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Title of book: Research methods: building a knowledge Base

Malec, T. & Newman, M. (2013). Research methods: Building a knowledge base. San Diego, CA: Bridgepoint Education, Inc. ISBN-13: 9781621785743, ISBN-10: 1621785742.

Chapter 1

Psychology as a Science

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Chapter Contents

· Research Areas in Psychology

· Scientific Thinking and Paths to Knowledge

· Research Problem and Questions

· Hypotheses and Theories

· Searching the Literature

· Writing a Research Proposal

· Ethics in Research

In an article in Wired magazine, journalist Amy Wallace described her visit to the annual conference sponsored by Autism One, a nonprofitgroup organized around the belief that autism is caused by mandatory childhood vaccines:

I flashed more than once on Carl Sagan's idea of the power of an "unsatisfied medical need." Because a massive research efforthas yet to reveal the precise causes of autism, pseudoscience has stepped into the void. In the hallways of the Westin O'Harehotel, helpful salespeople strove to catch my eye ... pitching everything from vitamins and supplements to gluten-free cookies ...hyperbaric chambers, and neuro-feedback machines.

(Wallace, 2009, p. 134)

The "pseudoscience" to which Wallace refers is the claim that vaccines generally do more harm than good and specifically cause children todevelop autism. In fact, an extensive statistical review of epidemiological studies, including tens of thousands of vaccinated children, found noevidence of a link between vaccines and autism. But something about this phrasing doesn't sit right with many people; "no evidence" rings ofscientific mumbo jumbo, and a "statistical review" pales in comparison with tearful testimonials from parents that their child developed autisticsymptoms shortly after being vaccinated. The reality is this: Research tells us that vaccines bear no relation to autism, but people still believethat they do. Because of these beliefs, increasing numbers of parents are forgoing vaccinations, and many communities are seeing a loss of herdimmunity and a resurgence of rare diseases including measles and mumps.

So what does it mean to say that "research" has reached a conclusion? Why should we trust this conclusion over a parent's personalexperience? One of the biggest challenges in starting a course on research methods is learning how to think like a scientist—that is, to framequestions in testable ways and to make decisions by weighing the evidence. The more personal these questions become, and the bigger theirconsequences, the harder it is to put feelings aside. But, as we will see throughout this course, it is precisely in these cases that listening to theevidence becomes most important.

There are several reasons to understand the importance of scientific thinking, even if you never take another psychology course. First, at apractical level, critical thinking is an invaluable skill to have in a wide variety of careers and in all areas of life. Employers of all types appreciatethe ability to reason through the decision-making process. Second, understanding the scientific approach tends to make you a more skepticalconsumer of news reports. If you read in Newsweek that the planet is warming, or cooling, or staying the same temperature, you will be able todecipher and evaluate how the author reached this conclusion and possibly reach a different one on your own. Third, understanding sciencemakes you a more informed participant in debates about public policy. If we want to know whether the planet is truly getting warmer, thisconclusion should come from carefully weighing the scientific evidence rather than trusting the loudest pundit on a cable news network.

Where does psychology fit into this picture? Objectivity can be a particular challenge in studying our own behavior and mental processesbecause we are intimately familiar with the processes we are trying to understand. The psychologist William C. Corning captured this sentimentover 40 years ago: "In the study of brain functions we rely upon a biased, poorly understood, and frequently unpredictable organ in order tostudy the properties of another such organ; we have to use a brain to study a brain" (Corning, 1968, p. 6). (Or, in the words of comedian EmoPhilips, "I used to think that the brain was the most wonderful organ in my body. Then I realized who was telling me this.") The trick, then, islearning to take a step back and apply scientific thinking to issues you encounter and experience every day.

This textbook provides an introduction to the research methods used in the study of psychology. It will introduce you to the full spectrum ofresearch designs, from observing behavior to manipulating conditions in a laboratory. We will cover the key issues and important steps for eachtype of design, both qualitative and those that observe, predict, and explain behavior, as well as the analysis strategies most appropriate foreach type. In this chapter, we begin with an overview of the different areas of psychological science. We then introduce the research process bydiscussing the key features of the scientific approach and then cover the process of forming testable research questions, developing hypothesesand theories, and searching the literature. In the final two sections, we cover writing a research proposal and discuss the importance ofadhering to ethical principles at all stages of the research.

Research: Making an Impact

The Vaccines and Autism Controversy

In a 1998 paper published in the well-respected medical journal The Lancet, British physician AndrewWakefield and his colleagues studied the link between autism symptoms and the measles, mumps, andrubella (MMR) vaccine in a sample of twelve children (Wakefield et al., 1998). Based on a review ofthese cases, the authors reported that all twelve experienced adverse effects of the vaccine, includingboth intestinal and behavioral problems. The finding that grabbed the headlines was the authors' reportthat nine of the twelve children showed an onset of autism symptoms shortly after they received theMMR vaccine.

Immediately after the publication of this paper, the scientific community criticized the study for its smallsample and its lack of a comparison group (i.e., children in the general population). Unfortunately, itturned out these issues were only the tip of the iceberg (Godlee, Smith, & Marcovitch, 2011). The Britishjournalist Brian Deer conducted an in-depth investigation of Wakefield's study and discovered somestartling information (Deer, 2004). First, the study had been funded by a law firm that was in the processof suing the manufacturers of the MMR vaccine, resulting in a real threat to the researchers' objectivity.Second, there was clear evidence of scientific misconduct; the data had been falsified and altered to fitWakefield's hypothesis—many of the children had shown autism symptoms before receiving the vaccine.In his report, Deer stated that every one of the twelve cases showed evidence of alteration andmisrepresentation.

Ultimately, the Lancet withdrew the article in 2010, effectively removing it from the scientific record anddeclaring the findings no longer trustworthy. But in many respects, the damage was already done.Vaccination rates in Britain dropped to 80% following publication of Wakefield's article, and these ratesremain below the recommended 95% level recommended by the World Health Organization (Godlee etal., 2011). That is, even though the article was a fraud, it made parents afraid to vaccinate their children.Vaccinations work optimally when most members of a community get the vaccines because thisminimizes the opportunity for an outbreak. When even a small portion refuses to vaccinate theirchildren, the entire community is at risk of infection (National Institute of Allergy and InfectiousDiseases, n.d.). Thus, it should be no surprise that many communities are seeing a resurgence ofmeasles, mumps, and rubella: In 2008, England and Wales declared measles to be a prevalent problemfor the first time in 14 years (Godlee et al., 2011).

This scenario highlights the importance of conducting science honestly. While disease outbreaks are themost obvious impact of Wakefield's fraud, they are not the only one. In a 2011 editorial in the BritishMedical Journal condemning Wakefield's actions, British doctor Fiona Godlee and colleagues capturedthis rather eloquently:

But perhaps as important as the scare's effect on infectious disease isthe energy, emotion, and money that have been diverted away fromefforts to understand the real causes of autism and how to helpchildren and families who live with it. (p. 7452)

1.1 Research Areas in Psychology

Psychology is a diverse discipline, encompassing a wide range of approaches to asking questions about why people do the things that they do.The common thread among all of these approaches is the scientific study of human behavior. So, while psychology might not be the only field tospeculate on the causes of human behavior—philosophers have been doing this for millennia—psychology is distinguished by its reliance on thescientific method to draw conclusions. We will examine the meaning and implications of this scientific perspective later in the chapter. In thissection, we discuss the major content areas within the field of psychology, along with samples of the types of research questions asked by eachone. For further reading about these areas, the American Psychological Association (APA) has an excellent collection of web resources: http://www.apa.org/topics/index.aspx .

Biopsychology

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A study investigating changes in the brain anatomy of newmothers explores the connection between a biological system andthe emotions, thoughts, and behaviors involved in caring for anewborn child.

Biopsychology, as the name implies, combines research questions and techniquesfrom both biology and psychology. It is typically defined as the study ofconnections between biological systems (including the brain, hormones, andneurotransmitters) and our thoughts, feelings, and behaviors. As a result, theresearch conducted by biopsychologists often overlaps research in other areas—but with a focus on biological processes. Biopsychologists are often interested inthe way interactions between biological systems and thoughts, feelings, andbehaviors impact the ability to treat disease, as seen in the following questions:What brain systems are involved in the formation of memories? Can Alzheimer'sbe cured or prevented through early intervention? How does long-term exposureto toxins such as lead impact our thoughts, feelings, and behaviors? How easilycan the brain recover after a stroke?

In one example of this approach, Kim and colleagues (2010) investigated changesin brain anatomy among new mothers for the first 3 months following delivery.These authors were intrigued by the numerous changes new mothers undergo inattention, memory, and motivation; they speculated that these changes might beassociated with changes in brain structure. As expected, new mothers showedincreases in gray matter (i.e., increased complexity) in several brain areasassociated with maternal motivation and behavior. And, the more these brainareas developed, the more positively these women felt toward their newborn children. Thus, this study sheds light on the potential biologicalprocesses involved in the mother–infant bond.

Cognitive Psychology

Whereas biopsychology focuses on studying the brain, cognitive psychology studies the mind. It is typically defined as the study of internalmental processes, including the ways that people think, learn, remember, speak, perceive, and so on. Cognitive psychologists are interestedprimarily in the ways that people navigate and make sense of the world, including questions such as the following: How do our minds translateinput from the five senses into a meaningful picture of the world? How do we form memories of emotional versus mundane experiences? Whatdraws our attention in a complex environment? What is the best way to teach children to read?

In one example of this approach, Foulsham, Cheng, Tracy, Henrich, & Kingstone (2010) were interested in what kinds of things people payattention to in a complex social scene. The world around us is chock-full of information, but we can pay attention only to a relatively thin sliceof it. Foulsham and colleagues were particularly interested in where our attention is directed when we observe groups of people. Theyanswered this question by asking people to watch videos of a group discussion and using tools to track eye movements. It turned out thatpeople in this study spent most of their time looking at the most dominant member of the group, suggesting that we are wired to pay attentionto those in positions of power. Thus, this study sheds light on one of the ways that we make sense out of the world.

Developmental Psychology

Developmental psychology is defined as the systematic study of physical, social, and cognitive changes over the human life span. Although thisfield initially focused on childhood development, many researchers now study changes and key stages over the entire life span. Developmentalpsychologists study a wide range of phenomena related to physical, social, and cognitive change, including, How do children bond with theirprimary caregiver(s)? What are our primary needs and goals at each stage of life? Why do some cognitive skills decline in old age? At what agesdo infants develop basic motor skills?

In one example of this approach, Hill and Tyson (2009) explored the connection between children's school achievement and their parents'involvement with the school. In other words, Do children perform better when their parents are actively involved in school activities? Theauthors addressed this question by combining results from several studies into one data set. Across 50 studies, the answer to this question wasyes—children do better in school if their parents are involved. Thus, this study sheds light on a key predictor of academic achievement duringan important developmental period.

Social Psychology

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Social psychologist Norman Triplett'sstudy of cyclists led to conclusions abouthow people influence one another.

Social psychology attempts to study behavior in a broader social context. It is typically defined as thestudy of the ways our thoughts, feelings, and behaviors are shaped by other people. As you mightimagine, this broad perspective allows social psychologists to tackle a wide range of research questions,including the following: What kinds of things do we look for in selecting romantic partners? Why dopeople stay in bad relationships? How do other people shape our sense of who we are? When and whydo people help in emergencies?

Norman Triplett conducted the first published social psychology study at the end of the 19th century(Triplett, 1898). Triplett had noticed that professional cyclists tended to ride faster when racing againstother cyclists than when competing in solo time trials. He tested this observation in a controlledlaboratory setting, asking people to do a number of tasks either alone or next to another person. Hisresults (and countless other studies since) revealed that people worked faster in groups, suggesting thatother people can have definite and concrete influences on our behavior.

Clinical Psychology

Finally, the area of clinical psychology is an applied field focused on understanding the best ways totreat psychological disorders. It is typically defined as the study of best practices for understanding,treating, and preventing distress and dysfunction. Clinical psychologists engage in both the assessmentand the treatment of psychological disorders, as seen in the following research questions: What is themost effective treatment for depression? How can we help people overcome posttraumatic stressdisorder following a traumatic event? Should anxiety disorders be treated with drugs, therapy, or a combination? What is the most reliable wayto diagnose schizophrenia?

One example of this approach is found in a study by Kleim and Ehlers (2008), which attempted to understand the risk factors for posttraumaticstress disorder, a prolonged reaction to a severe traumatic experience. Kleim and Ehlers found that assault victims who tend to form lessspecific memories about life in general might be more likely to develop a disorder in response to trauma than victims who tend to form detailedmemories. People who tend to form vague memories may have fewer resources to draw on in trying to reconnect with their daily life after atraumatic event. Thus, this study sheds light on a possible pathway contributing to the development of a psychological disorder.

