what reviews research that involves the use of human participants

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Ch 2: Psychological Research Methods

Have you ever wondered whether the violence you see on television affects your behavior? Are you more likely to behave aggressively in real life after watching people behave violently in dramatic situations on the screen? Or, could seeing fictional violence actually get aggression out of your system, causing you to be more peaceful? How are children influenced by the media they are exposed to? A psychologist interested in the relationship between behavior and exposure to violent images might ask these very questions.

The topic of violence in the media today is contentious. Since ancient times, humans have been concerned about the effects of new technologies on our behaviors and thinking processes. The Greek philosopher Socrates, for example, worried that writing—a new technology at that time—would diminish people’s ability to remember because they could rely on written records rather than committing information to memory. In our world of quickly changing technologies, questions about the effects of media continue to emerge. Is it okay to talk on a cell phone while driving? Are headphones good to use in a car? What impact does text messaging have on reaction time while driving? These are types of questions that psychologist David Strayer asks in his lab.

Watch this short video to see how Strayer utilizes the scientific method to reach important conclusions regarding technology and driving safety.

You can view the transcript for “Understanding driver distraction” here (opens in new window) .

How can we go about finding answers that are supported not by mere opinion, but by evidence that we can all agree on? The findings of psychological research can help us navigate issues like this.

Introduction to the Scientific Method

Learning objectives.

• Explain the steps of the scientific method
• Describe why the scientific method is important to psychology
• Summarize the processes of informed consent and debriefing
• Explain how research involving humans or animals is regulated

Scientists are engaged in explaining and understanding how the world around them works, and they are able to do so by coming up with theories that generate hypotheses that are testable and falsifiable. Theories that stand up to their tests are retained and refined, while those that do not are discarded or modified. In this way, research enables scientists to separate fact from simple opinion. Having good information generated from research aids in making wise decisions both in public policy and in our personal lives. In this section, you’ll see how psychologists use the scientific method to study and understand behavior.

The Scientific Process

The goal of all scientists is to better understand the world around them. Psychologists focus their attention on understanding behavior, as well as the cognitive (mental) and physiological (body) processes that underlie behavior. In contrast to other methods that people use to understand the behavior of others, such as intuition and personal experience, the hallmark of scientific research is that there is evidence to support a claim. Scientific knowledge is empirical : It is grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing.

While behavior is observable, the mind is not. If someone is crying, we can see the behavior. However, the reason for the behavior is more difficult to determine. Is the person crying due to being sad, in pain, or happy? Sometimes we can learn the reason for someone’s behavior by simply asking a question, like “Why are you crying?” However, there are situations in which an individual is either uncomfortable or unwilling to answer the question honestly, or is incapable of answering. For example, infants would not be able to explain why they are crying. In such circumstances, the psychologist must be creative in finding ways to better understand behavior. This module explores how scientific knowledge is generated, and how important that knowledge is in forming decisions in our personal lives and in the public domain.

Process of Scientific Research

Scientific knowledge is advanced through a process known as the scientific method. Basically, ideas (in the form of theories and hypotheses) are tested against the real world (in the form of empirical observations), and those empirical observations lead to more ideas that are tested against the real world, and so on.

The basic steps in the scientific method are:

• Observe a natural phenomenon and define a question about it
• Make a hypothesis, or potential solution to the question
• Test the hypothesis
• If the hypothesis is true, find more evidence or find counter-evidence
• If the hypothesis is false, create a new hypothesis or try again
• Draw conclusions and repeat–the scientific method is never-ending, and no result is ever considered perfect

In order to ask an important question that may improve our understanding of the world, a researcher must first observe natural phenomena. By making observations, a researcher can define a useful question. After finding a question to answer, the researcher can then make a prediction (a hypothesis) about what he or she thinks the answer will be. This prediction is usually a statement about the relationship between two or more variables. After making a hypothesis, the researcher will then design an experiment to test his or her hypothesis and evaluate the data gathered. These data will either support or refute the hypothesis. Based on the conclusions drawn from the data, the researcher will then find more evidence to support the hypothesis, look for counter-evidence to further strengthen the hypothesis, revise the hypothesis and create a new experiment, or continue to incorporate the information gathered to answer the research question.

Basic Principles of the Scientific Method

Two key concepts in the scientific approach are theory and hypothesis. A theory is a well-developed set of ideas that propose an explanation for observed phenomena that can be used to make predictions about future observations. A hypothesis is a testable prediction that is arrived at logically from a theory. It is often worded as an if-then statement (e.g., if I study all night, I will get a passing grade on the test). The hypothesis is extremely important because it bridges the gap between the realm of ideas and the real world. As specific hypotheses are tested, theories are modified and refined to reflect and incorporate the result of these tests.

Other key components in following the scientific method include verifiability, predictability, falsifiability, and fairness. Verifiability means that an experiment must be replicable by another researcher. To achieve verifiability, researchers must make sure to document their methods and clearly explain how their experiment is structured and why it produces certain results.

Predictability in a scientific theory implies that the theory should enable us to make predictions about future events. The precision of these predictions is a measure of the strength of the theory.

Falsifiability refers to whether a hypothesis can be disproved. For a hypothesis to be falsifiable, it must be logically possible to make an observation or do a physical experiment that would show that there is no support for the hypothesis. Even when a hypothesis cannot be shown to be false, that does not necessarily mean it is not valid. Future testing may disprove the hypothesis. This does not mean that a hypothesis has to be shown to be false, just that it can be tested.

To determine whether a hypothesis is supported or not supported, psychological researchers must conduct hypothesis testing using statistics. Hypothesis testing is a type of statistics that determines the probability of a hypothesis being true or false. If hypothesis testing reveals that results were “statistically significant,” this means that there was support for the hypothesis and that the researchers can be reasonably confident that their result was not due to random chance. If the results are not statistically significant, this means that the researchers’ hypothesis was not supported.

Fairness implies that all data must be considered when evaluating a hypothesis. A researcher cannot pick and choose what data to keep and what to discard or focus specifically on data that support or do not support a particular hypothesis. All data must be accounted for, even if they invalidate the hypothesis.

Applying the Scientific Method

To see how this process works, let’s consider a specific theory and a hypothesis that might be generated from that theory. As you’ll learn in a later module, the James-Lange theory of emotion asserts that emotional experience relies on the physiological arousal associated with the emotional state. If you walked out of your home and discovered a very aggressive snake waiting on your doorstep, your heart would begin to race and your stomach churn. According to the James-Lange theory, these physiological changes would result in your feeling of fear. A hypothesis that could be derived from this theory might be that a person who is unaware of the physiological arousal that the sight of the snake elicits will not feel fear.

Remember that a good scientific hypothesis is falsifiable, or capable of being shown to be incorrect. Recall from the introductory module that Sigmund Freud had lots of interesting ideas to explain various human behaviors (Figure 5). However, a major criticism of Freud’s theories is that many of his ideas are not falsifiable; for example, it is impossible to imagine empirical observations that would disprove the existence of the id, the ego, and the superego—the three elements of personality described in Freud’s theories. Despite this, Freud’s theories are widely taught in introductory psychology texts because of their historical significance for personality psychology and psychotherapy, and these remain the root of all modern forms of therapy.

In contrast, the James-Lange theory does generate falsifiable hypotheses, such as the one described above. Some individuals who suffer significant injuries to their spinal columns are unable to feel the bodily changes that often accompany emotional experiences. Therefore, we could test the hypothesis by determining how emotional experiences differ between individuals who have the ability to detect these changes in their physiological arousal and those who do not. In fact, this research has been conducted and while the emotional experiences of people deprived of an awareness of their physiological arousal may be less intense, they still experience emotion (Chwalisz, Diener, & Gallagher, 1988).

Link to Learning

Why the scientific method is important for psychology.

The use of the scientific method is one of the main features that separates modern psychology from earlier philosophical inquiries about the mind. Compared to chemistry, physics, and other “natural sciences,” psychology has long been considered one of the “social sciences” because of the subjective nature of the things it seeks to study. Many of the concepts that psychologists are interested in—such as aspects of the human mind, behavior, and emotions—are subjective and cannot be directly measured. Psychologists often rely instead on behavioral observations and self-reported data, which are considered by some to be illegitimate or lacking in methodological rigor. Applying the scientific method to psychology, therefore, helps to standardize the approach to understanding its very different types of information.

The scientific method allows psychological data to be replicated and confirmed in many instances, under different circumstances, and by a variety of researchers. Through replication of experiments, new generations of psychologists can reduce errors and broaden the applicability of theories. It also allows theories to be tested and validated instead of simply being conjectures that could never be verified or falsified. All of this allows psychologists to gain a stronger understanding of how the human mind works.

Scientific articles published in journals and psychology papers written in the style of the American Psychological Association (i.e., in “APA style”) are structured around the scientific method. These papers include an Introduction, which introduces the background information and outlines the hypotheses; a Methods section, which outlines the specifics of how the experiment was conducted to test the hypothesis; a Results section, which includes the statistics that tested the hypothesis and state whether it was supported or not supported, and a Discussion and Conclusion, which state the implications of finding support for, or no support for, the hypothesis. Writing articles and papers that adhere to the scientific method makes it easy for future researchers to repeat the study and attempt to replicate the results.

