Hosts Richard Landers and Tara Behrend welcome Dr. Joe Mazzola, Professor of Psychology and Director of the IO Master’s Program at Meredith College, to discuss qualitative research methods. Dr. Mazzola shares his journey from quantitative training at the University of South Florida to becoming an advocate for qualitative and mixed methods approaches. The conversation explores how qualitative methods reveal the human element often lost in quantitative research, particularly when studying occupational health topics like workplace stress, fitness, and nutrition. Dr. Mazzola discusses the practical applications of qualitative research for master’s students, the challenges of publishing qualitative work, and the integration of AI into content analysis.
Key Takeaways:
- Qualitative research allows researchers to capture the human element and personal experiences behind statistical patterns
- Mixed methods approaches can answer questions that neither quantitative nor qualitative methods can address alone
- Students often find qualitative research more accessible and practical for real-world organizational consulting
- Purposeful research design should drive methodology choices rather than researcher comfort zones
- The Triangle area of North Carolina offers growing opportunities for IO psychology graduates
- AI tools are increasingly capable of content analysis but shouldn’t replace human interpretation
- Publishing qualitative research can be challenging but is increasingly valued in the field
- Balancing research and program administration requires intentionality and student collaboration
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Transcript
[Richard Landers] (0:00 – 0:36)
Welcome to the Great IO Get-Together. On tonight’s show, quips and queries about the world of work as IO psychology comes alive. Now please welcome our hosts, Richard and Tim.
Welcome everyone to the Great IO Get-Together number 31. My name is Richard, this is my co-host Tara. Today we are exploring chapter five of my textbook, of our textbook, Research Methods for IO Psychology.
And this chapter is all about the fundamentals of qualitative methods. So to help us understand on the show today, we have Dr. Joe Mazzola, Professor of Psychology and Director of the IO Master’s Program at Merida College. Welcome to the show.
Thank you. Glad to be here.
[Tara Behrend] (0:36 – 0:46)
Well, we’re very excited to talk to you today. Maybe you could start by just telling us a little bit more about your background, your journey and the work that you do at Merida.
[Joe Mazzola] (0:46 – 1:45)
Sure. Yeah. So as you mentioned, my name is Joe Mazzola.
I got my PhD in IO Psychology from the University of South Florida with a concentration in occupational health psychology. So my research is generally in stress and fitness and nutrition in the workplace. Not always, but a lot of times qualitative, which is why I’m here to talk to y’all.
Kind of started my career at Roosevelt University in Chicago. I taught there for a few years and then ended up taking over, directing the master’s program there. And then when I got an opportunity to actually come down here to Meredith in Raleigh, North Carolina, they were looking to start a program.
So I’ve been here about eight years. We started a program that was supposed to kind of start small, but actually started kind of big pretty quickly. And so we’re kind of really proud of where the program is.
We have great students that get jobs all over the country and world, but also we’re the only master’s program terminally in Raleigh. So it’s kind of great to have that place in the market and to be able to bring in and send out great students. So it’s something brings me a lot of joy to be able to run that program and see where it’s come.
[Tara Behrend] (1:45 – 1:49)
And the Triangle area is growing so fast. I’m sure your students have lots of opportunities.
[Joe Mazzola] (1:49 – 1:55)
Yeah, it really is. I love living here too. So mostly great weather, maybe not so much the last few months, but we’re moving into the good times.
[Tara Behrend] (1:55 – 2:08)
I remember those not fondly. You mentioned that you attended graduate school at University of South Florida, which I think most people would think of as primarily a quantitative focus program. So how did you get into qualitative methods?
[Joe Mazzola] (2:09 – 3:30)
Yeah, it’s interesting. I never set out to be a qualitative researcher. I feel like it’s something that happens by accident.
Not sure something I’d recommend early career. It does take a little more time and sometimes a little harder to publish. Maybe we’ll get into some of that.
