1
Psychology as a Science
VisitBritain/Jason Knott/Getty Images
Learning Outcomes
By the end of this chapter, you should be able to:
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Outline the major areas of research in the field of psychology.
Explain the process of testing research ideas through the scientific method.
Describe what it means to turn an idea into a testable hypothesis.
Identify the criteria for a good theory.
Search online databases for previous research studies.
Summarize the key ethical principles that apply to conducting research on human and non-human
animals.
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In an article in Wired magazine, journalist Amy Wallace (2009) described her visit to the
annual conference sponsored by Autism One, a nonprofit group 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 effort has yet to reveal the precise causes of autism, pseudoscience has stepped in to the void. In the hallways of the Westin O’Hare hotel, helpful salespeople strove to catch my eye . . .
pitching everything from vitamins and supplements to gluten-free cookies . . .
hyperbaric chambers, and neuro-feedback machines. (p. 134)
The “pseudoscience” to which Wallace refers is the claim that vaccines generally do more harm
than good and specifically that they cause children to develop autism. In fact, an extensive statistical review of epidemiological studies, including tens of thousands of vaccinated children,
found no evidence of a link between vaccines and autism (Madsen et al., 2002). The reality is
this: Research tells us that vaccines bear no relation to autism, but people still believe that
they do. Because of these beliefs, increasing numbers of parents are foregoing vaccinations,
and many communities are seeing a resurgence of rare diseases like measles and mumps.
So what does it mean to say that “research” has reached a conclusion? Why should we trust
this conclusion over parents’ personal experience with their own child? One of the biggest
challenges in starting a course on research methods is learning how to think like a scientist—
that is, to frame questions in testable ways and to make decisions by weighing the evidence.
The more personal these questions become, and the bigger their consequences, the harder
it is to put feelings aside. However, as we will see throughout this course, in these cases precisely, listening to the evidence becomes most important.
Understanding the importance of scientific thinking matters for several reasons, even if a
student never takes another psychology course. First, at a practical level, critical thinking is
an invaluable skill in a wide variety of careers. Employers of all types appreciate the ability to
reason through the decision-making process. Second, understanding the scientific approach
tends to make people more skeptical consumers of news reports. Someone who reads in
Newsweek that the planet is warming, or cooling, or staying the same will be able to decipher and evaluate how the author reached this conclusion and possibly reach a different one.
Third, understanding science makes a person a more informed participant in debates about
public policy. To know whether the planet is truly getting warmer requires 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 processes because we are intimately familiar with the processes we are trying to understand. The psychologist William C. Corning (1968) captured this
sentiment over 40 years ago: “In the study of brain functions, we rely upon a biased, poorly
understood, and frequently unpredictable organ in order to study the properties of another
such organ; we have to use a brain to study a brain” (p. 6). (Or, in the words of comedian Emo
Phillips, “I used to think that the brain was the most wonderful organ in my body. Then I realized who was telling me this” [Jarski, 2007].) The trick, then, is learning to take a step back
and apply scientific thinking to issues we encounter and experience every day.
This textbook provides an introduction to the research methods used in the study of psychology. It introduces the full spectrum of research designs, from observing behavior to carefully
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controlling conditions in a laboratory. The text will cover the key issues and important steps
for each type of design, as well as the analysis strategies most appropriate for each one. This
chapter begins with an overview of the different areas of psychological science. It then introduces the research process by discussing the key features of the scientific approach and the
process of forming testable research questions. The final section discusses the importance of
adhering 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 Andrew Wakefield and his colleagues studied the link between autism symptoms
and the measles, mumps, and rubella (MMR) vaccine in a sample of twelve children. Based
on a review of these cases, the authors reported that all twelve experienced adverse effects of
the vaccine, including both intestinal and behavioral problems. The finding that grabbed the
headlines was the authors’ report that nine of the twelve children showed an onset of autism
symptoms shortly after they received the MMR vaccine.
Immediately after the publication of this paper, the scientific community criticized the
study for its small sample and its lack of a comparison group (i.e., children in the general
population). Unfortunately, these issues turned out to be only the tip of the iceberg (Godlee,
Smith, & Marcovitch, 2011). British journalist Brian Deer (2004) conducted an in-depth
investigation of Wakefield’s study and discovered some startling information. First, the
study had been funded by a law firm that was in the process of suing the manufacturers of
the MMR vaccine, thereby threatening researchers’ objectivity. Second, Deer’s investigation
showed clear evidence of scientific misconduct: The data had been falsified and altered to fit
Wakefield’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 and misrepresentation.
Ultimately, The Lancet withdrew the article in 2010, effectively removing it from the scientific
record and declaring 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 rates remain below the recommended 95% level recommended
by the World Health Organization (Godlee et al., 2011). Even though the article was a fraud, it
made parents afraid to vaccinate their children.
Vaccinations work optimally when most members of a community receive the vaccines
because this minimizes the opportunity for an outbreak. When even a small portion of a
population refuses to vaccinate children, it places the entire community at risk of infection
(National Institute of Allergy and Infectious Diseases, n.d.). Thus, it should be no surprise
that many communities are seeing a resurgence of measles, mumps, and rubella: In 2008,
England and Wales declared measles to be a prevalent problem for the first time in 14 years
(Godlee et al., 2011).
This scenario highlights the importance of conducting science honestly. While disease
outbreaks are the most obvious impact of Wakefield’s fraud, they are not the only one. In a
2011 editorial in the British Medical Journal condemning Wakefield’s actions, British doctor
Fiona Godlee and colleagues captured this rather eloquently: “But perhaps as important as
the scare’s effect on infectious disease is the energy, emotion, and money that have been
diverted away from efforts to understand the real causes of autism and how to help children
and families who live with it.”
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Major Research Areas in Psychology
Section 1.1
1.1 Major Research Areas in Psychology
Psychology is a diverse discipline, encompassing a wide range of approaches to 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 to speculate on the causes of human behavior—philosophers have been doing this
for millennia—psychology is distinguished by its reliance on the scientific method to draw
conclusions. Later, the chapter will examine the meaning and implications of this scientific
perspective. This section discusses the major research areas within the field of psychology,
along with samples of the types of research questions asked by each one.
Biopsychology
Biopsychology, as the name implies, combines research questions and techniques from both
biology and psychology. It is typically defined as the study of connections between biological
systems (including the brain, hormones, and neurotransmitters) and thoughts, feelings, and
behaviors. As a result, the research conducted by biopsychologists often overlaps research in
other areas—but with a focus on biological processes. Biopsychologists are often interested
in the way interactions between biological systems and thoughts, feelings, and behaviors
affect the ability to treat disease, as the following questions reflect: What brain systems are
involved in the formation of memories? Can Alzheimer’s be cured or prevented through early
intervention? How does long-term exposure to toxins such as lead influence our thoughts,
feelings, and behaviors? How easily can the brain recover after a stroke?
In one example of this approach, Kim and colleagues (2010) investigated changes in brain
anatomy among new mothers for the first three months following delivery. These authors
were intrigued by the numerous changes new mothers undergo in attention, memory, and
motivation; they speculated that these changes might be associated with changes in brain
structure. As expected, new mothers showed increases in grey matter (i.e., increased complexity) in several brain areas associated with maternal motivation and behavior. In addition,
the more these brain areas developed, the more positively these women felt toward their
newborn children. Thus, Kim et al.’s study sheds light on the potential biological processes
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 internal mental processes, including the ways
that people think, learn, remember, speak, perceive, and so on. Cognitive psychologists are
primarily interested in the ways that people navigate and make sense of the world. Research
questions in this field might ask: How do our minds translate input from the five senses into
a meaningful picture of the world? How do we form memories of emotional versus mundane
experiences? What draws 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, and Kingstone (2010)
were interested in what kinds of things people pay attention to in a complex social scene.
