The Importance of Scientific Research
Because social psychology concerns the relationships among people, and because we can frequently find answers to questions about human behavior by using our own common sense or intuition, many people think that it is not necessary to study it empirically (Lilienfeld, 2011). But although we do learn about people by observing others and therefore social psychology is in fact partly common sense, social psychology is not entirely common sense.
H5P: TEST YOUR LEARNING: CHAPTER 1 DRAG THE WORDS – CLASSIC FINDINGS IN SOCIAL PSYCHOLOGY
Read through each finding, taken from Table 1.5 in the chapter summary, and decide if you think the research evidence shows that it is either mainly true or mainly false by dragging the correct word into each box. Pay attention to the number of “trues” and “falses” available! When you have figured out the answers, think about why each finding is either mainly true or mainly false. You may also find some other ideas on this as you work your way through the textbook chapters!
Opposites attract.
An athlete who wins the bronze medal (third place) in an event is happier about his or her performance than the athlete who wins the silver medal (second place).
Having good friends you can count on can keep you from catching colds.
Subliminal advertising (i.e., persuasive messages that are displayed out of our awareness on TV or movie screens) is very effective in getting us to buy products.
The greater the reward promised for an activity, the more one will come to enjoy engaging in that activity.
Physically attractive people are seen as less intelligent than less attractive people.
Punching a pillow or screaming out loud is a good way to reduce frustration and aggressive tendencies.
People pull harder in a tug-of-war when they’re pulling alone than when pulling in a group.
See Table 1.5 at the end of Chapter 1.3 Conducting Research in Social Psychology for answers and explanations. [Production: Please retain text link to Table 1.5]
One of the reasons we might think that social psychology is common sense is that once we learn about the outcome of a given event (e.g., when we read about the results of a research project), we frequently believe that we would have been able to predict the outcome ahead of time. For instance, if half of a class of students is told that research concerning attraction between people has demonstrated that “opposites attract,” and if the other half is told that research has demonstrated that “birds of a feather flock together,” most of the students in both groups will report believing that the outcome is true and that they would have predicted the outcome before they had heard about it. Of course, both of these contradictory outcomes cannot be true. The problem is that just reading a description of research findings leads us to think of the many cases that we know that support the findings and thus makes them seem believable. The tendency to think that we could have predicted something that we probably would not have been able to predict is called the hindsight bias.
Our common sense also leads us to believe that we know why we engage in the behaviors that we engage in, when in fact we may not. Social psychologist Daniel Wegner and his colleagues have conducted a variety of studies showing that we do not always understand the causes of our own actions. When we think about a behavior before we engage in it, we believe that the thinking guided our behavior, even when it did not (Morewedge, Gray, & Wegner, 2010). People also report that they contribute more to solving a problem when they are led to believe that they have been working harder on it, even though the effort did not increase their contribution to the outcome (Preston & Wegner, 2007). These findings, and many others like them, demonstrate that our beliefs about the causes of social events, and even of our own actions, do not always match the true causes of those events.
Social psychologists conduct research because it often uncovers results that could not have been predicted ahead of time. Putting our hunches to the test exposes our ideas to scrutiny. The scientific approach brings a lot of surprises, but it also helps us test our explanations about behavior in a rigorous manner. It is important for you to understand the research methods used in psychology so that you can evaluate the validity of the research that you read about here, in other courses, and in your everyday life.
Social psychologists publish their research in scientific journals, and your instructor may require you to read some of these research articles. The most important social psychology journals are listed in “Social Psychology Journals.” If you are asked to do a literature search on research in social psychology, you should look for articles from these journals.
Social Psychology Journals:
Journal of Personality and Social Psychology
Journal of Experimental Social Psychology
Personality and Social Psychology Bulletin
Social Psychology and Personality Science
Social Cognition
European Journal of Social Psychology
Social Psychology Quarterly
Basic and Applied Social Psychology
Journal of Applied Social Psychology
Note. The research articles in these journals are likely to be available in your college or university library.
We’ll discuss the empirical approach and review the findings of many research projects throughout this book, but for now let’s take a look at the basics of how scientists use research to draw overall conclusions about social behavior. Keep in mind as you read this book, however, that although social psychologists are pretty good at understanding the causes of behavior, our predictions are a long way from perfect. We are not able to control the minds or the behaviors of others or to predict exactly what they will do in any given situation. Human behavior is complicated because people are complicated and because the social situations that they find themselves in every day are also complex. It is this complexity—at least for me—that makes studying people so interesting and fun.
The Research Hypothesis
Because social psychologists are generally interested in looking at relationships among variables, they begin by stating their predictions in the form of a precise statement known as a research hypothesis. A research hypothesis is a specific prediction about the relationship between the variables of interest and about the specific direction of that relationship. For instance, the research hypothesis “People who are more similar to each other will be more attracted to each other” predicts that there is a relationship between a variable called similarity and another variable called attraction. In the research hypothesis “The attitudes of cult members become more extreme when their beliefs are challenged,” the variables that are expected to be related are extremity of beliefs and the degree to which the cult’s beliefs are challenged.
Because the research hypothesis states both that there is a relationship between the variables and the direction of that relationship, it is said to be falsifiable, which means that the outcome of the research can demonstrate empirically either that there is support for the hypothesis (i.e., the relationship between the variables was correctly specified) or that there is actually no relationship between the variables or that the actual relationship is not in the direction that was predicted. Thus the research hypothesis that “People will be more attracted to others who are similar to them” is falsifiable because the research could show either that there was no relationship between similarity and attraction or that people we see as similar to us are seen as less attractive than those who are dissimilar.
Activity 4: Abstract Breakdown
[Production: please update this statement to include mention of 3271.] *This section of the open course textbook is designed to support PSYC 3261 and PSYC 3271, and the activity numbering corresponds to Unit 1 in both courses.
Introduction
In this activity, you are going to practice pulling information out of a real academic journal article as quickly and easily as possible. Take notes as you work through the activity because we will revisit this content in activity 5 and 7.
Let’s start at the beginning—the abstract—that wonderful little blurb that condenses all the most important information from the article to make our lives easier. The abstract provided to you for analysis was taken from the following Cameron et al. (2010) article:
Acceptance Is in the Eye of the Beholder: Self-Esteem and Motivated Perceptions of Acceptance from the Opposite Sex [Production: please link article text to course Moodle]
You don’t need to search for the article, the abstract section of the article is provided here for you.
Instructions
Read through the abstract below once before looking at the next steps.
[article section is in a text box:]
Acceptance Is in the Eye of the Beholder: Self-Esteem and Motivated Perceptions of Acceptance From the Opposite Sex
Social risk elicits self-esteem differences in signature social motivations and behaviors during the relationship initiation process. In particular, the present research tested the hypothesis that lower self-esteem individuals’ (LSEs) motivation to avoid rejection leads them to self-protectively underestimate acceptance from potential romantic partners, whereas higher self-esteem individuals’ (HSEs) motivation to promote new relationships leads them to overestimate acceptance. The results of 5 experiments supported these predictions. Social risk increased activation of avoidance goals for LSEs on a word-recall task but increased activation of approach goals for HSEs, as evidenced by their increased use of likeable behaviors. Consistent with these patterns of goal activation, even though actual acceptance cues were held constant across all participants, social risk decreased the amount of acceptance that LSEs perceived from their interaction partner but increased the amount of acceptance that HSEs perceived from their interaction partner. It is important to note that such self-esteem differences in avoidance goals, approach behaviors, and perceptions of acceptance were completely eliminated when social risk was removed.
[Production: end of text box]
Now, looking back over the abstract, try to identify the following elements. You can turn the cards to see the correct answer.
[Three H5P show/hide dialogue cards were created by Media and inserted here. Correct answer and accompanying feedback shown in red font.]
[front of card 1] What is the independent variable (IV)?
[Back of card 1] Self-Esteem
This one can be a bit tricky. The authors mention both self-esteem and the mechanism (i.e., motivation to avoid rejection), but the most important piece here is the person’s self-esteem.
[front of card 2] What is the dependent variable (DV)?