But my advisor, Paul Spector kind of got me interested in this idea of looking at stressors qualitatively. I think it’s something he had read about and kind of looked at, but hadn’t done much on his own. I think some of his past students had looked at it.
And so my first project that was qualitative was actually taking a bunch of things, a bunch of studies that had looked at stress qualitatively and actually reviewing them and seeing what common bonds, what common things we could find between them. And then that kind of inspired me to look at stress in graduate assistance specifically, because that’s what we were and we knew we were stressed. It’s like, let’s learn more about it in a qualitative way.
And so then I just kind of really kind of fell in love with that style. And once you kind of learn a method, you want to dabble in different things, but it’s like, okay, here’s something I’m good at. Let me keep doing that and learn things as I go.
I love the human element of qualitative, really getting to learn, not just like, oh, stress is at this level. It’s, okay, stress is at this level, but this person is telling me that they’re so overworked that they’re having physical symptoms or all these other things and kind of how it affected them. And I really liked that.
I think it does get lost in our research sometimes because we do so much quant. And quant is great. I do lots of quant stuff too, but I think that’s really what got me interested in it.
[Tara Behrend] (3:30 – 3:50)
Well, and I also appreciated that you mentioned sort of looking to your own experiences as a also, I think, a strength of qualitative research is being able to do that and sort of use your reflection and your introspection more than we might encourage in quantitative research. Was that a hard adjustment or do you feel like that went naturally?
[Joe Mazzola] (3:51 – 4:21)
I think for me, it was natural. And it’s weird because I was good in my stats classes, not to brag, but I could do the quant. At some point, you start getting into the really fancy ones and we’re not all, Richard, just great quant stuff.
And I’ve actually learned a little from you on our stuff on YouTube. So I enjoy, I appreciate those resources. I think it just really appealed to me to learn about people’s experiences and like just meld some of that personal and professional life.
It’s also why I study both like stress and fitness because those are things that interest me in my day-to-day life as well.
[Tara Behrend] (4:21 – 4:43)
So I think it’s really unusual that you both teach and do research in qualitative and quantitative. I can’t think of very many people who go back and forth that fluidly. So how do you think about those two approaches together?
And when you’re starting a new project, is it obvious which approach makes sense for that project or do you have to sort of think about it and consider more thoughtfully? How does that work?
[Joe Mazzola] (4:44 – 6:56)
Yeah. And that’s a great question because one of the things I was thinking about as I was talking today is that as much as I am a qualitative researcher, I kind of try not to label myself as a qualitative researcher because I think, you talk about this a little bit in the chapter, it’s a little bit limiting to think of like, oh, I do this or I do that. And it kind of forces people into corners and may even cause some of the things you were talking about, like people having less respect for qualitative and vice versa.
So I think even from early on, I mentioned that graduate assistance article, that’s actually a mixed methods study and it’s actually published in the Journal of Mixed Method Research that I didn’t know existed until after I did that study because I do think it’s great that qualitative can kind of compensate for the weaknesses of quantitative and vice versa. Again, I think you all talk about that a little bit. I like looking at what my research question is.
Again, you guys mentioned that in the chapter and thinking about what I need to answer it. But I also like the fact that those things, and particularly mixed methods, let me ask questions that you couldn’t ask with one or the other. So one of the things we ended up doing in that study, we took some of the common scales in quantitative that looked at stress, particularly I think there’s interpersonal conflict, work overload, and marginal constraints.
And we tried to look at, okay, when somebody scores on that scale, but in the qualitative where they can only give us one stressor, which is either one of those categories, a different category, or they told us no stressor in the last 30 days. I tend to not believe that occurred, but there’s something personality wise about those people who would say that. So I do think it’s a meaningful difference.
And we found basically on each of those scales, if you reported interpersonal conflict event, you had the most interpersonal conflict on the scale. If you reported a different type of events, you had the second most. And then if you reported no events, you had the third most or the least.
