mind. Just let me know.

Moderator:Great, thank you. The next person writes, “Great presentation. Have you ever tried rapid analysis concurrent with the data...” I am sorry. “Have you ever...?” Just lost that question, there we go. “Have you ever tried rapid analysis concurrent with the data collection in which you would not transcribe the interviews but have an analyst identify bullet points of the interviews being conducted?”

Dr. Hamilton:I would personally find that pretty difficult. Well, certainly, I would not want to do—just for me, I would not want to do it if I were the interviewer. I would not want to be trying to capture those key points as I am conducting an interview because I think the two processes of documenting and interviewing are really different cognitive tasks. You might have someone with you who is taking notes. But the challenge with that, as I see it, is that you do not always know what is the highlight as it is being stated. And so probably what you would be more inclined to do would just be to take notes on everything that is the person is saying, that the respondent is saying, and then later go back and turn it into more of a summary. But it is not something that everyone is super good at doing in terms of documenting an interview as it is going on. Of course, a computer can be very disruptive to the interview experience and so if it is an in-person interview, that might not be a preferable way to go. Even writing, you know, someone kind of scribbling furiously while the interview is going on, can be kind of distracting.

One thing that we may even have to do in some of our projects because of some delays in transcription is create summaries from the recordings. And I think it will take more time but if that is what you have to do, then that might be what you have to do. And that, I think, would be possible although I think—and I hope it is possible, actually—but I think it will necessitate some going back and refining the summary once you have listened and documented the key points. Because you may still end up with more than you actually want in the summary once you kind of go back and reflect on everything that you wrote down. 

So it is possible. I do not think it is the quickest way to go about it but it might be the only option that you have.

Moderator:Thank you. We had somebody with a very similar question and wanted to see if you agree with the team interview approach. They said they had done  this by phone and it seemed to work well.

Dr. Hamilton:Yeah, I mean, I think team interviewing is ideal, actually. You know, if possible, it is always better to have more than one person present in an interview for a number of different reasons, depending on what approach you are taking in your project. So if part of that question was you could be taking notes while you are on the phone, that, I think, is a little bit more feasible because the respondent is not aware necessarily of whether someone is writing or typing. Of course, they need to be aware in terms of their consent that someone is documenting what is being said.

Moderator:She adds that this was without transcripts.

Dr. Hamilton:Yeah, yeah. Even then, though, I personally would not want to attempt to summarize while the interview was going on. I would document what is going on in the interview and then create a summary from those notes.

Moderator:Thank you. We are down to our last [interruption]...

Dr. Hamilton:...to step back from your process of documenting everything to know kind of what to keep and what not to keep. I would not want to make those judgement calls while I am in the process of documenting an interview.

Moderator:Great. As I mentioned, we are down to our last six or so questions. And what do you suggest for explaining this approach to funders/clients who have said they wanted qualitative research but then they want answers, which are not well-answered using qualitative methods?

Dr. Hamilton:Can you repeat that so I make sure I get it?

Moderator:Yeah. What do you suggest for explaining this approach to funders and clients who have said they wanted qualitative research but then they want answers, which are not well-answered using qualitative methods?

Dr. Hamilton:Well, you know, for me, this is another case of it is not necessarily this rapid approach that is the problem but you know, what was the audience or the funder, etc., what were they expecting? And if they are not hearing what they want to hear—you know, when people are requesting qualitative methods, if they are not aware of what that will yield for them, they need to be made aware of what that will yield for them. So in other words, they may not hear what they want to hear. They may not get from it exactly what they thought they would, which is part of the beauty of qualitative methods is that we discover things that we did not already know. So there has to be that openness to discovery and to serendipitous findings in the qualitative inquiry that hopefully, the requests are wanted. 

And then if this process is not yielding what the requestor wanted, then I mean, to me, it really goes back to the data collection. And doing interim reports can be really helpful to avoid this type of thing from happening at the end. So you do not want to get all the way down the road, you have finished the project, you have presented, and they say, “Well, that is not at all what we wanted you do.” You know, you are really going to be in a bind at that point.

So letting people know in some iterative sort of interim fashion, “Here is what we are learning. Are we going in the right direction,” can help to avoid those unexpected sort of crashes at the end. But I think you know, the issues in terms of not getting what you want really come back to was the project set up to address the concerns and desires of the requestor. And you know, if data collection had taken a different turn and is yielding findings that were not consistent with the original intent, I think the requestor needs to be informed of that at a pretty early stage and you need to find out whether they still want you to go down the road that you are on.

Hopefully that answers the question. I am not sure it does.

Moderator:Thank you for the response. The next question—Can you elaborate on the role of transcription as a process? How many resources and time was budgeted for this in a similar rapid project?

Dr. Hamilton:Well, I mean, we typically do budget for transcription in all of our projects and that is a professional transcription service that we use. So we send out our recordings to be professionally transcribed. I know that is not always possible. Sometimes people have team members transcribing or you know, maybe you are trying your hand with some of the voice recognition software, maybe you are taking notes—many different options. But because the transcription does unavoidably add, you know, a costly component to your budget, but we do try to build that into our project. So if you are not building that in, you want to let your funder know how you are going to handle the qualitative data.