[Back of card 2] Perceived Acceptance
There is a bit of nuance here. The authors mention underestimating and overestimating acceptance. You might answer “estimation of acceptance” here, but the most accurate answer is “perceived acceptance.” You can always look back at the title to help you as well. If you answered just “acceptance,” be careful because this study is about how much acceptance the participants THOUGHT they were receiving, not how much acceptance they actually were receiving.
[front of card 3] What is the Hypothesis (Hint: How are the IV and DV connected?)
[Back of card 3] Lower Self-Esteem leads to lower perceived acceptance
*You could phrase this in one of two ways. You could either say that lower self-esteem leads to lower perceived acceptance or that higher self-esteem leads to more perceived acceptance, they are two sides of the same coin, so to speak, and both statements are accurate.
[Production: end of H5P activity]
Measuring Affect, Behavior, and Cognition
One important aspect of using an empirical approach to understand social behavior is that the concepts of interest must be measured (Figure 1.7, “The Operational Definition”). If we are interested in learning how much Sarah likes Robert, then we need to have a measure of her liking for him. But how, exactly, should we measure the broad idea of “liking”? In scientific terms, the characteristics that we are trying to measure are known as conceptual variables, and the particular method that we use to measure a variable of interest is called an operational definition.
For anything that we might wish to measure, there are many different operational definitions, and which one we use depends on the goal of the research and the type of situation we are studying. To better understand this, let’s look at an example of how we might operationally define “Sarah likes Robert.”
Figure 1.7 The Operational Definition. An idea or conceptual variable (such as “how much Sarah likes Robert”) is turned into a measure through an operational definition.
One approach to measurement involves directly asking people about their perceptions using self-report measures. Self-report measures are measures in which individuals are asked to respond to questions posed by an interviewer or on a questionnaire. Generally, because any one question might be misunderstood or answered incorrectly, in order to provide a better measure, more than one question is asked and the responses to the questions are averaged together. For example, an operational definition of Sarah’s liking for Robert might involve asking her to complete the following measure:
I enjoy being around Robert.
Strongly disagree 1 2 3 4 5 6 Strongly agree
I get along well with Robert.
Strongly disagree 1 2 3 4 5 6 Strongly agree
I like Robert.
Strongly disagree 1 2 3 4 5 6 Strongly agree
The operational definition would be the average of her responses across the three questions. Because each question assesses the attitude differently, and yet each question should nevertheless measure Sarah’s attitude toward Robert in some way, the average of the three questions will generally be a better measure than would any one question on its own.
Although it is easy to ask many questions on self-report measures, these measures have a potential disadvantage. As we have seen, people’s insights into their own opinions and their own behaviors may not be perfect, and they might also not want to tell the truth—perhaps Sarah really likes Robert, but she is unwilling or unable to tell us so. Therefore, an alternative to self-report that can sometimes provide a more valid measure is to measure behavior itself. Behavioral measures are measures designed to directly assess what people do. Instead of asking Sarah how much she likes Robert, we might instead measure her liking by assessing how much time she spends with Robert or by coding how much she smiles at him when she talks to him. Some examples of behavioral measures that have been used in social psychological research are shown in Table 1.3, “Examples of Operational Definitions of Conceptual Variables That Have Been Used in Social Psychological Research.”
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Table 1.3 Examples of Operational Definitions of Conceptual Variables that have been used in Sociological Research. |
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Conceptual variable |
Operational definitions |
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Aggression |
Number of seconds taken to honk the horn at the car ahead after a stoplight turns green Number of presses of a button that administers shock to another student |
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Interpersonal attraction |
Number of millimeters of pupil dilation when one person looks at another Number of times that a person looks at another person |
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Altruism |
Number of hours of volunteering per week that a person engages in Number of pieces of paper a person helps another pick up |
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Group-decision making skills |
Number of seconds in which a group correctly solves a problem Number of groups able to correctly solve a group performance task |
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Prejudice |
Number of groups able to correctly solve a group performance task Number of negative words used in a creative story about another person |
Activity 5: How It Works
[Production: please update this statement to include mention of 3271.] *This section of the open course textbook is designed to support PSYC 3261 and PSYC 3271, and the activity numbering corresponds to Unit 1 in both courses.
Introduction
Now that you have learned about operational definitions of variables (also called operationalizations), we are going to dig a bit deeper into the Cameron et al. (2010) article used in Learning Activity 4: Abstract Breakdown. We know from our earlier exercise that our main independent variable is Self-Esteem and our main dependent variable is Perceived Acceptance. It is important to keep this in mind as you read through the next section, as real research studies will often include other variables as well and we want to stay focused on the main ones.
Instructions
Read the following excerpt from the article once before looking at the questions. This article presents multiple studies, but we will be focusing only on Study 1. Take notes as you work through the activity because we will revisit this content in Activity 7.
[content from study 1 is in a text box]
“Study 1: Does Self-Esteem Predict Perceptions of Acceptance When Social Risk is Present?
Two previous studies have demonstrated that LSEs think they are less accepted by novel interaction partners than do HSEs (Brockner & Lloyd, 1986; Campbell & Fehr, 1990). In these previous studies, actual acceptance by the participants’ interaction partner was not related to participants’ self-esteem, suggesting that the self-esteem effect may actually represent motivated perception, consistent with our hypotheses. However, even though self-esteem did not influence interaction partners’ explicit reports, it might still have influenced the interaction partners’ social behavior. Thus, the possibility remains that LSE and HSE participants in these studies actually received different social cues from their interaction partners. If this is the case, then the self-esteem effect on perceptions of acceptance in these previous studies may have reflected real differences in social cues.
Hence, this first study was designed to test H1 by examining whether self-esteem predicts perceptions of acceptance when social risk is present. It is important to note that we test this hypothesis when social cues from one’s interaction partner are held completely constant across participants. Even in such controlled conditions, we predict that LSEs will perceive less acceptance than HSEs from an attractive, single, opposite-sex stranger, presumably because of self-esteem differences in signature social motivations in response to the social risk inherent to such a first-meeting situation. Moreover, we sought to measure the pervasiveness of the self-esteem effect on perceptions of acceptance by examining participants’ perceptions of acceptance when social cues reflect low and high levels of acceptance.
Method
Participants. Seventy-nine undergraduate students (58 women, 21 men) enrolled in introductory psychology classes at the University of Manitoba participated in exchange for partial course credit. Participants ranged from 18 to 25 years of age (M = 18.77 years, SD = 1.43). The majority of participants were not involved in romantic relationships (i.e., single; n = 62), and all participants reported that they were heterosexual.
Procedure. Upon arriving for their individual lab sessions, participants completed a preliminary survey in which they indicated their self-esteem using the 10-item Rosenberg (1965) Self Esteem Inventory (α = .86), which was adapted to use a 9-point response format (1 = very strongly disagree, 9 = very strongly agree), rather than the original 4-point response format. This version of Rosenberg’s scale was used throughout the studies reported in this article. The preliminary survey also included demographic questions (e.g., age) and filler items intended to disguise our focus on self-esteem (e.g., scales assessing morning vs. evening personality types).
We devised an elaborate cover story that allowed us to expose all participants to identical social cues while also maintaining the believability of the interpersonal context. When participants arrived for their individual lab sessions, they were informed that the present study was investigating compatibility between opposite sex strangers. Hence, participants thought that there was a second, opposite-sex participant in the lab room next to theirs. Participants were also informed that because the study was interested in examining “constrained communication,” the participants would be communicating with their interaction partner via video camera. To enhance the personal relevance of the experiment and the importance of the participants’ communication, the researcher informed the participants that there might also be the opportunity for them to meet their interaction partner later in a face-to-face interaction.
In the constrained communication task that participants completed, the participants first introduced themselves to their inter-action partner by recording a video. Their interaction partner supposedly watched this introductory statement on a closed-circuit television in the room next door. To ensure consistency across participant introductions, the participants all discussed the same list of seven general conversation topics, adapted from Aron, Melinat, Aron, Vallone, and Bator’s (1997) closeness-generating procedure (e.g., “What is your dream job?”). After their interaction partner had supposedly watched the participants’ introductory tape, participants watched a “response” from their interaction partner, in which the interaction partner answered the same seven questions that the participants had answered. Once the participants had finished watching their interaction partner’s response tape, they completed a final survey that contained the dependent measures.