And so you can see that there is this connection between the qualitative and the quantitative. But at the same time, it wasn’t like a perfect correlation. So it’s not like one can substitute for the other.
And I’ve always kind of thought about qualitative, telling us more about salience, like, what’s the thing you think of when I ask you, like, what was your stressful event, versus like intensity, which we get more of the scale. So I’m not 100% sure I still got to answer your question. But just the idea that you need to like match your question to what you’re doing.
And being able to generate questions you wouldn’t be able to do otherwise with one method or the other.
[Tara Behrend] (6:57 – 7:13)
Yeah, I love that point. And, you know, I think what you’re raising for me is that qualitative research allows you to be surprised by things you weren’t necessarily looking for. Do you have any other examples of surprising findings that that you weren’t expecting, but came out of your qualitative research?
[Joe Mazzola] (7:13 – 8:39)
Yes. And also from other people’s research. So again, I’ve done some reviews.
So it’s gotten a chance to like really dive into the history of what people have done. And obviously, a lot of what I do is stress. So there’s going to be some examples.
But there’s an article, and I’ll say it’s from the early 90s, by Glaser and Busing about nurses. And they had done an intervention basically to the nurses were burnt out. And so they wanted to create a new type of ward where these people work, basically, some are still going to be in the traditional get through as many patients as you can sort of boards, and these new or holistic awards where they were working really one on one with patients that had much less patients, patient, doctor patients, or hospital patients, not they had less patients, and they didn’t want to work with them. But to give them more time to kind of work with them interpersonally, and they found like all the things they thought they would find, like, those people were more satisfied, they were more productive, most ways like their job better, but they were more burnt out, which was the opposite of what they expected. And the reason was that the areas that they were working with had, you know, relatively high mortality rates.
And so they were getting really close to these people. And then, you know, sometimes, unfortunately, losing them as happens in hospitals. And so they had so identified with them that now is creating this burnout, even though it had all these other and they had, like, they weren’t expecting that to happen.
And they’d almost kind of collected the qualitative as a secondary to the quantitative. But when they looked at the qualitative, they understood why because when they were asking these people, they would find out like, oh, this is the reason that they’re they’re having these burnout issues.
[Tara Behrend] (8:39 – 9:09)
That’s a great example. Earlier, you mentioned that qualitative research takes a lot of time, which I think is something that we can all identify with, like the years of interviews, and especially if you’re doing something like an ethnography. In addition to the extra amount of time, I think there is a lot that has to go into designing the research so that it can be defensible and rigorous.
So what are some things you mentioned, you’re a reviewer frequently, what are some things you look for in a qualitative study to know whether it was conducted rigorously?
[Joe Mazzola] (9:10 – 10:22)
Really, it’s that rigorous reporting of not only like, what did you do kind of step by step in collecting, but then also, like, if you’re doing some sort of coding, you’re doing something with the data, like, how did, how did you set that up? How did you stay objective? You know, normally, when I do these type of things, we usually have two or three different coders, we’re very careful on how we like set up categories to like create boundaries, like this goes in here, this goes in there.
And then like, how do you deal with discrepancies, because no one’s going to agree, you know, 100% of the time. So how did you basically all those decision points? What did you decide?
And kind of why did you decide it? Because quantitative versus qualitative aren’t necessarily more rigorous aren’t necessarily more objective, it’s how you do it, and what you’re doing with it. And having a reviewer, and like, sometimes I review a lot of qualitative papers, because I think sometimes at journals, I am the one expert, or one of the only ones.
And the ones that I’ve seen that are done poorly, I think are people who don’t have maybe the respect for qualitative, and they’re like, well, I gather some information, and here’s some results, but their, their method section doesn’t tell you anything about how they made those decisions, or how they tried to stay objective. And so you don’t know if the themes they’re reporting are just the thing that like, oh, that stood out, that was interesting to me, we’re putting it out there, we want to be as rigorous and objective as possible.
