​Causation importance persuasion research waterslide

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Bob is in charge of the local waterpark. At the beginning of the summer, he built a new waterslide for his park. At the end of the summer, he saw that his ticket sales were double what they were a year ago. What criteria should Bob consider to determine if the new waterslide caused the increase in ticket sales? Should Bob conclude that a causal relationship exists between the addition of the new waterslide and the increase in ticket sales? Why is it important to determine causation when conducting persuasion research?

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4 Persuasion Research: How Do We Know What We Know? Wavebreakmedia Ltd/Wavebreak Media/Thinkstock Learning Objectives After reading this chapter, you should be able to: • Appraise the value of research in understanding how we know what we know about persuasion. • Understand the three criteria for establishing causation. • Explain the methodology involved in conducting experiments, as well as the limitations of experimental research. • Evaluate the utility of verbal reports, behavioral measures, and physiological measures in assessing experimental outcomes. • Discuss the different ways in which verbal reports, behavioral measures, and physiological measures can be conducted. mag81516_04_c04_073-096.indd 73 8/15/14 2:46 PM Persuasion Research: How Do We Know What We Know? Look at this video of a persuasion experiment: http://www.youtube.com/watch?feature=player _detailpage&v=osUwukXSd0k. The researchers wanted to know what it would take to get kids to clean their hands before eating. They divide 80 kids into four experiment conditions, and each condition includes one or more factors that might encourage kids to clean their hands. You can think of each of these four elements as a cause and hand cleaning as the effect, with three different forms of influence—1) personal motivation (i.e., fear of getting sick from germs), 2) changing the environment (i.e., moving the hand sanitizer and adding a sign), and 3) increasing personal ability (i.e., practice using the hand sanitizer). They concluded that having four sources of influence is sufficient to get people to change their behavior. They called it “peer pressure,” but really the influence was a verbal reminder from a peer to the kids to wash their hands. Note that in the condition in which the kids practiced using the hand sanitizer that some kids (i.e., three kids) indeed used the hand sanitizer, but that was not enough to lead the other nine children to use it. Notice, however, that the data did not support the conclusion. An alternate explanation for kids washing their hands is that the “social influence” factor alone might have influenced their behavior. We don’t know if the verbal reminder by itself would be sufficient to get the kids to wash their hands. That possibility was not tested. Further, if you ask kids, or anyone else, after the fact to provide an explanation for why they did something, they will readily come up with a plausible explanation. Drawing conclusions that are not supported by the evidence is called “arguing beyond the data,” and we should be careful not to draw conclusions that the data do not support. The book that is promoted at the end of the video might provide ample evidence for the conclusion, but the experiment portrayed in the video itself does not provide compelling evidence. Such ambiguity in reaching definitive conclusions even in controlled environments prompts questions as to how we ever reach definitive conclusions generally in real life. How, in effect, do we know what we know? For example, if you’re trying to persuade someone to engage in a diet and exercise plan, should you use a testimonial that illustrates a typical case, or should you use statistics that summarize a lot of cases? How do you know which one is more effective? Or, if you are a salesperson, how does your appearance affect your performance? Would wearing a white shirt instead of a blue shirt help you close more sales? What about your hairstyle and hair color? Would wearing eyeglasses make you more credible? Are these factors in the sales process? If you’re a marketing executive, should you consider using product placements in movies to promote your brand? How would you be able to know if that would increase sales? In short, how do you know if a persuasion technique is effective? The way you can know—the only way we can really know anything for certain—is through research. In this chapter, you will learn about the experimental method, which is an important source of generating evidence for the science of persuasion and social influence. In doing so, you will also become a better “consumer” of experimental research so that you will be better able to evaluate the strengths of the evidence. Just as we were able to assess the experiment concerning children washing their hands, you will also be able to evaluate the merits of the research that is used to test many theories of persuasion and social influence. mag81516_04_c04_073-096.indd 74 8/15/14 2:46 PM How to Show Causation Section 4.2 4.1 The Value of Research Epistemology is the study of knowledge. Research is a way in which we acquire knowledge. Much of what we know today is due to systematic research endeavors. Often, though, we take our own personal experience and extend it, or generalize it, to a larger group. The problem with this is that our own experience may be different from the larger population. How can you know if what you experience is common to most other people? What is true in our own experience may not hold true for many other people. So, we conduct research to find out how we can know what we know, or what we think we know. Simply put, research provides evidence. Empirical research can employ many methods, such as focus groups, surveys, in-depth interviews, field observation, or experiments. What all of these methods have in common, though, is their purpose to help us discover an answer to a question. They are intended to help us acquire knowledge. Each method has strengths and weaknesses, and, often, the weaknesses of one method are the strengths of another method. The choice of best method to use depends on the question the researcher is asking. If the researcher wishes to explore a phenomenon, focus groups can be a good choice. If the researcher wants an in-depth understanding of why certain people do something, then in-depth interviews might be a good choice. Experiments are best suited for testing causation. Most of the theories in the science of persuasion deal with causal relationships; therefore, most of these theories are tested through experiments. If you are asking causal questions, then you must use experiments to test your answers, which is why this chapter focuses heavily on the experimental method. This is important because each of the theories that we will study and learn to apply must provide evidence that supports them. By understanding the experimental method, you can better evaluate the evidence that was used to test a theory. Before we describe experiments, let’s look at the three elements that are necessary to show evidence of a causal relationship. 4.2 How to Show Causation Philosopher John Stuart Mill established that three conditions are necessary to conclude that a causal relationship exists. To show that A, an independent variable, causes B, a dependent variable, you must show that A occurred before B. You must also show that there is a relationship between A and B. Thirdly, you must rule out alternate explanations for the relationship between A and B. The experiment is the best method for showing causation because it can be used to meet all three of these conditions. Through measures of the independent variable and the dependent variable, you can show a relationship between the variables. By manipulating the way you introduce the independent variable, you can establish time order. The experiment allows you to control for other types of factors and rule out alternate explanations. Let’s look at each of the three conditions. mag81516_04_c04_073-096.indd 75 8/15/14 2:46 PM How to Show Causation Section 4.2 Time Order To demonstrate a causal relationship between A and B, you must show that A happened before B. In laboratory experiments, it is rather easy to control the order in which the procedures take place. For example, Yang and Roskos-Ewoldsen (2007) tested the effect of type of product placement in movies. They showed people movie clips that featured product placements in which the protagonist used the product or the product just appeared in the background. Then they measured people’s brand attitudes and recorded their product