Ethics in Research

Today, scientists agree that good research is ethical in nature and is guided by a basic respect for human dignity and safety. However, as you will read in the Tuskegee Syphilis Study, this has not always been the case. Modern researchers must demonstrate that the research they perform is ethically sound. This section presents how ethical considerations affect the design and implementation of research conducted today.

Research Involving Human Participants

Any experiment involving the participation of human subjects is governed by extensive, strict guidelines designed to ensure that the experiment does not result in harm. Any research institution that receives federal support for research involving human participants must have access to an institutional review board (IRB) . The IRB is a committee of individuals often made up of members of the institution’s administration, scientists, and community members (Figure 6). The purpose of the IRB is to review proposals for research that involves human participants. The IRB reviews these proposals with the principles mentioned above in mind, and generally, approval from the IRB is required in order for the experiment to proceed.

An institution’s IRB requires several components in any experiment it approves. For one, each participant must sign an informed consent form before they can participate in the experiment. An informed consent  form provides a written description of what participants can expect during the experiment, including potential risks and implications of the research. It also lets participants know that their involvement is completely voluntary and can be discontinued without penalty at any time. Furthermore, the informed consent guarantees that any data collected in the experiment will remain completely confidential. In cases where research participants are under the age of 18, the parents or legal guardians are required to sign the informed consent form.

While the informed consent form should be as honest as possible in describing exactly what participants will be doing, sometimes deception is necessary to prevent participants’ knowledge of the exact research question from affecting the results of the study. Deception involves purposely misleading experiment participants in order to maintain the integrity of the experiment, but not to the point where the deception could be considered harmful. For example, if we are interested in how our opinion of someone is affected by their attire, we might use deception in describing the experiment to prevent that knowledge from affecting participants’ responses. In cases where deception is involved, participants must receive a full debriefing  upon conclusion of the study—complete, honest information about the purpose of the experiment, how the data collected will be used, the reasons why deception was necessary, and information about how to obtain additional information about the study.

Dig Deeper: Ethics and the Tuskegee Syphilis Study

Unfortunately, the ethical guidelines that exist for research today were not always applied in the past. In 1932, poor, rural, black, male sharecroppers from Tuskegee, Alabama, were recruited to participate in an experiment conducted by the U.S. Public Health Service, with the aim of studying syphilis in black men (Figure 7). In exchange for free medical care, meals, and burial insurance, 600 men agreed to participate in the study. A little more than half of the men tested positive for syphilis, and they served as the experimental group (given that the researchers could not randomly assign participants to groups, this represents a quasi-experiment). The remaining syphilis-free individuals served as the control group. However, those individuals that tested positive for syphilis were never informed that they had the disease.

While there was no treatment for syphilis when the study began, by 1947 penicillin was recognized as an effective treatment for the disease. Despite this, no penicillin was administered to the participants in this study, and the participants were not allowed to seek treatment at any other facilities if they continued in the study. Over the course of 40 years, many of the participants unknowingly spread syphilis to their wives (and subsequently their children born from their wives) and eventually died because they never received treatment for the disease. This study was discontinued in 1972 when the experiment was discovered by the national press (Tuskegee University, n.d.). The resulting outrage over the experiment led directly to the National Research Act of 1974 and the strict ethical guidelines for research on humans described in this chapter. Why is this study unethical? How were the men who participated and their families harmed as a function of this research?

Learn more about the Tuskegee Syphilis Study on the CDC website .

Research Involving Animal Subjects

This does not mean that animal researchers are immune to ethical concerns. Indeed, the humane and ethical treatment of animal research subjects is a critical aspect of this type of research. Researchers must design their experiments to minimize any pain or distress experienced by animals serving as research subjects.

Whereas IRBs review research proposals that involve human participants, animal experimental proposals are reviewed by an Institutional Animal Care and Use Committee (IACUC) . An IACUC consists of institutional administrators, scientists, veterinarians, and community members. This committee is charged with ensuring that all experimental proposals require the humane treatment of animal research subjects. It also conducts semi-annual inspections of all animal facilities to ensure that the research protocols are being followed. No animal research project can proceed without the committee’s approval.

Introduction to Approaches to Research

• Differentiate between descriptive, correlational, and experimental research
• Explain the strengths and weaknesses of case studies, naturalistic observation, and surveys
• Describe the strength and weaknesses of archival research
• Compare longitudinal and cross-sectional approaches to research
• Explain what a correlation coefficient tells us about the relationship between variables
• Describe why correlation does not mean causation
• Describe the experimental process, including ways to control for bias
• Identify and differentiate between independent and dependent variables

Psychologists use descriptive, experimental, and correlational methods to conduct research. Descriptive, or qualitative, methods include the case study, naturalistic observation, surveys, archival research, longitudinal research, and cross-sectional research.

Experiments are conducted in order to determine cause-and-effect relationships. In ideal experimental design, the only difference between the experimental and control groups is whether participants are exposed to the experimental manipulation. Each group goes through all phases of the experiment, but each group will experience a different level of the independent variable: the experimental group is exposed to the experimental manipulation, and the control group is not exposed to the experimental manipulation. The researcher then measures the changes that are produced in the dependent variable in each group. Once data is collected from both groups, it is analyzed statistically to determine if there are meaningful differences between the groups.

When scientists passively observe and measure phenomena it is called correlational research. Here, psychologists do not intervene and change behavior, as they do in experiments. In correlational research, they identify patterns of relationships, but usually cannot infer what causes what. Importantly, with correlational research, you can examine only two variables at a time, no more and no less.

Watch It: More on Research

If you enjoy learning through lectures and want an interesting and comprehensive summary of this section, then click on the Youtube link to watch a lecture given by MIT Professor John Gabrieli . Start at the 30:45 minute mark  and watch through the end to hear examples of actual psychological studies and how they were analyzed. Listen for references to independent and dependent variables, experimenter bias, and double-blind studies. In the lecture, you’ll learn about breaking social norms, “WEIRD” research, why expectations matter, how a warm cup of coffee might make you nicer, why you should change your answer on a multiple choice test, and why praise for intelligence won’t make you any smarter.

You can view the transcript for “Lec 2 | MIT 9.00SC Introduction to Psychology, Spring 2011” here (opens in new window) .

Descriptive Research

There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it. Some methods rely on observational techniques. Other approaches involve interactions between the researcher and the individuals who are being studied—ranging from a series of simple questions to extensive, in-depth interviews—to well-controlled experiments.

The three main categories of psychological research are descriptive, correlational, and experimental research. Research studies that do not test specific relationships between variables are called descriptive, or qualitative, studies . These studies are used to describe general or specific behaviors and attributes that are observed and measured. In the early stages of research it might be difficult to form a hypothesis, especially when there is not any existing literature in the area. In these situations designing an experiment would be premature, as the question of interest is not yet clearly defined as a hypothesis. Often a researcher will begin with a non-experimental approach, such as a descriptive study, to gather more information about the topic before designing an experiment or correlational study to address a specific hypothesis. Descriptive research is distinct from correlational research , in which psychologists formally test whether a relationship exists between two or more variables. Experimental research  goes a step further beyond descriptive and correlational research and randomly assigns people to different conditions, using hypothesis testing to make inferences about how these conditions affect behavior. It aims to determine if one variable directly impacts and causes another. Correlational and experimental research both typically use hypothesis testing, whereas descriptive research does not.

Each of these research methods has unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions. For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes. Survey research, on the other hand, allows researchers to easily collect data from relatively large samples. While this allows for results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data. Some researchers conduct archival research by using existing records. While this can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control on how or what kind of data was collected.

Correlational research can find a relationship between two variables, but the only way a researcher can claim that the relationship between the variables is cause and effect is to perform an experiment. In experimental research, which will be discussed later in the text, there is a tremendous amount of control over variables of interest. While this is a powerful approach, experiments are often conducted in very artificial settings. This calls into question the validity of experimental findings with regard to how they would apply in real-world settings. In addition, many of the questions that psychologists would like to answer cannot be pursued through experimental research because of ethical concerns.

The three main types of descriptive studies are, naturalistic observation, case studies, and surveys.

Naturalistic Observation

If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances are that almost everyone in the classroom will raise their hand, but do you think hand washing after every trip to the restroom is really that universal?

This is very similar to the phenomenon mentioned earlier in this module: many individuals do not feel comfortable answering a question honestly. But if we are committed to finding out the facts about hand washing, we have other options available to us.

Suppose we send a classmate into the restroom to actually watch whether everyone washes their hands after using the restroom. Will our observer blend into the restroom environment by wearing a white lab coat, sitting with a clipboard, and staring at the sinks? We want our researcher to be inconspicuous—perhaps standing at one of the sinks pretending to put in contact lenses while secretly recording the relevant information. This type of observational study is called naturalistic observation : observing behavior in its natural setting. To better understand peer exclusion, Suzanne Fanger collaborated with colleagues at the University of Texas to observe the behavior of preschool children on a playground. How did the observers remain inconspicuous over the duration of the study? They equipped a few of the children with wireless microphones (which the children quickly forgot about) and observed while taking notes from a distance. Also, the children in that particular preschool (a “laboratory preschool”) were accustomed to having observers on the playground (Fanger, Frankel, & Hazen, 2012).