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Major Research Areas in Psychology
Section 1.1
The world around us is chock-full of information, but we can only pay attention to a relatively thin slice of it. Foulsham and colleagues were particularly interested in where our
attention is directed when we observe groups of people. They answered this question by
asking people to watch videos of a group discussion and using tools to track eye movements. It turned out that people in this study spent most of their time looking at the most
dominant member of the group, suggesting that individuals are wired to pay attention to
those in positions of power. Thus, this study sheds light on one of the ways that people make
sense 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 this field initially focused on childhood development, many researchers now study changes and key stages over a person’s
entire life span. Developmental psychologists look at a wide range of phenomena related to
physical, social, and cognitive change, including: How do children bond with their primary
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 ages do 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? The authors addressed this question by combining results from several studies into one
data set. Across 50 studies, the answer to this question was yes—children do better in school
if their parents are involved. Hill and Tyson’s study sheds light on a key predictor of academic
achievement during an important developmental period.
Social Psychology
Social psychology, which attempts to study behavior in a broader social context, is typically defined
as the study of the ways humans’ thoughts, feelings, and behaviors are shaped by other people.
This broad perspective allows social psychologists
to tackle a wide range of research questions, such
as: What kinds of things do individuals look for in
selecting romantic partners? Why do people stay in
bad relationships? How do other people shape individuals’ sense of who they are? When and why do
people help in emergencies?
Norman Triplett (1898) conducted the first published social psychology study at the end of the
19th century. Triplett had noticed that professional
cyclists tended to ride faster when racing against
other cyclists than when competing in solo time
trials. He tested this observation in a controlled
Thomas Northcut/Photodisc/Thinkstock
Social psychologist Norman Triplett’s
study of competition among cyclists led
to conclusions about how people influence one another.
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Major Research Areas in Psychology
Section 1.1
laboratory setting, asking people to do a number of tasks either alone or next to another
person. His results (and countless other studies since) revealed that people worked faster
in groups, suggesting that other people can have definite and concrete influences on human
behavior.
Clinical Psychology
The area of clinical psychology focuses on understanding the best ways to treat 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 assessment and the treatment of psychological disorders, as the following research questions suggest: What is the most effective treatment for depression? How can we help people overcome post-traumatic stress disorder following a traumatic event? Should anxiety disorders
be treated with drugs, therapy, or a combination? What is the most reliable way to diagnose
schizophrenia?
A study by Kleim and Ehlers (2008) offers an example of this approach. The study attempted
to understand the risk factors for post-traumatic stress disorder, a prolonged reaction to a
severe traumatic experience. Kleim and Ehlers found that assault victims who tend to form
less specific memories about life in general might be more likely to develop a disorder in
response to trauma than victims who tend to form detailed memories. People who tend to
form vague memories may have fewer resources to draw on in trying to reconnect with their
daily life after a traumatic event. This study, then, sheds light on a possible pathway contributing to the development of a psychological disorder.
Applied Research Areas
The research areas listed thus far represent the majority of basic research within psychology, but the list is not exhaustive. A great deal of additional psychological research focuses
on understanding human behavior in a more applied context. For example, the field of health
psychology applies psychological principles to the study of health, wellness, and illness.
Health psychologists often have a background in either clinical or social psychology and use
these insights toward a broader understanding of why people get sick. One major insight
from this field is that the quality and quantity of our relationships with other people can actually have a dramatic impact on our physical health. Close relationships can provide practical
support in times of need (e.g., making it easier to get to the doctor), as well as making stressful events seem less stressful (for review, see Newman & Roberts, 2012).
Similarly, the field of industrial–organizational psychology (often abbreviated as I/O psychology) applies psychological principles to the scientific study of human behavior in the
workplace. I/O psychologists often have a background in social or cognitive psychology and
generally help organizations function more effectively by improving employee satisfaction,
performance, and safety of employees. One major insight from this field shows that people are often more productive in the workplace if given more freedom over their time. This
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The Research Process
Section 1.2
model started in the high-tech industry. For example, Google employees have game rooms
around the office; the company requires workers to spend time each week developing “side”
projects unrelated to their main responsibilities. This approach makes employees feel more
valued as individuals, more dedicated to the company, and thus more industrious in completing their work.
As a final example, the field of school psychology applies psychological principles to the
goal of helping children learn effectively. School psychologists, who are typically trained in
developmental, clinical, and educational psychology, work to meet the learning and behavioral health needs of students. More so than the previous examples, school psychologists play
a “practitioner” role, applying their broad knowledge base to provide psychological diagnosis, conduct health promotions, evaluate services, and conduct interventions with individual
students as needed.
To learn more about all of these areas, see the American Psychological Association’s collection of web resources: http://www.apa.org/about/division/index.aspx.
1.2 The Research Process
With a broad understanding of the major research areas in psychology, we now turn our
attention to the research process. How do psychologists conduct research? What are their
goals? This section will answer these questions. This section will also compare quantitative
and qualitative research, two different approaches to scientific inquiry.
The Scientific Method
What does it mean to draw conclusions based on science? Scientists across all quantitative
disciplines use the same process of forming and testing their ideas. The overall goal of this
research process—also known as the scientific method—is to draw conclusions based on
empirical observations. In this section, we cover the four steps of the research process—
hypothesize, operationalize, measure, and explain, abbreviated with the acronym HOME.
Step 1—Hypothesize
The first step in the research process turns an initial research question into a testable prediction, or hypothesis. A hypothesis is a specific statement about the relationship between two
or more variables. For example, if we start with a question about the link between smoking
and cancer, our hypothesis might be that smoking causes lung cancer. Or, if we want to know
whether a new drug will be helpful in treating depression, we might hypothesize that drug X
will lead to a reduction in depression symptoms. The next section of this chapter will cover
hypotheses in more detail, but for now it is important to understand that the way a hypothesis is framed guides every other step of the research process.
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The Research Process
Section 1.2
Step 2—Operationalize
Once a researcher develops a hypothesis, the next step is to decide how to test it. The process
of operationalization involves choosing measurable variables to represent the elements
of the hypothesis. In the depression-drug example, we need to decide how to measure both
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 of the drug should we investigate? How many different doses should we compare? And, how will we measure depression symptoms? Will it
work to have people complete a questionnaire? Or do we need to have a clinician interview
participants before and after they take the drug?
An additional complication for psychology studies is that many of research questions deal
with abstract concepts. Turning these concepts into measurable variables requires some
art. For example, the abstract concept of happiness could be defined in countless different
ways—being “happy” likely means something different to one individual than it does to his
neighbors. To include happiness in a research study, we need to translate it into a more concrete concept, measured by a person’s score on a happiness scale or by the number of times a
person smiles in a five-minute period, or perhaps even by a person’s subjective experience of
happiness during an interview. Chapter 2 (2.2) will cover this process in more detail, with a
discussion of guidelines for making these important decisions 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. The text will cover this process in great detail, dedicating
Chapters 3 through 5 to the three primary approaches to data collection. Collection of data
is a critical step in the research process, as researchers gather empirical observations that
will help address their hypothesis. As Chapter 2 will explain, these observations can range
from questionnaire responses to measures of brain activity, and they can be collected in a
variety of ways, from online questionnaires to carefully controlled experiments. Regardless
of the details of data collection, investigators will ultimately use these observations to make
a decision.
Step 4—Explain
After data have been collected, the final step is to analyze and interpret the results. The goal
of this step is to return full circle to the initial research question and determine whether
the results support the hypothesis. Recall the hypothesis that drug X should reduce depression symptoms. If we find at the end of the study that people who took drug X showed a
70% decrease in symptoms, this result would be consistent with the hypothesis. However,
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 turns out, a fairly easy way of fixing
this problem exists; Chapter 5 will cover that solution.
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The Research Process
Section 1.2
As Table 1.1 summarizes, the research process involves four stages: forming a hypothesis,
deciding how to test it, collecting data, and interpreting the results. This process is used to
draw conclusions across all scientific disciplines, regardless of whether research questions
involve depression drugs, reading speed, or the speed of light in a vacuum.
Table 1.1 The HOME method
Stage of Process
Main Idea
Example
Hypothesize
Take a research question, turn it into a
testable prediction
Operationalize
Turn the key concepts from your
hypothesis into measurable variables
Question: Will my new drug help
depression patients?
Hypothesis: Drug X will reduce depression symptoms.
