So, I'm starting in the fall at a clinical PhD program. I am scheduled to work with a specific adviser, although recently, I've been looking at published research by other faculty members in the department. One faculty member's work, which I am intrigued by, specializes in "practitioner-generated case-based" psychotherapy research (i.e., the researcher/therapist tracks the symptom status of one psychotherapy patient across baseline and intervention phases). I'm hoping to get your opinions about this type of research and whether you find it to be valid and worthwhile. I understand that RCT (large group, nomothetic designs) are unambiguously the mainstay of clinical science and "the design of choice" because of potential issues with intersubject variability and the importance of considering aggregate benefit. But are these n=1 studies also a viable option for understanding human behavior? Does this type of idiothetic research qualify as a true experiment and can it stand next to the more mainstream, large N studies? Does it hold water in terms of rigorous, scientific research? Thanks!
N=1 studies, valid?
- Thread starter McClinas
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I think a carefully designed N=1 study allows for a rich and unique window into human psyche. Having said that, these days there is a trend towards RCT, specially if you want to get published and get real respect in the scientific community.
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Case studies can allow for very in depth information that cannot be studied (or at least easily) by quantitative studies. They can also be wonderful starting points for a particular area of research, which can then be branched out to quantitative studies. There's definitely a place for case studies and qualitative research as a whole in clinical psychology.
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I would only add that comparing traits can sometimes lead down a theoretical framework nightmare if not conducted properly and I would add after a raw qualitative result is found, I would still conduct quantitative analysis to see what what kind of results might be found.
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It is not a bad way to gain understanding that strictly mathematical apps do not tease out well. However, if not carefully funded and constructed these qualitative methods can become a big joke.
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I'm not too familiar with it but the area of behavioral analysis mainly uses single-case design and it's definitely not "not mainstream". While studies with large n give you an idea what the the average of the population is like but it doesn't tell you anything about the individual. Single-case design allows you to assess the the process of change step by step and what is responsible for it, whereas in quantitative studies you just get an idea what "on average" caused a change.
Well bottomline ( I know most of you know this) is, that both design have its ups and downs.
Well bottomline ( I know most of you know this) is, that both design have its ups and downs.
Nothing wrong with doing this kind of research when appropriate opportunities arise, though its not something I would plan on basing a career off (at least at a major university).
Like much of science, the devil is in the details. Framed as exploratory or illustrative, they can be incredibly helpful. Trying to infer causality without a comparison group....that's not going to make you any friends in academic circles. I wouldn't make it a focus and the end-all be-all of your scientific training, but I think it can be an important complement in appropriate situations.
Like much of science, the devil is in the details. Framed as exploratory or illustrative, they can be incredibly helpful. Trying to infer causality without a comparison group....that's not going to make you any friends in academic circles. I wouldn't make it a focus and the end-all be-all of your scientific training, but I think it can be an important complement in appropriate situations.
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There's always something to be said about small N research and case studies. Research in general has to be balanced; without the small sample research that finds new and alternative things to study, many large sample stuff wouldn't happen. OTOH, large sample research tends to be more valid. So, in short, both are important and you should pick which one is right for you.
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Well, again, that is not necessarily correct. In single-case design you can very well infer causality, (e.g. with different design like multiple baseline, etc.) because you are essentially comparing the individual's behavior during the treatment condition and the baseline condition and if you switch back and forth between those multiple times and the behavior changes accordingly, you can very well infer causality. However, like the name says, it s-i-n-g-l-e case design and what works for one individual, might not work for another. On the other hand, this is similar for studies with a large n: Just because the population on average behaves in/reacts to something in a certain way, doesn't mean, it helps the individual, simply because he or she doesn't necessarily represent 'the average."
As a matter of fact, if you read journals like the Journal of Applied Behavior Analysis (which is highly reputable), you'll see that the majority of those studies are single-case design and those researchers are very successful in their field.
True, I probably should have been more specific. In multiple baseline research, you do essentially have a "comparison group" it is just within-subjects, rather than between. This is perhaps a representation of more optimal designs for single subjects research, though I think it carries its own set of problems I won't get into here.
Regardless, I maintain that anyone focusing solely on a single-subject designs is going to have a tough time of it in this field. Perhaps within the specific domain of ABA that is an exception, but I'm hard-pressed to think of a single well-known individual in the broader field who has made a name for themselves doing this type of research exclusively, though many include it as part of a broader research program (which I'd consider a significant strength).
Regardless, I maintain that anyone focusing solely on a single-subject designs is going to have a tough time of it in this field. Perhaps within the specific domain of ABA that is an exception, but I'm hard-pressed to think of a single well-known individual in the broader field who has made a name for themselves doing this type of research exclusively, though many include it as part of a broader research program (which I'd consider a significant strength).
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McClinas, because I'm currently looking at many faculty at many universities, deciding where to apply, my question/observations would be are you seeking an academic career? My observations are that the majority of faculty (I've only been looking at funded programs) are quantitative. If I were to guess (and again, this is only funded clinical and counseling PhDs) I'd say maybe 8 percent that I've come across so far fit the qualitative research school, and of those probably 75 percent are older.
Now, things also seem to come in waves in psychology (and given the length of training it will take a while to catch up) so I'd predict in a few years there will be a lot more faculty who state positive psychology is their main area of focus, and maybe there is a qualitative movement out there as well?
Now, things also seem to come in waves in psychology (and given the length of training it will take a while to catch up) so I'd predict in a few years there will be a lot more faculty who state positive psychology is their main area of focus, and maybe there is a qualitative movement out there as well?
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Truly nomothetic/ idiothetic methods are really difficult to really conduct in the real world.
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As others have said, N=1 studies can be very useful and informative, and definitely have their place in the scientific scheme of things if done well (especially in terms of exploratory/pilot work). Cognitive rehabilitation as a field, for example, often seems to use case-study designs in the initial phases of treatment and theory development, given how difficult it can be to truly match different types of insult/injury sequelae into well-defined groups. N=1 designs can also, at times, allow you to pay more attention to how/why a particular treatment works rather than just determining if it is, in fact, effective.