Although participants anticipated that they would meet their interaction partner face to face following the constrained communication task, no second interaction ever took place, because there was actually no second participant in the next room. The taped response from the participants’ interaction partner was a prerecorded videotape of an attractive opposite-sex confederate. The content of the confederate’s taped response represented the experimental manipulation in this study. Hence, after watching the confederate’s response and completing the dependent measures, participants were thoroughly debriefed.
Materials and measures.
Confederate responses. The confederates, one male and one female, were recruited and filmed at the University of Waterloo, ensuring that the University of Manitoba participants did not recognize them. To ensure both the believability of the tapes and to increase the likelihood that participants would want to meet the confederate, both confederates had minor acting experience and were above average in attractiveness. Each confederate filmed two responses. A summary of the confederates’ behavior and the confederate scripts in the two experimental conditions are presented in Table 1. In the response used for the low-acceptance condition, the confederate answered the same seven questions that the participant initially answered but engaged in minimal self-disclosure, did not make any reference to the participant’s videotape, and expressed minimal nonverbal liking cues (e.g., no smiling, no laughing, little eye contact). In the high-acceptance condition, the majority of the informative content of the response was the same as the low-acceptance condition, but in this case, the confederate agreed with some of the participant’s responses (e.g., “I’m with you on this one”), self-disclosed personal information, expressed strong nonverbal liking cues (e.g., smiling, eye contact), and finally displayed a verbal overture of interest (i.e., “So, I hope to see you in the second part of the study!”).
Summary perceptions of acceptance. In the final survey, participants reported their perceived acceptance from the confederate with five items (i.e., “The other participant probably likes me,” “The other participant probably wants to meet me again,” “The other participant probably enjoyed the interaction with me,” “The other participant is probably willing to spend time with me,” “The other participant probably wants to have another interaction with me”), using a 7-point response format (1 = strongly disagree,7 = strongly agree). These items were averaged to form a reliable index of summary perceptions of acceptance (α = .83).”
[Production: end of text box content]
Questions
This section gives a comprehensive overview of the procedure for Study 1. You may have noticed that the researchers included an additional variable in the form of a manipulation. Participants were randomly assigned to be in either the “Low Acceptance” or “High Acceptance” condition. This is important due to the implications for the underlying theory, but not important for our practice activity. For this activity, we will only be focusing on identifying the operational definitions for our two main variables. Think about how the researchers actually measured the variables in this study.
[Two H5P show/hide dialogue cards created by Media replaces the following 2 questions & corresponding answers]
How was Self-Esteem operationalized in this study?
Self-Esteem was measured at the start of the study using the 1-item Rosenberg (1965) Self-Esteem Inventory (RSEI). The operational definition of Self-Esteem in this study is the score on the RSEI.
How was Perceived Acceptance operationalized in this study?
Perceived Acceptance was measured using a 5-item scale at the end of the study. The operational definition of Perceived Acceptance in this study is, like with self-esteem, the score on the perceived acceptance scale.
[end of H5P activity content]
Although this activity may have seemed a little straightforward, it gives you a perfect example of how simple identifying the operational definitions really is. Some studies may be much more complex and use very unique and unintuitive operational definitions for their independent and dependent variables, but the process is always the same: Find the hypothesis, identify the main variables, then identify their operational definitions.
So, why all this emphasis on identifying the main variables and their operational definitions? Well, because when we get to the results section and things get really complicated, this information will act as our roadmap and show us exactly what we need to look for. You will have a chance to experience that firsthand in Learning Activity 7: Connecting the Dots.
[end of learning activity]
Social Neuroscience: Measuring Social Responses in the Brain
Still another approach to measuring thoughts and feelings is to measure brain activity, and recent advances in brain science have created a wide variety of new techniques for doing so. One approach, known as electroencephalography (EEG), is a technique that records the electrical activity produced by the brain’s neurons through the use of electrodes that are placed around the research participant’s head. An electroencephalogram (EEG) can show if a person is asleep, awake, or anesthetized because the brain wave patterns are known to differ during each state. An EEG can also track the waves that are produced when a person is reading, writing, and speaking with others. A particular advantage of the technique is that the participant can move around while the recordings are being taken, which is useful when measuring brain activity in children who often have difficulty keeping still. Furthermore, by following electrical impulses across the surface of the brain, researchers can observe changes over very fast time periods.
Figure 1.8 Person with numerous electrodes on their skull and face, in preparation for an EEG.
Although EEGs can provide information about the general patterns of electrical activity within the brain, and although they allow the researcher to see these changes quickly as they occur in real time, the electrodes must be placed on the surface of the skull, and each electrode measures brain waves from large areas of the brain. As a result, EEGs do not provide a very clear picture of the structure of the brain.
But techniques exist to provide more specific brain images. Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that uses a magnetic field to create images of brain structure and function. In research studies that use the fMRI, the research participant lies on a bed within a large cylindrical structure containing a very strong magnet. Nerve cells in the brain that are active use more oxygen, and the need for oxygen increases blood flow to the area. The fMRI detects the amount of blood flow in each brain region and thus is an indicator of which parts of the brain are active.
Very clear and detailed pictures of brain structures (see Figure 1.9, “MRI BOLD activation in an emotional Stroop task”) can be produced via fMRI. Often, the images take the form of cross-sectional “slices” that are obtained as the magnetic field is passed across the brain. The images of these slices are taken repeatedly and are superimposed on images of the brain structure itself to show how activity changes in different brain structures over time. Normally, the research participant is asked to engage in tasks while in the scanner, for instance, to make judgments about pictures of people, to solve problems, or to make decisions about appropriate behaviors. The fMRI images show which parts of the brain are associated with which types of tasks. Another advantage of the fMRI is that is it noninvasive. The research participant simply enters the machine and the scans begin.
Figure 1.9 MRI BOLD activation in an emotional Stroop task [click to see image full size]
Although the scanners themselves are expensive, the advantages of fMRIs are substantial, and scanners are now available in many university and hospital settings. The fMRI is now the most commonly used method of learning about brain structure, and it has been employed by social psychologists to study social cognition, attitudes, morality, emotions, responses to being rejected by others, and racial prejudice, to name just a few topics (Eisenberger, Lieberman, & Williams, 2003; Greene, Sommerville, Nystrom, Darley, & Cohen, 2001; Lieberman, Hariri, Jarcho, Eisenberger, & Bookheimer, 2005; Ochsner, Bunge, Gross, & Gabrieli, 2002; Richeson et al., 2003).
Observational Research
Once we have decided how to measure our variables, we can begin the process of research itself. As you can see in Table 1.4, “Three Major Research Designs Used by Social Psychologists,” there are three major approaches to conducting research that are used by social psychologists—the observational approach, the correlational approach, and the experimental approach. Each approach has some advantages and disadvantages.
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Table 1.4 Three Major Research Designs Used by Social Psychologists |
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Research Design |
Goal |
Advantages |
Disadvantages |
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Observational |
To create a snapshot of the current state of affairs |
Provides a relatively complete picture of what is occurring at a given time. Allows the development of questions for further study. |
Does not assess relationships between variables. |
|
Correlational |
To assess the relationships between two or more variables |
Allows the testing of expected relationships between variables and the making of predictions. Can assess these relationships in everyday life events. |
Cannot be used to draw inferences about the causal relationships between the variables. |
|
Experimental |
To assess the causal impact of one or more experimental manipulations on a dependent variable |
Allows the drawing of conclusions about the causal relationships among variables. |
Cannot experimentally manipulate many important variables. May be expensive and take much time to conduct. |
The most basic research design, observational research, is research that involves making observations of behavior and recording those observations in an objective manner. Although it is possible in some cases to use observational data to draw conclusions about the relationships between variables (e.g., by comparing the behaviors of older versus younger children on a playground), in many cases the observational approach is used only to get a picture of what is happening to a given set of people at a given time and how they are responding to the social situation. In these cases, the observational approach involves creating a type of “snapshot” of the current state of affairs.