Measure
Explain
Choose and implement the best
research design for your hypothesis
Interpret your findings and make
a decision about the state of your
hypothesis
Depression can be measured using
clinician interviews
Compare two groups of people over
time, half of whom have been given the
new drug
If the people who take the new drug are
less depressed at the end, that supports
our hypothesis
Research: Applying Concepts
Examples of the Research Process
To make the steps of the scientific method a bit more concrete, the following two examples
show 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 (NIMH, 2007). Depression is associated with a range
of emotional and physical symptoms, including feelings of hopelessness and guilt, loss of
appetite, sleep disturbance, and suicidal thoughts. This list has recently been expanded even
further to include an increased risk of heart disease. Individuals who are otherwise healthy
but suffering from depression are more likely to develop and to die from cardiovascular
disease than those without depression. According to one study, patients who experience
depression following a heart attack experience a fourfold increase in five-year mortality rates
(research reviewed in Glassman et al., 2011).
Research Question
Based on these findings, we could ask the question, “Would it make sense to treat heart
attack patients with antidepressant drugs?”
Recall that the goal of the scientific method is to take this research question, turn it into a
testable hypothesis, and conduct a study that will test it. The following steps use the HOME
method discussed earlier.
(continued)
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The Research Process
Section 1.2
Research: Applying Concepts (continued)
Step 1: Form a testable hypothesis from the research question.
We might predict that, “People who have had heart attacks and take prescribed
antidepressants are more likely to survive in the years following the heart attack than
those who do not take antidepressants.” We have taken a general idea about the benefits
of a drug and stated it in a way that a research study can directly test.
Step 2: Decide how to operationalize the concepts in the study into measurable
variables.
First, we would need to decide who qualifies as a “heart attack patient”: Would we include
only those who had been hospitalized with severe heart attacks, or anyone with abnormal
cardiac symptoms? These types of decisions will have implications for how we interpret the
results.
We would also need to decide on the doses of antidepressant drugs to use and the time
period to measure survival rates. How long would we need to follow patients to obtain an
accurate sense of mortality rates? In this case, earlier research had focused on five-year
mortality rates, so that would be a reasonable time period for this study as well.
Step 3: Measure the key concepts based on the decisions made in Step 2.
This step involves collecting data from participants and then conducting statistical analyses
to test the hypothesis. We will cover the specifics of research designs beginning in Chapter 2
(2.1), but one good option would be to give antidepressant drugs to half of our sample and
compare their survival rates with the half not given these drugs.
Step 4: Explain the results and tie the statistical analyses back into the hypothesis.
We would want to know whether antidepressant drugs did, indeed, benefit heart-attack
patients and increase their odds of survival for five years. If so, our hypothesis is supported.
If not, we would go back to the drawing board and try to determine whether a) something
went wrong with the study, or b) antidepressant drugs actually do not have any benefits for
this population. Answering these kinds of questions often involves conducting additional
studies. Either way, the goal of this final step is to return to our research question and discuss
the implications of antidepressant drug treatment 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, authorities discovered she had drowned her children in a
lake and fabricated the kidnapping story to cover her actions. Before Smith was a suspect in
the children’s deaths, she had told reporters, “My children wanted me. They needed me. And
now I can’t help them” (The Washington Post, November 5, 1994, A15). 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 agents that she already viewed them as dead (Adams, 1996).
(continued)
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The Research Process
Section 1.2
Research: Applying Concepts (continued)
Research Question
The story about Susan Smith highlights one way that people communicate differently when
they are lying—they use past tense when present tense is more natural. This observation
might lead us to ask, more broadly, “How do people communicate differently when they are
lying versus when they are telling the truth?” We will again apply the HOME paradigm (or
scientific method) to design a study that will ideally provide insight into this question.
Step 1: Form a testable hypothesis from the research question.
This example is somewhat more challenging because “communicating” can be defined in
many ways. Thus, we need a hypothesis that will narrow the focus of our study. It turns out
several studies have been conducted on the ways that people communicate when they are
lying, ranging from variations in speech rate to differences in the use of certain types of
words (for a review, see Depaulo et al., 2003). Based on one of these studies, we could offer
the following specific prediction: “Liars communicate using more negative emotion (e.g.,
anger, fear) than truth-tellers do” (e.g., Newman, Pennebaker, Berry, & Richards, 2003). We
have taken a general idea (“communicate differently”) and stated it in a way that can be
directly tested in a research study (“use more negative emotion”).
Step 2: Decide how to operationalize the concepts in our study into measurable
variables.
To determine measurable variables, we need to decide what counts as “using more negative
emotion.” We could take the approach used in a previous study (Newman et al., 2003) and
scan the words people use, looking for those reflecting emotions such as anger, anxiety, and
fear. The theory behind this approach posits that the words people use reflect something
about their underlying thought processes. In this case, people who are trying to lie will be
more anxious and fearful as a result of the lie, and therefore use more words indicative of
these negative emotions.
Step 3: Measure the key concepts based on the decisions made in Step 2.
To measure the variables identified in Step 2, we must devise a way to determine whether
and when people are lying. One way to do this in a research study is to instruct some people
to lie and others to be truthful and then compare differences in the amount of negative
emotion language between these groups.
Step 4: Explain the results and tie the statistical analyses back into the hypothesis.
We want to know whether people who were instructed to lie indeed used more words
suggestive of negative emotion. If so, this outcome supports our hypothesis. If not, we
would go back to the drawing board and try to determine whether a) the study design was
flawed, or b) people in fact do not use more negative emotion when they lie. Either way, the
goal of this final step is to return to our research question and discuss the implications for
understanding language-based indicators of deception.
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The Research Process
Section 1.2
Goals of Science
In addition to sharing an overall approach to answering questions, all forms of scientific
inquiry tend to adopt one of four overall goals. This section provides an overview of these
goals, with a focus on how they apply to psychological research. We will encounter the first
three goals throughout the course and use them to organize our discussion of different
research methods.
Description
One of the most basic research goals is to describe
a phenomenon, including descriptions of behavior,
attitudes, and emotions. Most people are probably
very familiar with this type of research because
it tends to crop up in everything from the nightly
news to their favorite magazine. For example, if
CNN reports that 60% of Americans approve of the
president, it is describing a trend in public opinion.
Descriptive research should always be the starting
point when studying a new phenomenon. That is,
before we start trying to explain why college students
binge drink, we need to know how common the phenomenon is. We might, therefore, start with a simple
survey that asks college students about their drinking behavior, and we might find that 29% of them
show signs of dangerous binge drinking. Having
described the phenomenon, we are in a better position to conduct more sophisticated research. (See
Chapter 3 for more detail on descriptive research.)
Stockbyte/Thinkstock
Before a phenomenon can be explained
it must first be described. For example,
a survey might be used to collect information to describe the phenomenon of
binge drinking.
Prediction
A second goal of research is predicting a phenomenon. This goal takes us from describing
the occurrence of binge drinking among college students to attempting to understand when
and why they do it. Do students give in to peer pressure? Is drinking a way to deal with the
stress of school? We could address these questions by using a more detailed survey that asked
people to elaborate on the reasons that they drink. The goal of this approach is to understand
the factors that make something more likely to occur. (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 moves from predicting relationships to drawing stronger conclusions about causal
links. Whereas predictive research attempts to find associations between two phenomena (e.g., college student drinking is more likely when students are stressed), 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
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The Research Process
Section 1.2
an important one, and closely related to the way that psychologists design their 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 socialscience fields: When we are dealing with questions about behaviors, attitudes, and emotions, we can sometimes conduct research to try to change the phenomenon of interest.
Researchers who attempt to change behaviors, attitudes, or emotions are essentially applying research findings towards 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. Research conducted at the time was
discovering that prejudice is often triggered by feelings of competition; in the classroom, students competed for the teacher’s attention. Aronson and his colleagues decided to change the
classroom structure in a way that required students to cooperate in order to finish an assignment. Essentially, students worked in small groups, and each person mastered a piece of the
material. Aronson found that using this technique, known as the “jigsaw classroom,” both
enhanced learning and decreased prejudice among the students (Aronson, 1978). Read the
details of Aronson’s study here: http://www.jigsaw.org/.