It is critical that the observer be as unobtrusive and as inconspicuous as possible: when people know they are being watched, they are less likely to behave naturally. If you have any doubt about this, ask yourself how your driving behavior might differ in two situations: In the first situation, you are driving down a deserted highway during the middle of the day; in the second situation, you are being followed by a police car down the same deserted highway (Figure 9).

It should be pointed out that naturalistic observation is not limited to research involving humans. Indeed, some of the best-known examples of naturalistic observation involve researchers going into the field to observe various kinds of animals in their own environments. As with human studies, the researchers maintain their distance and avoid interfering with the animal subjects so as not to influence their natural behaviors. Scientists have used this technique to study social hierarchies and interactions among animals ranging from ground squirrels to gorillas. The information provided by these studies is invaluable in understanding how those animals organize socially and communicate with one another. The anthropologist Jane Goodall, for example, spent nearly five decades observing the behavior of chimpanzees in Africa (Figure 10). As an illustration of the types of concerns that a researcher might encounter in naturalistic observation, some scientists criticized Goodall for giving the chimps names instead of referring to them by numbers—using names was thought to undermine the emotional detachment required for the objectivity of the study (McKie, 2010).

The greatest benefit of naturalistic observation is the validity, or accuracy, of information collected unobtrusively in a natural setting. Having individuals behave as they normally would in a given situation means that we have a higher degree of ecological validity, or realism, than we might achieve with other research approaches. Therefore, our ability to generalize  the findings of the research to real-world situations is enhanced. If done correctly, we need not worry about people or animals modifying their behavior simply because they are being observed. Sometimes, people may assume that reality programs give us a glimpse into authentic human behavior. However, the principle of inconspicuous observation is violated as reality stars are followed by camera crews and are interviewed on camera for personal confessionals. Given that environment, we must doubt how natural and realistic their behaviors are.

The major downside of naturalistic observation is that they are often difficult to set up and control. In our restroom study, what if you stood in the restroom all day prepared to record people’s hand washing behavior and no one came in? Or, what if you have been closely observing a troop of gorillas for weeks only to find that they migrated to a new place while you were sleeping in your tent? The benefit of realistic data comes at a cost. As a researcher you have no control of when (or if) you have behavior to observe. In addition, this type of observational research often requires significant investments of time, money, and a good dose of luck.

Sometimes studies involve structured observation. In these cases, people are observed while engaging in set, specific tasks. An excellent example of structured observation comes from Strange Situation by Mary Ainsworth (you will read more about this in the module on lifespan development). The Strange Situation is a procedure used to evaluate attachment styles that exist between an infant and caregiver. In this scenario, caregivers bring their infants into a room filled with toys. The Strange Situation involves a number of phases, including a stranger coming into the room, the caregiver leaving the room, and the caregiver’s return to the room. The infant’s behavior is closely monitored at each phase, but it is the behavior of the infant upon being reunited with the caregiver that is most telling in terms of characterizing the infant’s attachment style with the caregiver.

Another potential problem in observational research is observer bias . Generally, people who act as observers are closely involved in the research project and may unconsciously skew their observations to fit their research goals or expectations. To protect against this type of bias, researchers should have clear criteria established for the types of behaviors recorded and how those behaviors should be classified. In addition, researchers often compare observations of the same event by multiple observers, in order to test inter-rater reliability : a measure of reliability that assesses the consistency of observations by different observers.

Case Studies

In 2011, the New York Times published a feature story on Krista and Tatiana Hogan, Canadian twin girls. These particular twins are unique because Krista and Tatiana are conjoined twins, connected at the head. There is evidence that the two girls are connected in a part of the brain called the thalamus, which is a major sensory relay center. Most incoming sensory information is sent through the thalamus before reaching higher regions of the cerebral cortex for processing.

The implications of this potential connection mean that it might be possible for one twin to experience the sensations of the other twin. For instance, if Krista is watching a particularly funny television program, Tatiana might smile or laugh even if she is not watching the program. This particular possibility has piqued the interest of many neuroscientists who seek to understand how the brain uses sensory information.

These twins represent an enormous resource in the study of the brain, and since their condition is very rare, it is likely that as long as their family agrees, scientists will follow these girls very closely throughout their lives to gain as much information as possible (Dominus, 2011).

In observational research, scientists are conducting a clinical or case study when they focus on one person or just a few individuals. Indeed, some scientists spend their entire careers studying just 10–20 individuals. Why would they do this? Obviously, when they focus their attention on a very small number of people, they can gain a tremendous amount of insight into those cases. The richness of information that is collected in clinical or case studies is unmatched by any other single research method. This allows the researcher to have a very deep understanding of the individuals and the particular phenomenon being studied.

If clinical or case studies provide so much information, why are they not more frequent among researchers? As it turns out, the major benefit of this particular approach is also a weakness. As mentioned earlier, this approach is often used when studying individuals who are interesting to researchers because they have a rare characteristic. Therefore, the individuals who serve as the focus of case studies are not like most other people. If scientists ultimately want to explain all behavior, focusing attention on such a special group of people can make it difficult to generalize any observations to the larger population as a whole. Generalizing refers to the ability to apply the findings of a particular research project to larger segments of society. Again, case studies provide enormous amounts of information, but since the cases are so specific, the potential to apply what’s learned to the average person may be very limited.

Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally (Figure 11). Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.

Surveys allow researchers to gather data from larger samples than may be afforded by other research methods . A sample is a subset of individuals selected from a population , which is the overall group of individuals that the researchers are interested in. Researchers study the sample and seek to generalize their findings to the population.

There is both strength and weakness of the survey in comparison to case studies. By using surveys, we can collect information from a larger sample of people. A larger sample is better able to reflect the actual diversity of the population, thus allowing better generalizability. Therefore, if our sample is sufficiently large and diverse, we can assume that the data we collect from the survey can be generalized to the larger population with more certainty than the information collected through a case study. However, given the greater number of people involved, we are not able to collect the same depth of information on each person that would be collected in a case study.

Another potential weakness of surveys is something we touched on earlier in this chapter: people don’t always give accurate responses. They may lie, misremember, or answer questions in a way that they think makes them look good. For example, people may report drinking less alcohol than is actually the case.

Any number of research questions can be answered through the use of surveys. One real-world example is the research conducted by Jenkins, Ruppel, Kizer, Yehl, and Griffin (2012) about the backlash against the US Arab-American community following the terrorist attacks of September 11, 2001. Jenkins and colleagues wanted to determine to what extent these negative attitudes toward Arab-Americans still existed nearly a decade after the attacks occurred. In one study, 140 research participants filled out a survey with 10 questions, including questions asking directly about the participant’s overt prejudicial attitudes toward people of various ethnicities. The survey also asked indirect questions about how likely the participant would be to interact with a person of a given ethnicity in a variety of settings (such as, “How likely do you think it is that you would introduce yourself to a person of Arab-American descent?”). The results of the research suggested that participants were unwilling to report prejudicial attitudes toward any ethnic group. However, there were significant differences between their pattern of responses to questions about social interaction with Arab-Americans compared to other ethnic groups: they indicated less willingness for social interaction with Arab-Americans compared to the other ethnic groups. This suggested that the participants harbored subtle forms of prejudice against Arab-Americans, despite their assertions that this was not the case (Jenkins et al., 2012).

Think It Over

Archival research.

In comparing archival research to other research methods, there are several important distinctions. For one, the researcher employing archival research never directly interacts with research participants. Therefore, the investment of time and money to collect data is considerably less with archival research. Additionally, researchers have no control over what information was originally collected. Therefore, research questions have to be tailored so they can be answered within the structure of the existing data sets. There is also no guarantee of consistency between the records from one source to another, which might make comparing and contrasting different data sets problematic.

Longitudinal and Cross-Sectional Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research  is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again at age 40.

Another approach is cross-sectional research . In cross-sectional research, a researcher compares multiple segments of the population at the same time. Using the dietary habits example above, the researcher might directly compare different groups of people by age. Instead of observing a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old individuals. While cross-sectional research requires a shorter-term investment, it is also limited by differences that exist between the different generations (or cohorts) that have nothing to do with age per se, but rather reflect the social and cultural experiences of different generations of individuals make them different from one another.

To illustrate this concept, consider the following survey findings. In recent years there has been significant growth in the popular support of same-sex marriage. Many studies on this topic break down survey participants into different age groups. In general, younger people are more supportive of same-sex marriage than are those who are older (Jones, 2013). Does this mean that as we age we become less open to the idea of same-sex marriage, or does this mean that older individuals have different perspectives because of the social climates in which they grew up? Longitudinal research is a powerful approach because the same individuals are involved in the research project over time, which means that the researchers need to be less concerned with differences among cohorts affecting the results of their study.