choice. They found that having a protagonist use a product (compared with the product merely appearing in a scene) led to higher positive attitudes toward that brand. They also found, though, that people were more likely to choose a product if it appeared in the movie, regardless of whether it was used by a character or it merely appeared in the background. Because the researchers were able to show the clips before people reported their attitudes and made a choice, the researchers were able to demonstrate time order. TGPRN Kraft Foods Inc./PR Newswire/ Associated Press Besides the use of a celebrity athlete, what else might a social scientist study in this food advertisement? In other types of studies, particularly those that occur in the field, time order can be more difficult to ascertain. Some relationships are cyclical, and it can be hard to determine which factor causes which. For example, if you wanted to test the effect of Mountain Dew® product placements in movies on a person’s attitude toward the brand in a natural setting, you would have a harder time demonstrating time order. Because people have preexisting attitudes toward Mountain Dew, it can be hard to tell if seeing the Mountain Dew in a television show would increase a favorable brand attitude, or if people who have a favorable brand attitude would be more likely to notice the product placement in the first place. Existing Relationship It is not enough to show that A occurred before B. You must also show that there is a relationship between A and B. If there is a direct relationship, then when A moves higher, B also moves higher. If there is an inverse relationship, then when A moves higher, B moves lower, or vice versa. The relationship does not need to be directly proportional. That is, it is possible, for example, that when A moves two steps higher, B moves only one step higher. Ultimately, the experiment is trying to determine if there is a relationship between two variables, but this relationship can vary in degrees of strength; some relationships are stronger than others. mag81516_04_c04_073-096.indd 76 8/15/14 2:46 PM How to Show Causation Section 4.2 For example, there is a strong relationship between smoking and lung cancer. The more one smokes, the higher the incidence of lung cancer. There is also a link between smoking and skin cancer, but this relationship is not as strong. In the product placement study (Yang & RoskosEwoldsen, 2007), the researchers were able to manipulate the type of product placement (i.e., product used by the character versus only appearing in the background) and then measure attitudes toward the different brands to show that brand attitudes were higher when a protagonist used the product than when the product only appeared in the background. Thus, they were able to show a relationship between the type of product placement and brand attitudes. Rule Out Alternate Explanations To conclude that A caused B, it is not enough to demonstrate that A occurred before B and that there is an association between A and B. The third condition for demonstrating a causal relationship between A and B is to show that no other factor could account for the relationship between A and B. This third condition is the most difficult to establish because it involves accounting for many other potential variables—but often there are too many variables for research to adequately account for. This means no experiment will allow a researcher to claim causation between two variables with 100% certainty, but it also makes researchers strive to do everything they can to obtain the most convincing results. A variable that can influence a study’s findings is called a confound and diminishes the confidence we have in the study’s results because it provides an alternate explanation for the study’s findings. In other words, a confound is some variable outside the relationship of interest that can influence the behavior of the dependent variable. Researchers must begin by trying to account for other factors that are likely explanations for the apparent relationship between two variables. The relationship must be probable or plausible, not merely possible. Determining the extent of confidence in the research findings requires the refutation of as many alternative explanations as possible. If a legitimate alternative explanation of a study’s results can be presented, then the study’s conclusions are suspect. Importantly, an outcome such as this also prevents possibly passing on erroneous information to the rest of the scientific community. If, on the other hand, no alternate explanation is found, then that increases the confidence in the relationship found between the two variables. For example, Yang and Roskos-Ewoldsen (2007) had to consider several alternate explanations for why someone might choose a product that had appeared in the movie over a similar product that did not appear in the movie. It is likely that some people had previously seen one of the movies, or that they already were familiar with the brand, or that they already had a favorable attitude toward that brand. To account for these potential alternate explanations, the researchers recorded this information and then included it in their statistical tests. They were able to show that there was a relationship between product placements and people’s choice even after they took into account (or “controlled for”) these other variables. Example Imagine that Anna runs a clothing boutique and spends money on advertising only in November of each year. She also records a surge in sales in December compared with the other months of the year when she does not spend money on advertising. Can she conclude that the mag81516_04_c04_073-096.indd 77 8/15/14 2:46 PM Experiments: Ways to Test Causation Section 4.3 independent variable of advertising caused the dependent variable, namely, the increase in sales? Let’s examine the three criteria to establish causation. Anna can show time order because the advertising expenditure occurred before the increase in sales. She can also use the measures of advertising expenditures and sales to demonstrate an association. That leaves us with the third criterion of accounting for alternate explanations. Are there any other ways to explain this increase in sales? In the United States, retail sales surge in December because of holiday-season gift giving. The variable of holiday gift giving, or more generally, seasonality, can explain the increase in sales in December. So, Anna cannot be fully confident that her advertising is the cause of the increase in her sales. Now, let’s describe experiments. 4.3 Experiments: Ways to Test Causation Most of the theories in persuasion science concern cause-effect relationships. For example, a theory might propose that demonstrating to someone the personal relevance of the topic of a persuasion appeal will increase that person’s motivation to pay attention to the appeal. Another theory might propose that using vivid imagery in an entertaining story will increase the likelihood that a reader or viewer will adopt beliefs that are embedded in the story. These types of theorized relationships are causal in nature. Among the many research methods available to investigators, the experiment is the best way to test a causal relationship (or lack thereof) between two variables because it allows for some element of control not available in most real-life settings. In simplest terms, an experiment is a research study whereby a researcher manipulates one variable in order to see the consequences of that manipulation. Experiment Basics In experiments, an independent variable can be thought of a cause that has some sort of effect on a dependent variable, or outcome variable. In the video of the hand- cleaning experiment, the four different elements—the sign, the verbal reminder, and so on—were the independent variables. Cleaning hands was the dependent variable, measured as the number of kids who used the hand sanitizer, not the number of kids who wiped their hands on their pants. Experimental researchers often refer to the independent variable as a factor. An independent variable is sometimes called a manipulated variable because the researcher changes the variable (e.g., adding a sign) to see what effect it might have on the dependent variable (e.g., using hand sanitizer before eating a cupcake). The independent variable is also referred to as a treatment variable because one group, the treatment condition, will receive the experimental treatment, while another group, the control condition, will not receive the treatment. A control condition serves as a comparison group or baseline against which the researcher can compare the treatment’s effects. With these two conditions, the researcher can