PREVIEW - Summary and Study Notes Summary - Introduction to Behavioral Research Methods - Leary - 6th edition

Reading guide for Introduction to Behavioral Research Methods of Leary - Chapter 0 What is Leary's book Introduction to Behavioral Research Methods about?

The book Introduction to Behavioral Research Methods is a widely used book in studies within the field of human and behavioural sciences. The book was specially written for student use. According to the writer the book focuses on the four main approaches to behavioral research; namely descriptive research, correlational research, experimental research and quasi-experimental research. The book explains how to conduct these methods and how to analyze the results. The book also examines the ethical issues that may arise during research into human behavior.

Who is the author?

Mark R. Leary is professor of Psychology and Neuroscience at Duke University. Before that he has also taught various other American universities.

His research focuses on the topics of social motivation and emotions, within the field of social and personality psychology. He has published more than 200 scientific articles on these topics and in 2001 he also founded the scientific research magazine "Self and Identity".

What are the main differences between the 6th and 7th editions?

Various updates were made in the 7th edition, including:

• The subject of 'replicating research' is discussed in more detail.

• The difference between reflective and formative measurements is explained in more detail.

• Information has been added about doing research via the Internet, in view of the fact that the use of telephones with Internet connection has increased enormously in recent years.

• The disadvantages and shortcomings of the traditional 0-hypothesis significance test are discussed further. Alternative methods for statistical inference are also discussed, including with regard to confidence intervals and effect sizes.

• The order of topics dealt with within Chapters 11 and 12 has changed.

• Information has been added about the safety of research via computers and the confidentiality of data.

• Given the major fraud cases that have played a role since the last edition, information has also been added on this subject.

• A new topic has been added, namely "ethical issues when analyzing research data and reporting the results".

Research in the Behavioural Sciences - Chapter 1

What does the history of this research look like?

Many people think that psychologists are only concerned with treating people with mental problems. That is partly true, but psychologists also conduct research to find out more about people's behavior and mental processes. People have been explaining human behavior for centuries. Aristotle and Buddha for example systematically asked questions about why people behave in certain ways. In the past, however, explaining human behavior was not done scientifically. The statements that were made were mainly speculative. It was therefore impossible to test the validity of the statements. Consequently the accuracy and correctness of the statements could not be tested either. Declarations were often given on the basis of, for example, religious dogmas. Scientific psychology originated in the last 25 years of the 19th century. Scientists such as Wundt, James, Watson and Hall began to see that psychological issues can be answered using scientific methods that are also used in, for example, biology or physics.

What types of investigations can be distinguished?

Researchers distinguish between two types of research that are used for different purposes:

1. ' Basic research': this type of research is conducted to gain a better understanding of psychological processes. It is not important in this context whether this knowledge can be applied immediately. The primary goal is just to increase knowledge about a psychological process.

2. ' Applied research': this type of research is carried out to find solutions to specific problems instead of increasing our general knowledge about certain processes. For example, sometimes psychologists are hired to detect and resolve problems in the workplace. In this context research is a matter of understanding and eliminating problems.

3. In addition to these types of research, some scientists also speak of a third type of research, namely 'evaluation research' (also known as 'program evaluation' ). This type of research is aimed at understanding the effects of programs on behavior using scientific research methods.
   In this context, think of new school programs that are being applied. It is important to investigate to what extent these programs are effective.

What is the purpose of these kinds of research?

Sometimes it is difficult to determine whether it is 'basic' or 'applied' research based on the design of a scientific study. Moreover, both types of research do not necessarily exclude each other. 'Basic research' can also be applied in the long term and 'applied research' can ensure that we gain more knowledge about a phenomenon. It is also often the case that problem solving ('applied research') can only be done when there is sufficient knowledge about a phenomenon ('basic research'). The main difference between 'basic' and 'applied' research lies in the intention of the researcher. It is often difficult to read from the research itself. Whether it is a matter of 'applied' or 'basic' research, research always has three goals:

1. Description: Some studies are mainly designed to describe behavioral patterns, thoughts or emotions. Consider, for example, opinion polls held just before the elections. Developmental psychologists, as another example, are concerned with describing age-related changes in behavior.

2. Prediction: in this case, scientists try to predict behavior. For example, some psychologists try to predict the academic performance of people based on scores on standardized tests. It is important that these types of tests are critically analyzed and meet all kinds of statistical criteria. The prediction is analyzed on the basis of various other data to ensure that the prediction is correct. You can deduce from this that description is also used when predicting behavior ​​​​​​.