Often longitudinal studies are employed when researching various diseases in an effort to understand particular risk factors. Such studies often involve tens of thousands of individuals who are followed for several decades. Given the enormous number of people involved in these studies, researchers can feel confident that their findings can be generalized to the larger population. The Cancer Prevention Study-3 (CPS-3) is one of a series of longitudinal studies sponsored by the American Cancer Society aimed at determining predictive risk factors associated with cancer. When participants enter the study, they complete a survey about their lives and family histories, providing information on factors that might cause or prevent the development of cancer. Then every few years the participants receive additional surveys to complete. In the end, hundreds of thousands of participants will be tracked over 20 years to determine which of them develop cancer and which do not.

Clearly, this type of research is important and potentially very informative. For instance, earlier longitudinal studies sponsored by the American Cancer Society provided some of the first scientific demonstrations of the now well-established links between increased rates of cancer and smoking (American Cancer Society, n.d.) (Figure 13).

As with any research strategy, longitudinal research is not without limitations. For one, these studies require an incredible time investment by the researcher and research participants. Given that some longitudinal studies take years, if not decades, to complete, the results will not be known for a considerable period of time. In addition to the time demands, these studies also require a substantial financial investment. Many researchers are unable to commit the resources necessary to see a longitudinal project through to the end.

Research participants must also be willing to continue their participation for an extended period of time, and this can be problematic. People move, get married and take new names, get ill, and eventually die. Even without significant life changes, some people may simply choose to discontinue their participation in the project. As a result, the attrition  rates, or reduction in the number of research participants due to dropouts, in longitudinal studies are quite high and increases over the course of a project. For this reason, researchers using this approach typically recruit many participants fully expecting that a substantial number will drop out before the end. As the study progresses, they continually check whether the sample still represents the larger population, and make adjustments as necessary.

Correlational Research

Did you know that as sales in ice cream increase, so does the overall rate of crime? Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone? There is no question that a relationship exists between ice cream and crime (e.g., Harper, 2013), but it would be pretty foolish to decide that one thing actually caused the other to occur.

It is much more likely that both ice cream sales and crime rates are related to the temperature outside. When the temperature is warm, there are lots of people out of their houses, interacting with each other, getting annoyed with one another, and sometimes committing crimes. Also, when it is warm outside, we are more likely to seek a cool treat like ice cream. How do we determine if there is indeed a relationship between two things? And when there is a relationship, how can we discern whether it is attributable to coincidence or causation?

Correlation Does Not Indicate Causation

Correlational research is useful because it allows us to discover the strength and direction of relationships that exist between two variables. However, correlation is limited because establishing the existence of a relationship tells us little about cause and effect . While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable , is actually causing the systematic movement in our variables of interest. In the ice cream/crime rate example mentioned earlier, temperature is a confounding variable that could account for the relationship between the two variables.

Even when we cannot point to clear confounding variables, we should not assume that a correlation between two variables implies that one variable causes changes in another. This can be frustrating when a cause-and-effect relationship seems clear and intuitive. Think back to our discussion of the research done by the American Cancer Society and how their research projects were some of the first demonstrations of the link between smoking and cancer. It seems reasonable to assume that smoking causes cancer, but if we were limited to correlational research , we would be overstepping our bounds by making this assumption.

Unfortunately, people mistakenly make claims of causation as a function of correlations all the time. Such claims are especially common in advertisements and news stories. For example, recent research found that people who eat cereal on a regular basis achieve healthier weights than those who rarely eat cereal (Frantzen, Treviño, Echon, Garcia-Dominic, & DiMarco, 2013; Barton et al., 2005). Guess how the cereal companies report this finding. Does eating cereal really cause an individual to maintain a healthy weight, or are there other possible explanations, such as, someone at a healthy weight is more likely to regularly eat a healthy breakfast than someone who is obese or someone who avoids meals in an attempt to diet (Figure 15)? While correlational research is invaluable in identifying relationships among variables, a major limitation is the inability to establish causality. Psychologists want to make statements about cause and effect, but the only way to do that is to conduct an experiment to answer a research question. The next section describes how scientific experiments incorporate methods that eliminate, or control for, alternative explanations, which allow researchers to explore how changes in one variable cause changes in another variable.

Watch this clip from Freakonomics for an example of how correlation does  not  indicate causation.

You can view the transcript for “Correlation vs. Causality: Freakonomics Movie” here (opens in new window) .

Illusory Correlations

The temptation to make erroneous cause-and-effect statements based on correlational research is not the only way we tend to misinterpret data. We also tend to make the mistake of illusory correlations, especially with unsystematic observations. Illusory correlations , or false correlations, occur when people believe that relationships exist between two things when no such relationship exists. One well-known illusory correlation is the supposed effect that the moon’s phases have on human behavior. Many people passionately assert that human behavior is affected by the phase of the moon, and specifically, that people act strangely when the moon is full (Figure 16).

There is no denying that the moon exerts a powerful influence on our planet. The ebb and flow of the ocean’s tides are tightly tied to the gravitational forces of the moon. Many people believe, therefore, that it is logical that we are affected by the moon as well. After all, our bodies are largely made up of water. A meta-analysis of nearly 40 studies consistently demonstrated, however, that the relationship between the moon and our behavior does not exist (Rotton & Kelly, 1985). While we may pay more attention to odd behavior during the full phase of the moon, the rates of odd behavior remain constant throughout the lunar cycle.

Why are we so apt to believe in illusory correlations like this? Often we read or hear about them and simply accept the information as valid. Or, we have a hunch about how something works and then look for evidence to support that hunch, ignoring evidence that would tell us our hunch is false; this is known as confirmation bias . Other times, we find illusory correlations based on the information that comes most easily to mind, even if that information is severely limited. And while we may feel confident that we can use these relationships to better understand and predict the world around us, illusory correlations can have significant drawbacks. For example, research suggests that illusory correlations—in which certain behaviors are inaccurately attributed to certain groups—are involved in the formation of prejudicial attitudes that can ultimately lead to discriminatory behavior (Fiedler, 2004).

We all have a tendency to make illusory correlations from time to time. Try to think of an illusory correlation that is held by you, a family member, or a close friend. How do you think this illusory correlation came about and what can be done in the future to combat them?

Experiments

Causality: conducting experiments and using the data, experimental hypothesis.

In order to conduct an experiment, a researcher must have a specific hypothesis to be tested. As you’ve learned, hypotheses can be formulated either through direct observation of the real world or after careful review of previous research. For example, if you think that children should not be allowed to watch violent programming on television because doing so would cause them to behave more violently, then you have basically formulated a hypothesis—namely, that watching violent television programs causes children to behave more violently. How might you have arrived at this particular hypothesis? You may have younger relatives who watch cartoons featuring characters using martial arts to save the world from evildoers, with an impressive array of punching, kicking, and defensive postures. You notice that after watching these programs for a while, your young relatives mimic the fighting behavior of the characters portrayed in the cartoon (Figure 17).

These sorts of personal observations are what often lead us to formulate a specific hypothesis, but we cannot use limited personal observations and anecdotal evidence to rigorously test our hypothesis. Instead, to find out if real-world data supports our hypothesis, we have to conduct an experiment.

Designing an Experiment

The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group  gets the experimental manipulation—that is, the treatment or variable being tested (in this case, violent TV images)—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to experimental manipulation rather than chance.

In our example of how violent television programming might affect violent behavior in children, we have the experimental group view violent television programming for a specified time and then measure their violent behavior. We measure the violent behavior in our control group after they watch nonviolent television programming for the same amount of time. It is important for the control group to be treated similarly to the experimental group, with the exception that the control group does not receive the experimental manipulation. Therefore, we have the control group watch non-violent television programming for the same amount of time as the experimental group.

We also need to precisely define, or operationalize, what is considered violent and nonviolent. An operational definition is a description of how we will measure our variables, and it is important in allowing others understand exactly how and what a researcher measures in a particular experiment. In operationalizing violent behavior, we might choose to count only physical acts like kicking or punching as instances of this behavior, or we also may choose to include angry verbal exchanges. Whatever we determine, it is important that we operationalize violent behavior in such a way that anyone who hears about our study for the first time knows exactly what we mean by violence. This aids peoples’ ability to interpret our data as well as their capacity to repeat our experiment should they choose to do so.

Once we have operationalized what is considered violent television programming and what is considered violent behavior from our experiment participants, we need to establish how we will run our experiment. In this case, we might have participants watch a 30-minute television program (either violent or nonviolent, depending on their group membership) before sending them out to a playground for an hour where their behavior is observed and the number and type of violent acts is recorded.

Ideally, the people who observe and record the children’s behavior are unaware of who was assigned to the experimental or control group, in order to control for experimenter bias. Experimenter bias refers to the possibility that a researcher’s expectations might skew the results of the study. Remember, conducting an experiment requires a lot of planning, and the people involved in the research project have a vested interest in supporting their hypotheses. If the observers knew which child was in which group, it might influence how much attention they paid to each child’s behavior as well as how they interpreted that behavior. By being blind to which child is in which group, we protect against those biases. This situation is a single-blind study , meaning that one of the groups (participants) are unaware as to which group they are in (experiment or control group) while the researcher who developed the experiment knows which participants are in each group.

In a double-blind study , both the researchers and the participants are blind to group assignments. Why would a researcher want to run a study where no one knows who is in which group? Because by doing so, we can control for both experimenter and participant expectations. If you are familiar with the phrase placebo effect, you already have some idea as to why this is an important consideration. The placebo effect occurs when people’s expectations or beliefs influence or determine their experience in a given situation. In other words, simply expecting something to happen can actually make it happen.