then compare the effect of the manipulation on the dependent variable. mag81516_04_c04_073-096.indd 78 8/15/14 2:46 PM Experiments: Ways to Test Causation Section 4.3 A true experiment includes random assignment, which means that the study’s participants were assigned to the treatment and control groups in a random way (Keppel & Wickens, 2004). Doing this lets the researcher assume that the groups are equal in virtually every way. So, if the treatment and control groups differ after a manipulation, then the only plausible explanation is the manipulation itself. The children in the hand-cleaning study likely were assigned to the four groups in a random manner. If so, then we can assume, for example, that even ©Getty Images/Jupiter Images/Goodshoot/Thinkstock though some of the kids’ parents might When performing a field experiment, a researcher observes relationships between variables in natural have stressed cleanliness, these kids were randomly distributed across all settings, such as an elementary school. four groups, that they didn’t somehow all wind up in the fourth group. Sometimes, however, the researcher cannot realistically assign people to the treatment and control groups in a random fashion. In this case, when random assignment is absent, the experiment is called a quasi-experiment. For example, let’s say the researchers had wanted to test whether boys, more than girls, would respond more favorably to the experiment’s treatments. The researchers can’t randomly assign some kids to be boys and others to be girls. In this case, the study would be a quasi-experiment. Usually, a researcher wants to remove, or control for, all the possible sources of extraneous influence on the independent and dependent variables so that she can focus on the relationship between the independent and dependent variables. To do so, she conducts the experiment in a controlled setting such as a laboratory. An experiment that occurs in this type of setting is called a laboratory experiment. In the hand-cleaning experiment, for example, the researchers wanted to have control over the placement of signs and hand sanitizing gel. Sometimes, however, a researcher will want to test the relationship between the independent and dependent variables in a natural setting to see if the relationship will hold up in the field. An experiment that occurs in this type of environment is called a field experiment (Shadish, Cook, & Campbell, 2002). For example, you will read (in Chapter 12) about an experiment involving a donation box that took place at the entrance to an art gallery, not in a controlled laboratory setting. As you can imagine, most lab experiments are true experiments (if they include random assignment), and most field experiments are quasi-experiments (because random assignment is difficult to achieve). Because lab experiments involve tight control, researchers are concerned with external validity, which is the degree to which the phenomena manipulated and measured in the experiment can be extended beyond the lab (Shadish, Cook, & Campbell, 2002). A lab experiment that has high levels of external validity tends to have independent variable manipulations that reflect what occurs in the “real world.” Field experiments tend to be strong in mag81516_04_c04_073-096.indd 79 8/15/14 2:46 PM Experiments: Ways to Test Causation Section 4.3 external validity if the relationship between the independent variable manipulations and dependent variable observations hold up in a natural setting. Random Assignment Random assignment is critical to the validity of a research study because it makes sure the treatment and control groups are equal before the study begins, and it also helps eliminate potential researcher bias. If you implement random assignment correctly, then you can assume that each of the groups in the experiment is essentially equal to the other (Shadish, Cook, & Campbell, 2002). In this way, random assignment is an important feature that helps rule out potential confounds. If you assign your participants to the experiment’s treatment and control conditions using a method of randomization, then you can assume that any unique or idiosyncratic characteristic that might exist among the participants is distributed across both conditions. If, for example, you think that a person’s birth order might make a difference in how they respond to an advertisement, you can randomly assign people to the treatment and control conditions and assume that the factor of birth order is distributed across both conditions. Likewise, if you think that ethnicity might influence responses to a persuasive appeal, then random assignment will help ensure equal distribution among experimental groups. Many times random assignment is not possible for practical or ethical reasons. As mentioned earlier, quasi-experiments, or field experiments, occur outside of a laboratory setting. Because quasi-experiments are conducted outside of a lab, researcher control is diminished and random assignment is not possible. Some variables are naturally occurring in society, and you cannot really assign people to one of those variables. For example, you cannot assign someone to be a particular age, to be of a particular race, or to live in a particular region. In these cases, you cannot have random assignment. This type of quasi-experiment can be a useful test of causal relationships, but you must take extra care to demonstrate that anything that might have led the study participants to be in either the treatment or control condition did not also affect the way they responded during the study (Shadish, Cook, & Campbell, 2002). To assert a causal relationship between an independent and dependent variable, it is rather easy to demonstrate time order and the existence of a relationship between the variables. Ruling out alternate explanations, however, is the hardest part of drawing conclusions about a causal relationship. That is why random assignment is so important—because it makes it easier for you to conclude that a difference between the treatment and control conditions is due to your experimental manipulation and not something else. Interaction Effect As we noted earlier, the independent variable that is manipulated in an experiment is often referred to as a factor. When you have two factors that are crossed with each other, that is, mag81516_04_c04_073-096.indd 80 8/15/14 2:46 PM Experiments: Ways to Test Causation Section 4.3 when you have two independent variables that are manipulated in conjunction with each other, you have what is called a factorial design (Keppel & Wickens, 2004). This type of experimental design lets you see if one independent variable interacts with another independent variable. Let’s say you wanted to examine ways to persuade children to take baths, and let’s say that seeing an animated character sing a song in the bathtub leads to an increase in children’s bathing intentions compared with a video in which the character does not sing a song. Another technique that leads to an increase in children’s bathing intentions is to present a rubber duck compared to an absence of a rubber duck. You might then wonder if the combination of seeing a rubber duck and having a character sing a song might interact with each other to have a joint effect. Now we have two factors, the presence or absence of a yellow rubber duck, and a character who either sings a song or does not sing a song. This is referred to as a 2 by 2 (or 2 3 2) factorial design because each of the factors has two levels: the yellow rubber duck (present versus absent) and the character (singing versus not singing). So, to conduct the experiment, we would prepare four videos. The first video would feature a yellow rubber duck present and a character singing a song. In the second video, the yellow rubber duck would be absent, and the character would sing a song. The third video would feature a yellow rubber duck, with the character not singing a song. In the fourth video, the yellow rubber duck would be absent and the character would not sing a song. Then, we could measure children’s bathing intentions in each of the four conditions. If bathing intentions are highest in the condition in which the yellow rubber duck is present and the character sings a song, then we would have evidence of an interaction. That is, the presence of the yellow rubber duck and the character singing a song work together to increase in bathing intentions more than they would on their own. To express it more precisely, the effect of one factor depends in part on the other factor. These effects of such a study are illustrated in Table 4.1. Table 4.1: Bathing intentions (on a scale of 1–5) Yellow Rubber Duck Character Yes Singing No Present Absent 4.7 3.5 3.8 2.2 In