One advantage of observational research is that in many cases it is the only possible approach to collecting data about the topic of interest. A researcher who is interested in studying the impact of an earthquake on the residents of Tokyo, the reactions of Israelis to a terrorist attack, or the activities of the members of a religious cult cannot create such situations in a laboratory but must be ready to make observations in a systematic way when such events occur on their own. Thus observational research allows the study of unique situations that could not be created by the researcher. Another advantage of observational research is that the people whose behavior is being measured are doing the things they do every day, and in some cases they may not even know that their behavior is being recorded.
One early observational study that made an important contribution to understanding human behavior was reported in a book by Leon Festinger and his colleagues (Festinger, Riecken, & Schachter, 1956). The book, called When Prophecy Fails, reported an observational study of the members of a “doomsday” cult. The cult members believed that they had received information, supposedly sent through “automatic writing” from a planet called “Clarion,” that the world was going to end. More specifically, the group members were convinced that Earth would be destroyed as the result of a gigantic flood sometime before dawn on December 21, 1954.
When Festinger learned about the cult, he thought that it would be an interesting way to study how individuals in groups communicate with each other to reinforce their extreme beliefs. He and his colleagues observed the members of the cult over a period of several months, beginning in July of the year in which the flood was expected. The researchers collected a variety of behavioral and self-report measures by observing the cult, recording the conversations among the group members, and conducting detailed interviews with them. Festinger and his colleagues also recorded the reactions of the cult members, beginning on December 21, when the world did not end as they had predicted. This observational research provided a wealth of information about the indoctrination patterns of cult members and their reactions to disconfirmed predictions. This research also helped Festinger develop his important theory of cognitive dissonance.
Despite their advantages, observational research designs also have some limitations. Most importantly, because the data that are collected in observational studies are only a description of the events that are occurring, they do not tell us anything about the relationship between different variables. However, it is exactly this question that correlational research and experimental research are designed to answer.
Correlational Research
Correlational research is designed to search for and test hypotheses about the relationships between two or more variables. In the simplest case, the correlation is between only two variables, such as that between similarity and liking, or between gender (male versus female) and helping.
In a correlational design, the research hypothesis is that there is an association (i.e., a correlation) between the variables that are being measured. For instance, many researchers have tested the research hypothesis that a positive correlation exists between the use of violent video games and the incidence of aggressive behavior, such that people who play violent video games more frequently would also display more aggressive behavior.
Figure 1.10 Correlational Design. The research hypothesis that a positive correlation exists between the use of violent video games and the incidence of aggressive behavior
A statistic known as the Pearson correlation coefficient (symbolized by the letter r) is normally used to summarize the association, or correlation, between two variables. The Pearson correlation coefficient can range from −1 (indicating a very strong negative relationship between the variables) to +1 (indicating a very strong positive relationship between the variables). Recent research has found that there is a positive correlation between the use of violent video games and the incidence of aggressive behavior and that the size of the correlation is about r = .30 (Bushman & Huesmann, 2010).
One advantage of correlational research designs is that, like observational research (and in comparison with experimental research designs in which the researcher frequently creates relatively artificial situations in a laboratory setting), they are often used to study people doing the things that they do every day. Correlational research designs also have the advantage of allowing prediction. When two or more variables are correlated, we can use our knowledge of a person’s score on one of the variables to predict his or her likely score on another variable. Because high-school grades are correlated with university grades, if we know a person’s high-school grades, we can predict his or her likely university grades. Similarly, if we know how many violent video games a child plays, we can predict how aggressively he or she will behave. These predictions will not be perfect, but they will allow us to make a better guess than we would have been able to if we had not known the person’s score on the first variable ahead of time.
Despite their advantages, correlational designs have a very important limitation. This limitation is that they cannot be used to draw conclusions about the causal relationships among the variables that have been measured. An observed correlation between two variables does not necessarily indicate that either one of the variables caused the other. Although many studies have found a correlation between the number of violent video games that people play and the amount of aggressive behaviors they engage in, this does not mean that viewing the video games necessarily caused the aggression. Although one possibility is that playing violent games increases aggression,
Figure 1.11 Playing violent video games leads to aggressive behavior.
another possibility is that the causal direction is exactly opposite to what has been hypothesized. Perhaps increased aggressiveness causes more interest in, and thus increased viewing of, violent games. Although this causal relationship might not seem as logical, there is no way to rule out the possibility of such reverse causation on the basis of the observed correlation.
Figure 1.12 Increased aggressiveness causes more interest in, and thus increased viewing of, violent games.
Still another possible explanation for the observed correlation is that it has been produced by the presence of another variable that was not measured in the research. Common-causal variables (also known as third variables) are variables that are not part of the research hypothesis but that cause both the predictor and the outcome variable and thus produce the observed correlation between them (Figure 1.13, “Correlation and Causality”). It has been observed that students who sit in the front of a large class get better grades than those who sit in the back of the class. Although this could be because sitting in the front causes the student to take better notes or to understand the material better, the relationship could also be due to a common-causal variable, such as the interest or motivation of the students to do well in the class. Because a student’s interest in the class leads them to both get better grades and sit nearer to the teacher, seating position and class grade are correlated, even though neither one caused the other.
Figure 1.13 Correlation and Causality. The correlation between where students sit in a large class and their grade in the class is likely caused by the influence of one or more common-causal variables.
The possibility of common-causal variables must always be taken into account when considering correlational research designs. For instance, in a study that finds a correlation between playing violent video games and aggression, it is possible that a common-causal variable is producing the relationship. Some possibilities include the family background, diet, and hormone levels of the children. Any or all of these potential common-causal variables might be creating the observed correlation between playing violent video games and aggression. Higher levels of the male sex hormone testosterone, for instance, may cause children to both watch more violent TV and behave more aggressively.
You may think of common-causal variables in correlational research designs as “mystery” variables, since their presence and identity is usually unknown to the researcher because they have not been measured. Because it is not possible to measure every variable that could possibly cause both variables, it is always possible that there is an unknown common-causal variable. For this reason, we are left with the basic limitation of correlational research: correlation does not imply causation.
Experimental Research
The goal of much research in social psychology is to understand the causal relationships among variables, and for this we use experiments. Experimental research designs are research designs that include the manipulation of a given situation or experience for two or more groups of individuals who are initially created to be equivalent, followed by a measurement of the effect of that experience.
In an experimental research design, the variables of interest are called the independent variables and the dependent variables. The independent variable refers to the situation that is created by the experimenter through the experimental manipulations, and the dependent variable refers to the variable that is measured after the manipulations have occurred. In an experimental research design, the research hypothesis is that the manipulated independent variable (or variables) causes changes in the measured dependent variable (or variables). We can diagram the prediction like this, using an arrow that points in one direction to demonstrate the expected direction of causality:
viewing violence (independent variable) → aggressive behavior (dependent variable)
Consider an experiment conducted by Anderson and Dill (2000), which was designed to directly test the hypothesis that viewing violent video games would cause increased aggressive behavior. In this research, male and female undergraduates from Iowa State University were given a chance to play either a violent video game (Wolfenstein 3D) or a nonviolent video game (Myst). During the experimental session, the participants played the video game that they had been given for 15 minutes. Then, after the play, they participated in a competitive task with another student in which they had a chance to deliver blasts of white noise through the earphones of their opponent. The operational definition of the dependent variable (aggressive behavior) was the level and duration of noise delivered to the opponent. The design and the results of the experiment are shown in Figure 1.14, “An Experimental Research Design (After Anderson & Dill, 2000).”
Figure 1.14 An Experimental Research Design (After Anderson & Dill, 2000). Two advantages of the experimental research design are (a) an assurance that the independent variable (also known as the experimental manipulation) occurs prior to the measured dependent variable and (b) the creation of initial equivalence between the conditions of the experiment (in this case, by using random assignment to conditions).