The placebo effect is commonly described in terms of testing the effectiveness of a new medication. Imagine that you work in a pharmaceutical company, and you think you have a new drug that is effective in treating depression. To demonstrate that your medication is effective, you run an experiment with two groups: The experimental group receives the medication, and the control group does not. But you don’t want participants to know whether they received the drug or not.

Why is that? Imagine that you are a participant in this study, and you have just taken a pill that you think will improve your mood. Because you expect the pill to have an effect, you might feel better simply because you took the pill and not because of any drug actually contained in the pill—this is the placebo effect.

To make sure that any effects on mood are due to the drug and not due to expectations, the control group receives a placebo (in this case a sugar pill). Now everyone gets a pill, and once again neither the researcher nor the experimental participants know who got the drug and who got the sugar pill. Any differences in mood between the experimental and control groups can now be attributed to the drug itself rather than to experimenter bias or participant expectations (Figure 18).

Independent and Dependent Variables

In a research experiment, we strive to study whether changes in one thing cause changes in another. To achieve this, we must pay attention to two important variables, or things that can be changed, in any experimental study: the independent variable and the dependent variable. An independent variable is manipulated or controlled by the experimenter. In a well-designed experimental study, the independent variable is the only important difference between the experimental and control groups. In our example of how violent television programs affect children’s display of violent behavior, the independent variable is the type of program—violent or nonviolent—viewed by participants in the study (Figure 19). A dependent variable is what the researcher measures to see how much effect the independent variable had. In our example, the dependent variable is the number of violent acts displayed by the experimental participants.

We expect that the dependent variable will change as a function of the independent variable. In other words, the dependent variable depends on the independent variable. A good way to think about the relationship between the independent and dependent variables is with this question: What effect does the independent variable have on the dependent variable? Returning to our example, what effect does watching a half hour of violent television programming or nonviolent television programming have on the number of incidents of physical aggression displayed on the playground?

Selecting and Assigning Experimental Participants

Now that our study is designed, we need to obtain a sample of individuals to include in our experiment. Our study involves human participants so we need to determine who to include. Participants  are the subjects of psychological research, and as the name implies, individuals who are involved in psychological research actively participate in the process. Often, psychological research projects rely on college students to serve as participants. In fact, the vast majority of research in psychology subfields has historically involved students as research participants (Sears, 1986; Arnett, 2008). But are college students truly representative of the general population? College students tend to be younger, more educated, more liberal, and less diverse than the general population. Although using students as test subjects is an accepted practice, relying on such a limited pool of research participants can be problematic because it is difficult to generalize findings to the larger population.

Our hypothetical experiment involves children, and we must first generate a sample of child participants. Samples are used because populations are usually too large to reasonably involve every member in our particular experiment (Figure 20). If possible, we should use a random sample   (there are other types of samples, but for the purposes of this section, we will focus on random samples). A random sample is a subset of a larger population in which every member of the population has an equal chance of being selected. Random samples are preferred because if the sample is large enough we can be reasonably sure that the participating individuals are representative of the larger population. This means that the percentages of characteristics in the sample—sex, ethnicity, socioeconomic level, and any other characteristics that might affect the results—are close to those percentages in the larger population.

In our example, let’s say we decide our population of interest is fourth graders. But all fourth graders is a very large population, so we need to be more specific; instead we might say our population of interest is all fourth graders in a particular city. We should include students from various income brackets, family situations, races, ethnicities, religions, and geographic areas of town. With this more manageable population, we can work with the local schools in selecting a random sample of around 200 fourth graders who we want to participate in our experiment.

In summary, because we cannot test all of the fourth graders in a city, we want to find a group of about 200 that reflects the composition of that city. With a representative group, we can generalize our findings to the larger population without fear of our sample being biased in some way.

Now that we have a sample, the next step of the experimental process is to split the participants into experimental and control groups through random assignment. With random assignment , all participants have an equal chance of being assigned to either group. There is statistical software that will randomly assign each of the fourth graders in the sample to either the experimental or the control group.

Random assignment is critical for sound experimental design. With sufficiently large samples, random assignment makes it unlikely that there are systematic differences between the groups. So, for instance, it would be very unlikely that we would get one group composed entirely of males, a given ethnic identity, or a given religious ideology. This is important because if the groups were systematically different before the experiment began, we would not know the origin of any differences we find between the groups: Were the differences preexisting, or were they caused by manipulation of the independent variable? Random assignment allows us to assume that any differences observed between experimental and control groups result from the manipulation of the independent variable.

Issues to Consider

While experiments allow scientists to make cause-and-effect claims, they are not without problems. True experiments require the experimenter to manipulate an independent variable, and that can complicate many questions that psychologists might want to address. For instance, imagine that you want to know what effect sex (the independent variable) has on spatial memory (the dependent variable). Although you can certainly look for differences between males and females on a task that taps into spatial memory, you cannot directly control a person’s sex. We categorize this type of research approach as quasi-experimental and recognize that we cannot make cause-and-effect claims in these circumstances.

Experimenters are also limited by ethical constraints. For instance, you would not be able to conduct an experiment designed to determine if experiencing abuse as a child leads to lower levels of self-esteem among adults. To conduct such an experiment, you would need to randomly assign some experimental participants to a group that receives abuse, and that experiment would be unethical.

Introduction to Statistical Thinking

Psychologists use statistics to assist them in analyzing data, and also to give more precise measurements to describe whether something is statistically significant. Analyzing data using statistics enables researchers to find patterns, make claims, and share their results with others. In this section, you’ll learn about some of the tools that psychologists use in statistical analysis.

• Define reliability and validity
• Describe the importance of distributional thinking and the role of p-values in statistical inference
• Describe the role of random sampling and random assignment in drawing cause-and-effect conclusions
• Describe the basic structure of a psychological research article

Interpreting Experimental Findings

Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this experiment 100 times, we would expect to find the same results at least 95 times out of 100.

The greatest strength of experiments is the ability to assert that any significant differences in the findings are caused by the independent variable. This occurs because random selection, random assignment, and a design that limits the effects of both experimenter bias and participant expectancy should create groups that are similar in composition and treatment. Therefore, any difference between the groups is attributable to the independent variable, and now we can finally make a causal statement. If we find that watching a violent television program results in more violent behavior than watching a nonviolent program, we can safely say that watching violent television programs causes an increase in the display of violent behavior.

Reporting Research

When psychologists complete a research project, they generally want to share their findings with other scientists. The American Psychological Association (APA) publishes a manual detailing how to write a paper for submission to scientific journals. Unlike an article that might be published in a magazine like Psychology Today, which targets a general audience with an interest in psychology, scientific journals generally publish peer-reviewed journal articles aimed at an audience of professionals and scholars who are actively involved in research themselves.

A peer-reviewed journal article is read by several other scientists (generally anonymously) with expertise in the subject matter. These peer reviewers provide feedback—to both the author and the journal editor—regarding the quality of the draft. Peer reviewers look for a strong rationale for the research being described, a clear description of how the research was conducted, and evidence that the research was conducted in an ethical manner. They also look for flaws in the study’s design, methods, and statistical analyses. They check that the conclusions drawn by the authors seem reasonable given the observations made during the research. Peer reviewers also comment on how valuable the research is in advancing the discipline’s knowledge. This helps prevent unnecessary duplication of research findings in the scientific literature and, to some extent, ensures that each research article provides new information. Ultimately, the journal editor will compile all of the peer reviewer feedback and determine whether the article will be published in its current state (a rare occurrence), published with revisions, or not accepted for publication.

Peer review provides some degree of quality control for psychological research. Poorly conceived or executed studies can be weeded out, and even well-designed research can be improved by the revisions suggested. Peer review also ensures that the research is described clearly enough to allow other scientists to replicate it, meaning they can repeat the experiment using different samples to determine reliability. Sometimes replications involve additional measures that expand on the original finding. In any case, each replication serves to provide more evidence to support the original research findings. Successful replications of published research make scientists more apt to adopt those findings, while repeated failures tend to cast doubt on the legitimacy of the original article and lead scientists to look elsewhere. For example, it would be a major advancement in the medical field if a published study indicated that taking a new drug helped individuals achieve a healthy weight without changing their diet. But if other scientists could not replicate the results, the original study’s claims would be questioned.

Dig Deeper: The Vaccine-Autism Myth and the Retraction of Published Studies

Some scientists have claimed that routine childhood vaccines cause some children to develop autism, and, in fact, several peer-reviewed publications published research making these claims. Since the initial reports, large-scale epidemiological research has suggested that vaccinations are not responsible for causing autism and that it is much safer to have your child vaccinated than not. Furthermore, several of the original studies making this claim have since been retracted.