1.2 Scientific Thinking and Paths to Knowledge

One of the easiest ways to understand the scientific approach is to contrast it with other ways of understanding the world. While science offersus the most objective and rigorous approach to decision making, it is by no means the only approach. Some of the following paths toknowledge have been popular and acceptable during different historical periods. Other approaches are currently in use by different academicdisciplines. To showcase the distinctions among them, the following examples illustrate how each perspective might approach the link betweenvaccines and autism.

Authority

In a number of contexts, people understand the world based on what authority figures tell them. Parents dictate curfews to children; citiesassign speed limits within their borders; and churches interpret the meaning of holy texts. In each case, the rules and knowledge are acceptedbecause there is trust in the source of the knowledge. In the debate over vaccines and autism, this perspective would be evident in those whotrust their doctor's advice to vaccinate their children. It would also be evident in those who trust celebrity spokesperson Jenny McCarthy'stestimony that vaccines gave her son autism.

Phenomenology

Many academic disciplines take a phenomenological approach to studying the world around us. This approach focuses on each individual'sintuition and subjective experience and treats truth as a subjective concept. In other words, if you believe that your alcoholism stems from abad relationship with your father, there is some "truth" to this belief (regardless of the objective truth). In the debate over vaccines and autism,this perspective would be evident in those who are swayed by a parent's testimony, despite all evidence to the contrary. If Jenny McCarthybelieves vaccines gave her child autism, then there must be some "truth" to her belief.

Rationalism

For several centuries, scientific inquiry was guided by a rationalist approach, and this approach is still dominant in many of the humanitiesdisciplines. Rationalism involves making decisions based on logical arguments; if something "makes sense," it must be the right answer. In thedebate over vaccines and autism, this perspective would be evident in the narrowly constructed argument that because autism symptomsappear shortly after vaccination, vaccines must be the cause. (This reasoning ignores the rules about the kinds of evidence needed to makestatements about causation, which we will cover in later chapters.)

Empiricism

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Rather than relying on reason and logic, empiricism focuses onwhat one can learn through observations and sensory experiences.

The scientific approach, which is our focus in this book, makes decisions based onevidence. This approach, also called empiricism, focuses on the role ofobservation and sensory experience over the role of reason and logic alone. It isall well and good to come up with a creative idea about how the world works, butthis idea does not carry scientific weight until it has been supported throughcarefully collected observations of the world around us. These observations formthe basis of science, which set it apart from the other paths to knowledge. In thedebate over vaccines and autism, scientific evidence leads to the unambiguousconclusion: There is no link between vaccines and autism. But if the oppositepicture were true, scientists would gladly change their minds. One of the keyadvantages of science is that it is not bound to a particular ideology (e.g., apolitical point of view or prejudice) but is dedicated to the belief in the superiorityof observable evidence. Although the experimenter's values are certain to enterthe picture, they can be a powerful motivating force to uncover the truth ratherthan a source of bias.

In summary, scientific inquiry offers us one of many ways to understand theworld. In theory, these perspectives are not incompatible, although in practice, differing perspectives can lead to drastically different conclusions.(The writer Stephen Jay Gould famously made this argument about science and religion, arguing that they are essentially suited to answeringdifferent types of questions. You can read an essay by Gould by going to the following website: http://www.stephenjaygould.org/ and searchingfor "Nonoverlapping Magisteria." And, on a particularly practical note, the scientific approach is the one that we will adopt throughout thisclass. So when you are asked to evaluate research results on your exams, your interpretation will need to be based on weighing the evidence; itis not acceptable to claim that a finding "just makes sense."

The Research Process

So what does it mean to draw conclusions based on science? Scientists across all disciplines use the same process of forming and testing theirideas. The overall goal of this research process—also known as the scientific method—is to draw conclusions based on empirical observationsand experiments (e.g., random assignment and manipulation) designed to test causal theories. In this section, we cover the four steps of theresearch process—hypothesize, operationalize, measure, and explain, abbreviated with the acronym HOME.

Step 1—Hypothesize

The first step in the research process is to develop a testable prediction, or hypothesis. A hypothesis is a specific and falsifiable statement aboutthe relationship between two or more variables (more on that "falsifiable" bit in a minute ...). For example, if we study the link betweensmoking and cancer, our hypothesis might be that smoking causes lung cancer. Or, if we are studying a new drug for treating depression, wemight hypothesize that drug X will lead to a reduction in depression symptoms. We will cover hypotheses in more detail in the next section, butfor now it is important to understand that the way we frame our hypothesis guides every other step of the research process. Even the mostpromising theories will not be testable if you do not clearly define the variables, or if many contradictory outcomes are possible (e.g.,depression can lead to weight gain or weight loss).

Step 2—Operationalize

Once we have developed a hypothesis, the next step is to decide how to test it. The process of operationalization involves choosing measurablevariables to represent the components of our hypothesis. In the preceding depression drug example, we would need to decide how to measureboth cause and effect; in this case, we define the cause as the drug and the effect as reduced symptoms of depression. That is, what doses ofthe drug should we investigate? How many different doses should we compare? Also, how will we measure depression symptoms? Will it workto have people complete a questionnaire? Or do we want to have a clinician interview participants before and after they take the drug? Anadditional complication for psychology studies is that many of our research questions deal with abstract concepts. There is an art to turningthese concepts into measurable variables. For example, the concept of "happiness" could be operationalized as a person's score on a happinessscale, or as the number of times a person smiles in a 5-minute period, or perhaps even as a person's subjective experience of happiness duringan interview. We will cover this process in more detail in Chapter 2 (Section 2.2), where we discuss guidelines for making these importantdecisions about the study.

Step 3—Measure

Now that we have developed both our research question and our operational definitions, it is time to collect some data. We will cover thisprocess in great detail; Chapters 3 through 5 are dedicated to the three primary approaches to data collection: descriptive designs (includingqualitative approaches, although quantitative studies can be descriptive as well), survey designs, and experimental designs. The goal of the datacollection stage is to gather empirical observations that will help address our hypothesis. As we discuss in Chapter 2, these observations canrange from questionnaire responses to measures of brain activity, and they can be collected in ways ranging from online questionnaires tocarefully controlled experiments.

Step 4—Explain

After the data has been collected, the final step is to analyze and interpret the results. The goal of this step is to return full circle to ourresearch question and determine whether the results support our hypothesis. Let's go back to our hypothesis that drug X should reducedepression symptoms. If we find at the end of the study that people who took drug X showed a 70% decrease in symptoms, this would beconsistent with the hypothesis. But the explanation stage also involves thinking about alternative explanations and planning for future studies.What if depression symptoms dropped simply due to the passage of time? How could we address this concern in a future study? As it turnsout, there is a fairly easy way to fix this problem, which we'll cover in Chapter 5.

In summary, the research process involves four stages: forming a hypothesis, deciding how to test it, collecting data, and interpreting the results.This process is used regardless of whether our research questions involve depression drugs, reading speed, or the speed of light in a vacuum.

Examples of the Research Process

To make these steps a bit more concrete, let's walk through two examples of how they could be applied to specific research topics.

Example 1—Depression and Heart Disease

Depression affects approximately 20 million Americans, and 16% of the population will experience it at some time in their lives (NationalInstitute of Mental Health [NIMH], 2007). Depression is associated with a range of emotional and physical symptoms, including feelings ofhopelessness and guilt, loss of appetite, sleep disturbance, and suicidal thoughts. This list has expanded even further to include an increasedrisk of heart disease. Individuals who are otherwise healthy but suffering from depression are more likely to develop and to die fromcardiovascular disease than those without depression. According to one study, patients who experience depression following a heart attackexperience a fourfold increase in 5-year mortality rates (research reviewed in Glassman et al., 2011).

One intriguing idea that comes from these findings is that it might make sense to treat heart attack patients with antidepressant drugs. The goalof the HOME method is to take this idea, turn it into a testable question, and conduct a study that will test it.

Step 1 is to form a testable hypothesis from this research question. In this case, we might predict that people who have had heart attacks andtake prescribed antidepressants are more likely to survive in the years following the heart attack than those who do not take antidepressants.What we've done here is to take a general idea about the benefits of a drug and state it in a way that can be directly tested in a research study.

Step 2 is to decide how we want to operationalize the concepts in our study. In this case, we would first decide who qualified as a heart attackpatient: Would we include only those hospitalized with severe heart attacks or include anyone with abnormal cardiac symptoms? As we willdiscuss in later chapters, this decision will have implications for how we interpret the results. We would also need to decide on the doses ofantidepressant drugs to use and the time period to measure survival rates. How long would we follow patients?

Step 3 is to measure these key concepts based on the decisions we made in step 2. This step involves collecting data from participants and thenconducting statistical analyses to test our hypothesis. We will cover the specifics of research designs beginning in Chapter 2 (Section 2.1), butessentially we would want to give antidepressants to half of our sample and compare their survival rates with the half not given these drugs.

Step 4 is to explain the results and tie the statistical analyses back into our hypothesis. In this case, we would want to know whetherantidepressant drugs did indeed benefit heart attack patients and increase their odds of survival for 5 years. If so, our hypothesis is supported.If not, we would go back to the drawing board and try to determine whether something went wrong with the study or antidepressant drugsreally don't have any benefit for this population. As we'll discuss, answering these kinds of questions usually involves conducting additionalstudies. Either way, the goal of this final step is to return full circle to our research question and discuss the implications of antidepressant drugtreatment for heart attack patients.

Example 2—Language and Deception

In 1994, Susan Smith appeared on television claiming that her two young children had been kidnapped at gunpoint. Eventually, authoritiesdiscovered she had drowned her children in a lake and fabricated the kidnapping story to cover her actions. Before Smith was a suspect in thechildren's deaths, she told reporters, "My children wanted me. They needed me. And now I can't help them" (Lee and Vobejda, 1994). Normally,relatives speak of a missing person in the present tense. The fact that Smith used the past tense in this context suggested to trained FBI agentsthat she already viewed them as dead (Adams, 1996).

One intriguing idea that comes from this story is that people may communicate in different ways when they are lying than when they are tellingthe truth. The goal of the HOME method is to take this idea, turn it into a testable question, and conduct a study that will test it.

Step 1 is to form a testable hypothesis from this research question. This example is somewhat more challenging because "communicatingdifferently" can be defined in many ways. Thus, we need a hypothesis that will narrow the focus of our study. One hypothesis, based onresearch literature, might be that liars show more negative emotion (e.g., anger, fear) in the way that they communicate than truth-tellers do(e.g., Newman, Pennebaker, Berry, & Richards, 2003). What we've done here is to take a general idea and state it in a way that can be directlytested in a research study.

Step 2 is to decide how we want to operationalize the concepts in our study. In this case, we would need to decide what counts as "showingnegative emotion." We might take the approach used in a previous study (Newman et al., 2003) and scan the words people use, looking forthose reflecting emotions such as anger, anxiety, and fear. The logic here is that the words people use reflect something about their underlyingthought processes and that people who are trying to lie will be more anxious and fearful as a result of the lie.

Step 3 is to measure these key concepts based on the decisions we made in step 2. This step involves collecting data from participants and thenconducting statistical analyses to test our hypothesis. In this example, the challenge comes in determining whether and when people are lying.In Susan Smith's case, the truth was ultimately discovered, so we can say with some certainty that her language was deceptive. One way to dothis in a research study is to tell people to lie, tell others to be truthful, and compare differences in the way they use language.

Step 4 is to explain the results and tie the statistical analyses back into our hypothesis. In this case, we want to know whether people who wereinstructed to lie did indeed use more words suggestive of negative emotion. If so, this supports our hypothesis. If not, we would go back to thedrawing board and try to determine whether something went wrong with the study or people really don't use more negative emotion whenthey lie. Either way, the goal of this final step is to return full circle to our research question and discuss the implications for understandingindicators of deception.

Goals of Science

In addition to sharing an overall approach, all forms of scientific inquiry tend to adopt one of four overall goals. This section provides anoverview of these goals, with a focus on their application to psychological research. We will encounter the first three goals throughout thecourse and use them to organize our discussion of different research methods.

Description

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Before a phenomenon can be explained, it must first be described.For example, a survey might be used to collect information used todescribe the phenomenon of binge drinking.

One of the most basic research goals is to describe a phenomenon, includingdescriptions of behavior, attitudes, and emotions. Basic research is the foundationon which all subsequent research will be laid and therefore should be built solidly.You are probably very familiar with this type of research because it tends to cropup in everything from the nightly news to your favorite magazine. For example, ifCNN reports that 60% of Americans approve of the president, they are describinga trend in public opinion. Descriptive research should always be the starting pointwhen studying a new phenomenon. That is, before we start trying to explain whycollege students binge drink, we need to know how common the phenomenonreally is. So we might start with a simple survey that asked college students abouttheir drinking behavior, and we might find that 29% of them show signs ofdangerous binge drinking. Now that we have described the phenomenon, we arein a better position to conduct more sophisticated research. (See Chapter 3 formore detail on descriptive research.)