Aronson’s research also illustrates the distinction between two categories of research. The
first three goals we have discussed fall mainly under the category of basic research, in which
the primary goal is to acquire knowledge, with less focus on how to apply the knowledge. Scientists conducting basic research might spend their time trying to describe and understand
the causes of binge drinking but stop short of designing interventions to stop binge drinking.
Researchers more often involve for this fourth goal of research in applied research, in which
the primary goal is to solve a problem, with less focus on why the solution works. Scientists
conducting applied research might spend their time trying to stop binge drinking without
becoming caught up in the details of why these interventions are effective. Aronson’s research
serves as a great example of how these two categories can work together. The basic research
on sources of prejudice informed his applied research on ways to reduce prejudice, which in
turn informed further basic research on why this technique is so effective.
One final note on changing behavior: Any time researchers set out with the goal of changing
what people do, their values enter the picture. Inherent in Aronson’s research was the assumption that prejudice was a bad thing that needed to be changed. Although few people would
disagree with him, he risked the difficulty of remaining objective throughout the research
project. As we suggested earlier, the more emotionally involved we are in the research question, the more we have to be aware of the potential for bias, and the more closely we must pay
attention to the data.
Approaches to Science: Quantitative versus Qualitative Research
Imagine for a moment that a psychologist wants to study depression across the life span.
The researcher might approach this research question in one of two ways. She could design
a survey that asked people to report their experiences with depression, as well as how often
they had experienced various positive and negative life events. By conducting statistical
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The Research Process
Section 1.2
analyses of these reports, she could gain a broad understanding of the relationships between
life events and the development of depression. Alternatively, the investigator could spend her
resources interviewing people who had been diagnosed with depression. Her goal is trying
to understand what the experience felt like and whether people believed that it started in
response to some major life event. This approach would provide a very deep understanding
of the experience of depression from the inside out.
These alternative approaches highlight the differences between quantitative research
and qualitative research, respectively. Quantitative research is a systematic and empirical approach that attempts to generalize results to other contexts. By surveying the population using structured scales, our hypothetical psychologist could learn about depression
and life events in general. Qualitative research, in contrast, is a more descriptive approach
that attempts to gain a deep understanding of particular cases and contexts. By interviewing
depressed people in detail, the hypothetical psychologist could learn a great deal about how
individuals experience depression.
The two approaches have traditionally been popular with different social science fields. For
example, much of the current research in psychology is quantitative because the research
aims for generalizable knowledge about behavior and mental processes. In contrast, much
of the current research in sociology and political studies tends to be qualitative because
research aims for a rich understanding of a particular context. To understand why college
students around the country suffer from increased depression, quantitative methods are the
better choice. To understand why the citizens of Egypt revolted against their government,
then qualitative methods are more appropriate. However, many psychological phenomena
are best understood by starting from the ground up, with a rich, qualitative understanding of
people’s experiences. As later chapters will discuss, the qualitative approach has been used
to gain insight into questions ranging from forming stigmatized identities to helping children
cope with traumatic events.
In an ideal world, a true understanding of any phenomenon requires the use of both methods.
That is, researchers can best understand depression if they both study statistical trends and
conduct in-depth interviews with depressed people. Researchers can best understand binge
drinking by conducting both surveys and focus groups. And investigators can best understand the experience of being bullied in school by both talking to the victims and collecting
school-wide statistics. This text will discuss the ways that both approaches are used to shed
light on pressing questions throughout the field of psychology. Table 1.2 compares the quantitative and qualitative approaches.
Table 1.2 Comparing quantitative and qualitative approaches
Main
Approach
Use of
Hypotheses
Examples
of Research
Quantitative
Qualitative
Systematic, empirical, tries to generalize to
other contexts
Descriptive, tries to gain rich understanding of a single context or example
• Study depression by surveying the
population
• Study bullying by comparing reported
incidents between schools
• Study depression by interviewing
patients
• Study bullying by interviewing bullies to
understand their motivation
Starting point for all quantitative research
Not necessary; hypotheses sometimes the
result of qualitative study
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Hypotheses and Theories
Section 1.3
1.3 Hypotheses and Theories
The use of hypotheses is one of the key distinguishing features of quantitative research.
Rather than making things up as they go along, scientists develop a hypothesis ahead of time
and design a study to test this hypothesis. (Qualitative research, in contrast, often starts by
gathering information and ends with a hypothesis for future inquiries.) This section covers
the process of turning rough ideas about the world into testable hypotheses. We discuss the
primary sources of hypotheses as well as several criteria for evaluating hypotheses. Watch
the following video for an entertaining introduction to hypotheses and theories, which the
chapter will then explore in detail: https://www.youtube.com/watch?v=lqk3TKuGNBA.
Sources of Research Ideas
Every study starts with an idea that researchers frame as a question. But where do all of these
great ideas come from in the first place? Students are often nervous about starting a career
in research for fear that they might not be able to come up with great ideas to test. In reality,
though, ideas are easy to come by, a person knows where to look. The following material suggests some handy sources for developing research ideas.
Real-World Problems
A great deal of research in psychology and other
social sciences is motivated by a desire to understand—or even solve—a problem in the world. This
process involves asking a big question about some
phenomenon and then trying to think of answers
based on psychological mechanisms.
In 1961, Adolf Eichmann was on trial in Jerusalem for his role in orchestrating the Holocaust.
Eichmann’s repeated statements that he was only
“following orders” caught the attention of Stanley
Milgram, a young social psychologist who had just
earned a Ph.D. from Harvard University and who
began to wonder about the limits of this phenomenon. To understand the power of obedience, Milgram designed a well-known series of experiments
that asked participants to help with a study of “punishment and learning.” The protocol required them
to deliver shocks to another participant—actually
an accomplice of the experimenter—every time he
got an answer wrong. Milgram discovered that twothirds of participants would obey the experimenter’s commands to deliver dangerous levels of shocks,
even after the victim of these shocks appeared to lose
consciousness. These results revealed that all people have a frightening tendency to obey authority.
Getty Images/Handout
Nazi Lieutenant Colonel Adolf Eichmann’s claims during his trial that he
was just “following orders” throughout the Holocaust inspired Stanley
Milgram to conduct a groundbreaking
study about obedience to authority.
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Hypotheses and Theories
Section 1.3
We will return to this experiment in our discussion of ethics later in the chapter. Read more
about Milgram and his landmark study on this website: http://www.experiment-resources
.com/stanley-milgram-experiment.html.
Reconciliation and Synthesis
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 about the development of self-esteem, members
of racial and ethnic minority groups would have been expected to have lower-than-average
self-esteem because of the prejudice they faced. However, study after study demonstrated
that, in particular, African-American college students had equivalent or higher self-esteem
than European-American students. Crocker and Major (1989) offered a new theory to resolve
this conflict, suggesting that the existence of prejudice actually grants access to a number of
“self-protective strategies.” For example, minority group members can 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,
which many people credit with launching an entire research area on the targets of prejudice.
Learning From Failure
Kevin Dunbar, a professor at Dartmouth University, has spent much of his career studying the
research process. That is, he interviews scientists and sits in on lab meetings in order to document how people actually do research in the trenches. In a 2010 interview with Jonah Lehrer,
Dunbar reported the shocking statistic that approximately 50 to 75% of research results are
unexpected. Even though scientists plan their experiments carefully and use established techniques, the data are surprising more often than not. But even more surprising was the tendency of most researchers to discard the data if it did not fit their hypothesis. “These weren’t
sloppy people,” Dunbar commented. “They were working in some of the finest labs in the
world. But experiments rarely tell us what we think 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
study seem like a failure (Lehrer, 2009).
According to Dunbar, the secret to turning failure into opportunity is twofold: First, question assumptions about why the study feels like a failure in the first place. Perhaps the data
contradict the hypothesis but can be explained by a new one, or perhaps the data suggest
a dramatic shift in perspective. Second, seek new and diverse perspectives to help in interpreting the results. Perhaps a cognitive psychologist can shed light on reactions to prejudice.
Alternatively, perhaps an anthropologist knows what to make of the surprising results of a
study on aggression. Some of the best and most fruitful research ideas have sprung from
combining perspectives from different disciplines. Sometimes, all that a strange dataset
needs is a fresh set of eyes.