Experimental designs have two very nice features. For one, they guarantee that the independent variable occurs prior to measuring the dependent variable. This eliminates the possibility of reverse causation. Second, the experimental manipulation allows ruling out the possibility of common-causal variables that cause both the independent variable and the dependent variable. In experimental designs, the influence of common-causal variables is controlled, and thus eliminated, by creating equivalence among the participants in each of the experimental conditions before the manipulation occurs.
The most common method of creating equivalence among the experimental conditions is through random assignment to conditions before the experiment begins, which involves determining separately for each participant which condition he or she will experience through a random process, such as drawing numbers out of an envelope or using a website such as randomizer.org. Anderson and Dill first randomly assigned about 100 participants to each of their two groups. Let’s call them Group A and Group B. Because they used random assignment to conditions, they could be confident that before the experimental manipulation occurred, the students in Group A were, on average, equivalent to the students in Group B on every possible variable, including variables that are likely to be related to aggression, such as family, peers, hormone levels, and diet—and, in fact, everything else.
Then, after they had created initial equivalence, Anderson and Dill created the experimental manipulation—they had the participants in Group A play the violent video game and the participants in Group B play the nonviolent video game. Then they compared the dependent variable (the white noise blasts) between the two groups and found that the students who had viewed the violent video game gave significantly longer noise blasts than did the students who had played the nonviolent game. When the researchers observed differences in the duration of white noise blasts between the two groups after the experimental manipulation, they could draw the conclusion that it was the independent variable (and not some other variable) that caused these differences because they had created initial equivalence between the groups. The idea is that the only thing that was different between the students in the two groups was which video game they had played.
When we create a situation in which the groups of participants are expected to be equivalent before the experiment begins, when we manipulate the independent variable before we measure the dependent variable, and when we change only the nature of independent variables between the conditions, then we can be confident that it is the independent variable that caused the differences in the dependent variable. Such experiments are said to have high internal validity, where internal validity is the extent to which changes in the dependent variable in an experiment can confidently be attributed to changes in the independent variable.
Despite the advantage of determining causation, experimental research designs do have limitations. One is that the experiments are usually conducted in laboratory situations rather than in the everyday lives of people. Therefore, we do not know whether results that we find in a laboratory setting will necessarily hold up in everyday life. To counter this, researchers sometimes conduct field experiments, which are experimental research studies that are conducted in a natural environment, such as a school or a factory. However, they are difficult to conduct because they require a means of creating random assignment to conditions, and this is frequently not possible in natural settings.
A second and perhaps more important limitation of experimental research designs is that some of the most interesting and important social variables cannot be experimentally manipulated. If we want to study the influence of the size of a mob on the destructiveness of its behavior, or to compare the personality characteristics of people who join suicide cults with those of people who do not join suicide cults, these relationships must be assessed using correlational designs because it is simply not possible to manipulate mob size or cult membership.
An interactive H5P element has been excluded from this version of the text. You can view it online here:
https://opentextbc.ca/socialpsychology/?p=3142#h5p-2
H5P: TEST YOUR LEARNING: CHAPTER 1 DRAG THE WORDS – INDEPENDENT AND DEPENDENT VARIABLES
Read through the following descriptions of experimental studies, and identify the independent and dependent variables in each scenario.
A social psychologist wants to conduct a study to see if playing a violent versus a non-violent video game influences peoples’ aggressiveness.
Amount of aggression:
Type of video game:
A researcher is investigating whether the speed of a helping response is affected by the size of a group of onlookers to an emergency situation.
Size of group of onlookers
Speed of helping response
A social psychologist is interested in determining if people show greater attitude change after being exposed to a one-sided versus a two-sided argument.
Amount of attitude change
Type of message
People are assigned to viewing either aggression-related or neutral words, and then their level of hostile intention bias is measured using a questionnaire.
Hostile intention bias score
Type of word
A team of researchers assess whether people make more external attributions when they are asked to evaluate their own rather than someone else’s behaviour.
Target of attribution
Type of attribution
Activity 6: Design a Study
[Production: please update this statement to include mention of 3271.] *This section of the open course textbook is designed to support PSYC 3261 and PSYC 3271, and the activity numbering corresponds to Unit 1 in both courses.
Introduction
In this activity, you will play the role of a researcher investigating how the amount of time couples spend with each other affects how happy they are together. You will trace the path of an initial correlational study, followed by an experimental study to build on what you find.
Instructions
Our research focuses on how time spent together is connected to relationship satisfaction. Let’s begin by designing a correlational study.
Step 1: What is your hypothesis? (Do you think spending more time together will increase satisfaction, decrease it, or have no effect?)
Step 2: How will you measure the two main variables?
Time spent together
Relationship satisfaction (There are many ways to measure this, try to be creative! How can we tell if people are happy / unhappy in their relationships?)
Now that we have our correlational study ready to go, let’s run it (or pretend we did at least)!
Let’s say your study produced a Pearson Correlation Coefficient of .56 (strong positive correlation) between the two variables. (Note: If you hypothesized a negative effect, feel free to say the correlation went the other way.)
Since this was a correlational design, we know that there are always THREE possible explanations for our findings. What are they?
[three H5P show/hide dialogue cards created by Media replaces the following text]
Explanations for Correlational Findings:
[Production: Card 1 Front:] Explanation 1… [Production: C1 Back:] The hypothesized causal path (i.e., A => B)
[Production: Card 2 Front:] Explanation 2… [Production: C2 Back:] Reverse-causality (i.e., B => A)
[Production: Card 3 Front:] Explanation 3… [Production: C3 Back:] A third variable (i.e., C => A and B)
[end of H5P content]
If we want to take this a step further and assert causality (e.g., we really want to show that it is, in fact, time spent together affecting relationship satisfaction), we need a follow-up experimental design.
Step 1: What is your hypothesis? (Hint: The design may have changed, but our hypothesis is still the same.)
Step 2: What is your independent variable and how will you manipulate it?
Step 3: What is your dependent variable and how will you measure it?
Congratulations, if you answered these follow-up questions, you have just built your very own research project!
Yes, this was a simplified approach, but you walked through all the steps of taking a research question, turning it into a testable hypothesis, operationalizing your variables, and designing an experimental study to provide evidence supporting your causal hypothesis.
You will follow these same steps later in your academic career if you decide to go into research. You will, of course, spend more time refining your design and considering possible issues and validity threats, but it all starts here.
[end of activity 6]
Factorial Research Designs
Social psychological experiments are frequently designed to simultaneously study the effects of more than one independent variable on a dependent variable. Factorial research designs are experimental designs that have two or more independent variables. By using a factorial design, the scientist can study the influence of each variable on the dependent variable (known as the main effects of the variables) as well as how the variables work together to influence the dependent variable (known as the interaction between the variables). Factorial designs sometimes demonstrate the person by situation interaction.
In one such study, Brian Meier and his colleagues (Meier, Robinson, & Wilkowski, 2006) tested the hypothesis that exposure to aggression-related words would increase aggressive responses toward others. Although they did not directly manipulate the social context, they used a technique common in social psychology in which they primed (i.e., activated) thoughts relating to social settings. In their research, half of their participants were randomly assigned to see words relating to aggression and the other half were assigned to view neutral words that did not relate to aggression. The participants in the study also completed a measure of individual differences in agreeableness—a personality variable that assesses the extent to which people see themselves as compassionate, cooperative, and high on other-concern.
Then the research participants completed a task in which they thought they were competing with another student. Participants were told that they should press the space bar on the computer keyboard as soon as they heard a tone over their headphones, and the person who pressed the space bar the fastest would be the winner of the trial. Before the first trial, participants set the intensity of a blast of white noise that would be delivered to the loser of the trial. The participants could choose an intensity ranging from 0 (no noise) to the most aggressive response (10, or 105 decibels). In essence, participants controlled a “weapon” that could be used to blast the opponent with aversive noise, and this setting became the dependent variable. At this point, the experiment ended.
Figure 1.15 A Person-Situation Interaction. In this experiment by Meier, Robinson, and Wilkowski (2006) the independent variables are a type of priming (aggression or neutral) and participant agreeableness (high or low). The dependent variable is the white noise level selected (a measure of aggression). The participants who were low in agreeableness became significantly more aggressive after seeing aggressive words, but those high in agreeableness did not.
