The scientific process is the foundation of the field of psychology. In other words, psychologists do not simply make claims about social phenomena; they utilize a systematic and rigorous process called empiricism to draw conclusions. In conducting empirical research, psychologists collect evidence using their senses (e.g., sight, sound) or using instruments that assist their senses (e.g., thermometers, questionnaires; Morling, 2020). The scientific process tends to be reliable because it can be independently verified by other scientists, creating a sense of stability and consistency. Let’s explore each step of the scientific process and then discuss how researchers make decisions throughout the process that might reflect hidden assumptions or bias.
Doing Research
What key elements of the research process do you need to understand in order to critique the research presented in this book?
Because we’re constantly in situations where sex/gender is relevant, ideas for research can come from everyday interactions. For example, you may have noticed that boys got into more physical fights in your high school than girls did. Such observations can result in the development of a theory, or a proposed explanation for why certain things occur. Initially, theories can come from personal observations or from previously established concepts. They are then refined through the process of collecting data and drawing conclusions based on those data (Figure 3.2). However, designing and executing a research study involves many decisions. With each decision, bias can creep into the process.
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A diagram depicts the circular nature of research. A series of five text boxes create a column down the center with arrows pointing from one down to the next. When read continuously, the text boxes read: Theory leads researchers to pose particular research questions which lead to an appropriate research design to test a specific hypothesis. The hypothesis is ideally preregistered before they collect and analyze data, which feed back into the cycle. The last text box has two arrows on either side pointing to two text boxes on either side of the center column. The one on the left reads: Supporting data strengthen the theory. The text box on the right reads: nonsupporting data lead to revised theories or improved research design. An arrow labeled “support” points from the text box on the left, back up to the first text box in the center column that begins with “theory”. The text box on the right has an arrow labeled “revision” also pointing back up to the first text box in the center column. Additionally, an arrow from the text box on the right about nonsupporting data points to the center text box of the center column that reads: research design to test a specific hypothesis.
Figure 3.2 The Research Process
One important thing to note about the research process is that it’s not a single line of steps with a defined end. Research is a circular cycle in which findings lead to new and revised questions and further investigation. Note: This figure is adapted from Morling (2021)
Let’s say you start with a theory that men are more aggressive than women. From the start, this theory itself is based on assumptions—specifically, that there is a gender binary and that women and men are different. So if you start with this theory, you may end up making decisions throughout the research process that work to confirm it (e.g., only recruiting cisgender participants, only assessing physical aggression). Your theory will lead to a testable hypothesis, or prediction. In our example, your hypothesis might be: “Men are more likely to commit acts of aggression than women.” Each of the italicized words in the hypothesis is a variable, and variables can be measured in many different ways. When we decide how to measure a variable, we operationalize that variable. So how do you operationalize aggression? Will you measure physical aggression or other, more relational, types of aggression such as teasing, gossiping, or excluding others? Decisions such as these will profoundly affect what questions you ask and what you find.
The research process requires expanding your investigation and collecting data from a larger number of people than those you can observe in your own life. The people in your study are called your sample. Recruiting people you already know or have access to results in what is known as a convenience sample. You might ask fellow classmates or post a message about your study on Twitter. Of course, this approach might mean that all the people in your sample share similar characteristics because they all have something in common: their relationship to you! It’s more challenging to recruit participants you don’t know, and for this reason, it might be necessary to offer an incentive for participating in your study. This type of recruitment takes longer and requires more resources—including money to pay for the incentives. An additional concern is that by virtue of assessing women and men, you have intentionally excluded people who do not identify within the sex/gender binary. This decision about your sample renders some people completely invisible and further reinforces the binary.
You next need to determine your research design. Will you use a survey, or will you put people in a situation and see whether they act in an aggressive manner? Most psychological research relies on quantitative methods, approaches that attempt to represent variables with numbers. For example, you might have a group of people fill out a survey that asks them to report how often they engage in aggressive behaviors. Once all participants respond, you would aggregate the data and analyze it. Psychologists often focus on evaluating statistical significance. For example, if men collectively score 20 on the aggression measure while women collectively score 15, what does this mean? How likely it is that this pattern reflects a group difference is often indicated as probability, or a p-value, and results are typically considered statistically significant if p < .05. This level of statistical significance means that there’s a probability (p) of less than 5% that the results of the study are due to chance.