Prediction

A second goal of research is to attempt to predict a phenomenon. This goal takesus from describing the occurrence of binge drinking among college students toattempting to understand when and why they do it. Do students give in to peerpressure? Is drinking a way to deal with the stress of school? These questions could be addressed through a more detailed survey that askedpeople to elaborate on the reasons that they drink. The goal of this approach is to understand the factors that make something more likely tooccur. (See Chapter 4 for more detail on the process of designing surveys and conducting predictive research.)

Explanation

A third, and much more powerful, goal of research is to attempt to explain a phenomenon. This goal takes us from predicting relationships totesting possible causal links. Whereas predictive research attempts to find associations between two phenomena (e.g., college student drinkingis more likely when students are under stress), explanatory research attempts to make causal statements about the phenomenon of interest(e.g., stress causes college students to drink more). This distinction may seem subtle at this point, but it is an important one and is closelyrelated to the way that we design our studies. (See Chapter 5 for more detail on explanatory research.)

Change

The fourth and final goal of research is generally limited to psychology and other social science fields: When we are dealing with questionsabout behaviors, attitudes, and emotions, we can conduct research to try to change the phenomenon of interest. Researchers who attempt tochange behaviors, attitudes, or emotions are essentially applying research findings with the goal of solving real-world problems. In the 1970s,Elliot Aronson, a social psychologist at the University of Texas at Austin, was interested in ways to reduce prejudice in the classroom. Researchconducted at the time was discovering that prejudice is often triggered by feelings of competition; in the classroom, students competed for theteacher's attention. Aronson and his colleagues decided to change the classroom structure in a way that required students to cooperate in orderto finish an assignment. Essentially, students worked in small groups, and each person mastered a piece of the material. (You can read thedetails on this website: http://www.jigsaw.org/ ). Aronson found that using this technique, known as the "jigsaw classroom," both enhancedlearning and decreased prejudice among the students (e.g., Aronson, 1978).

Aronson's work also illustrates the distinction between two categories of research. The first three goals we have discussed fall mainly under thecategory of basic research, in which the primary goal is to acquire knowledge, with less focus on how to apply the knowledge. Scientistsconducting basic research might spend their time trying to describe and understand the causes of binge drinking but stop short of designinginterventions to stop binge drinking. This fourth goal of research is more often seen in applied research, in which the primary goal is to solve aproblem, with less focus on why the solution works. Scientists conducting applied research might spend their time trying to stop binge drinkingbut not get caught up in the details of why these interventions are effective. But Aronson's research is a great example of how these twocategories should work together. The basic research on sources of prejudice informed his applied research on ways to reduce prejudice, which inturn informed further basic research on why this technique is so effective.

One final note on changing behavior: Any time you set out with the goal of changing what people do, your values enter the picture. Inherent inAronson's research was the assumption that prejudice was a bad thing that needed to be changed. Although few people would disagree withhim, the risk is that he might have trouble remaining objective throughout the research project. As we suggested earlier, the more emotionallyinvolved you are in the research question, the more you have to be aware of the potential for bias, and the more you have to force yourself topay attention to the data.

Quantitative Versus Qualitative Research

Imagine for a moment that you are a city planner interested in studying traffic patterns at different times of the day. You might approach thisresearch question in one of two ways. You could fly over the city in a helicopter, take snapshots of a random set of busy intersections, andconduct statistical analyses on cars moving in different directions at different times. This would give you a broad understanding of trafficpatterns in the city. Alternatively, you could spend your resources studying the busiest intersection in the middle of downtown, trying tounderstand everything from driver behaviors to the effects of weather conditions. This would give you a very deep understanding of traffic inthe middle of your city.

These two approaches illustrate the differences between quantitative research and qualitative research, respectively. Quantitative research is asystematic and empirical approach that attempts to generalize results to other contexts. By taking "samples" of different intersections and byconducting inferential statistics, our hypothetical city planner could learn a little bit about traffic in general. Qualitative research, in contrast, is amore descriptive approach that attempts to gain a deep understanding of particular cases and contexts. By studying the busiest intersection indetail, our hypothetical city planner could learn a great deal about the traffic patterns at that intersection.

The two approaches have traditionally been popular with different social science fields. For example, much of the current research in psychologyis quantitative because the goal is to gain generalizable knowledge about behavior and mental processes. In contrast, much of the currentresearch in sociology and political science tends to be qualitative because the goal is to gain a richer understanding of a particular context. Ifyou want to understand why college students around the country suffer from increased depression, quantitative methods are the better choice.If you want to understand why the citizens of Egypt revolted against their government, then qualitative methods are more appropriate. Overall,qualitative research is esp3ecially useful when behavior has multiple causes that researchers may not anticipate or when researchers have onlya limited understanding of the subjects' cultural point of view.

Table 1.1 presents a comparison of quantitative and qualitative methods, their descriptions, purposes and approaches, and the researcher'sroles. (See also the Centers for Disease Control and Prevention [CDC] website ) for further comparison.

Table 1.1: Comparing quantitative and qualitative research methodologies
	Quantitative	Qualitative
Description	Aim is to classify features, count them, and constructstatistical models in an attempt to explain what isobserved	Aim is a complete, detailed description
	Researcher knows clearly in advance what he/she islooking for	Researcher may only know roughly in advance whathe/she is looking for
	All aspects of the study are carefully designed beforedata are collected	The design emerges as the study unfolds
	Researcher uses tools, such as closed-endedquestionnaires, rating scales, tests, etc. or equipmentto collect numerical data	Researcher uses observations, interviews (open-ended questions), and written documents (historicalrecords, official publications, other articles,photographs, etc.)
	Data take the form of numbers and statistics and aremeasurable	Data take the form of words, pictures, or objects andare not as easy to measure
	Focus is on objective assessment: seeking precisemeasurement and analysis of target concepts, e.g.,uses closed-ended surveys, questionnaires, etc.	Focus is on subjective assessment: individuals'interpretation of events is important, e.g., usesparticipant observation, in-depth interviews, etc.
	Data are more efficient, able to test hypotheses, andcan be generalized	Data are more detailed, time-consuming, and lessable to be generalized
	Researcher is objectively separated from the subjectmatter	Researcher is immersed in the subject matter
Purpose	Generalizability Prediction Causal explanations	Contextualization Interpretation Understanding actors' perspectives
Approach	Begins with hypotheses and theories Manipulation and control of variables Uses formal instruments of measurement Experimentation Deductive reasoning	Ends with hypotheses or grounded theory Little control over variables Researcher as instrument Naturalistic observation Inductive reasoning
Researcher's Role	Detachment and impartiality Objective portrayal	Personal involvement and partiality Empathic understanding

In an ideal world, a true understanding of any phenomenon requires the use of both methods. That is, we can best understand depression if weboth study statistical trends and conduct in-depth interviews with depressed people. We can best understand binge drinking by conducting bothsurveys and focus groups. And we can best understand the experience of being bullied in school by both talking to the victims and collectingschoolwide statistics. Thus, researchers do not have to choose one method over another but can combine elements of both quantitative andqualitative approaches to produce mixed methods designs. Mixed methods designs are often used when one method does not provide acomplete picture of the phenomenon being investigated. In this text, the focus is primarily on quantitative methods, reflecting current trends inthe field of psychology. We will primarily cover qualitative methods in Chapter 3 (on descriptive research) and quantitative methods in Chapters4 (predictive research) and 5 (experimental research). A more thorough discussion on mixed methods designs will also be discussed in Chapter5.

1.3 Research Problem and Questions

Before conducting research, whether it be through qualitative or quantitative methods, a researcher must first identify a problem to investigateand then develop a research question or questions to ask about that particular problem. Theory and hypothesis play a crucial role, as doresearch, observation, and top-down and bottom-up thinking, informed by a thorough literature search.

While we often think we understand problems, we really do not. For example, a teacher might notice that a student is easily distracted andinattentive in the classroom, leading the teacher to believe, initially, that the student has an attention problem or attention-deficit/hyperactivitydisorder (ADHD). Upon further examination and possibly after testing has occurred, the results might instead show that the student has alearning disability in reading, writing, or math, and is being inattentive because he or she does not understand the material or have thenecessary skills to complete the assignment.

In another example, a teacher observes that a student is sleeping excessively during the first two periods of school. The teacher may assumethat the student stays up late playing on the computer or texting with his or her friends. After speaking to the parents, the teacher learns thatthe parents have recently gone through a divorce and that the student is working a part-time job in the evenings to help out with the finances.Thus, the student has been staying up late at night to complete his or her homework for the next school day. As we can see, in some cases ourinitial beliefs or thoughts about a problem may not be correct and may lead to inaccurate recommendations and treatments. Therefore, it isabsolutely crucial that we accurately identify the problem that we want to study.

Research Problems

A research problem is the topic or phenomenon that we want to address, investigate, and research, either through quantitative, qualitative, ormixed methods. It is the heart of any research project and is crucial to the success of the overall research effort (Leedy & Ormrod, 2010).Problems needing more research are everywhere; however, finding a research problem that interests you may take some work.

Sources of Research Problems

There are several different methods for identifying a good research problem. These include reviewing theories about a topic, reviewing currentprofessional literature on a topic, attending professional conferences, and having discussions with colleagues on the issue. A selective reading ofthe literature is probably the most advantageous method, as it can provide a theoretical base to generate research questions and hypothesesand assist in the selection of research methodologies and measurement methods. Later on, it can help you to interpret the results incomparison with other literature in the field. Attending professional conferences also provides advantages because there, researchers canexplore the most popular topics in their field as well as meet with experts who have been researching a given problem.

Charles (1995; as cited in Houser, 2009) provides several helpful suggestions for researchers when identifying research problems. These include(1) having personal interest in the topic, (2) selecting an important topic that will answer the "So what?" question we ask when evaluatingothers' research, (3) selecting a topic that is feasible and can be completed in a reasonable amount of time, and (4) selecting a topic that can becompleted with the amount of money allotted to studying it. Thus, it is important that we select something that we are interested in and havesome knowledge about, as we may not want to see the study through if the topic has no interest to us or relevance in our lives.

Stating the Research Problem

Student using laptop at home.

Digital Vision/Thinkstock

Investigating lack of student success in online classrooms requiresa researcher to develop a clear and focused problem statement.

Once a research problem is identified, the next step is to narrow the topic so thatit can be measurable and presented in a clear problem statement. For example,having a research problem of "Lack of student success in online classrooms" isextremely broad and could take many directions. For instance, would the researchinclude students' experiences with online learning, number and quality of student-to-teacher interactions, quality of student-to-student interactions, or anotherarea? Developing a problem statement, or aim of the study, will help to clearlydescribe the intent of the study.

Problem statements should be clearly and specifically stated and should describethe main goal of the total research project. For example, using the precedingexample, "Lack of student success in online classrooms" lacks clarity and does notprovide an understanding of what the researcher plans to do. Developing this intoa complete sentence that describes a researchable problem would entail thefollowing: "To determine the relationship between instructor involvement andstudent success during students' first online course in college." This latterstatement is clear regarding the intent of the study and the population that willbe included. Clearly defining a problem is key to the design and implementationof a research study. Without a clear and specific problem statement, theresearcher may find him- or herself going on a "wild goose chase" and wasting unnecessary time trying to investigate a vague problem orphenomenon.

The following guidelines adapted by Leedy and Ormrod (2010) will assist you in formulating a clear, precise, and accurate problem statement:

· Is the problem stated in complete and grammatically correct sentences?

· Is it clear what the study will focus on?

· Is it clear that the results could go either way? Thus, does the statement suggest an open mind to the research findings, or does it show aparticular expected outcome?

· Does the answer to the problem provide important and useful information regarding the topic?

· Is the problem statement focused enough for the research to be completed in a reasonable amount of time and within budget?

Dividing the Research Problem Into Subproblems

If your research problem covers more than one concept, you will want to break down your research problem into subparts or subproblems,each of which represents only one concept. For example, if we were to reword our problem statement as "To evaluate the influences thatinstructor involvement and student-to-student interactions have on students' success during their first online course in college," there would betwo concepts being evaluated: instructor involvement and quality of student-to-student interactions. To break this problem statement into twosubproblems, it would look like the following:

Problem Statement: To evaluate the influences that instructor involvement and quality of student-to-student interactions have onstudents' success during their first online course in college.

Subproblem 1: Evaluate the influences of instructor involvement on students' success during their first online course in college.

Subproblem 2: Evaluate the influence that quality of student-to-student interactions has on students' success during their firstonline course in college.

Thus, your problem statement should comprise all of the subproblems, while the subproblems should not introduce any new ideas or conceptsthat are not covered in the problem statement.

When developing subproblems, you will want to adhere to these guidelines: (1) Each subproblem should be a problem that can be researchedon its own; (2) each subproblem should be set forth as a statement and not as a question; and (3) the total number of subproblems should bebetween two and six (Leedy & Ormrod, 2010). Viewing a problem statement through its subproblems will give you a better idea of how toapproach the overall research project (Leedy & Ormrod, 2010).

The Purpose Statement

The purpose statement, similar to the problem statement, takes the goal of the study one step further. It not only includes the intent of thestudy but identifies what population will be studied, what type of research will be conducted (e.g., a comparison between variables), and whatthe dependent and independent variables will be. Using our research problem, "Lack of student success in online classrooms," a purposestatement might look like the following: "The present study was conducted to determine the relationship between instructor involvement andstudent success during students' first online course in college."