A published piece of work can be rescinded when data is called into question because of falsification, fabrication, or serious research design problems. Once rescinded, the scientific community is informed that there are serious problems with the original publication. Retractions can be initiated by the researcher who led the study, by research collaborators, by the institution that employed the researcher, or by the editorial board of the journal in which the article was originally published. In the vaccine-autism case, the retraction was made because of a significant conflict of interest in which the leading researcher had a financial interest in establishing a link between childhood vaccines and autism (Offit, 2008). Unfortunately, the initial studies received so much media attention that many parents around the world became hesitant to have their children vaccinated (Figure 21). For more information about how the vaccine/autism story unfolded, as well as the repercussions of this story, take a look at Paul Offit’s book, Autism’s False Prophets: Bad Science, Risky Medicine, and the Search for a Cure.

Reliability and Validity

Dig deeper:  everyday connection: how valid is the sat.

Standardized tests like the SAT are supposed to measure an individual’s aptitude for a college education, but how reliable and valid are such tests? Research conducted by the College Board suggests that scores on the SAT have high predictive validity for first-year college students’ GPA (Kobrin, Patterson, Shaw, Mattern, & Barbuti, 2008). In this context, predictive validity refers to the test’s ability to effectively predict the GPA of college freshmen. Given that many institutions of higher education require the SAT for admission, this high degree of predictive validity might be comforting.

However, the emphasis placed on SAT scores in college admissions has generated some controversy on a number of fronts. For one, some researchers assert that the SAT is a biased test that places minority students at a disadvantage and unfairly reduces the likelihood of being admitted into a college (Santelices & Wilson, 2010). Additionally, some research has suggested that the predictive validity of the SAT is grossly exaggerated in how well it is able to predict the GPA of first-year college students. In fact, it has been suggested that the SAT’s predictive validity may be overestimated by as much as 150% (Rothstein, 2004). Many institutions of higher education are beginning to consider de-emphasizing the significance of SAT scores in making admission decisions (Rimer, 2008).

In 2014, College Board president David Coleman expressed his awareness of these problems, recognizing that college success is more accurately predicted by high school grades than by SAT scores. To address these concerns, he has called for significant changes to the SAT exam (Lewin, 2014).

Statistical Significance

Does drinking coffee actually increase your life expectancy? A recent study (Freedman, Park, Abnet, Hollenbeck, & Sinha, 2012) found that men who drank at least six cups of coffee a day also had a 10% lower chance of dying (women’s chances were 15% lower) than those who drank none. Does this mean you should pick up or increase your own coffee habit? We will explore these results in more depth in the next section about drawing conclusions from statistics. Modern society has become awash in studies such as this; you can read about several such studies in the news every day.

Conducting such a study well, and interpreting the results of such studies requires understanding basic ideas of statistics , the science of gaining insight from data. Key components to a statistical investigation are:

• Planning the study: Start by asking a testable research question and deciding how to collect data. For example, how long was the study period of the coffee study? How many people were recruited for the study, how were they recruited, and from where? How old were they? What other variables were recorded about the individuals? Were changes made to the participants’ coffee habits during the course of the study?
• Examining the data: What are appropriate ways to examine the data? What graphs are relevant, and what do they reveal? What descriptive statistics can be calculated to summarize relevant aspects of the data, and what do they reveal? What patterns do you see in the data? Are there any individual observations that deviate from the overall pattern, and what do they reveal? For example, in the coffee study, did the proportions differ when we compared the smokers to the non-smokers?
• Inferring from the data: What are valid statistical methods for drawing inferences “beyond” the data you collected? In the coffee study, is the 10%–15% reduction in risk of death something that could have happened just by chance?
• Drawing conclusions: Based on what you learned from your data, what conclusions can you draw? Who do you think these conclusions apply to? (Were the people in the coffee study older? Healthy? Living in cities?) Can you draw a cause-and-effect conclusion about your treatments? (Are scientists now saying that the coffee drinking is the cause of the decreased risk of death?)

Notice that the numerical analysis (“crunching numbers” on the computer) comprises only a small part of overall statistical investigation. In this section, you will see how we can answer some of these questions and what questions you should be asking about any statistical investigation you read about.

Distributional Thinking

When data are collected to address a particular question, an important first step is to think of meaningful ways to organize and examine the data. Let’s take a look at an example.

Example 1 : Researchers investigated whether cancer pamphlets are written at an appropriate level to be read and understood by cancer patients (Short, Moriarty, & Cooley, 1995). Tests of reading ability were given to 63 patients. In addition, readability level was determined for a sample of 30 pamphlets, based on characteristics such as the lengths of words and sentences in the pamphlet. The results, reported in terms of grade levels, are displayed in Figure 23.

• Data vary . More specifically, values of a variable (such as reading level of a cancer patient or readability level of a cancer pamphlet) vary.
• Analyzing the pattern of variation, called the distribution of the variable, often reveals insights.

Addressing the research question of whether the cancer pamphlets are written at appropriate levels for the cancer patients requires comparing the two distributions. A naïve comparison might focus only on the centers of the distributions. Both medians turn out to be ninth grade, but considering only medians ignores the variability and the overall distributions of these data. A more illuminating approach is to compare the entire distributions, for example with a graph, as in Figure 24.

Figure 24 makes clear that the two distributions are not well aligned at all. The most glaring discrepancy is that many patients (17/63, or 27%, to be precise) have a reading level below that of the most readable pamphlet. These patients will need help to understand the information provided in the cancer pamphlets. Notice that this conclusion follows from considering the distributions as a whole, not simply measures of center or variability, and that the graph contrasts those distributions more immediately than the frequency tables.

Finding Significance in Data

Even when we find patterns in data, often there is still uncertainty in various aspects of the data. For example, there may be potential for measurement errors (even your own body temperature can fluctuate by almost 1°F over the course of the day). Or we may only have a “snapshot” of observations from a more long-term process or only a small subset of individuals from the population of interest. In such cases, how can we determine whether patterns we see in our small set of data is convincing evidence of a systematic phenomenon in the larger process or population? Let’s take a look at another example.

Example 2 : In a study reported in the November 2007 issue of Nature , researchers investigated whether pre-verbal infants take into account an individual’s actions toward others in evaluating that individual as appealing or aversive (Hamlin, Wynn, & Bloom, 2007). In one component of the study, 10-month-old infants were shown a “climber” character (a piece of wood with “googly” eyes glued onto it) that could not make it up a hill in two tries. Then the infants were shown two scenarios for the climber’s next try, one where the climber was pushed to the top of the hill by another character (“helper”), and one where the climber was pushed back down the hill by another character (“hinderer”). The infant was alternately shown these two scenarios several times. Then the infant was presented with two pieces of wood (representing the helper and the hinderer characters) and asked to pick one to play with.

The researchers found that of the 16 infants who made a clear choice, 14 chose to play with the helper toy. One possible explanation for this clear majority result is that the helping behavior of the one toy increases the infants’ likelihood of choosing that toy. But are there other possible explanations? What about the color of the toy? Well, prior to collecting the data, the researchers arranged so that each color and shape (red square and blue circle) would be seen by the same number of infants. Or maybe the infants had right-handed tendencies and so picked whichever toy was closer to their right hand?

Well, prior to collecting the data, the researchers arranged it so half the infants saw the helper toy on the right and half on the left. Or, maybe the shapes of these wooden characters (square, triangle, circle) had an effect? Perhaps, but again, the researchers controlled for this by rotating which shape was the helper toy, the hinderer toy, and the climber. When designing experiments, it is important to control for as many variables as might affect the responses as possible. It is beginning to appear that the researchers accounted for all the other plausible explanations. But there is one more important consideration that cannot be controlled—if we did the study again with these 16 infants, they might not make the same choices. In other words, there is some randomness inherent in their selection process.

Maybe each infant had no genuine preference at all, and it was simply “random luck” that led to 14 infants picking the helper toy. Although this random component cannot be controlled, we can apply a probability model to investigate the pattern of results that would occur in the long run if random chance were the only factor.

If the infants were equally likely to pick between the two toys, then each infant had a 50% chance of picking the helper toy. It’s like each infant tossed a coin, and if it landed heads, the infant picked the helper toy. So if we tossed a coin 16 times, could it land heads 14 times? Sure, it’s possible, but it turns out to be very unlikely. Getting 14 (or more) heads in 16 tosses is about as likely as tossing a coin and getting 9 heads in a row. This probability is referred to as a p-value . The p-value represents the likelihood that experimental results happened by chance. Within psychology, the most common standard for p-values is “p < .05”. What this means is that there is less than a 5% probability that the results happened just by random chance, and therefore a 95% probability that the results reflect a meaningful pattern in human psychology. We call this statistical significance .

So, in the study above, if we assume that each infant was choosing equally, then the probability that 14 or more out of 16 infants would choose the helper toy is found to be 0.0021. We have only two logical possibilities: either the infants have a genuine preference for the helper toy, or the infants have no preference (50/50) and an outcome that would occur only 2 times in 1,000 iterations happened in this study. Because this p-value of 0.0021 is quite small, we conclude that the study provides very strong evidence that these infants have a genuine preference for the helper toy.

If we compare the p-value to some cut-off value, like 0.05, we see that the p=value is smaller. Because the p-value is smaller than that cut-off value, then we reject the hypothesis that only random chance was at play here. In this case, these researchers would conclude that significantly more than half of the infants in the study chose the helper toy, giving strong evidence of a genuine preference for the toy with the helping behavior.