3. Explanation: Many scientists believe that explanation is the most important goal of scientific research. Scientists only have the feeling that they understand a phenomenon if they can explain it. For example, we can describe how many prisoners end up on the wrong path again after their release, but ultimately we want to be able to explain why some ex-prisoners go on the wrong path after their release, while that does not apply to other former prisoners.

What is meant by folk psychology?

In contrast to, for example, the natural sciences, the behavioral sciences often engage in research into phenomena that we all know.

The average person, for example, knows nothing about atoms, but knows a lot about memory, prejudice, sleep and emotion, because he or she has experience with these phenomena. This causes many people to think that behavioral sciences' findings are often logical and that they could have thought of the theories themselves. However, this is not always true. It is not the case that something is automatically true when almost everyone believes it. Scientists also have conducted many studies that show that much of our 'folk psychology' is wrong. An example is that many people think that very intelligent people are often a bit more weird than the average person. However, research shows that very intelligent people are often better adapted to their environment than other people. Another example is that many people think that the biggest differences between men and women are biological in nature. This appears not to be true; the role of socialization is also incredibly large. It is also important to consider the fact that folk psychology can cause scientists to be hesitant to start a research. Scientists often rely on common sense knowledge (folk psychology) when it comes to explaining behavior, thoughts and emotions. If folk psychology is incorrect with regard to a phenomenon, then this can cause scientists to explain psychological processes incorrectly.

Why is research in the behavioral sciences important?

It is important for us to learn more about conducting scientific research. This has four reasons:

1. Knowledge ensures that people can understand research that is important to their own profession. This is important because we must always be up-to-date with regard to new findings. For example, teachers need to understand why some teaching methods are effective, while others are not.

2. Knowledge about research methods also ensures that we can better analyze scientific findings in our daily lives. For example, if we want to buy a car, we can read several scientific studies that describe the pros and cons of a car. It is important that we can properly and critically analyze these findings.

3. A third advantage is that knowledge about research methods makes us critical thinkers. Scientists ask critical questions, try to come up with alternative possibilities and explanations, improve their methods and aim to find strong evidence.

4. A final advantage is that knowledge about research methods ensures that someone can become an expert; not only in the field of research methodology, but also in the field of specific subjects. In this way people can read and understand previous studies in their field of research, learn how to collect data and interpret results correctly.

What does the scientific method look like?

A method is scientific when it meets the following three criteria:

1. Empiricism: the use of observation to draw conclusions about the world. However, it is necessary that empiricism is systematic . Scientists structure their observations in a systematic way so that they can draw valid conclusions.

2. Verification ('public verification'): this means that the research results of one researcher must be able to be observed, replicated and verified (confirmed) by other researchers. This ensures that other researchers can see that what has been studied by one researcher actually exists and is observable. In addition, this process ensures that research can be improved: Other researchers can detect errors in the work of a researcher, so that these errors can be corrected. Verification often involves publishing articles in scientific journals. Replication does not only prevent errors, it also makes it possible for researchers to build upon the research of others and expand this research.

3. Solvable problems: science only deals with solvable problems. For example, the question of whether angels exist is not scientific, because there is no way to study angels in an empirical and systematic way. This does not mean that angels do not exist, but it does mean that no statements can be made about this using a scientific method.

What are the tasks of a scientist?

The scientists focus on two different tasks:

1. Discovering and recording new phenomena, patterns and relationships that they notice. Sometimes, however, it is not possible to conduct a research based on a hypothesis, because there is no theory yet about the phenomenon being studied. This can cause that there is too little information about the phenomenon to develop a theory. In that case it is better to design a survey to describe a phenomenon instead of testing hypotheses about the phenomenon.

2. The development and evaluation of phenomena they notice. Once they have identified the phenomena that are to be explained, they focus on developing theories to explain patterns and conduct research to test the theories.

What is the role of theories and models?

A theory consists of a set of propositions that tries to explain the relationships between a number of concepts. For example, with his contingency theory Fiedler tries to make a connection between concepts such as leadership effectiveness, task versus relationship-oriented leaders, leader-follower relationships, task structure and power. Scientific theories are only valid if they are supported by empirical findings. This means that a theory must be consistent with the facts discovered by scientists. A good theory meets the following criteria:

1. A good theory suggests a causal relationship. It therefore describes how one or more variables lead to a certain cognitive, emotional, behavioral or physical response.

