One of the secrets of science is to understand the language of science, and science’s primary language is the research study. Research studies allow scientists to communicate with one another and share results of their work. There are many different kinds of research and many varying fields of research. And although journals were designed to help professionals communicate such research findings with one another, many times professionals in one field don’t significantly interact with (or are even aware of) researchers in a different field than themselves (e.g., a neuropsychologist may not keep up on the same research findings as a neurologist). This article reviews the major types of research done in the social, behavioral and brain sciences and provides some guideposts to better evaluate the context in which to place new research.
Types of Research
The basis of a scientific research study follows a common pattern:
- Define the question
- Gather information and resources
- Form hypotheses
- Perform an experiment and collect data
- Analyze the data
- Interpret the data and draw conclusions
- Publish results in a peer-reviewed journal
While there are dozens of types of research, most research done falls into one of five categories: clinical case studies; small, non-randomized studies or surveys; large, randomized clinical studies; literature reviews; and meta-analytic studies. Studies can also occur in widely varying fields, from psychology, pharmacology and sociology (what I’ll call “behavioral and treatment studies”), to genetics and brain scans (what I’ll call “organic studies”) to animal studies. Some fields contribute results that are more instantly relevant, while others’ results may help researchers develop new tests or treatments decades from now.
Clinical Case Studies
A clinical case study involves reporting on a single case (or series of cases) that the researcher or clinician has tracked over a period of some significant time (usually months or even years). Many times, such case studies emphasize a narrative or more subjective approach, but may also include objective measures. For instance, a researcher might publish a case study about the positive effects of cognitive-behavioral psychotherapy for a person with depression. The researcher measured the client’s level of depression with an objective measure such as the Beck Depression Inventory, but also describes in detail the client’s progress with specific cognitive-behavioral techniques, such as doing regular “homework” or keeping a journal of one’s thoughts.
The clinical case study is a very good research design for generating and testing hypotheses that may be used in larger studies. It is also a very good manner for disseminating the effectiveness of specific or novel techniques for individuals, or for those that may have a fairly uncommon set of diagnoses. However, generally a clinical case study’s results are not able to be generalized to a broader population. A case study is therefore of limited value to the general population.
Small Studies and Survey Research
There’s no specific criteria that differentiates a “small study” from a “large study,” but I place any non-randomized study in this category, as well as pretty much all survey research. Small studies are generally conducted on student populations (because students are often required to be a research subject for their university psychology classes), involve less than 80 to 100 participants or subjects, and often lack at least one of the core, important research components most often found in larger studies. This component can be the lack of true randomization of subjects, a lack of heterogeneity (e.g., no diversity in the population being studied), or a lack of a control group (or a relevant control group, e.g. a placebo control).
Most survey research also falls into this category, because it also lacks one of these core research components. For instance, a lot of survey research asks participants to identify themselves as having a particular problem, and if they do, then they fill out the survey. While this will almost guarantee the researchers interesting results, it’s also not very generalizable.
The upshot is that while these studies often provide interesting insights and information that can be used for future research, people shouldn’t read too much into these research findings. They are important data points in our overall understanding of the subject. When you take 10 or 20 of these data points and string them together, they should provide a fairly clear and consistent picture about the topic. If the results don’t provide such a clear picture, then there is likely more work to be done in the subject area before meaningful conclusions can be made. Literature reviews and meta-analyses (discussed below) help professionals and individuals better understand such findings over time.