The nation of Chile went to heroic lengths to ensure that Los 33 made it out of the mountain alive. Most search-and-rescue missions are run by mine owners, but this was an extraordinary situation that demanded extraordinary measures. Lucky for the miners, Chilean President Sebastián Piñera decided that the government would lead the operation (Weiner, 2011, January 9). Engineers from the Chilean navy built the rescue capsule that ultimately lifted all 33 men back into the light of day, and the Health Ministry created a plan to care for the miners, which included voluntary psychological counseling for at least 6 months after the rescue (Kofman & Hopper, 2010, October 13; Kraul, 2010, October 11).

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But the Chilean government was not in it alone. Governments, businesses, and individuals from all over the world flooded the Atacama Desert offering whatever help they could. Even a group from the National Aeronautics and Space Administration (NASA) showed up to lend a hand: two doctors, one engineer, and a psychologist named Albert Holland who had trained astronauts to cope with the stressful living conditions of outer space. The NASA crew was impressed with the efforts of the Chileans, but they also offered a few bits of advice, including a recommendation to increase the men’s daily intake of vitamin D (Prengaman, 2010, September 3; Spotts, 2010, September 7).

Why would the miners need more vitamin D? Most people get a substantial amount of vitamin D through sun exposure. When the sun’s UV rays strike the skin, its cells begin synthesizing vitamin D—an important process, as this “sunshine vitamin” is essential for maintaining healthy bones, a strong immune system, and perhaps even optimal cognitive performance (Lee, O’Keefe, Bell, Hensrud, & Holick, 2008; Medline Plus, 2014; Przybelski & Binkley, 2007; Wilkins, Sheline, Roe, Birge, & Morris, 2006). Deprived of sunlight for weeks on end, the miners were at risk of becoming vitamin D deficient.

Imagine you are a psychologist who has been following the Chilean miner saga. You’ve read the news reports about NASA recommending more vitamin D, which makes you wonder if giving vitamin D supplements will, in fact, improve the men’s cognitive abilities. Here’s the hypothesis you come up with: If one group of miners is given vitamin D supplements and the other group of miners a sugar pill, those receiving the vitamin D supplement will show improvements in cognitive functioning.

Eager to begin your study, you ask the Chilean government for permission to study the cognitive effects of vitamin D supplementation on Los 33. Sadly, your request is promptly denied. Not to worry. You have another option that may be even better: taking your study to a laboratory setting. Performing research in a controlled laboratory environment has huge benefits. You have greater control over who participates in the study, freedom to manipulate the variables, and the ability to draw comparisons between groups that differ only with respect to your target variables. In other words, you have the opportunity to use the experimental method.

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LO 9 Explain how the experimental method relates to cause and effect.

At last, we arrive at the type of research method we have been alluding to all along, a design that reveals cause and effect. Unlike the descriptive studies discussed earlier, the experimental method can tell us about cause and effect, because it aims to ensure that every variable except those being manipulated by the researcher is held constant, or controlled (Infographic 1.5). To identify a particular cause of an outcome, we assign research participants to two or more groups, and with the exception of some sort of manipulation or treatment done by the experimenter, these groups are equivalent. If following the manipulation or treatment the groups differ on a measure of interest, we can say with confidence that the experimental manipulation caused that change. This allows researchers to observe the variable of interest without interference from other variables.

If you are having trouble understanding what it means to control variables, consider this analogy: You are outside a football stadium, desperately trying to follow a friend lost in a swarm of people. Everyone is moving in different directions, making it exceedingly difficult to pinpoint your friend’s location and direction of movement. But what if everyone in the crowd except your friend froze for a moment in time? Would it be easier to observe him now that he is the only one moving? This is similar to what researchers try to do with variables—hold everything steady except the variables they are examining.

Returning to the sun-deprived miners, let’s examine how you might design a simple research study using the experimental method to investigate the cognitive effects of a vitamin D supplement. Your hypothesis is that participants housed in a laboratory setting without natural light who are given vitamin D supplements will perform better on a cognitive task than participants in the same laboratory setting who receive a sugar pill. Although we cannot study Los 33 per se, it’s possible for us to put together a group of men who are very similar to the miners in age, educational background, physical health, and other variables that might affect their cognitive performance, and then subject them to a prolonged period of sun deprivation. Next you would divide the men into two groups—one receives vitamin D supplements and the other gets a sugar pill—and compare their performance on various mental tasks after a designated amount of time has passed. If the group receiving the vitamin D performs better, then you can attribute the difference to vitamin D. Although this may sound fairly straightforward, there are still a few more things you need to know.