2. A good theory is coherent in the sense of it being clear, simple, logical and consistent.

3. A good theory uses as few concepts and processes to describe a phenomenon as possible.

4. A good theory generates testable, falsifiable hypotheses to test the theory.

5. A good theory solves an existing theoretical question.

Researchers often use the concepts of 'model' and 'theory' interchangeably. However, a theory is different from a model. A model only describes how concepts are related to each other, while a theory also describes how and why concepts are related to each other. A model is therefore mainly descriptive in nature, while a theory is both descriptive and explanatory in nature.

What do research hypotheses look like?

Scientists mainly spend their time testing theories and models in order to discover if they really describe and explain behavior in a correct way. People can often find explanations for events after they have occurred. Such statements are also referred to as post hoc explanations - statements that are given after the fact has occurred. Scientists are very skeptical about this.

When a theory can explain phenomena afterwards, this hardly says anything about the accuracy of the theory. When a theory can predict in advance what will happen, this does say a lot about the correctness of the theory. For this reason, scientists come up with hypotheses before collecting data ('a priori') . Theories are often too broad to be tested immediately. That is why they are always tested in an indirect way. This is done using hypotheses.

• A hypothesis is a proposal that logically follows from a theory.

• Deduction is a process whereby a specific proposal (the hypothesis) is derived from a general proposal (the theory). In this process, the scientist is guided by the question of what would be discovered if the theory were actually correct. Hypotheses are therefore formulated in a ' if -A- then -B' form.

• Sometimes, a hypothesis does not arise through deduction, but through induction . In that case, a hypothesis is derived from a set of facts instead of a general theory. Hypotheses only based on previously observed results are also called empirical generalizations . A hypothesis must always be formulated in a way that makes it possible to be tested and to be de-energized ( 'falsified'). For example, Freud's psychoanalysis is criticized because it is not possible to derive hypotheses from this theory that can actually be tested (and therefore also falsified). For example, it is impossible to come up with hypotheses about the subconscious, because they cannot be tested.

• Some studies are stronger and designed better than others; giving stronger evidence for a hypothesis (and therefore a theory). In addition, the more different (measuring) methods are used to test a theory ('methodological pluralism' ) in different experiments, the more scientists have confidence in their findings.

• Sometimes there are two conflicting theories about a phenomenon. Scientists then design a study which can test both theories at the same time. Because the two theories are contradictory, it can never be the case that both theories are correct. If one theory is correct, the other (opposite) theory is automatically incorrect. This method is also called 'strategy of strong inference' . The results of this method lead to stronger conclusions about the relative value of the opposing theories. Methods that only test one theory lead to less strong conclusions.

Which types of definitions are important?

In order to test a hypothesis and possibly falsify it, it must be clearly formulated. For example, if a researcher is researching the effects of hunger on our attention, then he or she must be able to define these concepts well. Scientists use two types of definitions: (1) conceptual definitions and (2) operational definitions:

• A conceptual definition of a word is the definition that we could find in a dictionary. Hunger in this context is 'the desire for food'.

• An operational definition shows how a concept can be measured in a study. An operational definition converts an abstract, conceptual definition into concrete, situation-specific terms. For example, we could say in a survey that someone is hungry if he or she has not eaten for twelve hours. Multiple operational definitions can be devised for the same concept. Operational definitions are necessary because scientists can replicate each other's findings through these definitions. Using these definitions forces researchers to clearly describe their concepts and to circumvent any ambiguity.

How do we find evidence?

Because theories can only be tested indirectly through hypotheses, theories can never be proven. Scientists never say that a theory is proven , but only that a theory is supported . Hypotheses can be proven, but that a hypothesis is proven does not mean that the theory that goes with it is also true.

An example is that a murder has been committed and we are thinking of a theory about who the perpetrator is. The murder was committed at a beach party. Imagine that Pete is a suspect. If Pete is the killer, then he must have been present at the beach party (this is a hypothesis that takes an 'if -A- then -B' form). Then indeed it appears that he was present at the party. Does this mean that he is the killer because the hypothesis has been confirmed? Of course not. So we cannot prove a theory ('Pete is the killer') by confirming the hypotheses that follow ('Pete was at the beach party').

Proving that a hypothesis is not true is a logical valid operation. If it has been proven that Pete was not there at the beach party, Pete logically cannot be the killer. However, this is often different in daily life. The use of incorrect measurement techniques can, for example, lead to a hypothesis being rejected while the theory is correct, and vice versa. Disproving a hypothesis ('Pete was not at the beach party') does not necessarily mean that the theory ('Pete is the killer) is untrue. We think that Pete was not at the party, may be because we have made mistakes and his alibi, for example, is untrue. This is an example of an error in the measurement techniques. Because measurement techniques do not provide 100% certainty, a theory is never immediately rejected only because an investigation could not find any evidence for the theory.