practice, a single experiment rarely goes beyond the manipulation of three factors simultaneously because the statistical tests become too complex and difficult to interpret. These experiments can also become harder to implement. If scientists wish to examine several factors, they tend to do so with a series of simple focused experiments, and not a single complex experiment. mag81516_04_c04_073-096.indd 81 8/15/14 2:46 PM Experiments: Ways to Test Causation Section 4.3 Persuasion in Focus: Aztec Queso Dip and Scarcity Appeals Ever heard of the Aztec Queso Dip from Taco Bell? Don’t feel left out if you haven’t. It was a fictitious product made up for an experiment measuring the persuasiveness of ad copy. Aguirre-Rodriguez (2013) designed a set of experiments to assess whether people would be more likely to be persuaded by an ad if it made claims about scarcity, in terms of supply versus demand. She was interested in discovering if supply-related scarcity (SRS) was more effective to use than demand-related scarcity (DRS). Specifically, the supply was the number of coupons for the dip and the demand was interest in getting the coupons. To test her initial hypotheses, she conducted experiments. Here we will focus on her second experiment, which tested whether specificity in supply or demand would influence people’s reactions to the ads. First, she developed four ads. All ads started with the following language: “New! The Aztec Queso Dip. Try it for free!” The supplemental text for each of the four ads follows, based on supply-related appeals and also demand-related appeals: Supply-Related Scarcity Appeals a) Specific—”Only 500 households per zip code can claim a coupon. Due to restricted supply, this offer’s availability is limited!” b) Nonspecific: “A maximum number of households per zip code can claim a coupon. Due to restricted supply, this offer’s availability is limited!” Demand-Related Scarcity Appeals c) Specific: “Over 500,000 have already responded to this offer. Due to popular demand, this offer’s availability is limited!” d) Nonspecific: “Thousands have already responded to this offer. Due to popular demand, this offer’s availability is limited!” This was a 2 × 2 factorial experiment with type of scarcity (supply versus demand) as one independent variable, and specificity (specific versus nonspecific) as the other independent variable. First, Aguirre-Rodriguez created four ads, and each of these ads represented one of the combinations of the independent variables. Then, she randomly assigned each of the study’s participants to view one of the four ads. Both types of appeals proved to have degrees of persuasiveness. But what was the most persuasive strategy to gain participant interest? It was b)—Using nonspecific numbers and appealing to the scarcity of supply. With that strategy, audiences could logically assume the company could control how many coupons are released. The supply-related scarcity appeals were more persuasive because the were less likely to generate skepticism. In fact, Aguirre-Rodriguez explained that these types of scarcitybased appeals were perceived as being informative instead of being persuasive. Demandbased appeals were more likely to generate skepticism in the audience, as they could easily identify a persuasive element in the ad (i.e., the ads sounded like it was trying to persuade). With demand-based appeals, participants were more likely to question the ability to even measure demand, and, therefore, they questioned the whole ad, a phenomenon described in more detail in Chapter 9. —Cheri Ketchum, Ph.D. (continued) mag81516_04_c04_073-096.indd 82 8/15/14 2:46 PM Experiments: Ways to Test Causation Section 4.3 Persuasion in Focus: Aztec Queso Dip and Scarcity Appeals (continued) Critical Thinking Questions 1. 2. Look closely at the language of both supply and demand appeals. What language do you think set supply apart from demand appeals? That is, what about the supply appeals in option b proved most effective? Which of these appeals would you use as the marketer for this product? Choose one, or create a new appeal entirely that you feel would work better. Reference Aguirre-Rodriguez, A. (2013). The effect of consumer persuasion knowledge on scarcity appeal persuasiveness. Journal of Advertising, 42, 371–379. Strengths and Weaknesses of Experiments Experiments are the “gold standard” for demonstrating causation. This is because experiments provide the control that researchers need to show causation. Experiments allow the researcher to show time order, namely, that the independent variable occurred before the dependent variable. They also allow the measurement that is needed to show a relationship between the independent and dependent variables. Finally, they allow the researcher to take into account and rule out alternate explanations. Keep in mind, however, that experiments are not intended to address all of the factors that might influence the outcome of a persuasion appeal. Experiments are intended to answer a specific question that focuses on one factor or on one process. In the real world, you know that a multiplicity of factors can interact to influence the outcome of a particular persuasion episode. Most empirical studies are not designed to test all of the factors in a single setting. Experiments provide control, in the sense that they allow the researcher either to eliminate or to control for the influence of other factors so that the researcher may concentrate on a particular phenomenon of interest. This focus and tight control is an advantage of the experimental method. It is also a weakness because it can come at the expense of external validity. A scholar may demonstrate that a particular phenomenon occurs in a laboratory, but once he moves to the real world, this phenomenon also would interact with any other host of factors that tend to accompany a persuasion episode. Experiments rest on the ceteris paribus assumption that “all else is equal.” In the real world, though, “all else” is never equal. College Students as Participants Some people criticize experiments for using college students as participants. However, using college students in a study is not a weakness in itself. The appropriateness of any experiment’s sample depends on the question that the researcher is asking (Mook, 1983). To criticize a study for using college students, you first must explain how college students are different from some other population on an important variable that matters to the study. Then, you must explain mag81516_04_c04_073-096.indd 83 8/15/14 2:46 PM Measuring Experiment Outcomes Section 4.4 how the study’s results would have been different had the experiment used a different type of participant sample. Using a sample of college students actually can make for a stronger study because it is harder to detect a difference between treatment and control conditions when the conditions are very similar in every other way (Lynch, 1982; Mook, 1983). Number of Participants Some people criticize experiments for the small number of participants that are involved. However, a large sample size is not necessarily better in an experiment. It is not true that a greater number of participants leads to a more generalizable study, or greater external validity (Mook, 1983). The purpose of an experiment is to test a causal relationship, and the processes through which an effect occurs. If you can detect a causal relationship with a small sample, then the effect must be quite strong. If, for example, you can show that having a speaker wear glasses increases the speaker’s persuasiveness, and you can do so with a sample of 50 participants, you should expect the same result if you had 100 participants. As long as the research methodology was sound, you would not expect the pattern of results to change in a different direction merely because you added more participants to the experiment’s conditions. Overall, experiments remain the best method for testing causal relationships. By manipulating one or more independent variables, a persuasion researcher can see precisely what type of effect it might have on a person’s attitudes. 