[Tara Behrend] (10:23 – 10:28)
Yeah, where do you think that belief comes from that qualitative research is just like easier, or just your opinion?
[Joe Mazzola] (10:29 – 11:35)
I mean, some of it’s probably just a misunderstanding, and people who don’t do it, or don’t read it. And so they’re not seeing the amount of work and objectivity that goes into it. The idea that if you’re going to do a qualitative study, obviously, you want to have some knowledge, hopefully some training in qualitative.
If somebody who wanted to do a qualitative study tried to do it without that knowledge, they would be just as unsuccessful as somebody trying to run a structural equation model without having studied how to do a structural equation model. The skills are probably a little more accessible, because some people are very scared of math or statistics or just are never going to get some of those concepts. But the training and understanding how to do it are still important.
So I think people are like, well, I could pick up qualitative in a day. And yeah, I would say probably you can’t. But you could pick up qualitative a couple weeks, where some people may never be able to pick up structural equation modeling.
For better or worse, we’ve moved in IO to let’s do the fanciest statistics ever. That’s probably a separate podcast. You know, whether or not every study needs to do that, people see that the most and like, well, that’s really rigorous.
And that’s the latest technology. But you know, qualitative continues to evolve and continues to get better. And I think people who do good qualitative, or as I mentioned earlier, really good mixed methods are adding really great things to the literature that wouldn’t be there otherwise.
[Tara Behrend] (11:35 – 11:39)
That’s a great point. So do your students at Meredith work on any qualitative research?
[Joe Mazzola] (11:39 – 13:15)
They do. I will say our program is mostly applied in terms of our students. We do offer thesis, we do offer research.
But I do spend a couple days teaching them qualitative so that they can go out with that skill. I’m happy to be able to provide that kind of extra thing. I’m sure lots of programs do, but I’m glad that we can do it as well at our program.
But I do have some students who work in my lab. We actually are working on a study right now, looking at economic stressors, which is kind of an emerging area, almost like it’s a comeback area. I think people were studying it and it’s sort of coming back again.
There’s been lots of Craig Kwan stuff already on it. But there was kind of a niche where we found that we thought we could add something that hadn’t been done to make the qualitative interesting because it didn’t seem like people had really looked at what are the individual things that people are saying are the problem. Also, we wanted to compare gig economy workers to those that are in an organization because we feel like they’re going to have different types of economic stressors.
For those that read some of my stuff, I do a little bit on challenge hindrance. We wanted to look at how those stressors that they were reporting to us, how they rated them as challenge versus hindrance, just to kind of see how that was going. So that’s what we’re working on right now.
And we actually, I think this summer just finished, my students did the coding with me. We haven’t quite gone and compared our analysis yet of where we’re the same, but I think they really enjoy working on that again because they get to see that human element and they don’t necessarily get lost in the numbers. Because I think a lot of times you work on stuff with students and they’re really bright.
They understand this stuff, but sometimes they might just be like, oh, cool, we’ve done this data. And now you’re going to go run the meta-analysis. You’re going to run the structural equation modeling.
And then you’re just going to tell us what happened at the end, but they get to really dive into this type of data and really understand what we’re doing.
[Tara Behrend] (13:15 – 13:45)
I think that’s so important. I mean, we’re supposed to be a field that is studying human experiences. It’s so easy to forget that there are humans behind the Qualtrics data set.
I think it really helps you connect back to what this field is for on some fundamental level when you’re reading about the experiences of people, especially on the topics that you work on, which is about stressors and job security. And it seems like it’s incredibly helpful for questioning our assumptions as a field. You must see that when you’re reading other research, like they just don’t get it.
They haven’t talked to any people.
[Joe Mazzola] (13:46 – 14:31)
Right. Yeah. I think the stress field in general, we’re doing great things and we’re trying to help people.