I think that you really have to look at the cost benefit of what you are going to do with the transcripts, what cost you would have to go to without the transcripts, and you know, what you plan to do with the transcripts long-term. 

But I think in terms of budgeting, I do not know if the person is looking for an actual dollar amount but we find that about a one-hour interview is somewhere in the ballpark of maybe a hundred and fifty dollars to transcribe. So just in case they are looking for a dollar amount, that is usually the estimate that we provide as budgets.

Moderator:Okay, thank you. The next question—oh, I am sorry, this is a comment. One thing we have done regarding quotes in a matrix is to put an interview number and a line number in the matrix to point to a good quote rather than including the quote itself.

Dr. Hamilton:Great idea. Yeah, absolutely, that is a really, really great idea. Definitely recommend it. Thank you for adding that. I will make sure to add that into my slide.

Moderator:Are you aware of any publications or ongoing studies where this approach has been used in query service-directed projects?

Dr. Hamilton:Some of the papers that are in that list of references were query projects. And again, they are not using exactly what I laid out here. This is sort of a compilation of approaches that people have used and an approach that we are finding to be effective in our projects. But there is sort of a variation on this theme present in several of those papers, some of which were query projects. And we have used this approach in RP, in those proposals, you know, some of which were successfully funded.

Moderator:Great, thank you. Another comment. An advantage of this approach is the ability to respond to stakeholders who want preliminary findings before the full analysis is completely.

Dr. Hamilton:Yeah, I mean, that is really where one of the main motivations behind it. Because we did not want to say to  our stakeholders, especially our operations partners and so forth or it might be community partners, “Well, yes, we will do your project and then we will give you our analysis in two years.” It just was not  working for anyone. And so really one of the main drivers behind this is to be able to provide that preliminary understanding of a topic in a timely fashion. So I totally agree, and that is really one of the main drivers of this. [interruption] That person sees it that way, too.

Moderator:We have just got two questions left. This is another clarification on the size of the matrix. So six to eight maximum domains for a thirty-minute interview. Could there be up to twice as much for a sixty-minute interview?

Dr. Hamilton:I mean, for us, six to eight—you know, around eight domains works even for an hour-long interview. It really depends on how complex the questions are. Because you might have five main questions but then several probes related—substantive probes related—to each question. So it kind of depends on how you set it up. 

I mean, I would say not six to eight maximum but six to eight average. And again, it is kind of going back to how many questions do you have? How many questions do you need to ask in order to achieve your aim? And how much time do you have with the people who are responding? So trying to cover fifteen topics in a forty-five minute interview is going to be very difficult unless the topics are very, very limited in nature. So it really depends on that combination of scope, time, you know, priorities, aims, etc.

But when you are getting into sixteen domain sets, my gut reaction to that is that is a lot. That is a lot of territory to cover in a semi-structured, fairly quick interview, even if it is forty-five minutes.

Moderator:Thank you. We have had a lot of people writing in saying this is a great talk. And somebody writes, “You talked about brief methods for analysis. Would you also comment on brief message for interview data collection? For example, do you think it is valid to ask open ended questions about what is most helpful about an intervention and going with what is said rather than spending a lot of time asking about specifics?”

Dr. Hamilton:I think what I would propose is a little bit of a combination of that. So I still, even though this is a more targeted approach, I still prefer to ask some lay of the land questions before getting into specifics. So to take the example of an intervention, my preference would be to get at the respondent’s understanding of that intervention first. So asking more broadly as the person who asked the question indicated. So more broadly, just getting at what do they think about it,  how is it working, or how do they expect it to work—that kind of question—and see what they spontaneously tell you about their perceptions of the intervention.

However, what you might want to couple that with is some specifics. So they may mention three aspects of the intervention and yet, you know there to be eight aspects of the intervention. So they may bring up those three and then you may want to follow up with probe about aspects that they did not originally bring up. Some of those may go nowhere but you may have your project set up such that you do ask each person about each component of the intervention. Now they may say, you know, “I do not care about that piece,” or, “I do not know about it.” But nonetheless, you have consistently asked each person about each component and that can be really important for your later analysis.

But I would not dig into what you know to be the components before getting at that general understanding. Because you do not really want to constrain them by the details before they have give you their overall perspective on it. So I would actually propose a combination but that adding in as a particular details of an intervention or an implementation strategy or whatever the case may be, can be a really nice facet of this type of more rapid turnaround project because you want that consistency of information about each piece. 

So I think it would be a bit of a combination in my point of view.

Moderator:Great, thank you. Well, Alison, I really want to thank you for lending your expertise to this topic. And I also want to thank our ample number of participants that stuck with us. I am going to close the meeting out for our attendees. Please wait just a second. There is going to be a survey that pops up on your screen and we do appreciate your feedback. So thank you so much again to everyone and please enjoy the rest of your day.

Dr. Hamilton:Thank you, Molly.

Moderator:Thank you.

Dr. Hamilton:Thanks, everyone. Bye bye.

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