4.4 Measuring Experiment Outcomes Attitudes are the primary dependent variable in persuasion research. We defined attitude (in Chapter 1) as a tendency toward a particular object that has some sort of valence. That valence can be either favorable or unfavorable. It should occur to you now, however, that we cannot really see attitudes. Attitudes are mental states, so how can we measure something that we cannot see? Scientists have developed many ways to assess a person’s attitudes, but they can be grouped into three categories. The first way involves verbal reports—in other words, simply asking people to express how they feel about something. The second way involves measuring behavior, which reflects their attitudes. The third way involves taking measures of psychophysiological responses. That is, the body’s responses can be used to draw conclusions about a person’s attitudes. Verbal Reports: What People Say Obtaining verbal report data involves asking people questions, such as asking someone in person via an interview or via a survey that requires the person to answer a series of mag81516_04_c04_073-096.indd 84 8/15/14 2:46 PM Measuring Experiment Outcomes Section 4.4 questions. The most common type of verbal reports consists of self-report data. Experiments often involve survey-like questionnaires to assess a person’s attitudes. Verbal reports are the most common form of dependent variable in persuasion research because they are efficient and cost effective. If you want to know how your friend Heidi feels about your new website, you can just ask her. This is a type of self-report data. Usually people will tell you the truth. Sometimes, though, they do not want to hurt your feelings, and they might not tell you what they really feel. Another problem is that a person may not have an attitude one way or the other about an issue, but she will make one up for you just to please you. Researchers need to be aware of these potential pitfalls on the part of their research participants, but they also need to be mindful not to bias responses or elicit information from participants that might skew results in inauthentic ways. Consequently, researchers must be mindful of the methodology they employ in creating and administering questionnaires. The following sections look more closely at some of the elements that go into developing sound verbal report tools. Question Order ©Mohd Khairi Ibrahim/iStock/Thinkstock Many researchers utilize self-report questionnaires to measure attitudes. Many studies employ questionnaires because they are an efficient way of gathering information from many people. However, you need to be aware of things that might influence the way a person responds to the questions. For example, the order in which questions are asked can influence how a person responds to questionnaire items. In normal conversation, once we have provided an answer to a question, we assume that the next question takes the previous information into account. In one study, married people were asked two questions, one about how satisfied they were with their life as a whole, and another about how satisfied they were with their marriage (Schwarz, 1999). When they were asked first about their life in general, the two answers correlated at r = 0.32. (A value of r = 0 means there is no association; a value of r = 1.0 means a perfect 1-to-1 association.) When respondents were asked about their marriage first, the two answers correlated at r = 0.67, a much stronger relationship (see Figure 4.1). This is because asking about their marriage first made marriage-related information more accessible, and this information then influenced how they responded about their life in general. For a more in-depth and easy-to-read look at why this happens, see Schwarz (1999). mag81516_04_c04_073-096.indd 85 8/15/14 2:46 PM Measuring Experiment Outcomes Section 4.4 Figure 4.1: Effect of question order Response Alternatives 0.8 0.7 Correlation 0.6 0.5 0.4 0.3 0.2 0.1 0 Asked about life in general first Asked about marriage first Source: Schwarz, N. (1999). Self-reports: How questions shape the answers. American Psychologist, 54, 93–105. Published by the American Psychological Association. Adapted with permission. An open-ended question provides a blank space for a person to provide an answer. However, after collecting the responses, the researcher must read and code every response, which can be time consuming. A closed-ended question asks a person to choose a response from a list of likely or anticipated responses. However, the list might lead the person to provide an answer that he had not thought of before. For example, people were asked what they thought was “the most important thing for children to prepare them for life.” When a closed-ended scale of alternatives was presented, more than 60% of the respondents selected “To think for themselves.” However, when the question was posed in an open-ended format, less than 5% of the respondents said something equivalent (Schwarz, 1999). Scale Values Scales come in many forms, but you are probably familiar with Likert-type scales, the most common type of scale. A Likert scale consists of five ordered response alternatives that include 1 = strongly disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, and 5 = strongly agree. If the scale includes any number other than five responses, researchers call it a Likerttype scale. A semantic differential scale consists of presenting a person a target object, such as an organization followed by pairs of opposite adjectives (e.g., bad–good; boring–interesting, etc.) with seven response alternatives between them. The person then selects the option that reflects how he feels about that organization. The values on a response scale can influence a person’s responses. In one study, respondents were asked, “How successful would you say you have been in life?” and presented an 11-point scale (Schwarz, 1999). Some respondents saw a scale with the points labeled 0 through 10, while other respondents saw the scale’s points labeled –5 to +5. In the first group of respondents, about 34% marked an answer on the scale’s lower half. In the second group of respondents, only 13% chose a value on the scale’s lower half. What do you think accounted for the difference? When people saw the scale labeled 0 to 10, they interpreted 0 to mean the absence of successes. People who saw the scale labeled –5 to +5 interpreted the label –5 to mean the presence of failures. The number of points on a scale can be important, too. In one study, Hispanic respondents tended to give more extreme responses on a 5-point scale than on a 10-point scale, while the extremity of Anglo-Saxon respondents did not vary on the different scale types (Hui & Triandis, 1989). When researchers want to keep people from selecting a middle, neutral, option, they will use a forced-choice scale. This type of scale typically has four or six options, with no middle mag81516_04_c04_073-096.indd 86 8/15/14 2:46 PM Measuring Experiment Outcomes Section 4.4 point. For example, the General Social Survey (Davis, Smith, & Marsden, 2007), a national U.S. survey, asked respondents the degree to which they agreed with this statement: “Morality is a personal matter and society should not force everyone to follow one standard.” The responses were the following: “A. Agree strongly; B. Agree somewhat; C. Disagree somewhat; D. Disagree strongly.” This format encourages people to indicate a preference, however so slight, toward one side or the other. This format can be used with topics for which people may wish to take a “safe” neutral ground. Of course, a person is always free not to respond. Also, some people can become upset over being unable to express a neutral stance if they believe they truly are neutral toward that topic. This type of scale should be used with caution. Strengths and Weaknesses of Verbal Data Verbal reports have several strengths. Verbal reports, usually questionnaires, are efficient and cost-effective ways of gathering lots of information. Most people have experience completing questionnaires, so they are easily understood. Likewise, most people will make an earnest effort to tell a researcher what they think, so questionnaires can be a direct way of assessing a person’s attitudes. Keep in mind, though, that verbal reports are not always the best measure of a person’s attitude. Question type and question order can influence people’s responses so that you do not obtain as accurate an assessment as you want. Sometimes, the problem is not with the scale. People will just simply lie. Sometimes they do this merely to protect someone’s feelings. Sometimes they even lie to themselves (“I’m a moral person,” or “I don’t stereotype people”). Sometimes, people are actually afraid to tell the truth. At other times, they really have no attitude, but they will make one up on the spot, just to “help” the researcher. Also, by asking people questions, you risk sensitizing them to the purpose of the experiment, and they might adjust their answers or behavior because they are aware that they are part of a study. So, because self-report data may not always be truthful or accurate, we need to find other ways of measuring people’s attitudes. One of those ways involves measuring a person’s behavior. Behavioral Measures: What People Do whitetag/iStock/Thinkstock Many retail outlets use behavioral data