But again, when you just look at the numbers, yeah, we can compare this organization, their work overload is higher than other organizations or the norms or whatever. But then it’s like, OK, well, then why? And I think I can say for most of my career, I’ve been kind of the classic academic where I wasn’t that doing that much applied work, wasn’t like doing practitioner stuff, but I’ve done it in more recent years.
And I was always include some qualitative questions. And typically, I feel like the organization is more interested in those results a lot of times than the quantitative stuff. And I do think it’s it’s more actionable.
It’s like it’s one thing like, oh, they’re really dissatisfied with their leadership. But then you look at the qualitative stuff and it’s like, oh, here’s why. So we can address that specifically.
[Tara Behrend] (14:32 – 14:46)
That’s a great point that for people who are going in to work with organizations, they need to be able to do both and to be able to communicate with really salient examples that are also rigorous, though, right, that aren’t just like, someone told me in the hallway that this is true.
[Joe Mazzola] (14:47 – 14:47)
Exactly.
[Tara Behrend] (14:48 – 14:58)
Thinking back to your own sort of experiences and maybe learning the hard way in some cases, is there advice that you wish someone had given you before you started doing qualitative research?
[Joe Mazzola] (14:59 – 16:35)
I mean, besides don’t do qualitative research. One of the biggest lessons I’ve learned and this is like not every qualitative study is going to code. That’s also where like I maybe I don’t think of myself as much of a qualitative research because I take qualitative data and I make it quantitative a lot of times.
And I can actually tell you, I’ve I’ve sent it to qualitative journals and they’ve said, nope, this isn’t qualitative. Like so like asking, asking questionnaire, open ended questionnaires and coding it. They don’t think of that as enough as qualitative sometimes.
But when we do coding, it’s really, really important that you create really strong boundaries between the different categories that you’re trying to code. And I can tell you an example, like we said, this takes more time. So we did a study looking at barriers and facilitators to nutrition and exercise behaviors.
And it was we got a small grant to do it. So it was a diary study where they gave us four days of data on each of those. We actually had nutrition barriers, exercise barriers, nutrition facilitators, exercise.
So we had four questions, four days, 100 participants, and we had to code every single one of those. And I can’t remember what the specific categories were, but we did not create strong enough boundaries between them. And our iterator reliability was all over the place where basically we’re like, yeah, this coding isn’t usable.
We need to go back, recreate the categories and do all that again. So I think making sure you kind of know what you’re doing right the first time. So you’re not making a long process even longer is good advice.
And again, it comes down to that, like whether it’s qualitative or quant, you know, you’re going to make mistakes along the way always, no matter what you do. But like having that training so that they’re minimized as best as possible.
[Tara Behrend] (16:35 – 16:43)
So you mentioned that you read the chapter, which I appreciate. Are there things that you wish we had included if we had infinite space that sort of that weren’t in there?
[Joe Mazzola] (16:44 – 18:01)
That’s a good question. I don’t know if I thought of anything specific. I think it’s great that you all described all those different types of qualitative data or graphic collections at the end.
I will say I don’t, having read a lot of stuff in our field, I think most of those don’t get used at all in our field. So I think it’s good that’s in there. Maybe people will start doing more case studies and more ethnography.
But it’s like, for the most part, I think people are mostly just doing open ended questionnaires, interviews, and occasionally focus groups. And that’s kind of what we have in our field. But I think more naturalistic operation would be great.
I liked the idea of, you know, we teach action research, but I feel like it’s not something we do very often in our field. And that actually brought up an interesting point for me, kind of the reactivity of qualitative and could we actually use that as an advantage to do action research? Because that same study we did on nutrition facilities and barriers, a couple of people actually responded that they felt looking at their barriers and facilitators on a day-to-day basis and writing them down became a facilitator for them to exercise better and eat better than they were before, than they were planning.
So it was kind of interesting to see that as we went along, we almost kind of like primed them to do something different. And then it’d be interesting to almost like switch the research at that point, have everybody do that and see how it changed their behavior or something. So I think there’s lots of potential to do really interesting stuff with some of those areas, but again, we just kind of don’t do it as much as we could.