In most quantitative research as this, problem statements are often replaced with hypotheses, which will be discussed later in the chapter. Incontrast, qualitative research methods generally employ either problem statements or research questions. With any research method, however,the purpose statement should show that the purpose and problem are researchable.

Researchers utilizing quantitative methods generally include in their purpose statement whether the study involved a comparison among groupsor a relationship between two or more variables, or a descriptive examination of one or more variables. Including this information not onlyguides the researchers in selecting the appropriate data analyses but also provides information on the type of study being conducted (Houser,2009). For instance, Kerrigan (2011) provides an example of a purpose statement that includes a comparison study:

The purpose of this comparative quasi-experimental study was to compare the effect of coaching on comfort levels, as measuredby an adapted questionnaire, and blood sugars levels, as recorded on individuals' glucometers, between two groups of individualswith diabetes who had attended a formal diabetic education program (p. 7).

Researchers examining the types of relationships between two or more variables are interested in how well the variables correlate. For example,Cerit and Dinc (2013) conducted a study that focused on a relationship between variables. They discussed their purpose statement as follows:"The aim of this study was to investigate the correlation between nurses' professional behaviours and their ethical decision-making in a differentcultural context by adapting the Nursing Dilemma Test (NDT) into Turkish" (p. 202). Both examples provide the reader with informationregarding the type of study utilized (i.e., comparison or correlation) as well as what the dependent and independent variables were.

On the other hand, when examining a phenomenon, characteristic, or event in great detail, some researchers may choose to use qualitative ordescriptive methods rather than quantitative methods. In these cases, the purpose statement will focus more on describing and clarifying thephenomena or event than on comparing groups or identifying relationships between variables (Houser, 2009). Here is an example of aqualitative purpose statement, provided by Bradshaw, Sudhinaraset, Mmari, and Blum (2010):

The primary goals of the current study were to (a) describe the transition-related stressors experienced by mobile militarystudents; (b) describe the efforts employed to help these students cope with their stress; and (c) identify strategies that schoolscan use to ease the transition process for mobile military students. To address these three goals, we conducted separate focusgroups with adolescents in military families, military parents, and school staff in military-affected schools at select U.S. militarybases. (pp. 86–87)

The most important term in this purpose statement is the word describe, as it indicates that the study is employing qualitative or descriptivemethods rather than quantitative ones. Regardless of whether a researcher is utilizing quantitative or qualitative methods, the purposestatement is generally included at the end of the Introduction, usually in the last paragraph before the Literature Review section.

Research Questions

As we have learned, it is important to narrow down one's topic or ideas into a researchable problem. Examining existing literature will provideinformation about what is unclear in the field of study and whether any gaps exist. Doing so will also help to further clarify the research focusor aim of the study as well as assisting in the development of research questions.

Identifying a research problem, stating the problem, and providing a purpose statement are all steps toward describing the aim or goal of theoverall study. Research questions are then developed to guide researchers toward their objectives. In quantitative studies, research questionsgenerally take the form of hypotheses, which are specific predictions or educated guesses about the outcome of the study. However, somequantitative researchers choose to include hypotheses and research questions that are related to the research problem. Generally, quantitativeresearch questions focus on the Who, What, and When of specific variables and are closed-ended questions that provide cause-and-effectanswers.

In qualitative studies, research questions guide data collection and interpretation but do not include speculations or predictions about theoutcome. Qualitative research questions tend to focus on the Why and How of a phenomena or event, providing more descriptive and open-ended answers.

Both hypotheses and research questions provide the researcher with a starting point to explore a problem, as well as assist the researcher to"stay on topic" and answer those questions he or she initially wanted to address.

Developing Research Questions

How you conduct a research study depends largely on the research questions you develop. Let us look back on our previous research problemstatement involving online learning: "To determine the relationship between instructor involvement and student success during students' firstonline course in college." Some researchable questions might include the following:

1. Are there relationships between instructor involvement and students' success with respect to students' participation in the online classroomand students' quality of work completed?

2. Does the amount of instructor involvement have an influence on student involvement?

Notice how these questions provide specific information about what will be examined. For example, the first research question identifies howstudent success will be defined by measuring the amount of participation in the classroom and the quality of work submitted. Operationallydefining, or clearly identifying, how student success is going to be measured (i.e., through number of weekly participations and graded work)ensures that all researchers and reviewers have a clear understanding of what "student success" means in this study. Operational definitions,such as this one, establish the meaning of a concept or variable in relation to a particular study. Without operationally defining student successfor this study, it would be unclear how that variable would be assessed or measured. The second research question tells us that the researcheris going to measure the level of instructor involvement and see how it relates to student involvement in the course. Thus, we also need tooperationally define how we are going to identify and measure "level of instructor involvement." Will it be measured by number of times aninstructor responds to a student each week, by the length and quality of the responses, or both? Both research questions not only inform howthe research will be conducted but also serve as guides throughout the research project endeavor.

It is important to mention that, although research questions should be developed at the beginning of a project, they can change as you designyour study. Designing your study involves making several careful decisions about your research questions in order to prevent your study fromfoundering. Ask yourself, What types of data will be collected, and what methods will be used to collect the data? Where and for how long willthe research be conducted, and what participants or groups will be included? Are the data collection procedures consistent with the researchquestions? Once the project has started, if you find that your research questions were not appropriate for the research problem or that thedata collection and analysis methods were not consistent with the research questions, your study results may be unusable, forcing you to startthe project over again.

Previous section

Next section

1.3 Research Problem and Questions

Research Problems

Sources of Research Problems

Stating the Research Problem

Student using laptop at home.

Digital Vision/Thinkstock

Investigating lack of student success in online classrooms requiresa researcher to develop a clear and focused problem statement.

The following guidelines adapted by Leedy and Ormrod (2010) will assist you in formulating a clear, precise, and accurate problem statement:

· Is the problem stated in complete and grammatically correct sentences?

· Is it clear what the study will focus on?

· Is it clear that the results could go either way? Thus, does the statement suggest an open mind to the research findings, or does it show aparticular expected outcome?

· Does the answer to the problem provide important and useful information regarding the topic?

· Is the problem statement focused enough for the research to be completed in a reasonable amount of time and within budget?

Dividing the Research Problem Into Subproblems

Problem Statement: To evaluate the influences that instructor involvement and quality of student-to-student interactions have onstudents' success during their first online course in college.

Subproblem 1: Evaluate the influences of instructor involvement on students' success during their first online course in college.

Subproblem 2: Evaluate the influence that quality of student-to-student interactions has on students' success during their firstonline course in college.

Thus, your problem statement should comprise all of the subproblems, while the subproblems should not introduce any new ideas or conceptsthat are not covered in the problem statement.

The Purpose Statement

Research Questions

Developing Research Questions

1. Are there relationships between instructor involvement and students' success with respect to students' participation in the online classroomand students' quality of work completed?

2. Does the amount of instructor involvement have an influence on student involvement?

1.4 Hypotheses and Theories

The use of hypotheses is one of the key distinguishing features of scientific inquiry. Rather than making things up as they go along, scientistsdevelop a hypothesis ahead of time and design a study to test this hypothesis. In this section, we cover the process of turning rough ideasabout the world into testable hypotheses. We cover the primary sources of hypotheses as well as several criteria for evaluating hypotheses.

Sources of Hypotheses

Hypotheses can be generated from the bottom up or the top down. From the bottom up, hypotheses are built on real-world observations, usinginductive reasoning. From the top down, hypotheses begin with big ideas, or theories, which are then tested through deductive reasoning.

Bottom-Up: From Observation to Hypothesis

Research hypotheses are based on observations about the world around us. For example, you may have noticed the following tendencies as youobserve the people around you:

· Teenagers do a lot of reckless things when their friends do them.

· Close friends and couples tend to dress alike.

· Everyone faces the front of the elevator.

· Church attendees sit down and stand up at the same time.

Based on these observations, you might develop a general hypothesis about human behavior—that people will conform to, or go along with,what the group is doing. This process of developing a general statement out of a set of specific observations is called induction and is perhapsbest understood as a "bottom-up" approach. In this case, we have developed our hypothesis about conformity from the ground up, based onobserving behavioral tendencies.

The process of induction is a very common and very useful way to generate hypotheses. Most notably, this process is a great source of ideasthat are based in real-world phenomena. Induction also helps us to think about the limits of an observed phenomenon. For example, we mightobserve the same set of conforming behaviors and speculate whether people will also conform in dangerous situations. What if smoke startedpouring into a room and no one else reacted? Would people act on their survival instinct or conform to the group and stay put (Latané &Darley, 1969)? Your prediction about how this experiment might turn out forms your hypothesis for the experiment.

The process of qualitative research is an excellent example of induction, in that the researcher builds abstractions, concepts, hypotheses, andtheories from details and observations in the world. Hypotheses are not established a priori but may emerge from the research data andfindings. Thus, qualitative approaches often lead to hypothesis-generating research, which can lay the groundwork for future quantitativestudies.

Top-Down: From Theory to Hypothesis

The other approach to developing research hypotheses is to work down from a bigger idea. The term for these big ideas is a theory, whichrefers to a collection of ideas used to explain the connections among variables and phenomena. For example, the theory of evolution organizesour knowledge about how species have developed and changed over time. One piece of this theory is that life originated in Africa and thenspread to other parts of the planet. However, this idea in and of itself is too big to test in a single study. Instead, we move from the "top down"and develop a specific hypothesis out of a more general theory; this process is known as deduction.

When we develop hypotheses using a process of deduction, the biggest advantage is that it is easier to place the study—and our results—in thelarger context of related research. Because our hypotheses represent a specific test of a general theory, our results can be combined with otherresearch that tested the theory in different ways. For example, in the evolution example, you might hypothesize that older fossils would befound in Africa than would be found in other parts of the world. If this hypothesis were supported, it would be consistent with the overalltheory about life originating in Africa. And, as more and more researchers develop and test their own hypotheses about the origins of life, ourcumulative knowledge about evolution continues to grow.

Most research involves studying constructs that have been investigated extensively. In such situations, particular theories will guide decisionsabout the research. Some of these theories may be new and will have had only limited studies conducted on them. Others will be more mature,having hundreds of research studies validating their predictions. In some cases, a study may provide validation for more than one theory. Toillustrate this concept, consider a study on the causes of childhood obesity. The following are only some of the many theoretical ideas thatcould contribute to such a study:

· Parents do not provide healthy eating choices at home.

· Children from low-income neighborhoods do not have access to healthier food choices or cannot afford them.

· Busy families do not have time to cook and rely on fast food.

· Obesity is genetic. Thus, children with obese parents are 80% more likely to be obese themselves.

· Media encourages the consumption of fast food.

· Cultural and ethnic differences exist regarding what is considered a healthy or an unhealthy weight.

· Children are spending more time watching TV and playing video games, and consuming junk food while doing so.

· Schools are not providing healthy food options.

· Children are not exercising enough at school or at home.

This example only scratches the surface of the role of theory in a study such as this. Possible hypotheses that could be formulated from thesetheories include the following: Children exposed to a school-based intervention to reduce time spent watching television and playing videogames will have significantly reduced body mass index (BMI); or, Exposure to fast food, soft drink, and cereal advertising on television increaseschildren's food consumption behaviors and, in turn, their BMI.

Table 1.2 compares the two sources of research hypotheses, showcasing their relative advantages and disadvantages.

Table 1.2: Comparing sources of hypotheses
Deduction	Induction
"Top-down," from theory to hypothesis	"Bottom-up," from observation to hypothesis
Easy to interpret our findings	Can be hard to interpret without prior research
Helps science build and grow	Helps our understanding of the real world
Might miss out on new perspectives	Great way to get new ideas

Evaluating Theories

While experiments are designed to test one hypothesis at a time, the overall progress in a field is measured by the strength and success of itstheories. If we think of hypotheses as being like individual combat missions on the battlefield, then our theories are the overall battle plan. Sohow do we know whether our theories are any good? In this section, we cover four criteria that are useful in evaluating theories.

Explains the Past; Predicts the Future

One of the most important requirements for a theory is that it either supports, refutes, or provides additional perspectives on existingknowledge. If a physicist theorized that everything on earth should float off into space, this would conflict with millennia's worth of evidenceshowing that gravity exists. And if a psychologist argued that people learn better through punishment than through rewards, this would conflictwith several decades of research on learning and reinforcement. A theory should offer a new perspective and a new way of thinking aboutfamiliar concepts, but it cannot be so creative that it clashes with what we already know. Related to this, a theory also has to lead to accuratepredictions about the future, meaning that it has to stand up to empirical tests. There are usually multiple ways to explain existing knowledge,but not all of them will be supported as we test their assumptions in new circumstances. At the end of the day, the best theory is the one thatbest explains both past and future data.