As you can see in Figure 1.15, “A Person-Situation Interaction,” there was a person-by-situation interaction. Priming with aggression-related words (the situational variable) increased the noise levels selected by participants who were low on agreeableness, but priming did not increase aggression (in fact, it decreased it a bit) for students who were high on agreeableness. In this study, the social situation was important in creating aggression, but it had different effects for different people.
Activity 7: Connecting the Dots
[Production: please update this statement to include mention of 3271.] *This section of the open course textbook is designed to support PSYC 3261 and PSYC 3271, and the activity numbering corresponds to Unit 1 in both courses.
Introduction
Returning to the Cameron et al. (2010) article used in Activity 4: Abstract Breakdown and Activity 5: How It Works, we now know what our main variables are, how they are being operationalized in this study (i.e., their operational definitions), and what kind of relationship the researchers are hypothesizing between those variables. In this activity, you will be sifting through the results section for Study 1 to pick out only the most important results that are relevant to the researchers’ hypothesis. Referring back to the course notes you made for Activity 4 and 5 should help you to complete this activity.
Instructions
As you read through the results section, try not to get too stuck on the calculations and numbers. You will often encounter articles that go well beyond your current statistical capabilities. If you skim through the presentation of the results, you will arrive at the discussion portion where the authors explain the results in plain English. This can be very helpful when trying to decipher complex statistical analyses. There are some additional results presented here that are not needed to address the researchers’ primary hypothesis, which we identified in Activity 4. Read through this section of the article once before moving on to the question below.
[the following content is in a text box]
“Results and Discussion
Preliminary analyses indicated that gender and relationship status did not moderate the following results, so these variables were not included in the reported analyses.
To test whether self-esteem predicted differences in perceptions of acceptance, we conducted a hierarchical multiple regression in which self-esteem (mean centered; M = 7.20, SD = 1.09), condition (dummy coded: low acceptance = 0, high acceptance = 1), and the interaction between the variables were used to predict perceptions of acceptance (M = 4.25; SD = 0.97). In this hierarchical procedure, which we used in all of the regressions that we report in this article, we entered main effects at Step 1, and the two-way interaction was added to the equation at Step 2. We interpreted the main effects from Step 1 of the analysis and interpreted the interaction obtained at Step 2. Moreover, in all of the studies in this article, when a significant interaction emerged at Step 2 of the regression, tests of simple effects were conducted according to Aiken and West’s (1991) recommendations.
Results revealed a main effect of condition, β = .41, t(76) = 4.14, p = .001, such that participants perceived less acceptance in the low-acceptance condition (M = 3.78, SD = 0.92) than in the high-acceptance condition (M = 4.65, SD = 0.82). Also, a main effect of self-esteem, β = .23, t(76) = 2.32, p = .023, indicated that across conditions, LSEs (i.e., participants scoring one standard deviation below the mean; Mest = 3.59) detected much less acceptance than did HSEs (i.e., participants scoring one standard deviation above the mean; Mest = 4.04). The interaction between self-esteem and condition was not significant (β = .08, t = 1). Thus, it appears that self-esteem predicted perceptions of acceptance at both higher and lower levels of acceptance.
This result replicates previous research by Brockner and Lloyd (1986) and Campbell and Fehr (1990), which demonstrated that LSEs also perceive less acceptance than HSEs from an interaction partner in a naturalistic, face-to-face interaction. However, our results are the first to demonstrate that self-esteem moderates perceptions of acceptance, even when acceptance cues are held constant across participants. In naturalistic social interactions, it is possible that LSEs’ social doubts lead them to behave in a cold manner, which in turn causes their interaction partner to behave in a reciprocal fashion, leading LSEs to (perhaps accurately) perceive less acceptance. On the other hand, HSEs’ confidence allows them to behave in a friendly manner, which in turn may cause their interaction partner to reciprocate, leading HSEs to (perhaps accurately) perceive greater acceptance. Hence, self-esteem differences in anticipated acceptance could lead to a self-fulfilling prophecy (e.g., Stinson, Cameron, Wood, Gaucher, & Holmes, 2009). Such potential “actor effects” were controlled in the present study, which suggests that the observed self-esteem differences in the perception of acceptance were indeed the result of motivated perception.
The present results also suggest that the biasing influence of self-esteem does not overwhelm actual situational differences in acceptance cues, because everyone, regardless of self-esteem, perceived more acceptance from the high-acceptance confederate than from the low-acceptance confederate. This condition effect suggests that LSEs’ relative underdetection of acceptance may not be a skill deficit: LSEs were capable of differentiating between higher and lower levels of acceptance. Study 2 was designed to explore further the skill-deficit hypothesis.”
[end of text box content]
Question
Looking back over the Results and Discussion section above, try to identify only the results that are directly relevant to the hypothesis we identified in Activity 4.
Reminders of what we have identified so far:
- Independent Variable: Self-Esteem
- Dependent Variable: Perceived Acceptance
- Hypothesis: Self-Esteem is positively associated with Perceived Acceptance.
- (i.e., higher self-esteem = more perceived acceptance, and lower self-esteem = less perceived acceptance)
Take a moment to answer the following question before turning it over to check your response:
[A show/hide dialogue created by Media replaces the content below]
[front of card content:] What results can you see here that show the relationship between Self-Esteem and Perceived Acceptance directly?
[back of card content:]
“a main effect of self-esteem, β = .23, t(76) = 2.32, p = .023, indicated that across conditions, LSEs (i.e., participants scoring one standard deviation below the mean; Mest = 3.59) detected much less acceptance than did HSEs (i.e., participants scoring one standard deviation above the mean; Mest = 4.04).”
This one sentence tells us everything we need to know; lower self-esteem was associated with less perceived acceptance. The rest of the results presented, though interesting and theoretically important, are not crucial to addressing the hypothesis.
[end of Activity 7]
Deception in Social Psychology Experiments
You may have wondered whether the participants in the video game study that we just discussed were told about the research hypothesis ahead of time. In fact, these experiments both used a cover story—a false statement of what the research was really about. The students in the video game study were not told that the study was about the effects of violent video games on aggression, but rather that it was an investigation of how people learn and develop skills at motor tasks like video games and how these skills affect other tasks, such as competitive games. The participants in the task performance study were not told that the research was about task performance. In some experiments, the researcher also makes use of an experimental confederate—a person who is actually part of the experimental team but who pretends to be another participant in the study. The confederate helps create the right “feel” of the study, making the cover story seem more real.
In many cases, it is not possible in social psychology experiments to tell the research participants about the real hypotheses in the study, and so cover stories or other types of deception may be used. You can imagine, for instance, that if a researcher wanted to study racial prejudice, he or she could not simply tell the participants that this was the topic of the research because people may not want to admit that they are prejudiced, even if they really are. Although the participants are always told—through the process of informed consent—as much as is possible about the study before the study begins, they may nevertheless sometimes be deceived to some extent. At the end of every research project, however, participants should always receive a complete debriefing in which all relevant information is given, including the real hypothesis, the nature of any deception used, and how the data are going to be used.
An interactive H5P element has been excluded from this version of the text. You can view it online here:
https://opentextbc.ca/socialpsychology/?p=3142#h5p-3
H5P: TEST YOUR LEARNING: CHAPTER 1 DRAG THE WORDS – TYPES OF RESEARCH DESIGN
Now that you have reviewed the three main types of research design used in social psychology, read each brief summary of empirical findings below and identify which type of design the results were derived from – experimental, observational or correlational. Table 1.4 contains some helpful information here.
There is a positive relationship between level of academic self-concept and self-esteem scores in university students.
People are more persuaded if given a two-sided versus a one-sided message.
People assigned to a group of four are more likely to conform to the dominant response in a perceptual task than people tasked with performing the task alone.
People in individualistic cultures make predominantly internal attributions about the causes of social behavior.
The more hours per month individuals spend doing voluntary work with people who are socially marginalized, the less they tend to believe in the just world hypothesis.
13 year-olds engage in more acts of relational aggression towards their peers than 8 year-olds.
