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Abnormal Psychology. William J. Ray
Читать онлайн.Название Abnormal Psychology
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isbn 9781506333373
Автор произведения William J. Ray
Издательство Ingram
How could we demonstrate to our friend that his yelling is not causally related to the absence of tigers? One strategy might be to point out that the absence of tigers might have come about for other reasons, including the fact that there are no tigers roaming in the greater Boston area. Our friend’s reasoning was incorrect because it overlooked many other plausible explanations for the obvious absence of tigers. Although our friend sought to infer a relationship between his yelling and the absence of tigers, his inference was weak.
Logic is particularly important in science as an aid to answering this question: What question should my experimental study answer to test my ideas about the world? That is, logic can help us to answer questions of inference. Inference is the process by which we look at the evidence available to us and then use our powers of reasoning to reach a conclusion. Like Sherlock Holmes engaged in solving a mystery, we attempt to solve a problem based on the available evidence. Did the butler do it? No, the butler could not have done it because there was blond hair on the knife and the butler had black hair. But perhaps the butler left the blond hair there to fool us. Like a detective, scientists try to determine other factors that may be responsible for the outcome of their experiments or to piece together available information and draw general conclusions about the world. Also like the detective, the scientist is constantly asking, “Given these clues, what inference can I make, and is the inference valid?” Logic is one method for answering these questions.
Inference: the process by which we look at the evidence available and then use logic to reach a conclusion
What type of evidence would you need to show that a vaccine did not lead to the development of autism?
© iStockphoto.com/Gajus
One example of using logic to help solve a question in psychopathology involved the relationship between giving a child the MMR (measles, mumps, and rubella) vaccine and the development of autism. In the late 1990s, based on one published study (which was later discredited by the journal in which it appeared), it was suggested in the media that the MMR vaccine led to the development of autism. The MMR vaccine is given to a child around 12 to 15 months of age. The first signs of autism appear around 15 to 18 months of age. Thus, it was argued that the vaccine led to the development of autism. What type of evidence would you need to show this was not the case? You might first ask if everyone who receives the vaccine develops autism. Since many who receive the vaccine do not develop autism, then if the relationship exists, it is not a simple one. More important from a logical standpoint, you might ask if there exists a child who did not receive the vaccine but did develop autism. This would help to rule out vaccination being the single cause of autism. As you will see in Chapter 5, a critical finding is that there are signs of autism in children before the age of vaccinations. Thus, logically, researchers were able to rule out vaccines as the single cause of autism.
Validity
Logical procedures are also important for helping us understand the accuracy or validity of our ideas and research. Valid means true and capable of being supported. In studying mental illness, one important way to show that our ideas can be supported is to replicate them with different individuals in different locations. If we hypothesized that a certain type of stress led to depression, for example, then we would need to show that this is the case not only in our research clinic, but also in other clinics.
Historically, we have discussed various types of validity in psychology, which arise from differing contexts. These contexts range from developing types of tests to running experiments. The overall question is this: Does a certain procedure, whether it is a test of mental illness or an experiment, do what it was intended to do? There are two general types of validity (Campbell & Stanley, 1963).
internal validity: the ability to make valid inferences between the independent variables (IVs) and dependent variables (DVs)
external validity: also known as generalizability, the ability to apply the results from an internally valid experiment to other situations and other research participants
generalizability: also known as external validity, the ability to apply the results from an internally valid experiment to other situations and other research participants
The first is internal validity. The word internal refers to the experiment itself. Internal validity asks the following question: Is there another reason that might explain the outcome of our experimental procedures? Students are particularly sensitive to questions of internal validity, for example, when it is time for final exams; they can make a number of alternative suggestions about what the exam actually measures and why it does not measure their knowledge of a particular subject. Like students, scientists look for reasons (threats to internal validity) that a particular piece of research may not measure what it claims to measure. In the case of our friend from Boston, the absence of tigers near his house could have reflected a long-standing absence of tigers in his part of the world rather than the effectiveness of his yelling.
The second type of validity is external validity. The word external refers to the world outside the setting in which the experiment was performed. External validity often is called generalizability. Remember the story of Semmelweis. His finding that the deaths of the mothers who had just given birth were the result of physicians touching them after handling diseased tissue was true not only for his hospital, but also for all other hospitals. Thus, in addressing the question of external validity of Semmelweis’s work, we would infer that his answers could be generalized to other hospitals with other women and not just to his own original setting. External validity, therefore, refers to the possibility of applying the results from an internally valid experiment to other situations and other research participants.
We logically design our research to rule out as many alternative interpretations of our findings as possible and to have any new facts be applicable to as wide a variety of other situations as possible. In many real-life situations in which external validity is high, however, it is impossible to rule out alternative interpretations of our findings. In a similar way, in laboratory settings in which internal validity is high, the setting is often artificial, and in many cases our findings cannot be generalized beyond the laboratory. Consequently, designing and conducting research is always a trade-off between internal and external validity. Which one we emphasize depends on the particular research questions being asked.
Before continuing, let’s clear up one misconception. It is the idea of designing “the one perfect study.” Although we strive to design good research, there are always alternative explanations and conditions not included in any single study. It is for this reason that Donald Campbell, who introduced scientists to the idea of internal and external validity, also emphasized the importance of replicating studies. If the same study is performed a number of times with similar results, then we can have more assurance that the results were valid. Even better, if the study is performed in a variety of settings around the world, we have even more confidence in our results. I will return to this topic of replication later in the chapter.
What Do I Expect to Happen?
One characteristic of human beings is that we seek to determine what will happen next. When we are talking with someone, we anticipate the next word they will say. The same is true in psychological experiments. Participants imagine what they are expected to do. If their expectation interferes with the influence of the IV, then the study could give inaccurate results.
In research terminology, this type of bias is referred to as demand characteristics.