RANDOM ASSIGNMENT Assigning participants to groups is a crucial step of the experimental method. Fail to divide participants in the correct way and your whole study is compromised. For this reason, researchers use random assignment to ensure that participants have an equal chance of being assigned to any of the groups. Randomly choosing which treatment the participants receive reduces the possibility of some participant characteristics influencing the findings. You may have noticed some similarities between random assignment and the “random sample” introduced earlier in the chapter. But here’s the difference: Random sampling is used at the onset of a study to gather participants from a larger population. Random assignment comes into play later, when you are assigning participants to different groups. You can flip a coin, roll dice, or use a computer to generate numbers, but the goal of random assignment is always the same: to ensure that the groups are roughly equal on all characteristics. If the groups are lopsided with respect to some variable, the results may be affected. Getting back to your study on vitamin D and cognition, imagine that you assigned all the highly educated participants to one group and the less educated participants to the other. Might educational experience influence the results of a cognitive test? Perhaps. Random assignment helps reduce some of the interference resulting from these types of characteristics.

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EXPERIMENTAL AND CONTROL GROUPS Let’s assume you did use random assignment to divvy your participants into two groups. One will receive the treatment (a daily dose of vitamin D), and the other will receive no treatment at all (they will, however, be handed a sugar pill that looks identical to the vitamin D supplement). Those members of the group who get the treatment (the real vitamin D supplements) comprise the experimental group, and those participants who get the sugar pill are members of the control group, and they do not receive the treatment. (We explain the need for the fake treatment in a moment.)

INDEPENDENT AND DEPENDENT VARIABLES Let’s restate a point we already made earlier in the section, this time using our new vocabulary terms: The only difference between the experimental and control groups should be the variable the researchers are manipulating—in this case, vitamin D intake. The different treatments the two groups receive is called the independent variable (IV), because it is the one variable the researchers are deliberately changing (in this case, some participants get vitamin D, others a sugar pill). In the experimental method, an independent variable is that which the researcher is manipulating, and due to the complex nature of human behavior, often more than one independent variable may be used. The dependent variable (DV) is the characteristic or response the researchers are trying to observe or measure. In the hypothetical study, the dependent variable is the participants’ performance on cognitive tests. Just remember, the independent variable is what is manipulated and the dependent variable is what is being measured as a result of that manipulation. Stated slightly differently: The dependent variable, in this case, performance on the cognitive tests, “depends” on or is caused by the treatment (either vitamin D or the sugar pill).

EXTRANEOUS VARIABLES Another issue that must be considered by researchers as they plan their experiment is making sure that extraneous variables are not allowed to interfere with their measures. Extraneous variables are characteristics of the environment or participants that potentially interfere with the outcome of the research. While conducting your study of vitamin D supplements, you discover that three of the participants are reacting to the artificial light in the lab, making it very difficult for them to sleep. And this sleeplessness can definitely influence performance on cognitive tasks. Unfortunately, you failed to consider this very important variable in your research design, making it an extraneous variable. Researchers have to carefully contemplate the different kinds of variables that might influence the dependent variable.

There is a specific type of extraneous variable that can confound the results of an experiment. Confounding variables are a type of extraneous variable that changes in sync with the independent variable, making it very difficult to discern which variable—the independent variable or the confounding variable—is causing changes in the dependent variable. Imagine you house the participants in your study in a very nice lab setting, but because the lab can only hold half the participants at a time, you decide to wait and collect data from the control group later in the year. At that point, your lab assistant has gone on maternity leave, so you need to hire a new lab assistant, a young man who will administer the sugar pills to the control group. When the data are collected on cognitive performance, you can’t be sure whether differences between groups on test scores result from the vitamin D pills, or some variables related to the gender of the lab assistants or even the time of year that the data were collected. These other variables could be confounding variables.

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The good news is that there are numerous ways of eliminating the influence of an extraneous variable. This is called controlling a variable. As we mentioned earlier, random assignment to the treatment and control groups can help to lessen the impact of such variables. In this example, that means ensuring both groups have approximately the same number of participants who are having trouble sleeping in the lab. Or, if you wanted to control how sleep impacts the outcome of your study, you could just remove the poor sleepers from your sample and not include their information in your statistical analyses.

If you succeed in holding all variables constant except the independent variable, then you can make a statement about cause and effect. Let’s say your study does uncover cognitive differences between the experimental and control groups. It is relatively safe to attribute that disparity to the independent variable. In other words, you can presume that the vitamin D caused the superior performance of the experimental group.

DOUBLE-BLIND STUDY Earlier in the chapter, we mentioned that deception can sometimes be useful in scientific research. You are about to learn why. One way researchers use deception is by conducting a single-blind study in which participants do not know what treatment they are receiving. An even stronger experimental design is a double-blind study, an experiment in which neither the participants nor the researchers working directly with those participants know who is getting the real treatment and who is getting the pretend treatment. In our example, neither the person administering the pills nor the participants would know who was receiving the vitamin D supplement and who was receiving the sugar pill. Keeping participants in the dark is relatively easy; just make sure the treatment and sugar pill look the same from the outside (here, the vitamin D and sugar pill look identical). Blinding the researchers is a little trickier but can be accomplished with the help of clever assistants who make it appear that all participants are getting the same treatment.