Finally, you might want to write up the results of your study and submit them to an academic journal for peer review. During the peer-review process, experts in the field review the research and determine whether it meets a rigorous standard for publication. If the reviewers and the journal editor decide that the research is of high value, it will be published. In our example, you might submit your report to a journal that focuses on sex/gender, such as Sex Roles. By choosing this journal, you know that the reviewers are other scientists with expertise in sex/gender.
Not all research that is published can be easily read by others. Often there is a paywall, making research difficult to access. You also might publish your research, but no one will pay attention to it. In contrast, sometimes the media gets hold of a research article and writes about it. If that happens, your paper may be featured in blogs and Twitter posts. By the time your research findings reach the public, all the decisions you made that may have biased your results are no longer visible. Your research may take on a life of its own and may be integrated into a book such as the ones mentioned at the start of the chapter.
Experiments versus Correlational Research
What are the key differences between experimental and correlational designs?
If you have already taken a statistics or research methods course, you may have noticed that the survey example described above isn’t an experiment. Having people take a survey that asks about their experiences with aggression would be considered a correlational design. In a correlational design, relationships between variables are examined—in this case, the relationship between aggression and sex/gender. One of the most important tenets of research is that correlation does not imply causation. In other words, even if variables are related, it doesn’t mean that one caused the other. For example, if umbrella sales go up when grass grows, it doesn’t mean that selling umbrellas causes grass to grow or that growing grass causes increased umbrella sales. In this case, they’re both caused by another variable: rain. In an experiment, however, the researcher manipulates a variable in order to investigate whether changes in that variable (the independent variable) cause a change in another variable (the dependent variable).
Your Turn
In what ways have your views on any topic been influenced by reports about scientific findings? How often have you questioned the results of a scientific study presented in the news or through social media? Have you noticed bias in the way science is reported? If so, in what way? Ask three people if they would question a scientific finding presented in the popular press. Now find a news story summarizing a research study, locate the original research report, and compare the two. Is the summary in the news story accurate? Is it complete? What are the differences between the way the journalist framed the results and the way the scientists did?
A key component of many experiments is random assignment—the process of assigning participants to conditions in a way that guarantees all participants have an equal chance of being in any group. For example, you might randomly assign one group of participants to watch a violent video and another group to watch a nonviolent one. Then you could see whether levels of aggressive attitudes or behaviors are higher after watching the violent video. If they are, you could say that watching the violent video caused an increase in aggressive attitudes or behaviors among your study participants. However, variables like sex/gender, as well as race or sexual orientation, can’t be randomly assigned. Therefore, the ability to use psychological research to make causal statements about the role of sex/gender is limited.
If gender identity was an additional variable in the study described above, you might find group differences related to gender as well as video condition (e.g., men who watched the violent video may have been more aggressive than women who watched the same video). While you can draw causal conclusions about the impact of the type of video, you can’t make causal conclusions about the role of gender identity—all you can do is talk about the pattern of relationship among the variables. As discussed throughout this book, the experience of being a man, a woman, or a trans and/or gender nonbinary person is associated with many other experiences. So if people differ along sex/gender lines, any number of other things, including one’s access to resources and power, might cause these differences. Feminist scholars who utilize an intersectional approach might consider how experiences such as sexual harassment or social structures like poverty stemming from low wages might also contribute to aggression.
The use of a systematic and rigorous process through which ideas are explored and refined through an examination of evidence, generally collected through research studies.
A research design in which a variable is manipulated by the researcher in order to investigate whether changes in one variable (the independent variable) cause a change in another variable (the dependent variable).
The process of assigning participants to an experimental group or a control group in a way that ensures all participants have an equal chance of being in either group.