to learn about their customers. mag81516_04_c04_073-096.indd 87 The number of ways to measure a person’s behavior is almost limitless. Instead of asking a person how they feel about an attitude object, researchers can observe behavior and infer an attitude from the behavior. Many times, a person’s behavior can be a more authentic indicator than verbal data of their attitude toward an object. In other words, to obtain an accurate assessment of people’s attitudes, researchers can watch what people do and not just listen to what they say. 8/15/14 2:46 PM Measuring Experiment Outcomes Section 4.4 Choice Behavior A person’s choice behavior is an important dependent variable in experiments that marketers conduct. Many studies of persuasion offer a person a choice among two or more items, with the choice sometimes framed as a gift for participating in the study (e.g., Ferraro, Shiv, & Bettman, 2005; Yang & Roskos-Ewoldsen, 2007). Coupon redemption can be another behavioral measure in persuasion research. For example, supermarket shoppers were invited to sample jams from an assortment of either 6 or 24 flavors, after which they were offered a coupon that they could redeem for a jam within 1 week (Iyengar & Lepper, 2000). When 24 flavors were set out for sampling, 60% of shoppers stopped at the tasting booth. When 6 flavors were set out, only 40% of shoppers stopped for a taste. However, among the shoppers who encountered a wide array of choices, only 3% of them redeemed the coupon for a jam. In contrast, 30% of the shoppers who sampled jam from a limited variety redeemed the coupon. In this field experiment, stopping at a taste booth and redeeming a coupon were two behavioral measures that were used to see if the manipulation of assortment size would have an effect on shoppers. Response Latency The speed, or latency, with which someone answers a question can be an important outcome measure. Response latencies are measures of speed of activation, which are reflections of attitude and belief accessibility. If information is accessible to you, then you should be able to report that information more quickly, without having to “search” for or formulate an answer. For example, scientists can use keyboards that are accurate to the millisecond to record a baseline for how much time it takes for Xavier to respond to a set of questions. Then, they show him a product advertisement that includes either an appeal to pro-environment features or a focus on features that are unrelated to the environment. The pro-environment appeal should cause Xavier’s environmental values to become more accessible. After viewing the advertisement, Xavier completes a measure of his environmental values. If the values are truly important to Xavier, then the time it takes him to respond to the environmental scale items should be slightly faster after he views the pro-environment appeal. So, measuring the difference in response latencies between the treatment and control conditions can yield insight into the mental processes that are involved in persuasion. A specific test of attitudes that relies on response latencies is the Implicit Association Test (IAT). Remember, an attitude can be defined as an action tendency toward an attitude object (Chapter 1), and an implicit attitude (Chapter 2) is an attitude evaluation that we are not aware of and that we cannot control. The IAT assesses the relative strength of automatic associations between an attitude object (e.g., Barack Obama versus Hillary Clinton) and a valence (e.g., good versus bad). This test can also be used to measure the strength of an object (e.g., Black people versus White people) with a stereotype (e.g., athletic). The IAT shows a person an alternating series of objects and valence words and records the speed with which the person links the valence words with the object. If an object (e.g., Barack Obama) and a valence word (e.g., honest) are strongly associated in a person’s mind, then that individual will respond more quickly when seeing the word honest. So, if Krista feels that Barack Obama is more honest than Hillary Clinton, then she will associate the word honest with Barack Obama more quickly than she will with Hillary Clinton. If Krista does not associate honest with Barack Obama, then it will take her longer to link the two terms. The IAT is particularly useful for assessing biases concerning race, gender, and mag81516_04_c04_073-096.indd 88 8/15/14 2:46 PM Measuring Experiment Outcomes Section 4.4 other topics for which people are unable or unwilling to be truthful. For a more complete description of the IAT and its many uses, see Banaji and Greenwald (2013). Web Analytics Many marketers are interested in people’s behavior in online settings. Web analytics involves measuring a person’s interaction with online information (Kaushik, 2010). Many corporations collect and analyze this type of data because it is unobtrusive and occurs in a natural setting. This includes webpage navigation behavior such as which links a person clicks, how many pages a person browses, how much time is spent on a page, and so on. At a basic level, a report of a clickstream can provide a description of how people are navigating a website. However, if you have a good theory to help make sense of the data and discern relationships, a more advanced analysis can yield useful insights. Some marketers will try a promotion in one market (the treatment condition) but not in another (the control condition) to measure the promotion’s effectiveness using web analytics before trying it nationwide (Kaushik, 2010). Eye Tracking Scanning behavior can be measured by using eye-tracking equipment that follows a person’s focused gaze on a screen (Milosavljevic & Cerf, 2008). This equipment can be used to see what elements on a webpage, say, banner ads at the top or box ads on the side, first attract a person’s attention. It can also be used to see what type of content interests people most on a news site (see Bucher & Schumacher, 2006). In a study of magazine advertisements, consumers viewed magaReprinted by permission of LookTracker. www.looktracker.com zine advertisements to test which Eye-tracking devices measure what a person looks size factors (the brand, a picture, or at and how long he looks at it. ad copy) might influence visual attention (Pieters & Wedel, 2004). Eyetracking data revealed that the size of the text or copy (but not the brand or picture) predicted whether a consumer paid attention to the advertisement. Also, the larger the text, the more time consumers spent viewing the advertisement. However, the amount of time spent viewing ad copy was unrelated to the time spent viewing the picture. Instead of asking people to tell them about which ads interested them, the researchers were able to measure actual scanning behavior. Strengths and Weaknesses of Behavioral Measures Behavioral measures can be good indicators of a person’s attitudes because people sometimes cannot or will not report their attitudes accurately. Further, instead of assuming a relationship between attitudes and behavior, researchers can measure the actual behavior that they wish to study. Sometimes behavior can be measured unobtrusively in a field experiment mag81516_04_c04_073-096.indd 89 8/15/14 2:46 PM Measuring Experiment Outcomes Section 4.4 to maximize an experiment’s external validity. In this way, people are not sensitized to the fact that researchers are conducting a study and their behavior is more likely to be natural. With behavioral data, though, researchers have to infer the underlying attitude that is driving the behavior. Further, much of a person’s behavior can be the result of a complex interaction of several factors beyond any single attitude. A person’s shopping behavior can be influenced by the person they are with, if they are not shopping alone. Or, sometimes people’s motivation in a retail environment can vary. That is, some people go shopping as a pastime, while at other times they are seeking a specific item, such as a birthday gift. It can be difficult to an infer differences in attitude when the motives for behavior also vary, especially given that attitude functions can vary, too. Psychophysiological Measures: How the Body Responds Recall from Chapter 2 that instead of thinking of attitudes as things, you can also think of an attitude as mental states. Recall also that our definition of attitude includes the idea of an action tendency, or a readiness to respond, toward something, either favorably or unfavorably. If you have a mental state in which you are ready to respond favorably or unfavorably, or respond to something that is either favorable or unfavorable, then your body should be prepared to take action. Therefore, psychophysiological measures can