THINKING IS BELIEVING There are some very compelling reasons for making a study double-blind. Prior research tells us that the expectations of participants can influence results. If someone hands you a sugar pill but tells you it is real medicine, you might end up feeling better simply because this is what you expect will happen when you believe you are being treated. Apparently, thinking is believing. When people are given a fake pill or other inactive “treatment,” known as a placebo (plǝ-'sē-'bō), they often get better even though the contents of the pill are inert. The placebo effect has been shown to ease pain, anxiety, depression, and the symptoms of Parkinson’s disease. There are even some reports that, on occasion, the use of placebos has been linked to a reduction in the size of tumors (Niemi, 2009). Researchers believe that the placebo effect arises through both conscious expectations and unconscious associations between treatment cues and healing. One’s expectation influences the placebo's actual effect.

EXPERIMENTER BIAS We’ve discussed the rationale for keeping participants in the dark, but why is it necessary to keep the researchers clueless as well? Researchers’ expectations can influence the outcome of a study, a phenomenon known as experimenter bias. A researcher may unwittingly color a study’s outcome through subtle verbal and/or nonverbal communication with the participants, conveying hopes or beliefs about the experiment’s results. A statement by the researcher like “I really have high hopes for this medicine” might influence participants’ reactions to the treatment. The researcher’s value system may also impact the results in barely noticeable but very important ways. Beliefs and attitudes can shape the way a researcher frames questions, tests hypotheses, or interprets findings (Rosenthal, 2002b).

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Congratulations! You have now learned the nuts and bolts of the experimental method, one of psychology’s greatest myth-debunking, knowledge-gathering tools. This method gives us more control over variables than any other type of study we have discussed; it also stands out in its ability to establish cause and effect. However, like any scientific approach, the experimental method is not without its flaws. Laboratory settings are inherently unnatural and therefore cannot always paint an accurate picture of behaviors that would occur in a natural setting. Remember, when people know they are being observed, their behavior changes. Other weaknesses of the experimental method include cost (it’s expensive to maintain a laboratory) and time (collecting data in a laboratory setting can be much slower than, say, sending out a survey). Table 1.6 gives an overview of some of the advantages and disadvantages of the research methods we have described.

Now it’s time to test our understanding of the experimental method with the help of a sprightly yellow square named SpongeBob.

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LO 10 Demonstrate an understanding of research ethics.

Throughout this chapter, we have used the Chilean mining disaster as a subject for many hypothetical research endeavors, including studies on depression, aggression, and cognition. What we haven’t yet addressed is the enormous ethical responsibility psychologists take on when they decide to conduct these types of studies. Psychologists do not examine dinosaur fossils or atomic particles. They study humans and other living creatures who experience pain, fear, and other complex feelings, and it is their professional duty to treat them with dignity and respect.

Like most other professionals, psychologists have established specific guidelines to help ensure ethical behavior in their field. Professional organizations such as the American Psychological Association (APA), the Association for Psychological Science (APS), and the British Psychological Society (BPS) provide written guidelines their members agree to follow. These guidelines ensure the ethical treatment of research participants (human and animal). They encourage psychologists to do no harm; safeguard the welfare of humans and animals in their research; know their responsibilities to society and community; maintain accuracy in research, teaching, and practice; and respect human dignity, to name a few examples (APA, 2010a).

CONFIDENTIALITY Confidentiality is a primary issue in psychology. Researchers must take steps to protect research data from misuse or theft. Psychologists who offer therapy services are obligated to keep client and therapy session information confidential; in fact, they are required to keep this information safeguarded in their offices. Confidentiality enables clients to speak freely about deeply personal issues. It ensures that research participants feel confident when they share sensitive information (sexual or controversial matters, for example), because they may rest assured researchers will protect it.

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DECEPTION Other important ethical topics are informed consent and debriefing, both of which we discussed earlier. Informed consent is the process by which research participants acknowledge their understanding of their role in the study and sign off on it. Debriefing refers to the process in which researchers disclose important information to their participants after wrapping up a study. This includes informing participants about any deception. Throughout this textbook, you will read about experiments in which the participants did not know ahead of time what was being studied. In addition, they were often purposely lied to as a part of the manipulation, or to conceal what was being studied until the debriefing phase. It is important to note that no one is ever forced to become a participant in a research study. Participation is completely voluntary, and participants can drop out at any time.

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Question 1

1. experimenter bias

2. confounding

3. random assignment

4. cause-and-effect relationship

Question 2

1. dependent

2. independent

3. extraneous

4. confounding

Question 3

Question 4

1. informed consent.

2. debriefing.

3. deception.

4. naturalistic observation.