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Hypotheses and Theories
Section 1.3
Research: Thinking Critically
The Psychology Behind Pricing
Throughout this textbook, we will use short articles about research results as a way to
illustrate key points in the text. Follow the link below to an article by William Poundstone,
a bestselling author and expert on the psychology of pricing decisions. In this article,
Poundstone discusses the peculiar appeal of prices ending in the number “9” and reviews
recent research on this appeal by a pair of consumer psychology researchers. As you read the
article, consider what you have learned so far about the research process, and then respond
to the questions below.
https://www.psychologytoday.com/blog/priceless/201001/does-9-just-sound-cheap
Think About It:
1.
2.
3.
4.
5.
What hypothesis are Coulter and Coulter trying to test? Try to state this as succinctly
as possible.
How was “perception of discounts” operationalized in their studies?
How were the key variables measured?
How do Coulter and Coulter explain their findings? Are there other possible
alternative explanations?
Are these studies primarily aimed at description, explanation, prediction, or change?
Explain.
From Ideas to Hypotheses
Once a researcher develops a research question, the next step is to translate that question
into a testable hypothesis—the first step in the HOME method. Broadly speaking, hypotheses are developed in one of two ways: bottom-up and top-down. This section explores these
options in more detail.
Bottom-Up—From Observation to Hypothesis
Research hypotheses are often based on observations about the world around us. For example, people may have noticed the following tendencies as they observe those around them:
•
•
•
•
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 and stand at the same time.
Based on this set of four observations, we could develop a general hypothesis about human
behavior: People have a tendency to go along with the crowd and conform to group behaviors.
This process of developing a general statement from a set of specific observations is called
induction, and it is perhaps best understood as a “bottom-up” approach. In this case, we have
developed our hypothesis about conformity from the ground up, based on observing behavioral tendencies.
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Hypotheses and Theories
Section 1.3
The process of induction is a very common and useful way to generate hypotheses. Most notably, this process serves as a great source of ideas that are based in real-world phenomena.
Induction also helps us to think about the limits of an observed phenomenon. For example,
we might observe the same set of conforming behaviors and speculate whether people will
also conform in dangerous situations. What if smoke started pouring into a room and no one
else reacted? Would people act on their survival instinct or conform to the group and stay put?
Social psychologists Bibb Latané and John Darley (1969) conducted just such an experiment
with groups of college undergraduates. Participants were asked to sit in a classroom and complete a survey. Meanwhile, the experimenters piped in smoke (actually dry ice) through the
air vents. They hypothesized—and found—that the pressure to conform was stronger than
the instinct to flee from a potential fire.
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, which refers to a collection of ideas used to explain
the connections among variables and phenomena. For example, the theory of evolution organizes knowledge about how species have developed and changed over time. One piece of this
theory claims that human life originated in Africa and then spread to other parts of the planet.
This idea in and of itself, however, is too big to test in a single study. Instead, researchers move
from the “top down” and develop a specific hypothesis from a more general theory, a process
known as deduction.
By developing hypotheses using a process of deduction, researchers’ biggest advantage is the
ease of placing the study—and its results—in the larger context of related research. Because
the hypotheses represent a specific test of a general theory, results can be combined with
other research that tested the theory in different ways. For example, in the evolution example,
a researcher might hypothesize that the fossils from human ancestors found in Africa would
be older than those found in other parts of the world. If this hypothesis were supported, it
would be consistent with the overall theory about human life originating in Africa. And as
more and more researchers develop and test their own hypotheses about the origins of life,
our cumulative knowledge about evolution continues to grow.
Table 1.3 presents a comparison of these two sources of research hypotheses, showcasing
their relative advantages and disadvantages.
Table 1.3 Comparing sources of hypotheses
Deduction
Induction
“Top-down,” from theory to hypothesis
“Bottom-up,” from observation to hypothesis
Helps science build and grow
Helps understanding of the real world
Easy to interpret findings
Might miss out on new perspectives
Can be hard to interpret without prior research
Great way to discover new ideas
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Hypotheses and Theories
Section 1.3
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 its theories. If we think of hypotheses as individual combat missions on the battlefield, then theories are the overall battle plan. So, how do
researchers know whether their theories are any good? Next, 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 be consistent with existing
knowledge. If a physicist theorized that everything on earth should float off into space, that
theory would conflict with millennia’s worth of evidence showing that gravity exists. Similarly, if a psychologist argued that people learn better through punishment than through
rewards, that theory would conflict with several decades of research on learning and reinforcement. A new theory should offer a new perspective and a new way of thinking about
familiar concepts, but it cannot be so creative that it clashes with what scientists already
know. On a related note, a theory also has to lead to accurate predictions 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 researchers test their assumptions in new circumstances. At the end of the day, the best theory is the one that best explains
both past and future data.
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 a standard of
falsifiability, meaning that the right
set of conditions could prove it wrong
(Popper, 1959). Calling something
“falsifiable” does not mean it is false,
only that if it were false, demonstrating its falsehood would be possible.
The Darwinian theory of evolution
offers an example of this criterion.
oodelay/iStockphoto/Thinkstock
One of the primary components of The theory of evolution is falsifiable, meaning that it
evolutionary theory is the idea that could be disproved under the right conditions, such
species change and evolve from com- as the discovery of fossil evidence contradicting the
mon ancestors over time in response theory.
to changing conditions. So far, all evidence from the fossil record has supported this theory—older variants of species always
appear farther down in a fossil layer. If conflicting evidence ever were to appear, however,
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
buried in a much older fossil layer (Ridley, 2004).
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Hypotheses and Theories
Section 1.3
Research: Thinking Critically
Intelligence, Politics, and Religion
Follow the link below to an article by Daniela Perdomo, a staff writer and editor for Alternet.
In this article, Perdomo reviews the controversy over a recent scientific study claiming that
liberals and atheists are more intelligent. As you read the article, consider what you have
learned so far about the research process, and then respond to the questions below.
http://www.alternet.org/story/145903/controversy_grows_over_study_claiming_liberals
_and_atheists_are_smarter
Think About It:
1.
2.
3.
4.
What general theory is Kanazawa trying to test? How does the theory differ from his
specific hypothesis?
How did Kanazawa operationalize liberalism and intelligence in his research? Are
there problems with the way these constructs were operationalized? Explain.
What were Kanazawa’s main findings? How is the strength of this evidence
influenced by his research methods?
Why do you think this research is controversial? If Kanazawa’s methodology were
more rigorous, would it still be controversial?
Parsimonious
Third, a theory should strive to be parsimonious, or as simple and concise as possible without sacrificing completeness. (Or, as Einstein [1934] famously quipped during a lecture at
Oxford: “Everything should be made as simple as possible, but no simpler” [p. 165].) One
helpful way to think about this criterion is in terms of efficiency. Theories need to spell out the
components in a way that represents everything important but does not add so much detail
that they become hard to understand. This means that theories can lack parsimony either
because they are too complicated or because they are too simple.
At one end of this spectrum, Figure 1.1 presents a theoretical model of the causes of malnutrition (Cheah et al., n.d.). This theory does a superb job of summarizing all of the predictors of
child malnutrition across multiple levels of analysis. The theory’s potential problem, though,
is that it becomes too complicated to test.
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Hypotheses and Theories
Section 1.3
Figure 1.1: Predictors of malnutrition
Figure 1.1 presents a theoretical model of the causes of malnutrition.
Biological aspect
Environmental aspect
Behavioral aspect
Siblings shared
Sanitation
Weaning
Gender
Location
Diet
Age
Infrastructure
Feeding practice
Birth weight
Health services
Shared preference for food
Socio & economy factors
Childcare practice
Health practice
Maternal factors
Birth interval
Malnutrition indicator
Arm circumference
Weight for age
Breastfeeding
Key
Height for age
}
Unobserved/latent, exogenous
variables
Observed, exogenous variables
Observed, endogenous variables
Unobserved/latent, endogenous
variables
At the other end of the spectrum, Figure 1.2 shows the overall theoretical perspective behind
behaviorism. In the early part of the 20th century, the behaviorist school of psychology argued
that everything organisms do could be represented in behavioral terms, without any need to
invoke the concept of a “mind.” The overarching theory looked something like Figure 1.2, with
the “black box” in the middle representing mental processes. Nevertheless, the cognitive revolution of the 1960s eventually displaced this theory, as it became clear that behaviorism was
too simple. To strike an ideal balance, then, a researcher constructs a theory in a way that
includes only the necessary pieces, nothing unnecessary.