Research: Thinking Critically

Controversy Grows Over Study Claiming Liberals and Atheists Are Smarter

By Daniela Perdomo

There's a lot of buzz over a controversial study released in the journal Social Psychology Quarterly, titled"Why Liberals and Atheists Are More Intelligent," that compares IQ levels among liberals andconservatives, atheists and religious believers. The widely circulated study claims that "more intelligentindividuals may be more likely to acquire and espouse evolutionarily novel values and preferences (suchas liberalism and atheism ...) than less intelligent individuals." The study was written by SatoshiKanazawa (2010), a social scientist at the London School of Economics who employs evolutionarypsychology to analyze the social sciences, such as economics and politics, and who has a history ofattracting ire over his studies and opinions.

But before drawing any conclusions about Kanazawa's latest study, it's worth expanding on the data hebases his claims on. First of all, quantifying intelligence on a societal level—and even from person toperson—is incredibly tricky, if not impossible. As an evolutionary psychologist, Kanazawa likely recognizesthis, and that may be why he decided to limit his intelligence measures to IQ points, a convenient andnotoriously narrow way of assessing cognitive abilities.

The first problem in the study comes with Kanazawa's use of IQ as an accurate measure of intelligence.P. Z. Myers, a leader in the field of evolutionary developmental biology (and an avowed atheist andprogressive), is not surprised. He calls Kanazawa the "great idiot of social science" and points to a 2006paper in which Kanazawa took the mean IQ of various countries and used those to draw conclusions ontheir dedication to health care.

For example: Ethiopia has a mean IQ of 63. This low IQ explains why Ethiopia's health care system isawful, according to Kanazawa. Talk about simplistic. Not only does this ignore the fact that IQ mightbetter measure cognitive capabilities in the developed world, where it was designed, but it completelytunes out the fact that Ethiopia has been embroiled in wars for many years, which would appear to be abetter explanation for why the health care system there hasn't developed to Western levels yet."Intelligence is such a complex phenomenon—there are multiple parameters," Myers says. "And IQ isextremely sensitive to social conditions. Kanazawa wants to reverse it and say that IQ is causingproblematic social conditions."

In this more recent study, not only does Kanazawa gloss over structural inequalities that may lead tovarying IQ levels in American society, but even the disparities he finds in this imperfect measure ofintelligence are relatively minuscule. For the most part, he is not speaking of a difference of more thansix IQ points between liberals and conservatives, atheists and believers—a negligible difference onewould never notice in real person-to-person interactions.

Kanazawa isn't the first to study the intelligence–religiosity nexus. Other studies have also found a three-to six-point IQ difference between atheists and religious believers, in the atheists' favor. But thosestudies didn't claim that atheists were more evolved, as Kanazawa presumes, but merely concluded thatthey are more skeptical owing to a certain kind of schooling and cultural exposure (which might alsoaccount for why some people perform well on IQ tests).

Then there's the issue of Kanazawa's definition of liberalism, which he writes is the "contemporaryAmerican" denotation: "the genuine concern for the welfare of genetically unrelated others and thewillingness to contribute larger proportions of private resources for the welfare of such others."Practically speaking, this means Kanazawa's "liberalism" is defined as a willingness to pay a higher taxrate and donate money to charity.

This definition of liberalism, says Ilya Somin, a legal scholar whose expertise includes popular politicalparticipation, does not actually distinguish it from, say, conservatism or libertarianism. Somin writes:

[A] libertarian who believes that free market policies best promote thewelfare of genetically unrelated others and contributes a great deal ofhis money to charities promoting libertarian causes counts as a liberalunder this definition. The same goes for a Religious Right conservativewho believes that everyone will be better off under sociallyconservative policies and contributes lots of money to church charities.

On this last point, it should be noted that recent research shows American political conservativesactually give more money to charity (and donate more blood) than their politically liberal counterparts.

The problem inherent in Kanazawa's vague definition of liberalism is further compounded by the factthat he gleans his data on intelligence and attitudes toward topics of religion, politics, and charity fromtwo massive national surveys—the National Longitudinal Study of Adolescent Health and the GeneralSocial Survey.

These large-scale studies are greatly compromised by self-reporting. Most Americans don't even reallyknow where they fall on the left–right political continuum. Polling shows, for example, that more AfricanAmericans self-identify as conservative than liberal, but when it comes to actual votes, data indicate thatBlacks overwhelmingly vote for traditionally defined liberal causes and candidates.

And libertarians—estimated to be about 15% of the U.S. population—don't neatly identify as liberals orconservatives, or even centrists, depending on whether they more closely identify as economicconservatives or social liberals. Even progressives shy away from identifying themselves as liberals, aterm that carries a negative connotation for many of them.

A particularly problematic idea presented by the study is how Kanazawa defines certain values andpreferences as "evolutionarily novel." While he does not come out and say being atheist is a sign ofhaving evolved more than those who are religious, he does infer this, not only by referring to the slightlyhigher mean IQ levels of American atheists but also by pointing out that atheism goes against the grainof general human history. (Kanazawa doesn't even touch upon the idea that beliefs are more likelycolored by one's cultural background than one's genetics.)

Personal values do play a positive role in motivating researchers to get to the bottom of situations theycare about. However, as we can see from this scholarship, there are dangers in narrowing one's culturalpoint of view and allowing one's political bias to influence the interpretation of data. In the end,Kanazawa's study reinforces long-standing prejudices against conservatives and religious believers. Tothink that conservatives or religious people "are dumber than you and me," says Myers, "fosters thistribalism that we're out to replace people rather than to educate and inform them." And that's not verysmart.

Perdomo, D. (2010, March 5). Controversy grows over study claiming liberals and atheists are smarter. Alternet. Retrieved from http://www.alternet.org/story/145903/controversy_grows_over_study_claiming_liberals_and_atheists_are_smarter

Think about it:

1. What general theory is Kanazawa trying to test? How does the theory differ from his specifichypothesis?

2. How did Kanazawa operationalize liberalism and intelligence in his research? Are there problems withthe way these constructs were operationalized? Explain.

3. What were Kanazawa's main findings? Evaluate the strength of the evidence for and against hishypothesis. How is the strength of this evidence influenced by his research methods?

4. Why do you think this research is controversial? If Kanazawa's methodology were more rigorous,would it still be controversial?

Testable and Falsifiable

Second, a theory needs to be stated in such a way that it leads to testable predictions. More specifically, a theory should be subject to astandard of falsifiability, meaning that the right set of conditions could prove it wrong (Popper, 1959). Calling something "falsifiable" does notmean it is false, only that it would be possible to demonstrate its falsehood if it were false. The Darwinian theory of evolution offers a greatexample of this criterion. One of the primary components of evolutionary theory is the idea that species change and evolve from commonancestors over time in response to changing conditions. So far, all evidence from the fossil record has supported this theory—older variants ofspecies always appear farther down in a fossil layer. However, if conflicting evidence ever did appear, it would deal a serious blow to the theory.The biologist J. B. S. Haldane was once asked what kind of evidence could possibly disprove the theory of natural selection, to which he replied,"fossil rabbits in the Pre-Cambrian era"—that is, a modern version of a mammal in a much older fossil layer (Ridley, 2003).

Dinosaur fossil.

iStockphoto/Thinkstock

The theory of evolution is falsifiable,meaning that it could be disproved underthe right conditions—for example, if fossilevidence that contradicted the theorywas discovered.

Parsimonious

Third, a theory should strive to be parsimonious, or as simple and concise as possible without sacrificingcompleteness. (Or, as Einstein famously quipped during a lecture at Oxford, "Everything should be madeas simple as possible, but no simpler" [Einstein, 1934, p. 165]). One helpful way to think about thiscriterion is in terms of efficiency. Our theories need to spell out the components in a way thatrepresents everything important but doesn't add so much detail that it becomes hard to understand.This means that our theories can lack parsimony either because they are too complicated, or becausethey are too simple. At one end of this spectrum, Figure 1.1 presents a theoretical model of the causesof malnutrition (Cheah, Zabidi-Hussin, & Wan Manan, 2010.). This theory does a superb job ofsummarizing all of the predictors of child malnutrition across multiple levels of analysis. However, thepotential problem is that it becomes too complicated to test. At the other end of the spectrum, Figure1.2 presents the overall theoretical perspective behind behaviorism. In the early part of the 20thcentury, the behaviorist school of psychology argued that everything organisms do could be representedin behavioral terms, without any need to invoke the concept of a "mind." The overarching theory lookedsomething like Figure 1.2, with the "black box" in the middle representing mental processes. However,the cognitive revolution of the 1960s eventually displaced this theory, as it became clear thatbehaviorism was too simple. The ideal balance, then, is to lay out your theory in a way that includes thenecessary pieces and nothing unnecessary.

Figure 1.1: Predictors of malnutrition

A complex theoretical model of the causes of malnutrition including malnutrition indicators, behavioral aspects, environmental aspects, and biological aspects.

A complex theoretical model of the causes of malnutrition.

Adapted from Cheah, W.L., Zabidi-Hussein, Z., Wan Manan, W.M. (2010). A structural equation model of the determinants of malnutritionamong children in rural Kelantan, Malaysia. Rural and Remote Health 10: 1248 (Online).

Figure 1.2: The behaviorist model

Figure representing the overall theoretical perspective behind behaviorism. The figure shows a three-step process moving from "stimulus" on the left to "response (behavior)" on the right. In the middle is a black box representing mental processes.

The overall theoretical perspective behind behaviorism. The "black box" in the middle represents mental processes.

Promotes Research

Finally, science is a cumulative field, which means that a theory is really only as good as the research it generates. Or to state it more bluntly,the theory that you are so attached to is useless if no one follows up on it. Thus, one of the best bases for evaluating a theory is whether itencourages new hypotheses. Consider the following example, drawn from real research in social psychology. Since the early 1980s, Bill Swannand his colleagues have argued that we prefer consistent feedback to positive feedback, meaning that we would rather hear things that confirmwhat we think of ourselves. One provocative hypothesis that comes out of this theory is that people with low self-esteem are more comfortablewith a romantic partner who thinks less of them than anyone who might think well of them. This hypothesis has been tested and supportedmany times in various contexts and continues to draw people in because it is exciting. (For a review of this research, see Swann, Rentfrow, &Guinn, 2005.)

The Cycle of Science

Figure 1.3: The cycle ofscience

Figure illustrating the cycle of science progressing from top to bottom: theory, hypothesis, empirical data, revised theory. An arrow is shown leading from revised theory to hypothesis.

Let's take a step back and look at the big picture. We have now covered the processes of developingtheories, developing hypotheses, and evaluating all of them. But of course, none of these pieces occursin isolation; science is an ongoing process of updating and revising our views based on what the datashow. This overall process works something like the cycle depicted in Figure 1.3. We start with an overalltheory about how concepts relate to one another and use this to generate specific, testable, andfalsifiable hypotheses. These hypotheses then form the basis for research studies, which generateempirical data. Based on these data, we may have reason to suspect that the overall theory needs to berefined or revised. And so we develop a new hypothesis, collect some new data, and either confirm ordon't confirm our suspicion. But it doesn't end there: Other researchers may see a new perspective onour theory and develop their own hypotheses, which lead to their own data and possibly to a revision ofthe theory. If this is making your head spin, you're not alone. The scientific approach may be a slow andstrange way to solve problems, but it is the most objective one available.

In the 1960s, social psychologists were beginning to study the ways that people explain the behavior ofothers (e.g., when someone cuts you off in traffic, you tend to assume he is a jerk). One early theory,called "correspondent inference theory," argued that people would come up with these explanations in arational way. For example, if we read a persuasive essay but then learned that the author was assignedher position on the topic, we should refrain from drawing any conclusions about her actual position. However, research findings havedemonstrated that people make systematic errors in logical thinking. In a landmark 1967 study, participants actually ignored information aboutwhether authors had chosen their own position on the issue, assuming instead that whatever they wrote reflected their true opinions (Jones &Harris, 1967). In response to these data (and similar findings from other studies), the theory was gradually revised to account for what wastermed the "fundamental attribution error"—people tend to ignore situational influences and assume that behavior reflects the person's owndisposition. These authors developed a theory, came up with a specific hypothesis, and collected some empirical data to test it. But because thedata ran counter to the theory, the theory was ultimately revised to account for the empirical evidence. Theories of attribution continue to berefined to explain the way observers make sense of people's behavior.

Proof and Disproof

While we are on the subject of adjusting our theories, let's take a look at the notions of "proof" and "disproof." Because science is a cumulativefield, decisions about the validity of a theory are ultimately made based on results of several studies from several research laboratories. Thismeans that a single research study has rather limited implications for an overall theory. This also means that you, as a researcher, have to usethe concepts of proof and disproof in the correct way. We will elaborate on this as we move through the course, but for now we can rely ontwo very simple rules:

1. If the data from one study are consistent with our hypothesis, we support the hypothesis rather than "proving" it. In fact, we almost neverprove a theory, but our statistical tests can at least tell us how confident to be in our support.