also be used to assess attitudes, defined as a mental state. The prefix “psycho-” refers to the mind, and the root “physiology” refers to the body. So, scientists take physiological measures to infer psychological processes and states. Galvanic Skin Response Galvanic skin response (GSR) is like the lie detector test that you might be familiar with. When people have a favorable attitude toward something, their skin has slightly higher electric conductivity. You can hook a probe to someone’s ankle or hand and measure changes in GSR when they’re shown an advertisement or a product or person. Heart Rate You can also measure someone’s heart rate. When someone shows interest in something, their heart rate tends to drop. So, a decrease in someone’s heart rate indicates an interest in whatever they are looking at. This type of measure does not indicate a valence, that is, your attention can be drawn to something positive or something negative, and your heart rate would respond the same way toward both of them. It is merely an orienting response. Facial EMG You can also measure the electrical impulses of a person’s muscles. This is known as facial electromyography, or facial EMG. You can put probes around the corrugator muscles, which lie between the eyebrows on the forehead. People tend to contract those muscles, furrowing their brow, when they see something they do not like. You can also place probes on the zygomatic muscles, which lie above the corners of the mouth. We contract these smiling muscles when we see something we like. A person does not actually have to smile or furrow the brow. The electrical impulses appear even when a person tries not to smile. All scholars do is measure the increase in electrical activity, whether or not those muscles are fully activated. mag81516_04_c04_073-096.indd 90 8/15/14 2:46 PM Measuring Experiment Outcomes Section 4.4 Functional Magnetic Resonance Imaging Functional magnetic resonance imaging (fMRI) is used to see which parts of the brain become active after a person has been exposed to a particular stimulus. For example, the amygdala, which processes emotion and motivation, is activated after people see fearful faces or other stimuli that tend to create a fear or arouse fear in the person (Ito & Cacioppo, 2007). There is a modest amount of amygdala activation when we see positive stimuli. The prefrontal cortex of the brain, the part right behind the forehead, is involved in planning and control. This is the part of the brain that we use when we engage in hard thinking. The amygdala is activated when we see something negative that might instill fear or require caution. When we see something threatening, the amygdala is activated. However, we can control our fight-or-flight tendencies through our prefrontal cortex. Of course, marketers are particularly excited about using fMRI to explore how consumers react to a brand or a persuasive appeal (Penenberg, 2011). For example, some film studios use fMRI to gauge people’s reactions to movie trailers to create more appealing trailers, which, of course, are used to draw audiences for a film (Randall, 2013). One well-known study illustrated the usefulness of fMRI for understanding people’s attachment to brands (McClure, Li, Tomlin, Cypert, Montague, & Montague, 2004). Some individuals were served Pepsi® in two cups, one labeled Pepsi and one unlabeled, and were asked which one tasted better. Similarly, other individuals were given Coca-Cola® in two cups, one labeled Coca-Cola and the other unlabeled. The people who tasted Pepsi were evenly divided between the labeled and unlabeled cups of Pepsi. Among the people who tasted CocaCola, however, 85% of them chose the labeled cup of Coca-Cola over the unlabeled cup of the same Kul Bhatia/Science Source thing. In a follow-up study, the researchers used By using fMRIs, researchers can tell fMRI to see what parts of the brain were activated. how a person responds to ads. In this Before participants drank soda through a straw, fMRI scan, the visual cortex is active they were exposed briefly to an image of either as the person views an object (in this a Coca-Cola or Pepsi label. When people were case, a red hibiscus flower). exposed to the Coca-Cola, but not the Pepsi, label, they showed significant activity in the regions of the brain that are associated with memory, behavioral control, and emotion. These areas are not directly related with taste sensations. However, most of our attitude processes are rather complex, and researchers need to be careful not to attribute any particular attitude to a particular place that’s activated in the brain. For example, when people see ambivalent or conflicting information such as both positive and negative information about a target, different parts of the brain that tend to be relatively distinct are activated at the same time (Ito & Cacioppo, 2007). Of course, the activation of different parts of the brain depends on how strong the stimulus is, as well. There is also a time delay of a few seconds between when a person sees something and when the change in blood mag81516_04_c04_073-096.indd 91 8/15/14 2:46 PM Measuring Experiment Outcomes Section 4.4 flow is seen in the brain. The change in blood flow begins about 2 seconds after the person sees the stimulus, and the change in blood flow peaks about 4 to 6 seconds afterward and returns to its baseline measure about 10 to 15 seconds later (Ito & Cacioppo, 2007). So, it is harder to measure more complex evaluations using fMRI. Nevertheless, the method is useful for measuring cognitive processes involved in attitude formation, resistance, and change. Event-Related Brain Potentials Another type of measure is event-related brain potentials, known as ERP. Probes are placed on different points of the scalp, and changes in brain waves can indicate the degree to which someone likes or dislikes something. A person is presented with a series of positive items, and a measure of certain brain waves is taken. Then one negative item is placed in the series, and researchers measure the distance and change in the brain waves between the positive and negative items. ERPs are useful because they can also measure the degree of change or difference between positive and negative targets. Strengths and Weaknesses of Psychophysiological Measures Psychophysiological measures are believed to provide a “direct” link to attitudes that bypass some of the mental correction processes that people use to control what they say and do. This is particularly useful when researchers need to evaluate a phenomenon, such as racial stereotypes in advertisements, for which people try to control how they respond. Further, psychophysiological measures are one of the most effective ways of testing mind-body connections in persuasion. In some cases, they can be the only means of testing some of the mental processes that are believed to explain relationships between independent and dependent variables in some persuasion theories. However, psychophysiological measures are more cumbersome, more expensive, and more intrusive. You have to have specialized equipment to take the measures. Generally, you can only administer the experiment to one person at a time, unlike questionnaires, which can be administered to large groups of people at one time. And psychophysiological measures usually are insufficient, by themselves, to yield compelling information about attitudes, which is why they tend to be used in conjunction with verbal or behavioral measures. Media measurement giant Nielsen uses both psychophysiological measures and eye tracking to test ads, product packaging, the in-store experience, and so on (Nielsen, n.d.). Naturally, given the number of methods and research firms that offer neuroscience-based methods, advertisers, broadcasters, and other potential clients have begun to seek ways to measure their effectiveness (Advertising Research Foundation, n.d.). The Value of Multiple Measures How can you measure something you cannot see? As you have learned, different types of measures have their strengths and weaknesses. Any one of these measures likely is an imperfect assessment of a person’s attitude, but several types of measures, taken together, can produce a better assessment of a person’s attitude and the processes through which the independent variable affects the dependent variable (Fabrigar, Krosnick, & MacDougall, 2005). For example, psychophysiological measures by themselves are not necessarily good indicators of an attitude, but if you take psychophysiological measures and couple them with verbal measures such as questionnaires, you can get a better measure of someone’s attitude. As we mag81516_04_c04_073-096.indd 92 8/15/14 2:46 PM Measuring Experiment Outcomes Section 4.4 discussed