Most research methods in psychology are quantitative: numerical data are used to address a research question. Quantitative approaches include the following:
Some psychology research is qualitative (i.e., uses nonnumerical data to explore a research question). Qualitative research approaches include the following:
- Interviews and focus groups
- Case studies
- Survey research
- Observational research
Mixed-methods research combines qualitative and quantitative approaches.
Continue reading: What are common research methods in psychology?
Research methods are the steps you follow when conducting research. A methods section should describe the type of research you’re conducting, sampling techniques, data collection methods, and data analysis.
Research methodology instead focuses on the theory behind your research methods and why you chose them to address your research question.
Though people sometimes use the terms method and methodology interchangeably, they are not the same. Methods describe how you conduct your research, and methodology describes why you chose these methods.
Continue reading: In research, what is the difference between methods vs methodology?
Case studies have historically been used in psychology to understand rare conditions. For example, Phineas Gage was a railroad worker who had an iron rod driven through his head in an accident and miraculously survived. However, this accident drastically altered his personality and behavior for the remaining 12 years of his life.
Detailed studies of Phineas Gage helped scientists realize that different areas of the brain have specific functions. This famous case study is an example of how studying one individual in detail can provide insights that drive the formation of broader theories.
Continue reading: What is a case study example in psychology?
Though case studies can be classified in many ways, the most common types are intrinsic, instrumental, and collective case studies.
Intrinsic case studies focus on a specific subject (i.e., case). The point of such studies is to learn more about this specific subject rather than to generalize findings.
Instrumental case studies also focus on a single subject, but the intent is to generalize findings to a broader population.
Collective case studies have the same purpose as instrumental case studies—to use findings to increase one’s understanding of a broader topic—but they include multiple cases.
Continue reading: What are the types of case studies?
An interrupted time series design is a quasi-experimental research method. It is similar to a pretest-posttest design, but multiple data points, called a time series, are collected for a participant before and after an intervention is administered. The intervention “interrupts” the time series of observations.
If scores taken after the intervention are consistently different from scores taken before the intervention, a researcher can conclude that the intervention was successful. Considering multiple measurements helps reduce the impact of external factors
Continue reading: What is an interrupted time series design?
Regression discontinuity design is a quasi-experimental approach that compares two groups of participants that are separated based on an arbitrary threshold. This method assumes that people immediately above and immediately below this threshold are quite similar. Any subsequent differences between these groups can therefore be attributed to interventions that one group does or does not receive.
For example, imagine you’re testing the efficacy of a cholesterol medication. You administer this medication only to patients whose cholesterol levels exceed 200 mg/dl. You then compare heart health indicators of patients with cholesterol levels slightly over 200 mg/dl, who do receive the medication, to patients with cholesterol levels slightly below 200 mg/dl, who do not receive the medication. If the heart health of the former group improves relative to the latter group, you may conclude that the treatment worked.
Continue reading: What is regression discontinuity design?
A pretest-posttest design is a quasi-experimental research design. Two data points are collected for a participant: one from before an intervention is introduced and one from after an intervention. A difference in these scores may indicate that the intervention was effective.
For example, imagine you complete a depression inventory before and after a 6-week therapy program. An improvement in your score may indicate that the program worked.
Continue reading: What is pretest-posttest design?
In a true experiment, participants are randomly assigned to different study conditions. A quasi-experiment lacks this random assignment.
True experiments are also usually conducted in controlled laboratory settings, which facilitates control of confounding variables that may impact study results. Quasi-experimental designs often collect data in real-world settings, which increases external validity but reduces control of confounds.
Finally, both true experiments and quasi-experiments generally involve the manipulation of an independent variable to determine its causal effect on a dependent variable. However, in a quasi-experimental study, researchers may have less control over this manipulation (e.g., they may be studying the impact of an intervention or treatment that has already happened).
Continue reading: What is the difference between a true experiment and a quasi-experiment?
Practical or ethical concerns may prevent researchers from using a true experimental design:
Practical concerns that prevent researchers from conducting a true experiment may include the cost of a study or the time required to design the experiment and collect and analyze data.
Ethical concerns may also limit the feasibility of true experimental research. It would be unethical to intentionally prevent study participants from accessing medication or other treatments that the researcher knows would benefit them.
In these cases, a quasi-experimental design may be more appropriate.
Continue reading: When should I use quasi-experimental design?
The four main types of mixed methods research designs differ in when the quantitative and qualitative data are collected and analyzed:
- Convergent parallel design: Qualitative and quantitative data are collected and analyzed simultaneously and analyzed separately. The results are then compared, and similarities and dissimilarities between the findings are discussed.
- Embedded design: Either qualitative methods or quantitative methods are the focus of a study, and additional methods are used to support these main findings.
- Explanatory sequential design: Quantitative data are first collected and analyzed, then the results or patterns are explained using qualitative methods.
- Exploratory sequential design: Qualitative data are first collected and analyzed, then emergent themes are explored in more detail using quantitative methods.
Continue reading: What are the types of mixed methods research designs?