Interpreting Research
No matter how carefully it is conducted or what type of design is used, all research has limitations. Any given research project is conducted in only one setting and assesses only one or a few dependent variables. And any one study uses only one set of research participants. Social psychology research is sometimes criticized because it frequently uses university students from Western cultures as participants (Henrich, Heine, & Norenzayan, 2010). But relationships between variables are only really important if they can be expected to be found again when tested using other research designs, other operational definitions of the variables, other participants, and other experimenters, and in other times and settings.
External validity refers to the extent to which relationships can be expected to hold up when they are tested again in different ways and for different people. Science relies primarily upon replication—that is, the repeating of research—to study the external validity of research findings. Sometimes the original research is replicated exactly, but more often, replications involve using new operational definitions of the independent or dependent variables, or designs in which new conditions or variables are added to the original design. And to test whether a finding is limited to the particular participants used in a given research project, scientists may test the same hypotheses using people from different ages, backgrounds, or cultures. Replication allows scientists to test the external validity as well as the limitations of research findings.
Common Weaknesses in Experiment Design [6:17 min] by TRU (n.d.)
[Production: If transcript of video is not already available, please include the following transcript text and accordion it under the title.]
Some Common Weaknesses (or Strengths) in Social Psychological Research
This list is not intended to be comprehensive; the goal is to provide you with a few starting points to target when critically consuming research. All too often, undergraduate students will read an academic journal article and think it is infallible. The following topics should give you a better understanding of where you can look for shortcomings in even the most intimidating articles.
Sample Size – A smaller number of participants in a study means we can’t be as confident when trying to extend our findings to a larger population. Consider the example of flipping a coin. The probability of a coin toss coming up heads (or tails) is 50%. If we were to test this by flipping a coin 10,000 times, we would most likely end up fairly close to a 50:50 split between heads and tails. If, however, we only flipped the coin 10 times, we might end up with 7 heads and 3 tails. We would conclude from our little experiment that the probability of a coin toss landing on heads is 7/10 or 70%, which we know is not accurate. The smaller the sample size, the more likely we are to get a result due to chance that does not accurately represent the broader population (in this case, the population of all coin flips).
Demand Characteristics – If the participant knows what is expected of them, they will often act how they think they are supposed to act. This can be the result of the researchers’ behavior or the design of the study. For example, if a couple is brought into the lab and told that they will be testing a new form of couples’ therapy, they will likely show improvements in relationship satisfaction and managing conflict after the new treatment simply because they know that the treatment is supposed to improve their relationship. One of the best ways to avoid these kinds of demand characteristics is to have a convincing cover story. If participants don’t know what the true purpose of the study is, they won’t be able to act in a way that confirms the researchers’ hypothesis.
Third Variables / Confounds – This is especially important in correlational research as we have already discussed how there is always the possibility in correlational research that some other variable is causing the results we see. We may also have alternative explanations for our findings in experiments, though, as a side effect of our design. Imagine we are designing a study to explore the effects of choice on happiness. In one condition, participants get to choose between eating a carrot or eating a chocolate bar. In the other condition, participants are randomly assigned to eat either the carrot or the chocolate bar. We would likely find that participants in the choice condition are much happier at the end of the study, but was it really the choice that made them happier? Chances are, the participants in the no-choice condition were evenly split between eating the carrot and eating the chocolate, whereas most of the participants in the choice condition chose to eat the chocolate rather than the carrot. In this case, having a choice didn’t make them happier, eating chocolate did. We need to be particularly careful when designing studies to avoid introducing confounds. One of the best ways to do this is to try to make the experiences of participants in different conditions as similar as possible except for the one crucial piece that we are testing. (In the example above, the researchers could have test run the choice condition to find out what the average proportion of people choosing the carrot vs. the chocolate was and then used that proportion in the no-choice condition to ensure that the conditions were balanced.)
Sampling – This is a broad category and can apply to any numbers of characteristics related to the sample of participants being recruited for the study. If there is any reason to believe that this particular group of people is different from the broader population, it will limit our ability to generalize the results of our study to other people. This could include recruiting a sample that is all within the same age group (not representative of older or younger people), all heterosexual (not representative of anyone who does not identify as heterosexual), all white (not representative of other racial backgrounds), all supporting the same political party, etc. This could also apply to motivations. If we advertised a study that is intended to improve mindfulness for participants, we would likely find volunteers that are already motivated to practice mindfulness and don’t represent the broader population.
I have worded these examples quite strongly, but it doesn’t have to be this extreme. Any imbalance on any of these factors compared to the population as a whole could limit the generalizability of our findings. The best way to address this is by recruiting a representative sample that matches the population distribution as closely as possible. This approach is much more expensive and time-consuming, however, so the lack of sample representativeness tends to be one of the most common weaknesses you will find in academic research. The vast majority of research comes from WEIRD (White, Educated, Industrialized, Rich, and Democratic) samples resulting in findings that are potentially very biased and may not generalize to other groups / populations. One notable exception, however, is when we are dealing with research focused on one specific population. If we were interested in studying the effects of attachment styles in homosexual relationships, for example, then using a purely homosexual sample would actually be a strength rather than a weakness because we are not trying to generalize to non-homosexual populations.
[End of transcript text]
In some cases, researchers may test their hypotheses, not by conducting their own study, but rather by looking at the results of many existing studies, using a meta-analysis—a statistical procedure in which the results of existing studies are combined to determine what conclusions can be drawn on the basis of all the studies considered together. For instance, in one meta-analysis, Anderson and Bushman (2001) found that across all the studies they could locate that included both children and adults, college students and people who were not in college, and people from a variety of different cultures, there was a clear positive correlation (about r = .30) between playing violent video games and acting aggressively. The summary information gained through a meta-analysis allows researchers to draw even clearer conclusions about the external validity of a research finding.
Figure 1.16 Some Important Aspects of the Scientific Approach
Scientists generate research hypotheses, which are tested using an observational, correlational, or experimental research design.
The variables of interest are measured using self-report or behavioral measures.
Data is interpreted according to its validity (including internal validity and external validity).
The results of many studies may be combined and summarized using meta-analysis.
[Activity 8 added as new content:]
Activity 8: The Good, the Bad, and the Academic
[Production: please update this statement to include mention of 3271.] *This section of the open course textbook is designed to support PSYC 3261 and PSYC 3271, and the activity numbering corresponds to Unit 1 in both courses.
Introduction
It is finally time to tackle the Cameron et al. (2010) article used in Activity 4, 5 and 7, in its entirety. You can access the article in the Resources section of the course in Moodle or through the TRU Library using this link. We will once again be focusing only on Study 1. For this activity, you will be reading through the actual article from the Abstract up to the end of the Study 1 Results and Discussion section.
Read through the introduction and the theoretical rationale for this line of research, let the authors convince you that they have thought of everything and designed an incredible study, then remind yourself that they are only human and just a few short years ahead of you in their careers… and find a weak spot.
Instructions
As you read the Introduction and Study 1 in the article, keep in mind the common weaknesses (or strengths) in social psychological research outlined in the Interpreting Research section of “1.3: Conducting Research in Social Psychology” of your open access textbook. Try to identify two aspects of the study that you feel were done well and two that you feel are potential issues. You can compare your answers to the strengths and weaknesses identified in these slides:
[H5P slides created by Media]
[slide 1 – title slide:] Strengths and Weaknesses of Study 1 in Cameron et al.
[slide 2:] Strengths of Study 1:
Self-esteem scale disguised by including distractor scales in the survey
Elaborate cover story to disguise true purpose of the study
Similarities between conditions
Same confederates used in both conditions
Confederates answered the same questions in both conditions
[slide 3:] Weaknesses of Study 1:
Very small sample size
Homogenous sample (all psych undergrads, 18–25, all heterosexual)
Mostly single <= perhaps people who are better at estimating acceptance are more likely to be in a relationship
Perceived acceptance scale items all worded positively (i.e., refer to being liked and accepted rather than being disliked or rejected). The authors discussed how HSEs are more focused on acceptance and LSEs are more focused on avoiding rejection. LSEs and HSEs may respond differently to “Acceptance” items and “Rejection” items. This is not necessarily a weakness given the focus of this research but could represent a potential future direction for further research.