2. If the data from one study are not consistent with our hypothesis, we fail to support the hypothesis. As we will discuss throughout the course,many factors can cause a study to fail; however, these often result from flaws in the design rather than flaws in the overall theory.

Sources of Ideas

Where do all of these great ideas come from in the first place? Students are often nervous about starting a career in research because theymight not be able to come up with great ideas to test. In reality, though, ideas are easy to come by, once you know where to look. In thissection, we offer a few tips and suggest handy sources for developing research ideas.

Real-World Problems

Adolph Eichmann on the opening day of his trial for war crimes, Israel, April 11, 1961.

Courtesy: CSU Archives/Everett Collection

Adolf Eichmann claimed he was just "following orders" in his roleas a Nazi Lieutenant Colonel of Holocaust Logistics during WorldWar II.

A great deal of research in psychology and other social sciences is motivated by adesire to understand—or even solve—a problem in the world. This processinvolves asking a big question about some phenomenon and then trying to thinkof answers based on psychological mechanisms. For example, according to theNational Center for Education Statistics, approximately 42 million Americans areunable to read, and 20% of high school seniors are unable to read when theygraduate. These statistics might lead you to think about ways to improve readinginstruction in the school system. And that might lead you to the hypothesis thatindividual tutoring will significantly improve children's reading skills.

In 1961, Adolf Eichmann was on trial in Jerusalem for his role in orchestrating theHolocaust. Eichmann's repeated statements that he was only "following orders"caught the attention of Stanley Milgram, a young social psychologist who had justearned a PhD from Harvard University and who began to wonder about the limitsof this phenomenon. To understand the power of obedience, Milgram designed awell-known series of studies that asked participants to help with a study of"punishment and learning." The protocol required them to deliver "shocks" toanother participant (actually an accomplice of the researcher) every time he gotan answer wrong. Milgram discovered that two thirds of participants would obeythe researcher's commands to deliver dangerous levels of shocks, even after the victim of these shocks appeared to lose consciousness. Theseresults revealed that all people have a frightening tendency to obey authority, even to the point of violating their own conscience. We willreturn to this study in our later discussion of ethics; you can read more about Milgram and his work on this website: http://explorable.com/stanley-milgram-experiment

To take one more example, you might notice that criminal-trial juries often seem to make really poor decisions. This might lead you to wonderabout the process of making decisions in a group. And that might lead you to the hypothesis that juries are more interested in getting alongwith the group than in finding the truth. The possibilities here are endless but, as we discussed earlier, you must always be cautious when youdesign a research project to solve a problem. Sometimes your desire to make a difference can bias your interpretation of the data.

Reconciliation and Synthesis

New ideas can also spring from resolving conflicts between existing ideas. The process of resolving an apparent conflict involves both reconciliation, or finding common ground among the ideas, and synthesis, or merging all the pieces into a new explanation. In the late 1980s,psychologists Jennifer Crocker and Brenda Major noticed an apparent conflict in the prejudice literature. Based on everything then known aboutthe development of self-esteem, members of racial and ethnic minority groups would be expected to have lower-than-average self-esteembecause of the prejudice they faced. However, study after study demonstrated that, in particular, African American college students hadequivalent or higher self-esteem than European American students. Crocker and Major offered a new theory to resolve this conflict, suggestingthat the existence of prejudice may sometimes grant access to a number of "self-protective strategies." For example, minority group memberscan blame prejudice when they receive negative feedback, making the feedback much less personal and therefore less damaging to self-esteem.The results of this synthesis were published in a 1989 review paper that launched a vibrant new research area on the targets of prejudice(Crocker & Major, 1989).

Learning From Failure

Kevin Dunbar, a professor at Dartmouth University, has spent much of his career studying the research process. That is, he interviews scientistsand sits in on lab meetings in order to document how people actually do research in the trenches. In a 2010 interview with the journalist JonahLehrer, Dunbar reported the shocking statistic that approximately 50% to 75% of research results are unexpected (some of these could havebeen null results due to lack of statistical power). Even though scientists plan their experiments carefully and use established techniques, thedata are often surprising. But even more surprising was the tendency of most researchers to discard the data if they did not fit their hypothesis."These weren't sloppy people," Dunbar says. "They were working in some of the finest labs in the world. But experiments rarely tell us what wethink they're going to tell us. That's the dirty secret of science." The trick, then, is knowing what to do with data that make a particular studyseem like a failure (Lehrer, 2010).

The secret to turning failure into opportunity is twofold: First, question your assumptions about why the study feels like a failure in the firstplace. Perhaps the data contradict your hypothesis but can be explained by a new one. Or perhaps the data suggest a dramatic shift inperspective. Second, seek new and diverse perspectives to help in interpreting your results. Perhaps a cognitive psychologist can shed light onreactions to prejudice. Or perhaps an anthropologist knows what to make of the surprising results of your aggression study. Some of the bestand most fruitful research ideas have sprung from combining perspectives from different disciplines. Sometimes, all that your strange datasetneeds is a fresh set of eyes.

Research: Thinking Critically

Does 9 Just Sound Cheap?

By William Poundstone

We have all heard of calculating prodigies, those rare souls able to perform astounding feats withnumbers. For many of these individuals, numbers have colors, flavors, sounds, or other qualities alien tothe rest of us. Mental calculator Salo Finkelstein detested the number zero and adored 226. The Russianmnemonist S. V. Shereshevskii associated the number 87 with a visual image of a fat woman and a mantwirling his mustache. This is known as synesthesia, the association of sensory qualities with seeminglyinappropriate objects. A recent study suggests that most people may have a bit of number synesthesia.It might help explain the mysterious appeal of "charm" prices ending in the digit 9—beloved bydiscounters everywhere.

At least since the 19th century, retailers have been using prices like 99 cents (rather than an even $1.00)or $295 (rather than $300). There's evidence that these prices induce shoppers to buy more than thecorresponding round prices do. There's been a lot of debate among marketers, psychologists, and evencognitive scientists about why these prices trick people into buying something they wouldn't havebought at a round price that is hardly much higher. In fact, in some experiments, more bought at a 9-ending price than at a price that was lower.

New research by Keith Coulter and Robin Coulter, published in The Journal of Consumer Research,implies that certain numbers just sound bigger than others. This in turn can affect the perception ofdiscounts.

Coulter and Coulter begin by citing decades of research claiming that sounds pronounced with the frontof the mouth (long a, e, and i; fricatives like f, s, and z) trigger associations with smallness. (Think ofwords like tiny and wee.) The vowels pronounced at the back of the mouth, like the "oo" in foot orgoose, are linked to largeness. (Think huge or crowds oohing and ahhing something really big.) Crazy?Well consider how it applied to discounts in the study. Subjects were given "regular" and "sale" pricesand asked to estimate the percentage discount. The guesstimated discounts were skewed by the soundeffect. For instance, people estimated that a $3 product marked down to $2.33 was about a 28%discount. But when the product was marked down to $2.22, the estimated saving was only 24%. It was abigger discount, really, but it didn't seem that way. One explanation: Three, with a long e, sounds small,and two, with a back-of-the-mouth vowel, sounds large.

That doesn't prove the sounds were responsible. In one of the crucial experiments, Coulter and Coultertested perceptions of the prices $7.01 and $7.88 with English and Chinese speakers. In English one ispronounced with the back of the mouth, and eight with the front. In Chinese, this is reversed. So werethe perceptions of how big or small discounts were. The researchers use this to argue that it is indeed"phonetic symbolism" at work.

"Nine" has a long i, so it's one of the small-sounding digits. Assuming the hypothesis is right, pricesending in 9 would seem a little smaller than they would otherwise, enhancing the quick, largelyunconscious perception of a good deal. But 9 isn't unique: It would seem that all the digits from 3 on uphave a vowel or consonant sound supposedly associated with smallness. (Ironically, the truly bigger digitssound small. Zero is a problematic case: The fricative z might put it in the small category, but mostpeople say "o" when reciting a phone number, and zeros at the end of a price aren't pronounced at all:$70 is "seventy dollars," not "seven-zero dollars.")

Obviously, retailers would want to charge the largest "small-sounding" price (the sound they care aboutis ka-ching). From that perspective, the use of 9 makes sense.

This study adds more fuel to the debate about how 9-ending prices "work." Coulter and Coulter believethat shoppers must "rehearse" prices—say them to themselves, at least silently—for the sounds to affectthem. In the experiments, participants were told to repeat the sale prices to themselves. It's not clearwhether this would apply to silent reading of a fast-food menu. Still, the experiment hints at whatunexpected layers of meaning we may attach to simple numbers—including the ones with dollar signs.

Poundstone, W. (2010, January 26). Does 9 just sounds cheap? The poetry of prices might trump the math. Psychology Today. Retrieved from http://www.psychologytoday.com/node/37553

Think about it:

1. What hypothesis are Coulter and Coulter trying to test? Try to state this as succinctly as possible.

2. How was "perception of discounts" operationalized in their studies?

3. How were the key variables measured?

4. How do Coulter and Coulter explain their findings? Are there other possible alternative explanations?

5. Are these studies primarily aimed at description, explanation, prediction, or change? Explain.

1.5 Searching the Literature

Regardless of how you develop your hypothesis, an important step in the process is to connect it with what has been done before. Scientificknowledge accumulates one study at a time, so the best studies will build on earlier studies—by extending, correcting, or contradicting them.And, on a practical note, it would be a waste of your time to struggle over the best way to measure something when another researcher figuredit out 20 years ago. So, rather than reinvent the proverbial wheel, one of the first steps in a research project is to consult published relevantarticles. In this section, we will cover the process of finding these articles, followed by an overview of how to read these articles effectively.

Searching for Articles

Beginning a search for relevant research articles can seem like a daunting task, largely due to the sheer number of available sources. Should youask a librarian? Search Wikipedia? Browse the Web? Fortunately, you can use a few tricks to make sure that your reference sources are both objective and scholarly. First, it is important to understand the difference between primary and secondary sources.

Primary sources contain full reports of a research study, including information on the participants, the data collected, and the statistical analysesof these data. These types of sources appear in professional academic journals and are evaluated by a set of experts in the field before they arepublished—a process known as peer review. Thus, primary sources are a reliable way to determine what has been done in a particular field.

Students using a library computer and reading from books.

Jupiterimages/©Getty Images/Thinkstock

University libraries provide studentsaccess to hard copies and digital copies ofrelevant research articles.

Secondary sources, in contrast, consist only of summaries of primary sources. These types of sourcesinclude textbooks, some academic books, and review articles in journals such as Psychological Bulletin.As an analogy, think of the difference between telling your friends about your adventurous weekend(primary source) and one of your friends repeating the story to her roommate (secondary source). Whilesome secondary sources undergo a process of review and evaluation (academic books), others do not(e.g., websites, friends retelling stories).

In this day and age, people are becoming more and more comfortable searching for information via theInternet. Thus, it is particularly important to point out that websites are often not objective in theirsummaries of research. The vaccine/autism scare discussed at the beginning of the chapter is a greatexample of this point. If you search in Google for the terms vaccine and autism, you will get more than 4million hits, sorted in order of popularity. As of summer 2011, the top hit was a summary by the Centersfor Disease Control, arguing in favor of vaccines. At another time, the top hit might have been JennyMcCarthy's website arguing that vaccines gave her child autism. In January 2013, it was reported thatthe federal Vaccine Injury Compensation Program had awarded millions of dollars to compensatechildren who developed autism after vaccination, confusing the matter even more (Kirby, 2013). And thiscame after news of a recent study that found no link between currently recommended vaccines andautism. The bottom line is that search results in Google (or other Internet search engines) are not peerreviewed, are not listed in order of reliability, but are customized to your browsing history, confirmingyour biases. As a result, a Google search is a poor choice when it comes to finding trustworthyinformation about academic research.

Another popular but untrustworthy source of information is Wikipedia. Wikipedia is a tempting resource,given its marketing as a "free online encyclopedia." But unlike more authoritative or printed encyclopedias, Wikipedia can be edited by anyonewith access to the Internet. On the upside, this means that errors can be identified and corrected at any time. On the downside, this meansthat errors can be made—either accidentally or deliberately—at any time. The upshot is that there is no way to be sure that you are drawinginformation from a page at a time when it sticks to the facts, and the content is always evolving.

So what's a researcher to do? Fortunately, there are two reliable ways to access primary sources (research articles), which allow you to drawyour own conclusions based on the patterns of data. First, Google Scholar ( http://scholar.google.com ) is a free resource that is managed byGoogle and that works exactly like Google but is limited to peer-reviewed academic articles. Thus, Google Scholar provides one pipeline toaccess primary sources. Second, many university libraries have access to centralized databases of peer-reviewed articles. The best-knowndatabase for psychology articles is PsycINFO; this database contains abstracts and citations for articles in psychology and related fields,maintained by the American Psychological Association. PsycINFO is updated monthly and covers approximately 2,500 different primary-sourceacademic journals.

Searching in PsycINFO (or Google Scholar) is as easy as typing key terms into a text box— sometimes labeled "Find" or "Keywords." But, thatsaid, the process of choosing the best key words for your particular search can be a complex process. If your search terms are too general, thesearch might yield too many hits to be useful. If your search terms are too specific, the search might yield only one or two articles and fail tofully represent prior studies.