Drawing Conclusions from Statistics

Generalizability.

One limitation to the study mentioned previously about the babies choosing the “helper” toy is that the conclusion only applies to the 16 infants in the study. We don’t know much about how those 16 infants were selected. Suppose we want to select a subset of individuals (a sample ) from a much larger group of individuals (the population ) in such a way that conclusions from the sample can be generalized to the larger population. This is the question faced by pollsters every day.

Example 3 : The General Social Survey (GSS) is a survey on societal trends conducted every other year in the United States. Based on a sample of about 2,000 adult Americans, researchers make claims about what percentage of the U.S. population consider themselves to be “liberal,” what percentage consider themselves “happy,” what percentage feel “rushed” in their daily lives, and many other issues. The key to making these claims about the larger population of all American adults lies in how the sample is selected. The goal is to select a sample that is representative of the population, and a common way to achieve this goal is to select a r andom sample  that gives every member of the population an equal chance of being selected for the sample. In its simplest form, random sampling involves numbering every member of the population and then using a computer to randomly select the subset to be surveyed. Most polls don’t operate exactly like this, but they do use probability-based sampling methods to select individuals from nationally representative panels.

In 2004, the GSS reported that 817 of 977 respondents (or 83.6%) indicated that they always or sometimes feel rushed. This is a clear majority, but we again need to consider variation due to random sampling . Fortunately, we can use the same probability model we did in the previous example to investigate the probable size of this error. (Note, we can use the coin-tossing model when the actual population size is much, much larger than the sample size, as then we can still consider the probability to be the same for every individual in the sample.) This probability model predicts that the sample result will be within 3 percentage points of the population value (roughly 1 over the square root of the sample size, the margin of error. A statistician would conclude, with 95% confidence, that between 80.6% and 86.6% of all adult Americans in 2004 would have responded that they sometimes or always feel rushed.

The key to the margin of error is that when we use a probability sampling method, we can make claims about how often (in the long run, with repeated random sampling) the sample result would fall within a certain distance from the unknown population value by chance (meaning by random sampling variation) alone. Conversely, non-random samples are often suspect to bias, meaning the sampling method systematically over-represents some segments of the population and under-represents others. We also still need to consider other sources of bias, such as individuals not responding honestly. These sources of error are not measured by the margin of error.

Cause and Effect

In many research studies, the primary question of interest concerns differences between groups. Then the question becomes how were the groups formed (e.g., selecting people who already drink coffee vs. those who don’t). In some studies, the researchers actively form the groups themselves. But then we have a similar question—could any differences we observe in the groups be an artifact of that group-formation process? Or maybe the difference we observe in the groups is so large that we can discount a “fluke” in the group-formation process as a reasonable explanation for what we find?

Example 4 : A psychology study investigated whether people tend to display more creativity when they are thinking about intrinsic (internal) or extrinsic (external) motivations (Ramsey & Schafer, 2002, based on a study by Amabile, 1985). The subjects were 47 people with extensive experience with creative writing. Subjects began by answering survey questions about either intrinsic motivations for writing (such as the pleasure of self-expression) or extrinsic motivations (such as public recognition). Then all subjects were instructed to write a haiku, and those poems were evaluated for creativity by a panel of judges. The researchers conjectured beforehand that subjects who were thinking about intrinsic motivations would display more creativity than subjects who were thinking about extrinsic motivations. The creativity scores from the 47 subjects in this study are displayed in Figure 26, where higher scores indicate more creativity.

In this example, the key question is whether the type of motivation affects creativity scores. In particular, do subjects who were asked about intrinsic motivations tend to have higher creativity scores than subjects who were asked about extrinsic motivations?

Figure 26 reveals that both motivation groups saw considerable variability in creativity scores, and these scores have considerable overlap between the groups. In other words, it’s certainly not always the case that those with extrinsic motivations have higher creativity than those with intrinsic motivations, but there may still be a statistical tendency in this direction. (Psychologist Keith Stanovich (2013) refers to people’s difficulties with thinking about such probabilistic tendencies as “the Achilles heel of human cognition.”)

The mean creativity score is 19.88 for the intrinsic group, compared to 15.74 for the extrinsic group, which supports the researchers’ conjecture. Yet comparing only the means of the two groups fails to consider the variability of creativity scores in the groups. We can measure variability with statistics using, for instance, the standard deviation: 5.25 for the extrinsic group and 4.40 for the intrinsic group. The standard deviations tell us that most of the creativity scores are within about 5 points of the mean score in each group. We see that the mean score for the intrinsic group lies within one standard deviation of the mean score for extrinsic group. So, although there is a tendency for the creativity scores to be higher in the intrinsic group, on average, the difference is not extremely large.

We again want to consider possible explanations for this difference. The study only involved individuals with extensive creative writing experience. Although this limits the population to which we can generalize, it does not explain why the mean creativity score was a bit larger for the intrinsic group than for the extrinsic group. Maybe women tend to receive higher creativity scores? Here is where we need to focus on how the individuals were assigned to the motivation groups. If only women were in the intrinsic motivation group and only men in the extrinsic group, then this would present a problem because we wouldn’t know if the intrinsic group did better because of the different type of motivation or because they were women. However, the researchers guarded against such a problem by randomly assigning the individuals to the motivation groups. Like flipping a coin, each individual was just as likely to be assigned to either type of motivation. Why is this helpful? Because this random assignment  tends to balance out all the variables related to creativity we can think of, and even those we don’t think of in advance, between the two groups. So we should have a similar male/female split between the two groups; we should have a similar age distribution between the two groups; we should have a similar distribution of educational background between the two groups; and so on. Random assignment should produce groups that are as similar as possible except for the type of motivation, which presumably eliminates all those other variables as possible explanations for the observed tendency for higher scores in the intrinsic group.

But does this always work? No, so by “luck of the draw” the groups may be a little different prior to answering the motivation survey. So then the question is, is it possible that an unlucky random assignment is responsible for the observed difference in creativity scores between the groups? In other words, suppose each individual’s poem was going to get the same creativity score no matter which group they were assigned to, that the type of motivation in no way impacted their score. Then how often would the random-assignment process alone lead to a difference in mean creativity scores as large (or larger) than 19.88 – 15.74 = 4.14 points?

We again want to apply to a probability model to approximate a p-value , but this time the model will be a bit different. Think of writing everyone’s creativity scores on an index card, shuffling up the index cards, and then dealing out 23 to the extrinsic motivation group and 24 to the intrinsic motivation group, and finding the difference in the group means. We (better yet, the computer) can repeat this process over and over to see how often, when the scores don’t change, random assignment leads to a difference in means at least as large as 4.41. Figure 27 shows the results from 1,000 such hypothetical random assignments for these scores.

Only 2 of the 1,000 simulated random assignments produced a difference in group means of 4.41 or larger. In other words, the approximate p-value is 2/1000 = 0.002. This small p-value indicates that it would be very surprising for the random assignment process alone to produce such a large difference in group means. Therefore, as with Example 2, we have strong evidence that focusing on intrinsic motivations tends to increase creativity scores, as compared to thinking about extrinsic motivations.

Notice that the previous statement implies a cause-and-effect relationship between motivation and creativity score; is such a strong conclusion justified? Yes, because of the random assignment used in the study. That should have balanced out any other variables between the two groups, so now that the small p-value convinces us that the higher mean in the intrinsic group wasn’t just a coincidence, the only reasonable explanation left is the difference in the type of motivation. Can we generalize this conclusion to everyone? Not necessarily—we could cautiously generalize this conclusion to individuals with extensive experience in creative writing similar the individuals in this study, but we would still want to know more about how these individuals were selected to participate.

Statistical thinking involves the careful design of a study to collect meaningful data to answer a focused research question, detailed analysis of patterns in the data, and drawing conclusions that go beyond the observed data. Random sampling is paramount to generalizing results from our sample to a larger population, and random assignment is key to drawing cause-and-effect conclusions. With both kinds of randomness, probability models help us assess how much random variation we can expect in our results, in order to determine whether our results could happen by chance alone and to estimate a margin of error.

So where does this leave us with regard to the coffee study mentioned previously (the Freedman, Park, Abnet, Hollenbeck, & Sinha, 2012 found that men who drank at least six cups of coffee a day had a 10% lower chance of dying (women 15% lower) than those who drank none)? We can answer many of the questions:

• This was a 14-year study conducted by researchers at the National Cancer Institute.
• The results were published in the June issue of the New England Journal of Medicine , a respected, peer-reviewed journal.
• The study reviewed coffee habits of more than 402,000 people ages 50 to 71 from six states and two metropolitan areas. Those with cancer, heart disease, and stroke were excluded at the start of the study. Coffee consumption was assessed once at the start of the study.
• About 52,000 people died during the course of the study.
• People who drank between two and five cups of coffee daily showed a lower risk as well, but the amount of reduction increased for those drinking six or more cups.
• The sample sizes were fairly large and so the p-values are quite small, even though percent reduction in risk was not extremely large (dropping from a 12% chance to about 10%–11%).
• Whether coffee was caffeinated or decaffeinated did not appear to affect the results.
• This was an observational study, so no cause-and-effect conclusions can be drawn between coffee drinking and increased longevity, contrary to the impression conveyed by many news headlines about this study. In particular, it’s possible that those with chronic diseases don’t tend to drink coffee.