[Tara Behrend] (18:01 – 18:36)
That’s a great point. Like some of the, you know, the design and development of technology research actually could be thought about in a qualitative paradigm where you’re talking to people about their experiences. And I do think that most of us in the field have a automatic tendency to go towards numbers and things like inter-rater reliability, but then there are people who say, why would you expect two raters to have the same experience?
Why would you expect them to see the world the same way? Which is, I think, a very difficult resetting of the way we think about research and what research is. So I think it’s especially impressive when you can switch back and forth between those kinds of mindsets.
[Joe Mazzola] (18:36 – 19:09)
Yeah. And something else that I had in the chapter that I thought was a good point is like part of why we do less qualitative. It’s used more, it’s more valuable in like discovery or things that we don’t know much about, but I think we also have to remember our field is changing all the time.
Work is changing all the time. We barely talked about Zoom fatigue until a decade ago, and then it blew up in during COVID that everybody was like learning about it. That’s something that we can, we see it coming or it’s just, it’s new.
Let’s look at that qualitatively or, you know, quiet quitting, which now everybody, not just IOs, but everybody talks about quiet quitting, but again, it’s a relatively new concept.
[Tara Behrend] (19:10 – 19:12)
That’s a great point though. We can be responsive to current events.
[Richard Landers] (19:13 – 19:59)
So one of the things that, I don’t want to call it a gateway drug, but one of the ways that I often get want to focus folks to start thinking about fall is actually through the lens of meta-analysis. When, you know, completing the coding for a meta-analysis, you’re forced to tackle a lot of complicated questions that coders don’t expect to tackle and really start to begin sort of light exploration of some of those ideas of what biases am I bringing to how I’m doing this? And it seems to be at least an okay way to get, at least to encourage people to start, to start questioning their assumptions.
Are there any other good entry points you think? How do you start somebody that’s been like traditionally just all quant, like where do you begin to try to like unravel those beliefs?
[Joe Mazzola] (19:59 – 22:15)
I think what you mentioned is good to like think about, like we make decisions in research all the time. And a lot of times those are qualitative type decisions. And you said like, well, okay, I’m going to do a meta-analysis.
How am I going to code, you know, the gender of the study? Like what percentage they had, or how am I going to code location? Like that is qualitative coding in some sense.
That is a decision you’re making. The practitioners, I can be a good place for that entry again. Like ask some questions, you know, if you’re working in organizations, ask some questions that are more open-ended to get that.
And like, I think once you see that you get interested in it and you’re like, okay, well, how do I, how do I put this in a meaningful quantitative way that I can present to an organization? While also like, I can tell you, I sometimes forget about the rich descriptions and I want to make sure that it’s one of the strengths of qualitative. I want to make sure I’m bringing those out because I get so excited about coding, but it’s also like, okay, we’ve coded these in the categories.
We know these people had work overload. Let me now give some of those rich descriptions of the work overload. So I think that helps people to see the value and to see that they’re doing this, even if they don’t think of themselves as qualitative researchers.
And something I was thinking about as we were reading some of the, some of the chapter about like using archival data, I think that’s another area where a lot of that data is out there and people could really be utilizing that. And we could be learning a lot from it. My colleague and I, Chris Cunningham, we’re working on a study that basically is taking a lot of the stress theories because we’ve had stress theories popping up over the last 50, 60 years, even beyond, and trying to look at like, which ones are driving the research, which ones are maybe the, we came up with some definitions for what it means to be valid, but obviously that’s a very loaded word.
How practical are they? And when we started doing it, we didn’t think of it as a qualitative study, even as myself as a qualitative researcher. But at some point we had to develop a coding for, we’d end up doing a three-point scale of like, this is really high.
This is kind of average, you know, this is maybe a little bit lower on this. And so it sort of became a qualitative study that we didn’t even think was when we were doing it. And it also brought up another interesting point of something y’all talk about in your chapter of the context of who we are and the biases that we come with.