As an example, the following list of numbers represents different combinations of search terms related to the topic of self-esteem:

"self-esteem" (in all fields)	35,847 hits

"self-esteem" (title only; peer reviewed)	4,977 hits

It's clear we need to narrow the field a bit—you have better things to do than review almost 5,000 abstracts! What aspect of self-esteem do wefind most interesting? Perhaps we want to learn more about self-esteem and sexual behavior?

"self-esteem" and "condom use"

2 hits

It seems we may have overdone the limits—two articles may not be very helpful in giving you a sense of previous research. So let's try onemore combination, using a more general search term:

"self-esteem" and "sexual behavior"

133 hits

This number is a bit more manageable; we could tinker a bit more, but it no longer seems overwhelming to skim through the search results andfind the most useful articles. No two searches will be the same, so the real take-home point is to try several combinations of search terms inorder to strike a balance in your number of results.

Reading Research Articles

Now that you have assembled a collection of research articles relevant to your hypothesis, the next step is to read them. This may soundpainfully obvious, but psychological journal articles are written in a very formulaic way, which can be confusing at first glance. However, onceyou know what to look for, the format ultimately makes these articles easy to read (and easy to write). As a matter of fact, the format of ajournal article is designed to follow the steps of the scientific method, with a section devoted to each of the four steps—hypothesize,operationalize, measure, and explain. In this section, we examine each part of a journal article to give you a sense of what to expect of eachone. This overview is based on a fantastic article by Jordan and Zanna (1999); the goal of both is to let you appreciate the stories withoutgetting bogged down in the details.

The Title and the Abstract

At the top of every journal article (as well as in the search results in PsycINFO), you will see both the title and an abstract, or a short summaryof the article. While neither of these is a section per se, both provide you with a valuable first impression of the contents of the article. If yoursearch query results in a large number of hits, you can usually scan the titles to determine which ones are most likely to be useful. For example,if your research question concerns the links between depression and alcohol consumption among college students, you might search a databasefor the terms "alcohol" and "depression." Most of the results are likely to be relevant and useful, but you could most likely skip ones with a titlelike "Fetal Alcohol Syndrome and Postpartum Depression," since it is likely to focus on a different population.

Once you narrow the list to the most useful titles, the abstract provides additional information about the content of the article. A journal articleabstract follows a standard formula of stating the objectives of the study, followed by information on the methodology, results, and conclusions.Generally, an abstract has to fit all of this information in about 150 words; as a result, it provides a nice concise summary that is worth readingcarefully.

The Introduction

The first main section of a journal article is the introduction, corresponding to the first step (i.e., hypothesize) of our four-step research process.As the name implies, the goal of this section is to introduce the research question, review background research, and state the hypothesis thatwas investigated. When you are diving into a new research area for the first time, it is a good idea to read the entire introduction carefully. Thissection provides the context for the rest of the paper, as well as a valuable introduction to previous work in the area.

The Method Section

The second main section of a journal article is the method section, corresponding to the second step (i.e., operationalize) of our four-stepresearch process. The goal of this section is to explain how the hypothesis was translated into a set of specific measurable variables and howthe researchers gathered data to test their hypothesis. An additional—perhaps even more important—goal of this section is to provide enoughdetail about the study that someone could read the article and repeat the study.

The method section is typically divided into three parts: The participants section describes the people who provided data for the study,including information about their age, gender, and other relevant information. For example, in a study on treating depression, the authors wouldspecify whether the participants were "normal" college students or patients who had been hospitalized for treatment of severe, clinical levels ofdepression. The materials section describes any questionnaires or equipment used in the study, including both standardized measures and onesthat the researchers created. The third and related section, procedure, provides all of the details regarding the execution of the experiment.What did participants experience, and in what order? If specific instructions were given before a task, what were they?

The materials and procedure sections are crucial for two reasons. First, they provide the necessary detail for someone else to recreate thestudy. In reading these sections, you should focus on understanding the key variables and how they were defined. Second, they allow readers toenvision the study from the perspective of the participants and to decide whether the authors' interpretation of the results is the only one. Forexample, the authors might claim that participants were placed under stress and that the results showed a drop in concentration because of thestress. But, in reading over the procedure section, the "stress" part of the study might seem more likely to invoke boredom. This would give youan idea for a follow-up study: Perhaps people actually lose concentration when they are bored....

The Results Section

The third main section of a journal article is the results section, corresponding to the third step (i.e., measure) of our four-step research process.The goal of this section is to describe how the data were analyzed and to report the results of these analyses. The results section consistsprimarily of statistical analyses and, as Jordan and Zanna put it, "statistics can be intimidating" (1999, p. 356). When you first start to readjournal articles, the statistics can indeed seem overwhelming, but there are two reasons not to get discouraged. First, statistical results arealways followed by a translation into plain English and almost always by tables and graphs of the data. As we move through this course, you willhave the opportunity to practice interpreting results in both statistical and graphical form. And this brings us to the second reason: You will besurprised to learn how quickly the statistics stop being intimidating. The more you read journal articles and place them in the context of yourown ideas, the more you become comfortable with interpreting statistical analyses. In fact, as you become savvier with interpreting statistics,you may be surprised by how often authors make mistakes in either their analyses or their interpretations of them!

The Discussion Section

The fourth and final section of a journal article is the discussion section, corresponding to the fourth (i.e., explain) step of our four-step researchprocess. The goal of this section is to summarize the main findings and provide an evaluation of the hypothesis. Thus, the first few paragraphsof the discussion are often a great summary of the entire article. Authors state whether their predictions were confirmed and speculate on themeaning of the findings. If some of the predictions were not confirmed, authors suggest explanations for this and either acknowledge or defendpotential flaws in the study. In addition, to encourage others to follow up on the study, authors tie their findings into those of previousliterature and make suggestions for future research.

Evaluating Articles

Figure 1.4: Structure of journal articles

Hourglass figure representing the structure of journal articles beginning at the top with the introduction, narrowing to method and results, and widening at the bottom with discussion.

So, in sum, a journal article will follow a predictable structure: Authors first describe the problem andstate their hypothesis (introduction), then explain their approach to testing the hypothesis (method),then report the findings of this test (results), and finally discuss the meaning of these findings relative tothe hypothesis (discussion). These four sections are often described as following an hourglass structure—that is, the paper starts broadly in the introduction, narrows to the specific details of the study, andends broadly in the discussion by tying everything back into the overall problem (e.g., Bem, 1987). Thisstructure is shown in Figure 1.4.

Before we move on, let's review some general guidelines for evaluating journal articles. After reading thepaper in its entirety, the following five questions can be helpful in forming an overall evaluation of whatyou've read.

1. What am I being asked to believe? What is the author's main argument? Before critiquing in detail,make sure you have mastered the argument and can summarize it in a few sentences.

2. What evidence supports this claim? How does the author support the main argument? If it is anempirical paper, look to the data; if it is a theoretical paper, look at the literature the authorsummarizes.

3. Are there alternative explanations? Be creative here. Based on your reading of the article, what elseseems plausible? But, to make your critique a good one, you should be able to test it.

4. What additional evidence would help us test alternatives? This question is one of the keys to doinggood science. Once you identify something wrong with the original study, how can you test youralternative?

5. What conclusions are reasonable? Return to step 1 with your critiques in mind. What should the author reasonably conclude, given theproblems with the study?

1.6 Writing a Research Proposal

After reviewing the literature and putting considerable thought into planning a study, the next step is to prepare a research proposal. The goalof any research proposal is to present a detailed description about the research problem and the methods with which you think that theresearch should be conducted. Research proposals are extremely important because they are key to unlocking the research project (Leedy &Ormrod, 2010). They may determine whether you receive approval or funding, so they need to clearly articulate the purpose of the researchand persuade the audience it is worthwhile. If research proposals do not clearly and specifically define the research problem and methods, theproject might not be accepted. Therefore, it is imperative that the research proposal include "a clearly conceived goal and thorough, objectiveevaluation of all aspects of the research endeavor" (Leedy & Ormrod, 2010, p. 117).

Research proposals can range from three pages for some grant applications to more than 30 pages (e.g., for a dissertation or federal grant).They may or may not require an abstract and will have a different format for institutional review board (IRB) approval (see Section 1.7, Ethics inResearch). For our purposes, in general, research proposals follow a standard format. The following is an example you might use:

1. Title/Cover Page

2. Abstract

3. Introduction or Statement of the Problem

a. The research problem

b. The statement of the problem and possible subproblems

c. The purpose statement

d. Hypotheses and/or research questions

e. Independent and dependent variables

f. The assumptions

g. The importance of the study

4. Review of the Literature

5. Method

a. Research methodology

b. Participants and participant selection

c. Data collection procedures

d. Data analysis techniques

6. Discussion

a. Strengths and limitations

b. Ethical considerations

7. References

8. Appendixes

Research proposals are written like research articles in APA style, which is favored in academia. The language must be clear and precise, inparagraph format, and written in a professional, academic manner. Unlike stories or memoirs, proposals are not intended to be creative literaryworks; rather, they should set down certain facts. Organized with headings and subheadings, the proposal should clearly and specifically explainthe research problem, who the participants will be and how they will be selected, what data collection methods will be used, and how the datawill be analyzed and interpreted. Research proposals are required for all theses and dissertations. If you are currently working on a master'sthesis or doctoral dissertation, your university or committee chair may have a specific format for you to follow that may differ slightly from theformat presented in this book. An example of an APA formatted proposal is provided in the Appendix .

Formatting the Research Proposal

As mentioned previously, research proposals are written in APA style and follow an organized format. Although there are different ways toformat a proposal, most follow a similar format to the one that is discussed in this book. The following sections will discuss the specifics offormatting of your proposal as well as the content that should be included within each section.

Headings and Subheadings

Writing a proposal in APA style may seem complicated at first; however, the format is similar to a research paper or any academic paper that isrequired to be written in APA style. APA style uses a unique heading and subheading system that separates and classifies sections of researchpapers. The Publication Manual of the American Psychological Association Sixth Edition (2010) utilizes five heading levels; although all headinglevels may not be used, it is important to follow them in sequential order:

· Level 1: Centered, Boldface, Uppercase and Lowercase Heading

· Level 2: Left-aligned, Boldface, Uppercase and Lowercase Heading

· Level 3: Indented five spaces, boldface, lowercase heading with a period. For Level 3 headings, the body text begins after the period.

· Level 4: Indented five spaces, boldface, italicized, lowercase heading with a period. For Level 4 headings, the body text begins after theperiod.

· Level 5: Indented five spaces, italicized, lowercase heading with a period . For Level 5 headings, the body text begins after the period.

Section headings such as Review of the Literature, Methods, and so forth, are Level 1 headings. Subsection headings such as Participants, DataCollection, and so on, that follow under the section heading Methods, for example, are Level 2 headings. Subsections of subsection headings areLevel 3 through Level 5. The following is an example of the various heading levels you might use in your research proposal:

Introduction (Level 1)

The Research Problem (Level 2) Purpose of the Study (Level 2) Hypotheses and/or Research Questions (Level 2) Independent and Dependent Variables (Level 2) Assumptions (Level 2) Importance of the Study (Level 2)

Review of the Literature (Level 1)

The Cognitive Profile of Learning Disabilities in Reading (Level 2) The Cognitive Profile of Attention Deficit/Hyperactivity Disorder (Level 2)

Method (Level 1)

Research Methodology (Level 2) Participants (Level 2) Data Collection (Level 2) Instrumentation. (Level 3) WISC-IV. (Level 4) WISC-IV PI. (Level 4) Data Analysis (Level 2)

Discussion (Level 1)

Strengths and Limitations (Level 2) Ethical Considerations (Level 2)

References (Level 1)

Appendix (Level 1)

An important guideline to remember is that you should be consistent in your use of heading levels throughout the research proposal. Thus, allheadings with equal importance should follow the same heading level.

The Title Page

A title page is required for all research proposals as its first page. In general, title pages include a running head with the page number, as wellas the abbreviated title of the paper, the student's name, and the university or institution name. Although some universities may have specificrequirements regarding how the title page is formatted, the following is formatted according to APA style:

Running head: PREMORBID COGNITIVE ABILITIES

Estimation of Premorbid Cognitive Abilities in

Children with Traumatic Brain Injury

Graduate Student

Research University

The running head is a shortened version of the full title and is included in the top margin of the page. The running head is set flush left withthe abbreviated title in all capital letters. On the same line of the running head, the page number is set flush right. The title of the paper, thestudent's name, and the university affiliation are centered approximately in the middle of the page and formatted in uppercase and lowercaseletters. It is recommended that titles include no more than 12 words.

The Abstract Page

The abstract page is page two of your paper. An abstract is a summary of your proposal and should include the research problem, theparticipants, data collection methods, and any hypotheses or research questions. Abstracts for research proposals are generally between 150and 250 words in length.