The conclusion is therefore that we can never prove a theory, but we can prove that a theory is wrong. Science is developing because there is a lot of evidence for a theory or because there are dozens of studies that support it. The more studies that support a hypotheses, the greater the chance that the theory associated with those hypotheses is correct. You can also see science in terms of filters. First, a lot of different possible explanations for a phenomenon are thought of. Subsequently, the more plausible statements are retained by testing and further tested, while the non-plausible statements are rejected. The more filtered, the less potential explanations remain.

Scientific studies that have been read by other researchers and published in journals are in any case acceptable. Other scientists can then start replicating the findings that have been published.

Null findings are results that show that certain variables are not related to behavior. These results provide little information because they do not support a theory. The data may disconfirm the research for reasons that have nothing to do with the validity of a particular hypothesis. This does not make null findings informative. When studies containing null findings are not published, the file-drawer problem occurs: It often happens that researchers set up a design to test a theory, while this theory has yielded a null finding many times. All of these null findings have not been published, resulting in future researchers not knowing that "their" research has already been done before.

What is meant by the scientific filter?

You can also see science in terms of the so-called 'scientific filter'. Imagine a tube that gets narrower downwards. This tube consists of a number of layers, with a filter between each layer. The top layer consists of all unfiltered ideas, habits, thoughts, etc. that the researcher comes up with. Then, 4 filters follow:

1. In the first filter, the researcher examines which ideas can and cannot be implemented. The researcher abandons ideas that he or she has learned (in training or education) to be impossible. The researcher also thinks about his or her professional reputation. The ideas that come through filter 1 are not necessarily valid, but certainly not immediately incorrect.

2. The second filter consists of the researcher himself. At this stage, the researcher determines which ideas are worth investigating. If a research can lead to an interesting result and scientific publication, the researcher will probably want to continue with it. But if there is a good chance that the research will lead to null findings, the researcher will not further investigate the subject.

3. Filter 3 consists of peer review: other researchers check the research. They remove or improve research that has a poor methodology. Studies that are not useful for the scientific community are also removed at this stage. It is not the case that this filter removes all research that is not necessary; the filter mainly removes errors.

4. The last filter consists of the use, replication and addition by others. Only if a theory passes this filter it becomes a part of established scientific literature.

If a theory has passed all 4 filters, this does not mean that the theory is automatically true. Scientists rarely speak of their theory as 'the only truth'. Through the scientific filter and by constantly testing new hypotheses, we can only come closer to the truth. However, it remains uncertain whether our findings really contain the only truth.

What research techniques can be distinguished?

Scientists can use four types of research techniques to test hypotheses:

1. Descriptive research: this type of research describes the behaviors, thoughts and attitdes of a group of individuals. For example, developmental psychologists try to describe the behavior of children of different ages. Further studies are being conducted in clinical psychology to describe the prevalence, symptoms and severity of certain psychological problems.
   Descriptive research forms the basis for all other research methods.

2. Correlational research: In this type of research, the relationship between variables is studied. An example is an investigation towards the relationship between self-confidence and shyness. In such a case, a correlation between variables is calculated .However, with correlational studies, no statements can be made about cause-effect relationships. For example, we do not know if little self-confidence causes embarrassment or vice versa.

3. Experimental research: in this case a variable is manipulated (the independent variable) to see if this causes changes in behavior (the dependent variable). If this is indeed the case, then we can conclude that the independent variable is the cause of the dependent variable. The most important thing about an experiment is that a variable is manipulated.

4. Quasi-experimental research: this research technique is used when scientists cannot manipulate a variable. Consider in this context, for example, gender or age. The scientist then examines the effects of a variable or event that occurs naturally and cannot be manipulated. Quasi-experiments do not provide as much certainty as real experiments.

What role do animals play in these studies?

Most studies in psychology are conducted with humans, but it also happens that animals are used to find out more about psychological variables; often mice, rats and pigeons. The advantage of animal studies is that severely controlled studies can be conducted and most environmental influences can be eliminated. These two things are often not possible in studies in which humans participate. In addition, drugs are tested on animals so that people do not have to take medical risks. Through animal studies we now know much more about, for example, hunger, thirst and sexual behavior. We also learned a lot about vision, smell, taste and hearing. In addition, we know more about processes such as classical and operant conditioning through animal studies. Finally, we know a lot about the functioning of the brain through animal studies.

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