Differences in scripts adds potential confounds:
Accepting confederate seems more positive / extraverted
More self-disclosure <= can be a sign of acceptance, but LSEs and HSEs may differ in how they feel about receiving disclosures from a stranger (i.e., oversharing too early?)
[end of Activity 8]
It is important to realize that the understanding of social behavior that we gain by conducting research is a slow, gradual, and cumulative process. The research findings of one scientist or one experiment do not stand alone—no one study proves a theory or a research hypothesis. Rather, research is designed to build on, add to, and expand the existing research that has been conducted by other scientists. That is why whenever a scientist decides to conduct research, he or she first reads journal articles and book chapters describing existing research in the domain and then designs his or her research on the basis of the prior findings. The result of this cumulative process is that over time, research findings are used to create a systematic set of knowledge about social psychology (Figure 1.16, “Some Important Aspects of the Scientific Approach”).
An interactive H5P element has been excluded from this version of the text. You can view it online here:
https://opentextbc.ca/socialpsychology/?p=3142#h5p-4
[Production: remove ch.1 t/f quiz below]
H5P: Test your Learning: Chapter 1 True or False Quiz
Try these true/false questions, to see how well you have retained some key ideas from this chapter!
Social psychology is a scientific discipline.
Cultural differences are rarely studied nowadays in social psychology because it has been established that all of its important concepts are universal.
In social psychology, the primary focus in on the behavior of groups, not individuals.
Factorial designs are a type of correlational research.
Nonrandom assignments of participants to conditions in experimental social psychological research ensures that everyone has an equal chance of being in any of the conditions.
Key Takeaways
Social psychologists study social behavior using an empirical approach. This allows them to discover results that could not have been reliably predicted ahead of time and that may violate our common sense and intuition.
The variables that form the research hypothesis, known as conceptual variables, are assessed by using measured variables such as self-report, behavioral, or neuroimaging measures.
Observational research is research that involves making observations of behavior and recording those observations in an objective manner. In some cases, it may be the only approach to studying behavior.
Correlational and experimental research designs are based on developing falsifiable research hypotheses.
Correlational research designs allow prediction but cannot be used to make statements about causality. Experimental research designs in which the independent variable is manipulated can be used to make statements about causality.
Social psychological experiments are frequently factorial research designs in which the effects of more than one independent variable on a dependent variable are studied.
All research has limitations, which is why scientists attempt to replicate their results using different measures, populations, and settings and to summarize those results using meta-analyses.
Activity 9: Topic 2 – Research Methods Practice Quiz
[Production: please add this statement] *This open course textbook is designed to support PSYC 3261 and PSYC 3271, and the activity numbering corresponds to Unit 1 in both courses.
Introduction
Try these practice questions to see how well you have retained some key ideas from this section.
Instructions
You can attempt these quiz questions as many times as you like. If you find you are having difficulty with a particular question, try checking the feedback and reviewing the recommended sections.
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Non-random assignments of participants to conditions in experimental social psychological research ensures that everyone has an equal chance of being in any of the conditions.
True
False
[feedback for wrong answer:] Not quite. Try again! It could also be useful to look again at the section on experimental research, with particular focus on the importance of random assignment.
Factorial designs are a type of correlational research.
True
False
[feedback for wrong answer:] Not quite. Try again! Maybe also review the sections on correlational and experimental research, making notes on their key differences.
Cultural differences are rarely studied nowadays in social psychology because it has been established that all of its important concepts are universal.
True
False
[feedback for wrong answer:] Not quite. Try again! You may also want to take another look at the section in this topic on how different cultures have different norms.
Researchers find a significant correlation between peoples’ self-esteem and their conformity to fashion norms. What does this mean?
That changes in conformity to fashion norms cause changes in self-esteem
That changes in self-esteem have no effect on conformity to fashion norms
That changes in self-esteem and conformity to fashion norms are related to each other
That changes in self-esteem cause changes in conformity to fashion norms
[feedback for wrong answers:] Not quite. Try again! You may want to review the section of this topic on correlation.
A pharmacologist wants to know if their new invention, a smart pill, is effective. They measure intelligence using a popular IQ test before and after exposure to the compound. The difference in test scores is:
The dependent variable.
The control group.
Unethical.
The cause.
[feedback for wrong answers:] Not quite. Try again! Try looking over the section in this topic about operational definitions of variables again.
[end of quiz]
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For PSYC 3261, this marks the end of Unit 1, Topic 2: Research Methods. Please go to chapter section 2.2 How We Use Our Expectations to begin Topic 3: Accessibility in PSYC 3261.
For PSYC 3271, this marks the end of Unit 1, Topic 2: Research Methods. Please go to Chapter 4 Attitudes, Behaviour, and Persuasion to begin Topic 3: Behavior and Attitudes.
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Exercises and Critical Thinking
Using Google Scholar find journal articles that report observational, correlational, and experimental research designs. Specify the research design, the research hypothesis, and the conceptual and measured variables in each design.
For each of the following variables, (a) propose a research hypothesis in which the variable serves as an independent variable and (b) propose a research hypothesis in which the variable serves as a dependent variable.
Helping
Aggression
Prejudice
Liking another person
Life satisfaction
Visit the website Online Social Psychology Studies and take part in one of the online studies listed there.
References
Anderson, C. A., & Dill, K. E. (2000). Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life. Journal of Personality and Social Psychology, 78(4), 772–790.
Bushman, B. J., & Huesmann, L. R. (2010). Aggression. In S. T. Fiske, D. T. Gilbert, & G. Lindzey (Eds.), Handbook of social psychology (5th ed., Vol. 2, pp. 833–863). Hoboken, NJ: John Wiley & Sons.
Cameron, J. J., Stinson, D. A., Gaetz, R., & Balchen, S. (2010). Acceptance is in the eye of the beholder: Self-esteem and motivated perceptions of acceptance from the opposite sex. Journal of Personality and Social Psychology, 99(3), 513–529. https://doi.org/10.1037/a0018558
Eisenberger, N. I., Lieberman, M. D., & Williams, K. D. (2003). Does rejection hurt? An fMRI study of social exclusion. Science, 302(5643), 290–292.
Festinger, L., Riecken, H. W., & Schachter, S. (1956). When prophecy fails: A social and psychological study of a modern group that predicted the destruction of the world. Minneapolis, MN: University of Minnesota Press.
Greene, J. D., Sommerville, R. B., Nystrom, L. E., Darley, J. M., & Cohen, J. D. (2001). An fMRI investigation of emotional engagement in moral judgment. Science, 293(5537), 2105–2108.
Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world? Behavioral and Brain Sciences, 33(2–3), 61–83.
Lieberman, M. D., Hariri, A., Jarcho, J. M., Eisenberger, N. I., & Bookheimer, S. Y. (2005). An fMRI investigation of race-related amygdala activity in African-American and Caucasian-American individuals. Nature Neuroscience, 8(6), 720–722.
Lilienfeld, S. O. (2011, June 13). Public skepticism of psychology: Why many people perceive the study of human behavior as unscientific. American Psychologist. doi: 10.1037/a0023963
Meier, B. P., Robinson, M. D., & Wilkowski, B. M. (2006). Turning the other cheek: Agreeableness and the regulation of aggression-related crimes. Psychological Science, 17(2), 136–142.
Morewedge, C. K., Gray, K., & Wegner, D. M. (2010). Perish the forethought: Premeditation engenders misperceptions of personal control. In R. R. Hassin, K. N. Ochsner, & Y. Trope (Eds.), Self-control in society, mind, and brain (pp. 260–278). New York, NY: Oxford University Press.
Ochsner, K. N., Bunge, S. A., Gross, J. J., & Gabrieli, J. D. E. (2002). Rethinking feelings: An fMRI study of the cognitive regulation of emotion. Journal of Cognitive Neuroscience, 14(8), 1215–1229
Preston, J., & Wegner, D. M. (2007). The eureka error: Inadvertent plagiarism by misattributions of effort. Journal of Personality and Social Psychology, 92(4), 575–584.
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