The abstract should contain your running head title from the title page as well as the page number. As shown in the example, the first word ofthe abstract is not indented. Thus, the entire abstract is set flush left. Please keep in mind that the title "running head" is dropped after pageone and only the abbreviated title and page number are included, as shown below:

PREMORBID COGNITIVE ABILITIES

Abstract

The present study will review currently available methods for estimating premorbid intellectual abilities inchildren. It examines the potential of the Wechsler Intelligence Scale for Children–Fourth Edition (WISC–IV;Wechsler, 2003) as an estimate of premorbid IQ in children with traumatic brain injury (TBI). Archival data willbe obtained from a sample of 2,200 children aged 6:0–16:11 who participated in the standardization phase ofthe WISC–IV and 43 children aged 6:0–16:11 with a history of moderate or severe TBI who participated in aWISC–IV special group study. First, demographic variables including sex, ethnicity, parent education level, andgeographic region will be entered into a regression analysis to determine a demographic-based premorbidprediction equation for the WISC–IV Full Scale Intelligence Quotient (FSIQ). Second, a logistic regressionanalysis will be used to investigate which WISC–IV subtest–scaled scores improve the differential diagnosis ofTBI versus a matched control group. Third, analysis of variance (ANOVA) will be used to examine whichsubtests yielded the lowest mean scores for the TBI group. It is expected that parental education will be thestrongest predictor of premorbid IQ and that individuals with TBI will have lower scores on Processing Speedand Working Memory indices.

The Introduction Section

The Introduction section begins on page three of your proposal. The primary purpose of the Introduction section is to introduce the reader tothe nature of the study by including necessary background that describes and supports your research problem. The introduction generallyincludes a statement of the research problem, any potential subproblems, the purpose statement, hypotheses and/or research questions,identification of the variables, assumptions of the study, and importance of the study. The introduction typically begins with a statement of theresearch problem area and is followed by a justification for your proposed study. Only research needed to explain the purpose of or need foryour study should be included in this section.

As discussed previously, the purpose statement should include the focus, population, and methodology of the study. Depending upon whetheryour research is quantitative or qualitative, you will want to include your hypotheses and/or research questions next and discuss how yourhypotheses and/or research questions relate to your research problem and purpose statement. You should next review the key independent anddependent variables, followed by a discussion of the assumptions you will make about the research and how the research will be expected tocontribute to the field.

The length of the introduction can vary based on your university, committee chair, or instructor's requirements. In general, the introductionsection ranges anywhere from 3 to 5 pages to 15 to 25 pages. The more detailed information you include in your proposal, the closer you willbe to completing your thesis or dissertation.

The Literature Review Section

The primary purpose of the literature review is to provide theoretical perspectives and previous research findings on the research problem youhave selected (Leedy & Ormrod, 2010). As a researcher, you should investigate your topic extremely well so that you have a thoroughunderstanding about the research problem area. Thus, your literature review should contain both breadth and depth, and clarity and rigor, inorder to support the need for your research to be conducted. Any reader of your literature review should be able to comprehend theimportance of your research problem and the difference the research will make to the field. Keep in mind that a literature review is not simplya collection of summaries, abstracts, or annotated bibliographies but rather a thorough analysis and synthesized review of the research and howeach piece of research builds upon the other.

According to Levy and Ellis (2006), a literature review should go through the following steps: (a) methodologically analyze and synthesize qualityliterature, (b) provide a firm foundation to a research topic, (c) provide a firm foundation to the selection of research methodology, and (d)demonstrate that the proposed research contributes something new to the overall body of knowledge or advances the research field'sknowledge base (p. 182). Remember: Your literature review should provide a theoretical foundation and justification for your proposed study.

A good literature review does not simply report the literature but evaluates, organizes, and synthesizes it (Leedy & Ormrod, 2010). Whenreading and reviewing existing literature, it is important to critically evaluate what has already been done and what the findings showed. Do notjust take what the authors say at face value; instead, evaluate whether the findings support the methods that were used and the analyses thatwere conducted.

In addition to evaluating the literature, you must organize it. This means grouping the literature according to your subproblem areas, researchquestions, or variables being assessed. For example, if conducting a study on the demographic predictors of special education, you would wantto group your literature based on the various demographic variables and the influences that they may have on placement in special education.Finally and most importantly, you must synthesize the diverse perspectives and research results you've read into a cohesive whole (Leedy &Ormrod, 2010). Leedy and Ormrod (2010) discuss several approaches to synthesizing information, including the following:

· comparing and contrasting the literature

· showing how the literature has changed over time

· identifying trends or similarities in research findings

· identifying discrepancies or contradictions in research findings

· locating similar themes across the literature

The following example shows a paragraph synthesizing the literature. Note that the review does not include summaries of the articles but ratherdisplays similarities found in the research:

Several studies have examined the relationship between demographic variables and cognitive functioning.Research has shown that demographic variables such as socioeconomic status and education level are closelyrelated to scores on cognitive tests and contribute significantly to variance in IQ scores (Crawford, 1992;Kaufman, 1990). Utilizing this close relationship, Wilson et al. (1978) developed the first regression equation topredict premorbid IQ using the WAIS standardization sample. The equation included age, sex, race, education,and occupation and accounted for 53% of the variance in the Verbal IQ, 42% of the variance in thePerformance IQ, and 54% of the variance in the Full Scale IQ. Cross-validation studies have confirmed theWilson et al. equation to be a useful predictor of premorbid IQ. The equation has been used to predictoutcome from closed head injury (Williams, Gomes, Drudge, & Kessler, 1984), to estimate British WAIS scores(Crawford, Stewart et al., 1989), and to estimate premorbid functioning among healthy adults (Goldstein, Gary,and Levin, 1986). Although the use and application of Wilson's formula has tended to overpredict high scoresand underpredict low scores, the formula appears to provide adequate predictions for those within theaverage range of functioning.

An example of a compare-and-contrast synthesized review would look like the following:

As with all regression-based methods, a number of limitations are present in the use of demographic-basedprediction models. As Karzmark, Heaton, Grant, and Matthews (1985) found in their use of the Wilson et al.formula to predict WAIS IQ scores, demographic equations tend to overestimate and underestimate IQ scoresfor individuals who are one standard deviation or more from the population mean. Research has shown strongcorrelations between specific demographic variables and measured IQ scores, but Bolter, Gouvier, Veneklasen,and Long (1982) found the Wilson et al. equation to be limited in its ability to predict groups of head injuredindividuals and controls.

On the other hand, Wilson, Rosenbaum, and Brown (1979) compared the hold method of the DeteriorationIndex developed by Wechsler in 1958 against Wilson's 1978 demographic equation and found the Wilson et al.formula to have a 73% accuracy of classification, while the Wechsler method resulted in only 62% accuracy.Although the demographic-based method may have mixed results at an individual level, cross-validationstudies have shown them to do an adequate job of predicting mean IQ scores at the group level (Vanderploeg,1994).

Remember that writing a literature review takes time and organization. It is important that you thoroughly review the relevant literature youuncovered in your key term search. This can be a painstaking endeavor, but the search should not conclude until you are reasonably sure youhave researched all the critical viewpoints of your research problem. It is also helpful to develop an outline of topics you plan on addressing.

Finally, note that a good literature review is not plagiarized or copied and pasted from other sources, as the Internet makes so tempting. Whenreviewing literature, be sure you summarize the information in your own words and give credit where credit is due. It is sometimes helpful toread the literature and then develop summaries of the articles in your own words. You can then use these summaries to develop your literaturereview. Keep in mind that your literature review is a working draft that will be modified and perfected throughout the research process.

The Method Section

The method section includes a detailed description of the method of inquiry (quantitative, qualitative, or mixed design approach); researchmethodology used; the sample; data collection procedures; and data analysis techniques. The key purpose of the method section is to discussyour design and the specific steps and procedures you plan to follow in order to complete your study. A detailed description of methods isessential in any research proposal because it allows others to examine the efficacy of the study as well as replicate it in the future.

Research Methodology

This section discusses whether quantitative, qualitative, or a mixed design approach was used and the rationale for choosing this method ofinquiry. It also includes specific information on the selected research methodology. For example, will your study be utilizing experimentalmethods, quasi-experimental methods, or observational methods? And what is the purpose for selecting that method or methods? Rememberthat you should be making an argument and justifying the type of research methodology you plan to use, regardless of the type of inquiry.

Participants

The participant section describes the population of interest and the sample that will be used. In quantitative studies, the sample is intended torepresent the larger population and tends to be larger in size than for qualitative studies. In qualitative studies, the sample may be a smallnumber of participants or even only one participant and is not intended to represent the larger population. In both quantitative and qualitativestudies, this section should discuss the sample in detail: the population you want to learn about; where participants will be recruited or studied;how the participants will be notified about the study; how the participants will be selected (e.g., what type of sampling method will be used,such as random sampling, snowball sampling, etc.); what criteria will be required for inclusion in the study (e.g., age, level of educationobtained, marital status, employment position); and the overall proposed size of the sample. For quantitative studies, when discussing thesample, it is also important to include which demographic information (e.g., age, gender, ethnicity, level of education, socioeconomic status) youwill need to create a representative sample of the entire population. A representative sample ensures that the results can be generalized to theentire population as a whole.

Data Collection Procedures

The data collection section describes how the data will be collected, step by step. This section should detail how informed consent will beobtained from the participants, when the data will be collected and for how long, and what methods or measures will be used to collect thedata. Remember: Providing detailed information is crucial to ensure that others can follow your study and replicate it in the future. Thus, thissection should include a step-by-step description of each of the procedures you will follow to carry out the data collection. Describe the datacollection forms you will use, as well as any survey, research, or testing instruments you may use or develop to collect the data, and therationale for utilizing such procedures. Copies of any forms or instruments used should be included in the Appendix section of your researchproposal.

Data Analysis

The data analysis section includes a brief step-by-step description of how the data will be analyzed as well as what statistical methods or othermethods of analysis and software will be utilized. If you are doing quantitative method research, you will want to discuss how the data will beentered into a statistical software program, how the data will be kept confidential, and what statistical analyses will be run. If using qualitativemethods, you will want to discuss the type of qualitative method used, the interview type, interview questions, sample type (e.g., random,convenience), how the data will be reviewed (e.g., how interviews or observations will be reviewed or transcribed), and how the data will becoded.

The Discussion Section

As emphasized throughout this chapter, one of the most important characteristics of a research proposal is to make a strong case for or justifythe need to study your research problem. In doing so, you will want to discuss the strengths of your research study as well as any limitationsand ethical issues that will need to be considered. It should be noted that some universities require this information to be included in theMethod section. In those cases, you would include strengths, limitations, and ethical considerations after the Data Analysis heading in theMethod section.

Strengths and Limitations

This section is fairly straightforward. It should discuss the implications for future research, practice, and theory as well as any potentiallimitations that might impact the research process or results. Some limitations may include difficulty in obtaining participants, difficulty inobtaining a representative sample, or time and financial constraints.

Ethical Considerations

This section should include any potential issues that might be considered ethical dilemmas. For example, if studying minors, how will you obtainconsent and ensure confidentiality? If studying certain employees, how will you keep information from their supervisors? Or if your study maytrigger emotional trauma, such as memories about abuse, how will you reduce any stress or negative feelings that occur during the study?

The References Section

This section should include all references that were cited within your proposal in alphabetical order and using APA style. Only references usedwithin your proposal should be included on the References page; conversely, there should be no references listed on the References page thatwere not cited in your proposal.

It is important to list all references in correct APA format. The following examples show how to correctly cite journal articles, websites, andbooks according to the APA Publication Manual Sixth Edition:

Example of a journal article with the document ID number included:

Brownlie, D. (2007). Toward effective poster presentations: An annotated bibliography. European Journal of Marketing, 41, 1245–1283.doi:10.1108/03090560710821161

Example of a journal article with no document ID assigned to it:

Kenneth, I. A. (2000). A Buddhist response to the nature of human rights. Journal of Buddhist Ethics, 8. Retrieved fromhttp://www.cac.psu.edu/jbe/twocont.html

Example of a print (or hardcopy) journal article:

Harlow, H. F. (1983). Fundamentals for preparing psychology journal articles. Journal of Comparative and Physiological Psychology, 55, 893–896.

Example of a textbook:

Calfee, R. C., & Valencia, R. R. (1991). APA guide to preparing manuscripts for journal publication. Washington, DC: American PsychologicalAssociation.

Example of a chapter in a textbook:

O'Neil, J. M., & Egan, J. (1992). Men's and women's gender role journeys: A metaphor for healing, transition, and transformation. In B. R.Wainrib (Ed.), Gender issues across the life cycle (pp. 107–123). New York, NY: Springer.

Example of a website:

Keys, J. P. (1997). Research design in occupational education. Retrieved from http://www.okstate.edu

The Appendix Section

The Appendix section should include a copy of any forms that will be used during your research. These include consent forms, instructions forparticipants, and any additional tables or figures that might supplement study information but not provide additional data (e.g., a table ofsubtests included within an instrument you plan to use).