earlier, sometimes people do not want to tell the truth. So, in addition to recording verbal reports, scientists take behavioral or psychophysiological measures because it is much harder for someone to avoid telling the truth with these types of measures. When measuring an attitude, scholars often try to get several indicators of that attitude because several joint indicators should be a better assessment of an attitude than any single indicator. Any single measure might not be a good indicator of what we think we are measuring (see Figure 4.2). Let’s say that Elaine has a boyfriend, Ed, and she believes that Ed loves her. How does Elaine know that Ed loves her? Maybe Elaine knows that Ed loves her because he smiles whenever he sees her. Maybe she believes that Ed loves her because he brings her flowers. Maybe she believes that Ed loves her because he washes the dishes. Maybe she believes he loves her because every now and then he prepares a meal for her. However, maybe Ed smiles when he sees her because he thinks that she dresses funny. Maybe Ed brings her flowers whenever he feels guilty about something he has done. Maybe he does the dishes because he has some sort of cleanliness compulsion, not because he loves her. Maybe he cooks meals for her because she really can’t cook, and he figures that if he wants to eat a good meal he might as well prepare it himself. Any one of these actions, by itself, might not be a good indicator of whether Ed loves Elaine. But, taken together, they can be pretty good indicators that he loves Elaine. If he buys her flowers, and smiles when he sees her, and prepares meals for her, and does the dishes, maybe he really does love her. Or, maybe he just feels sorry for her (we can never be certain). The point is that multiple indicators of a phenomenon are better than a single indicator. Figure 4.2: Multiple measures of an attitude Attitude A single measure can be an incomplete assessment of an attitude... mag81516_04_c04_073-096.indd 93 Attitude ...but multiple measures can provide a better assessment of the attitude. 8/15/14 2:46 PM Summary and Resources Summary and Resources Summary • • • • • • Most of the theories in the science of persuasion deal with causal relationships. Therefore, most of these theories are tested through experiments. There are three ways to show causation between two variables: create a time order, establish a relationship, and rule out alternate explanations. If you are asking causal questions, then you must use experiments to test your answers. Experiments are the ideal method for meeting all three of the conditions that are necessary for showing a causal relationship. An experiment gives the researcher control over the order in which the stimulus materials are shown and how the dependent variable measures or observations are gathered, so it provides evidence for time order. Through the judicious use of measures, the researcher can also demonstrate an association between the independent variables and the dependent variables. An experiment allows the researcher to control the influence of extraneous factors to have a tight and focused test on the relationship that the researcher wants to study. The design and control of an experiment also allows the researcher to take into account the potential role of confounds. This type of control helps to rule out alternate explanations. Attitudes are the typical effects of experimental manipulations in persuasion research. Ways to assess attitudes can be grouped into three types: verbal, behavioral, and psychophysiological. Each method has its own strengths and weaknesses, but by combining several types of measures, scientists can have a more accurate measurement of attitudes. Questions for Reflection and Application 1. According to John Stuart Mill, what are the three elements needed to show a causal relationship? 2. Do you think that using psychophysiological measures is an improvement over traditional and more cost-effective self-report measures of attitudes? Why or why not? 3. What are the ethical implications of gathering behavioral data in a field experiment if you do not inform people that you are conducting a study? 4. A political consultant for a politician wants to test television ads that focus either on the politician’s character or on the politician’s policy position. What potential confounds should the consultant consider? 5. The Center for Science in the Public Interest has expressed concern over the number of celebrities who endorse sugar-laden beverages. (See http://cspinet.org/new /pdf/power-of-celebrity-soda-endorsements.pdf.) Design an experiment to test the hypothesis that a celebrity athlete’s endorsement of sugary beverages will increase the likelihood that children would try the beverages. mag81516_04_c04_073-096.indd 94 8/15/14 2:46 PM Summary and Resources Key Terms behavioral measures The measurement of what people do, such as choices they make, speed of response, and eye movements, rather than what people self-report. causation A relationship between two variables in which one variable causes the other variable to behave in a certain way. control condition The group in an experiment that does not receive the treatment or change. event-related brain potentials (ERP) The measurement of changes in brain waves to indicate the degree to which someone likes or dislikes something. experiment A research method whereby a researcher manipulates one variable to see the consequences of that manipulation; the best way to test a causal relationship between two variables. external validity The degree to which the phenomena manipulated and measured in the experiment can be extended beyond the lab to the “real world.” eye tracking A type of behavioral measure that uses specialized equipment to follow a person’s focused gaze on the screen; can be used to see what elements on a webpage first attract a person’s attention and what type of content interests people most. facial electromyography (EMG) The measurement of the electrical impulses of a person’s muscles, such as those between the eyebrows on the forehead and those above the corners of the mouth; can be measured whether or not the muscles are fully activated. factor Another word for the manipulated independent variable, which has an effect on the dependent variable. mag81516_04_c04_073-096.indd 95 factorial design An experimental design in which two independent variables are manipulated in conjunction with each other. field experiment An experiment that takes place in a natural setting. functional magnetic resonance imaging (fMRI) A scan used to see which parts of the brain experience more blood flow after a person has been exposed to a particular stimulus. galvanic skin response (GSR) The tendency of a person’s skin to have a higher electric conductivity when they have been exposed to a stimulus; measured with a probe on the ankle or hand. heart rate Tends to drop when someone shows interest in something. Implicit Association Test (IAT) A specific test of attitudes that relies on relative differences in response latencies; assesses the relative strength of automatic associations between an attitude object and a valence. laboratory experiment An experiment that takes place in the controlled setting of a laboratory. manipulated variable Another word for the independent variable, so used because the researcher changes the variable to see what effect it might have on the dependent variable. psychophysiology The measurement of the body’s responses; physiological measures are used to infer psychological processes and states. quasi-experiment An experiment in which random assignment is absent, typical of field experiments. 8/15/14 2:46 PM Summary and Resources random assignment A condition in a true experiment in which the study’s participants were assigned to the treatment and control groups in a random way; allows the researcher to assume that the groups are equal in virtually every way. response latency A measure of speed of activation; how quickly attitudes are accessed in a given situation. treatment condition The group in an experiment that receives the treatment or change; the independent variable. mag81516_04_c04_073-096.indd 96 treatment variable Another word for the independent variable, so used because this is the group receiving a treatment or change, whereas the control group does not receive the treatment. verbal reports Self-report data based on what a person says; the most common form of dependent variable in persuasion research. web analytics Involves measuring a person’s interaction with online information, such as which links a person clicks, how many pages a person browses, and how much time is spent on a page. 8/15/14 2:46 PM
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