I think it’s really important when we do publish this paper, like talking about like, here’s where we come from, because I’m sure people are going to disagree a little bit about how we rated them, no matter how objective we are, no matter how much we list out, like this is the process that we tried to do.
[Richard Landers] (22:16 – 23:38)
Yeah, that kind of differences in bias management between Qual and Quant are really fascinating to me, that in Quant there’s this constant fight to say, well, how do we make this as objective as possible, right? And in Qual, there is a much more of an embracing of the inherent complexity of whatever phenomenon that you’re trying to understand. You know, a dimension of that too is when we’ve written up, we haven’t done a lot of Qual work, but we have done a little bit.
And I found one of the biggest challenges I’ve hit with students, phrase for it, it’s a show don’t tell, I think is the, you know, the write up advice, where they’re like, their intuition is to try to take the complex phenomenon when they write it up in this like results of discussion section and like simplify as much as possible, like what’s the underlying rule or idea. And I found it’s a really big fight to be like, no, you’re, you don’t even know, like we’ve, we’ve talked about it, but you still don’t know the full range of assumptions you’re bringing. And someone else can just read this completely differently than you.
And that’s actually part of the point. That’s often a hard hill to get over in trying to explain how to, how to consider your own bias. Have you, I don’t know, I’m really curious about your experience training students in these ideas.
Like, are there, are there certain people that just take to Qual and, and take more to Quant or is it, is it always, is it just building up a, you know, a skillset from the base? Like what’s, what’s your experience?
[Joe Mazzola] (23:38 – 24:18)
Yeah, I think it’s more building up the skillset like anything else. I think they could be lying to me, but all the students that have worked with me and done Qualitative seem to enjoy it. I think it’s because they can get their hands on it a little bit more at the stage that they’re at, you know, particularly we have great master students in our program nationwide, and I, we have great master students, but most of them aren’t going to like learn really hard Quant and aren’t going to do that in their jobs.
So like, but this is something they, and we’ve been able to show them both in the practical stuff we do and in the research that like, this is stuff you might actually do. And that organizations are going to value, you know, they, they like this data on top of the quantitative data. So anybody can do it.
And I think people do take to it once, once they kind of get their hands on it.
[Richard Landers] (24:18 – 25:11)
Yeah, that the idea of practicality is, is really a fascinating one. You know, one of the, one of the things that I hear sometimes is that we train these students in really deep and complex stats sometimes. And then once they get out, like it’s like 75% Excel and they can do graphs.
And that, that deeper level is only occasionally needed. And it seems like Qual in a lot of ways is a much more practical skillset. And also it feels like that simplification on the Quant side, once you get into practice is in many cases dangerous because it sort of glosses over the realities of an organization in a way that if you’re doing good Qual work, it explicitly forces you to like tackle that head on.
Part of the reason why we included the content in the book, despite, you know, IO as a research domain certainly tends to aim more Quant, but the Qual side seems important in so many dimensions. We just, we need to emphasize it more.
[Joe Mazzola] (25:12 – 25:21)
And I, and I appreciate that. I only read the one, but I know it referenced that there is a second one. So I’m glad that it’s two qualitative chapters in your book.
That’s amazing. We appreciate that.
[Richard Landers] (25:21 – 26:12)
Brings another question. Cause we, we also in part talk about mixed methods approaches where, you know, there’s, there’s sort of this three bigger buckets where you have the kind of Qual Quant, which I think is exploration where you get some interesting, like, you know, novel ideas from your, your Qual side and you try to confirm them on the Quant side. And then you have the explanation path backwards where you do your Qual study, get some or do your Quant study and then try to get extra information about why that happened.
And then a triangulation where you’re just trying to do like multiple studies that all point kind of in the same direction. Mixed methods, I think is like the single most underused technique we have, like period is yeah. So how much you mentioned mixed methods a little bit earlier.