Figure 1.2: The behaviorist model
Figure 1.2 presents the overall theoretical perspective behind behaviorism. The “black box” in the middle
represents mental processes.
Stimulus
Response
(Behavior)
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Hypotheses and Theories
Section 1.3
Promotes Research
Finally, science is a cumulative field, which means that a theory is really only as good as the
research it generates. To state it more bluntly: A theory is essentially useless if no one follows
up on it with more research. Thus, one of the best bases for evaluating a theory is whether
it encourages new hypotheses. Consider the following example, drawn from real research
in social psychology. Since the early 1980s, Bill Swann and his colleagues have argued that
people prefer consistent feedback to positive feedback, meaning that they would rather hear
things that confirm what they think of themselves. One provocative hypothesis arising from
this theory proposes that people with low self-esteem are more comfortable with a romantic
partner who thinks less of them than with one who thinks well of them. This hypothesis has
been tested and supported many times in a variety of contexts and continues to draw people
in because it offers a compelling explanation for why some people stay in bad relationships—
a phenomenon that is regrettably recognizable. (For a review of this research, see Swann,
Rentfrow, & Guinn, 2005.)
The Cycle of Science
Now, let us take a step back and look at the big picture. We have covered the processes of developing and evaluating both broad theories and specific hypotheses. Of course, none of these
pieces occurs in isolation; science is an ongoing process of updating and revising our views
based on what the data show. This overall process of quantitative research works something
like the cycle depicted in Figure 1.3. Researchers start with either an overall theory or a set
of observations about how concepts relate to one another and
use this to generate specific, testable, and falsifiable hypothe- Figure 1.3: The cycle
ses. These hypotheses then form the basis for research studies,
which generate empirical data. Based on these data, we may of science
have reason to suspect the overall theory needs to be refined
Theory
or revised. And, so, we develop a new hypothesis, collect some
new data, and either confirm or do not confirm our suspicion.
The process does not end there, however: other researchers
Hypothesis
may see a new perspective on our theory and develop their
own hypotheses, which lead to their own data and possibly
Empirical Data
to a revision of the theory. The scientific approach may strike
some as a slow and strange approach to problem solving, but
Revised Theory
it is the most objective one available.
Consider an example of how this cycle works in real life. In the 1960s, social psychologists
were beginning to study the ways that people explain the behavior of others (e.g., when someone cuts me off in traffic, I tend to assume he is a jerk.) One early theory, called “correspondent
inference theory,” argued that people would come up with these explanations in a rational
way. For example, if we read a persuasive essay but then learn that the author was assigned
a position on the topic, we should refrain from drawing any conclusions about the writer’s
actual position. However, research findings demonstrated just the opposite. In a landmark
1967 study, participants actually ignored information about whether 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 correspondent inference theory was gradually revised to incorporate what
was termed the “fundamental attribution error”—people tend to ignore situational influence
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Searching the Literature
Section 1.4
and assume that all behavior simply reflects the person’s own disposition. The study’s authors
developed a theory, came up with a specific hypothesis, and collected some empirical data to
test it. But because the data ran counter to the theory, the theory was ultimately revised to
account for the empirical evidence. In this particular case, the cycle of research on understanding the fundamental attribution continues to this day, over 50 years later.
Proof and Disproof
While on the subject of adjusting theories, think about the notions of “proof” and “disproof.”
Because science is a cumulative field, decisions about the validity of a theory are ultimately
made based on results of several studies from several research laboratories. This means that
a single research study has rather limited implications for an overall theory. This also means
that a researcher must use the 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 on two very simple
rules:
1. If the data from one study are consistent with our hypothesis, we support the hypothesis rather than “prove” it. In fact, research almost never proves a theory, but statistical tests can at least suggest 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 the course will discuss, many factors can cause a study to fail;
these are often a result of flaws in the design rather than flaws in the overall theory.
1.4 Searching the Literature
Regardless of how a researcher develops a hypothesis, an important step in the process is to
connect it with what has been done before. Scientific knowledge accumulates one study at a
time, so the best studies will build on earlier studies—by extending, correcting, or contradicting them. On a practical note, to struggle over the best way to measure something when
another researcher figured it out 20 years ago would be a waste of time. So, rather than reinvent the proverbial wheel, one of the first steps in a research project is to consult published
relevant articles. This section 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 because
of the sheer number of available sources. Should I ask a librarian? Search Wikipedia? Browse
the web? Fortunately, we can use a few tricks to make sure that 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 analyses of these data.
These types of sources appear in professional academic journals and are evaluated by a set
of experts in the field before they are published—a process known as peer review. Thus,
primary sources offer a reliable way to determine what has been done in a particular field.
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Searching the Literature
Section 1.4
Secondary sources, in contrast, consist only of summaries of primary sources. These types
of sources include textbooks, some academic books, and review articles in journals such as
Psychological Bulletin. As an analogy, think of the difference between someone telling his
friends about an adventurous weekend (primary source) and one of those friends repeating
the story to her roommate (secondary source). While some secondary sources undergo a
process of review and evaluation (academic books), others do not (e.g., websites, friends
re-telling stories).
In this day and age, people are becoming more and more comfortable searching for information via the Internet. It
is particularly important, therefore, to
note that websites are often not objective in their summaries of research.
The vaccine/autism scare discussed at
the beginning of the chapter is a good
example of this point. A Google search
for the terms vaccine and autism produces more than 4 million results,
sorted in order of popularity. As of
anyaberkut/iStock/Thinkstock
this writing, the top result is an article
from WebMD describing the current College libraries provide students access to hard
controversy, followed by one by the copies and digital copies of relevant research
Centers for Disease Control, arguing in articles.
favor of vaccines. At another time, and
depending on recent events in the news, the top result might be celebrity Jenny McCarthy’s
website, which claims that vaccines gave her child autism. The key point is that search results
in Google are not peer-reviewed, are not listed in order of reliability, and are customized to an
individual’s browsing history, confirming those biases. As a result, Google is a poor resource
for finding trustworthy information 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.” Unlike other encyclopedias, however, Wikipedia can be edited by anyone with access to the Internet. On the
upside, this means that errors can be identified and corrected at any time. On the downside,
this means that errors can be made—either accidentally or deliberately—at any time. The
upshot is that there is no way to be sure that information is from a page at a time when it
sticks to the facts.
What, then, does a researcher do? Fortunately, two reliable ways exist to access primary
sources (research articles) that enable researchers to draw their own conclusions based
on the patterns of data. First, Google Scholar (http://scholar.google.com) is a free resource,
managed by Google, that works exactly like Google but is limited to peer-reviewed academic
articles. Thus, Google Scholar provides one pipeline to access primary sources. Second,
many university libraries have access to centralized databases of peer-reviewed articles. The
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Searching the Literature
Section 1.4
best-known database for psychology articles is PsycINFO; this database, maintained by the
American Psychological Association, contains abstracts and citations for articles in psychology and related fields. PsycINFO is updated monthly and covers approximately 2,500 different primary-source academic journals.
Searching in PsycINFO (or Google Scholar) is as easy as typing key terms into a text box—
sometimes labeled “Find,” or “Keywords.” That said, the process of choosing the best key
words for a particular search can be a complex process. If search terms are too general, the
search might yield too many results to be useful. If search terms are too specific, the search
might yield only one or two articles and fail to represent fully 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
Clearly, we need to narrow the field a bit—most of us have better things to do than review
almost 5,000 abstracts. What aspect of self-esteem is most interesting? Perhaps we want to
learn more about self-esteem and sexual behavior:
“self-esteem” and “condom use”
2 hits
“self-esteem” and “sexual behavior”
133 hits
Now we may have overdone the limits—two articles may not be very helpful in giving a sense
of previous research. So, let us try one more combination, using a more general search term:
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 and find the most useful articles. No two
searches will be the same, so the real takeaway point is to try several combinations of search
terms to strike a balance in the number of results.
