Here is another example. Suppose we are interested in how the color of a room might influence mood. A search using the terms mood and color produces 819 hits. Now, let’s refine (limit) the search to just peer-reviewed articles in English. Wow, still 685 articles—that’s more than we want. Perhaps color is too broad, so we try room color instead. A search with mood and room color gives only 10 articles. The third article in the list looks interesting: “Effects of Colour of Light on Nonvisual Psychological Processes,” by Igor Knez at the University of Gävle, Sweden. Again, your library may or may not have access to the full text of the article. Be sure to consult with your reference librarians. These people are well educated and typically underutilized by students. If you have a question, ask your librarian.
Once you have located an article, you can conduct a backward and forward citation search. A backward citation search is when you examine the references that have been cited in the article (termed “Cited References” in PsycINFO). If you find a relatively recent study, it’s likely that the authors conducted a thorough search when they wrote their article, so this can be very useful for your search. Another valuable strategy is to identify all the studies that have cited a particular article. This is called a forward citation search (termed “Times Cited in this Database” in PsycINFO). Using a forward search may show you where the research literature has gone since the publication of an article. Indeed, the impact of a study can be measured by how many times it has been cited in the literature.
The Research Article
Now that you have a research article in hand, let’s examine each section of the article separately. When reading the literature, you need to understand that each section has a purpose and contains specific types of information. Once you know how research articles are written, you will know which section will contain the information you need. The following discussion is presented to help you read the literature. You will find information on writing a research article in Chapter 14.
The Abstract
The abstract is a comprehensive summary of the article and describes what was done, to whom, and what was found. Online bibliographic search engines such as PsycINFO provide the title and the abstract. If the title seems relevant, you can read the abstract. It should provide you with enough information to decide whether you want to read the entire article.
The Introduction
The introduction directly follows the abstract. Here, the author provides background on the research problem. You will find a description of the relevant research (this is the researcher’s literature search) and how it logically leads to the research being reported in the article. Usually, near the end of the introduction, you will find a description of the research hypothesis of the author. Again, for information on writing an introduction, see Chapter 14.
Knez’s (2001) article mentioned in the previous section has an introduction with a typical layout. He begins with a general statement about the state of knowledge in the research area. He then presents a discussion of the previous research, organized by variables. He describes the various independent variables that have been identified as important and discusses various confounding variables and how these should be controlled. He also discusses a theoretical framework that is based largely on his own research. And, finally, he defines the purpose of the present research, how it will solve some of the problems identified in the literature review, and why it is important.
Before we continue to a discussion of the method section, it is probably a good idea to review the types of variables you will read about in the introduction of many research articles.
Independent Variable
You will recall that an independent variable (IV) is the variable in an experiment that is manipulated by the researcher. The researcher chooses levels of the IV that he or she thinks will have effects on some response measure. The researcher then assigns participants to each level of the IV (or all levels, in the case of repeated-measures designs) and compares the differences in response measures to see if the IV had an effect. You will recall that some variables are not true IVs. The values of these participant variables may be inherent in the participants. Examples include gender, age, disability type, and so on. Or participants might have self-selected the value of the variable. For example, differences in school success between children attending private and public schools is a comparison on a participant variable where the participants have, in effect, assigned themselves to the values of the variable. In either case, studies of group differences on participant variables are not true experiments; rather, they are quasi-experiments. Remember that a true IV is under the direct control of the researcher. The researcher chooses the values of the variable and assigns participants to each and then looks to see if that manipulation has any effect on the participants’ responses, the dependent variable. In an experiment, the IV can be thought of as the cause in a cause–effect relationship.
FYI
Statistical packages such as IBM® SPSS® Statistics do not distinguish between true IVs and participant (or subject) variables. They refer to both as IVs.
Dependent Variable
The dependent variable (DV) in psychological research is some response measure that we think will be influenced by our IV. Reading comprehension might be a DV, and we might measure the number of correct answers on a comprehension quiz as our operational definition of reading comprehension. Or we might measure depression by having participants rate how they feel on a scale. In an experiment, the DV can be thought of as the effect in a cause–effect relationship.
When we are trying to determine patterns of responding by measuring variables, we are always concerned with the natural variability of participants’ responses. Of course, our goal in research is to explain some of this variability. For example, if your research question is “Do students who read a lot understand better what they read?” then you are in a sense trying to account for the variability in student reading comprehension by determining how much they read. This is the variability that you are interested in explaining with your relationship. However, some variability is outside our primary interest. For example, if we are trying to determine whether classroom technology improves learning, we are not interested in variables such as temperature of the classroom, time of day of the class, or ability of the instructor. Rather, we want to control or account for these variables so that we can better assess the effect of our primary variable (i.e., technology).
If other variables that might have affected the DV have been controlled in some way, the researcher can conclude that differences in the DV are a result of, or caused by, the IV manipulation. This is the core of the experimental design, and to the degree that other variables have been controlled, we can be more confident in making causal inferences with these designs than we can with nonexperimental research. We discuss the various ways to control these other variables in Chapter 4.