So is that something you’re actively pursuing? How do you balance? Like, you know, it’s, it’s essentially doing more than one study now.
So how do you, how do you tackle that kind of?
[Joe Mazzola] (26:12 – 27:43)
Right. Yeah. And I will say it’s obviously several books on Quant cause you would need to learn like all the different stats there.
You can build in a huge book on qualitative. And I’ve read an entire book on mixed, just mixed methods. It’s a whole another field.
When I ended up publishing that mixed method journal, they’re like, well, you have to label it by what it specifically is and you need to set it within the mixed method research. So like there are, I want to say mine was like a concurrent exploratory. It’s like these really fancy words.
So that’s, there’s lots of really interesting ways to do. You mentioned a couple of them, but there’s even more than that. Again, I think it answers so many interesting questions.
I think whenever I’m designing a study at this point, I’m like, okay, if I’m going to be qualitative, like here’s the questions I really want to answer. So I think I do tend to start on the qualitative side, but then I’m like, but what quantitative stuff can I add in here? That’s going to add to that story.
So I think when we talk about the practical stuff, most people are going to come at it from the other way. I’m doing a quantitative study. Yeah, sure.
I’ll throw in a couple of qualitatives at the end because I might, I might need to be able to explain that data if something weird comes out or something like that, which is important. I’m glad people are doing that. I will say, and I tell my students this all the time when they’re doing like a thesis, don’t put in a qualitative question that you’re not going to do anything with because it’s, you know, coding, it takes forever.
So if you don’t want to do that, don’t do it. It’s going to put a fatigue on your participants that you don’t want, because it takes a lot longer to sit there and write something out or type something out for a qualitative question than it does a quantitative. So again, we want to be purposeful in anything we’re doing, but yeah, I think in my brain now it’s okay.
I’m doing something that’s more qualitative, but how do I make it mixed methods and how do I use that to answer questions I couldn’t answer otherwise?
[Tara Behrend] (27:43 – 27:56)
Oh, I do have one more question for you. We’ve been asking various guests how they feel about the integration of AI into their work. And so can AI do content coding and qualitative research?
[Joe Mazzola] (27:57 – 28:59)
So I will say that, A, this is something I have mostly avoided. And I think AI has been around longest in qualitative because I think natural language processing and content analysis has been one of the things that it’s been doing for us for a while. My understanding particularly in the early days was you still had to tell it everything that it was going to do.
So to me, I’d rather do human coders and just have that control over it. But I do think as it’s getting better, I mean, we know it can do all these summaries. Like right now, if I pulled up my texts on Apple, it would give me a summary of the text that I got.
So it can summarize things. I think it’s probably pretty decent at themes, but I’m the last person to have expertise in AI. But I think like anything else, we need to be careful both to make sure it’s doing what we want and that we’re not losing the human element, particularly when we just said that in qualitative, the human element is kind of the point.
So I think we should never dismiss a technology, but we always want to be careful. And again, we’re IO psychologists, so we always want to have our hands in it no matter what we’re doing.
[Tara Behrend] (28:59 – 29:13)
Right. You don’t want to just trust the answer without interacting with the data yourself and really thinking about it. I think that’s great advice.
Joe, thank you so much for this great conversation and for all of your insights and wisdom. We really appreciate you coming on the show.
[Joe Mazzola] (29:13 – 29:26)
Yeah. Thanks for having me. I’ve always enjoyed being, like I said, I didn’t set out to be either a qualitative researcher or a advocate for it, but it’s something I do believe in and do really love doing.
So I’m always glad when I can talk about it and get more people to learn about it.
[Richard Landers] (29:26 – 29:40)
Amazing. That’s it for another gig. To stay in touch, subscribe on YouTube, check out our website at thegig.online, join our LinkedIn group, sign up for our email notification list, and join our Discord. Thanks for joining us and see you next time for another great IO get-together.