Reading Research Articles
After assembling a collection of research articles relevant to the hypothesis, the researcher’s
next step is to read them. This may sound painfully obvious, but psychological journal articles
are written in a very formulaic way, which can be confusing at first glance. However, once we
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 a journal article is designed to follow the steps of the
scientific method, with a section devoted to each of the four steps. This section examines each
of the parts of a journal article to offer a sense of what to expect from each one. As a supplement to this discussion, the Appendix contains a copy of a real journal article, with the various
sections and parts highlighted for easy reference.
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Searching the Literature
Section 1.4
The Title and the Abstract
At the top of every journal article—as well as in the search results in PsycINFO—appear both
the title and an abstract or short summary of the article. While neither of these is a section
per se, both provide the reader with a valuable first impression of the contents of the article.
If a search query results in a large number of hits, a researcher can usually scan the titles
to determine which ones are most likely to be useful. For example, if the research question
concerns the links between depression and alcohol consumption among college students, the
database might be searched for the terms “alcohol” and “depression.” Most of the results will
be relevant and useful, but the researcher could probably skip an article with a title like “Fetal
Alcohol Syndrome and Postpartum Depression,” since it is likely to be focused on a different
population.
Once the list of results is narrowed to the most useful titles, the abstract provides additional
information about the content of the article. A journal article abstract 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 concise summary that is worth reading carefully. In some
cases, researchers decide after reading the abstract that this particular article is not relevant
to their research.
The Introduction
The first main section of a journal article is the introduction, corresponding to the first step
(i.e., hypothesize) of the 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 that was investigated. When diving into a new research area for the first time, it is a good
idea to read the entire introduction carefully. This section 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 the four-step research process. The goal of this section is to
explain how the hypothesis translated into a set of specific measurable variables and how the
researchers gathered data to test their hypothesis. An additional—perhaps even more important—goal of this section is to provide enough detail about the study that someone could read
the article and repeat the study.
The method section is typically divided into three parts: participants, materials, and procedure. 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 treatment of depression, the authors would specify whether the participants were “normal” college students or patients who have been hospitalized for treatment of severe, clinical
levels of depression. The materials section describes any questionnaires or equipment that
were used in the study, including both standardized measures and ones that the researchers
created. The third and related section, procedure, provides all of the details regarding the
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Searching the Literature
Section 1.4
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 the study. While reading these sections, focus
on understanding the key variables and how they were defined. Second, they allow readers to envision the study from the perspective of the participants and to decide whether the
authors’ interpretation of the results is the only one. For example, the authors might claim
that participants were placed under stress and that the results showed a drop in concentration because of the stress. The procedure section, though, might suggest to the reader that the
“stress” part of the study is more likely to invoke boredom. This could generate an 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 the four-step research process. This section aims to describe how the
data were analyzed and to report the results of these analyses. The results section consists
primarily of statistical analyses and, as Jordan and Zanna (1999) put it, “statistics can be
intimidating” (p. 356). When students first start to read journal articles, the statistics can
indeed seem overwhelming, but there are two reasons not to get discouraged. First, statistical
results are always followed by a translation into plain English and almost always by tables and
graphs of the data. This course will provide the opportunity to practice interpreting results
in both statistical and graphical form. And this point brings us to the second reason not to
become discouraged: The statistics stop being intimidating surprisingly quickly. The more we
read journal articles and place them in the context of our own ideas, the more comfortable
we become interpreting statistical analyses. In fact, as we become savvier with interpreting
statistics, we 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 four-step research process. The goal of this section is to summarize the main findings and provide an evaluation of the hypothesis. Thus, the first few
paragraphs of the discussion often supply a good summary of the entire article. Authors state
whether their predictions were confirmed and speculate on the meaning of the findings. If
some of the predictions were not confirmed, authors suggest explanations for this and either
acknowledge or defend potential flaws in the study. In addition, to encourage others to follow
up on the study, authors tie their findings to previous literature and make suggestions for
future research.
Evaluating Articles
So, in sum, a journal article will follow a predictable structure: Authors first describe the
problem and state their hypothesis (introduction), then explain their approach to testing the
hypothesis (method), then report the findings of this test (results), and finally discuss the
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Ethics in Research
meaning of these findings relative to the 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, and
ends broadly in the discussion by tying everything back into
the overall problem (e.g., Bem, 1987). Figure 1.4 depicts this
structure.
Before moving on, we will review some general guidelines
for evaluating journal articles. After reading the paper in its
entirety, use the following five questions to form an overall
evaluation of the paper.
Section 1.5
Figure 1.4: Structure
of journal articles
Introduction
Method
Results
1. What am I being asked to believe? What is the
author’s main argument? Before critiquing in detail,
Discussion
make sure you understand the argument completely
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 an empirical paper, look to the data; if it is
a theoretical paper, look at the literature the author summarizes.
3. Are there alternative explanations? Be creative here. Based on your reading of the
article, what else seems plausible? To make your critique a good one, though, you
should be able to test it.
4. What additional evidence would help us test alternatives? This question is one
of the keys to performing good science. Once you identify something wrong with the
original study, how can you test your alternative?
5. What conclusions are reasonable? Return to step 1 with your critiques in mind.
What should the author reasonably conclude, given the problems with the study?
1.5 Ethics in Research
In the summer of 1971, psychologist Phillip Zimbardo conducted an experiment at Stanford
University to test the power of social roles. Zimbardo hypothesized that people would take on
the characteristics and behaviors of whatever role was assigned to them, and he tested this by
creating a simulated prison in the basement of the psychology building. A group of 24 psychologically healthy young men were selected from the San Francisco Bay area and randomly
assigned to play the role of either “prisoner” or “guard.” Zimbardo appointed himself to the
role of “warden.” The researchers gave each participant pieces of a uniform meant to reinforce their role—smocks for the prisoners, khakis and mirrored sunglasses for the guards.
Almost immediately, and without instructions from the researchers, participants began to act
out their roles. The guards took it upon themselves to establish control and dominate the
prisoners by withholding privileges and devising clever ways to humiliate them. The prisoners, in turn, accepted all of this without much protest since it was part of their prisoner role.
The experiment was scheduled to run for 14 days but was stopped after only six because the
situation was out of control—prisoners were going on hunger strikes and being locked in
solitary confinement, and one even suffered a serious mental breakdown. This study is known
as the Stanford Prison Experiment; learn more about it and view video clips on a website
designed by Zimbardo and his colleagues: http://www.prisonexp.org/.
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Ethics in Research
©Duke Downey/San Francisco Chronicle/San
Francisco Chronicle/Corbis
The Stanford Prison Experiment
raised ethical concerns in the scientific community about how research is
conducted.
Section 1.5
For many, this experiment calls to mind the real-life
prisoner abuse at Abu Ghraib prison in Iraq. A group
of American military guards stationed at this prison
during the Iraq war were caught treating the prisoners in remarkably similar ways to the “guards” at
Stanford—inflicting cruel punishments and humiliations and photographing the entire ordeal. Interestingly, Zimbardo was even called to testify about
the power of social roles during the trial of one of
the Abu Ghraib guards. Zimbardo’s experiment also
strikes many people as ethically dubious. When the
research was published, it raised serious questions
about the amount of distress that can be inflicted
in the name of research. Although the proposal for
this study was approved under ethics standards of
the period, today’s more stringent standards would
not allow it. But how might researchers today balance the distress of the “prisoners” with the valuable knowledge gained from the study? Should the
Stanford Prison Experiment ever have been run?
Does the knowledge outweigh the distress? Before
moving on to the nuts and bolts of research design
in the next four chapters, it is important to spend
some time on the ethics of conducting research.
At the most basic level, all deliberations about the ethics of a particular study come down to
the balance between a) avoiding all unnecessary discomfort for participants; and b) finding
a way to capture real-world attitudes and behaviors to provide a valid test of the hypothesis.
In practice, however, achieving this balance can be complicated. This section first examines
some of the potential threats to participants’ well-being and then discusses how avoidance of
these threats has been formalized into rules for researchers. Finally, evaluate a set of ethical
dilemmas that represent the types of issues likely to arise in psychological studies.
Threats to Participants
To explain the need for ethical guidelines, this section introduces some of the possible threats
to participants’ welfare in the context of research studies.
Physical Harm
We will start with the most extreme threat: Sometimes a research paradigm, or worldview,
can place participants at risk for physical harm. As a general rule, these types of studies are
limited to the medical field. For example, a researcher testing a new medication for heartattack survivors faces the risk that an unexpected side effect could hasten the participants’
death. Alternatively, perhaps the participants could have benefitted more from another, more
established medication, but they were not taking it because they were participating in the
study to assess the new medication. Because of these risks, medical researchers are required
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Ethics in Research
Section 1.5
to perform preliminary testing—often using cell cultures and then animals—before testing
drugs on a human population.
Occasionally, psychological research can pose a physical threat to participants, albeit a more
minor one. As one example, for the past 25 years, Sheldon Cohen has been conducting studies
in which he exposes participants to the common cold virus and measures the development of
cold symptoms for several days. This work is designed to explore the link between individuals’ social environment and their susceptibility to illness; learn more about it on Dr. Cohen’s
website: http://www.psy.cmu.edu/~scohen/. While the cold virus can be considered a physical threat, it is mild in comparison to the knowledge gained from these studies.
Extreme Stress
More common among psychological studies are those that introduce high levels of mental or
emotional stress for participants. As the text will discuss later, the key in evaluating whether
a stressful research paradigm is ethical is to think about whether—and to what extent—it
exceeds the stress that participants encounter in everyday life. In the Stanford Prison Experiment, it is easy to see how the stress experienced by the “prisoners” exceeded normal levels.
In 1924, Carney Landis conducted the first studies of facial expression and emotion. His goal
was to map specific emotional states onto specific expressions—work that is now associated
with Paul Ekman (and popularized by the television show Lie to Me.). Landis photographed
his participants as they reacted to a variety of stimuli such as smelling ammonia and viewing pornography. But the most shocking and controversial task was the final one. To measure
responses to “disgust,” Landis asked his participants either to decapitate a live rat (a task they
lacked the training to perform humanely), or to watch Landis behead the rat. In this case, the
discomfort could not even be balanced by the knowledge gained from it; Landis found no support for his hypotheses regarding common facial expressions. Of course, this study is beyond
anything deemed ethically acceptable by today’s standards.
In reality, most research, and particularly psychological research, presents a much more minor
degree of stress to participants. For example, one very common task used in social psychology research is to observe college students’ reactions as they are asked to prepare and give a
speech. Most people become anxious at the thought of public speaking, but this anxiety is mild
and very much temporary. In fact, among studies that receive approval from ethics review
boards, the effects of the research on overall well-being are always mild and temporary.
Deception
Finally, at the lower end of the threat spectrum, many psychological studies involve deceiving
participants about the purpose of the research—at least until the study is finished. This deception is a way to ensure people’s honest reactions to the experimental setting. If, for example,
participants in Milgram’s obedience studies had known he was studying obedience, they would
have reacted very differently when asked to shock the confederate, and the study would have
been pointless. As an analogy, think of how car salespeople attempt to bond and form a relationship with customers by asking personal questions. Odds are that this trick would backfire
if a car salesperson said “I bet if I ask about your family, you’ll start to bond with me and be
more likely to buy a car!” Later chapters will elaborate, but people tend to change their behavior when they figure out the research question (as well as when they think they figure it out).
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Section 1.5
Deception is included here as a threat because of the potential for abuse. The history of science is rife with examples of medical research conducted on unsuspecting (and unwilling)
participants. In one of the most infamous, researchers in Tuskegee, Alabama, conducted a
study of the natural progression of syphilis among poor African-American farmers. The study
began in 1932 under the supervision of the Public Health Service and continued until 1972.
What was the deception? As it turned out, penicillin was discovered to be a reliable cure for
syphilis—in 1945. The researchers not only lied about the purposes of the study (participants
were never told they had syphilis), but they deliberately withheld treatment so as to continue
the study. (Read more about the study here: http://www.cdc.gov/tuskegee/timeline.htm.)
On the one hand, these types of studies are vastly different from research that could be
approved today, much less the type of research conducted in psychology. On the other hand,
all researchers must be mindful at all times that they do not abuse the trust of participants.
The chapter will later return to the issue of deception in the discussion of evaluating a set of
research scenarios.
Ethical Guidelines
In response to public outcry over the Tuskegee Syphilis Study, the U.S. Congress formed a
panel to develop guidelines that would ensure that all human subjects were treated ethically.
In 1979 this committee published the Belmont Report, a document that outlined a set of basic
ethical principles for the use of human subjects. (The full report is available at http://www
.hhs.gov/ohrp/humansubjects/guidance/belmont.html.) Essentially, the Belmont Report
guidelines argue for treating participants with respect, minimizing harm, and avoiding exploitation. These principles were formalized into a set of federal laws referred to as the common
rule, a baseline standard of ethics for all federally funded research.
One critical part of the common rule was the creation of review boards to evaluate the ethics
of every proposed research study. The common rule mandated that any institution receiving
federal money must have an institutional review board (IRB), which reviews and monitors all research involving humans to protect the welfare of research participants. The IRB
is tasked with determining whether a study is consistent with ethical principles, and it has
the authority to approve, reject, or require modification of any research proposal. To put it
another way, the IRB serves as a gatekeeper for research, ensuring that something like the
Tuskegee Syphilis Study, or Landis’s “facial expression” studies could not be run today.
An important piece of IRB review is to assess the degree of risk that a study poses for participants. Based on these assessments, each proposed study undergoes one of three categories of
review. The lowest risk studies are subject to exempt review, in which an IRB representative
simply verifies the low risk and approves the study. To qualify for exempt review, a study has
to fit into one of six predefined categories, including research done in educational settings
(e.g., testing a new way to teach reading skills), and reanalysis of existing data (e.g., looking
for patterns in polling data). The full set of guidelines is available online at http://www.mayo
.edu/research/institutional-review-board/policy-manual.
Studies classified as medium risk—including the majority of psychological studies—are subject to expedited review, in which an IRB representative conducts a full review of the proposed study’s procedures and ensures that participants’ welfare and identity are protected.
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Section 1.5
Expedited review also requires that a study fit into one of seven predefined categories (http://
www.hhs.gov/ohrp/policy/expedited98.html). These categories encompass most of the
research that psychologists conduct, even when these studies include collection of personal
information and biological specimens. The key to meeting expedited-review criteria is keeping the risk of harm and distress and the release of information to a minimum.
Finally, studies classified as high risk are subject to full-board review, in which all members
of the IRB review the proposed study’s procedures and then meet as a group to discuss the
degree of risk and protection. This category includes studies involving medical procedures,
children, prisoners, or pregnant women. Any time there is potential for physical harm, release
of confidential information, or undue pressure on people to participate (e.g., prisoners), the
IRB pays careful attention to the procedures for minimizing these risks.
The IRB also weighs the potential risks of the study against the potential benefits. These decisions are always made case by case, taking into account the goals of the study. For example,
imagine that researchers were developing a drug that could cure previously fatal birth defects
with an injection while the mother was still pregnant. Imagine also, however, that this drug
could cause serious risks to the mother’s health in about 1% of cases. Is this risk worth the
potential benefits? Is the small risk to the mother a reason to veto the study? Questions like
these are certainly not easy, but they will be at the heart of the IRB’s deliberations.
The American Psychological Association (APA) has its own version of an ethical code, written
specifically for the kinds of dilemmas faced by psychologists in both research and therapeutic settings. The APA ethics code lays out five specific rules for research that involves human
participants. These rules, described in the sections that follow, take their inspiration from
the Belmont guidelines—treat people with respect, minimize harm, and avoid exploitation.
(View the full APA ethics code here: http://www.apa.org/ethics/code/index.aspx.)
1. Informed Consent
First and foremost, research participants must be “informed of all features of the study
that would reasonably affect their decision to participate,” an ethical principle known as
in...
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