This study needs to be reviewed in the larger context of similar studies and consistency of results across studies, with the constant caution that this was not a randomized experiment. Whereas a statistical analysis can still “adjust” for other potential confounding variables, we are not yet convinced that researchers have identified them all or completely isolated why this decrease in death risk is evident. Researchers can now take the findings of this study and develop more focused studies that address new questions.

Explore these outside resources to learn more about applied statistics:

• Video about p-values:  P-Value Extravaganza
• Interactive web applets for teaching and learning statistics
• Inter-university Consortium for Political and Social Research  where you can find and analyze data.
• The Consortium for the Advancement of Undergraduate Statistics
• Find a recent research article in your field and answer the following: What was the primary research question? How were individuals selected to participate in the study? Were summary results provided? How strong is the evidence presented in favor or against the research question? Was random assignment used? Summarize the main conclusions from the study, addressing the issues of statistical significance, statistical confidence, generalizability, and cause and effect. Do you agree with the conclusions drawn from this study, based on the study design and the results presented?
• Is it reasonable to use a random sample of 1,000 individuals to draw conclusions about all U.S. adults? Explain why or why not.

How to Read Research

In this course and throughout your academic career, you’ll be reading journal articles (meaning they were published by experts in a peer-reviewed journal) and reports that explain psychological research. It’s important to understand the format of these articles so that you can read them strategically and understand the information presented. Scientific articles vary in content or structure, depending on the type of journal to which they will be submitted. Psychological articles and many papers in the social sciences follow the writing guidelines and format dictated by the American Psychological Association (APA). In general, the structure follows: abstract, introduction, methods, results, discussion, and references.

• Abstract : the abstract is the concise summary of the article. It summarizes the most important features of the manuscript, providing the reader with a global first impression on the article. It is generally just one paragraph that explains the experiment as well as a short synopsis of the results.
• Introduction : this section provides background information about the origin and purpose of performing the experiment or study. It reviews previous research and presents existing theories on the topic.
• Method : this section covers the methodologies used to investigate the research question, including the identification of participants , procedures , and  materials  as well as a description of the actual procedure . It should be sufficiently detailed to allow for replication.
• Results : the results section presents key findings of the research, including reference to indicators of statistical significance.
• Discussion : this section provides an interpretation of the findings, states their significance for current research, and derives implications for theory and practice. Alternative interpretations for findings are also provided, particularly when it is not possible to conclude for the directionality of the effects. In the discussion, authors also acknowledge the strengths and limitations/weaknesses of the study and offer concrete directions about for future research.

Watch this 3-minute video for an explanation on how to read scholarly articles. Look closely at the example article shared just before the two minute mark.

https://digitalcommons.coastal.edu/kimbel-library-instructional-videos/9/

Practice identifying these key components in the following experiment: Food-Induced Emotional Resonance Improves Emotion Recognition.

In this chapter, you learned to

• define and apply the scientific method to psychology
• describe the strengths and weaknesses of descriptive, experimental, and correlational research
• define the basic elements of a statistical investigation

Putting It Together: Psychological Research

Psychologists use the scientific method to examine human behavior and mental processes. Some of the methods you learned about include descriptive, experimental, and correlational research designs.

Watch the CrashCourse video to review the material you learned, then read through the following examples and see if you can come up with your own design for each type of study.

You can view the transcript for “Psychological Research: Crash Course Psychology #2” here (opens in new window).

Case Study: a detailed analysis of a particular person, group, business, event, etc. This approach is commonly used to to learn more about rare examples with the goal of describing that particular thing.

• Ted Bundy was one of America’s most notorious serial killers who murdered at least 30 women and was executed in 1989. Dr. Al Carlisle evaluated Bundy when he was first arrested and conducted a psychological analysis of Bundy’s development of his sexual fantasies merging into reality (Ramsland, 2012). Carlisle believes that there was a gradual evolution of three processes that guided his actions: fantasy, dissociation, and compartmentalization (Ramsland, 2012). Read   Imagining Ted Bundy  (http://goo.gl/rGqcUv) for more information on this case study.

Naturalistic Observation : a researcher unobtrusively collects information without the participant’s awareness.

• Drain and Engelhardt (2013) observed six nonverbal children with autism’s evoked and spontaneous communicative acts. Each of the children attended a school for children with autism and were in different classes. They were observed for 30 minutes of each school day. By observing these children without them knowing, they were able to see true communicative acts without any external influences.

Survey : participants are asked to provide information or responses to questions on a survey or structure assessment.

• Educational psychologists can ask students to report their grade point average and what, if anything, they eat for breakfast on an average day. A healthy breakfast has been associated with better academic performance (Digangi’s 1999).
• Anderson (1987) tried to find the relationship between uncomfortably hot temperatures and aggressive behavior, which was then looked at with two studies done on violent and nonviolent crime. Based on previous research that had been done by Anderson and Anderson (1984), it was predicted that violent crimes would be more prevalent during the hotter time of year and the years in which it was hotter weather in general. The study confirmed this prediction.

Longitudinal Study: researchers   recruit a sample of participants and track them for an extended period of time.

• In a study of a representative sample of 856 children Eron and his colleagues (1972) found that a boy’s exposure to media violence at age eight was significantly related to his aggressive behavior ten years later, after he graduated from high school.

Cross-Sectional Study:  researchers gather participants from different groups (commonly different ages) and look for differences between the groups.

• In 1996, Russell surveyed people of varying age groups and found that people in their 20s tend to report being more lonely than people in their 70s.

Correlational Design:  two different variables are measured to determine whether there is a relationship between them.

• Thornhill et al. (2003) had people rate how physically attractive they found other people to be. They then had them separately smell t-shirts those people had worn (without knowing which clothes belonged to whom) and rate how good or bad their body oder was. They found that the more attractive someone was the more pleasant their body order was rated to be.
• Clinical psychologists can test a new pharmaceutical treatment for depression by giving some patients the new pill and others an already-tested one to see which is the more effective treatment.

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American Psychological Association. (n.d.). Research with animals in psychology. Retrieved from https://www.apa.org/research/responsible/research-animals.pdf

Arnett, J. (2008). The neglected 95%: Why American psychology needs to become less American. American Psychologist, 63(7), 602–614.

Barton, B. A., Eldridge, A. L., Thompson, D., Affenito, S. G., Striegel-Moore, R. H., Franko, D. L., . . . Crockett, S. J. (2005). The relationship of breakfast and cereal consumption to nutrient intake and body mass index: The national heart, lung, and blood institute growth and health study. Journal of the American Dietetic Association, 105(9), 1383–1389. Retrieved from http://dx.doi.org/10.1016/j.jada.2005.06.003

Chwalisz, K., Diener, E., & Gallagher, D. (1988). Autonomic arousal feedback and emotional experience: Evidence from the spinal cord injured. Journal of Personality and Social Psychology, 54, 820–828.

Dominus, S. (2011, May 25). Could conjoined twins share a mind? New York Times Sunday Magazine. Retrieved from http://www.nytimes.com/2011/05/29/magazine/could-conjoined-twins-share-a-mind.html?_r=5&hp&

Fanger, S. M., Frankel, L. A., & Hazen, N. (2012). Peer exclusion in preschool children’s play: Naturalistic observations in a playground setting. Merrill-Palmer Quarterly, 58, 224–254.

Fiedler, K. (2004). Illusory correlation. In R. F. Pohl (Ed.), Cognitive illusions: A handbook on fallacies and biases in thinking, judgment and memory (pp. 97–114). New York, NY: Psychology Press.

Frantzen, L. B., Treviño, R. P., Echon, R. M., Garcia-Dominic, O., & DiMarco, N. (2013). Association between frequency of ready-to-eat cereal consumption, nutrient intakes, and body mass index in fourth- to sixth-grade low-income minority children. Journal of the Academy of Nutrition and Dietetics, 113(4), 511–519.

Harper, J. (2013, July 5). Ice cream and crime: Where cold cuisine and hot disputes intersect. The Times-Picaune. Retrieved from http://www.nola.com/crime/index.ssf/2013/07/ice_cream_and_crime_where_hot.html

Jenkins, W. J., Ruppel, S. E., Kizer, J. B., Yehl, J. L., & Griffin, J. L. (2012). An examination of post 9-11 attitudes towards Arab Americans. North American Journal of Psychology, 14, 77–84.

Jones, J. M. (2013, May 13). Same-sex marriage support solidifies above 50% in U.S. Gallup Politics. Retrieved from http://www.gallup.com/poll/162398/sex-marriage-support-solidifies-above.aspx

Kobrin, J. L., Patterson, B. F., Shaw, E. J., Mattern, K. D., & Barbuti, S. M. (2008). Validity of the SAT for predicting first-year college grade point average (Research Report No. 2008-5). Retrieved from https://research.collegeboard.org/sites/default/files/publications/2012/7/researchreport-2008-5-validity-sat-predicting-first-year-college-grade-point-average.pdf

Lewin, T. (2014, March 5). A new SAT aims to realign with schoolwork. New York Times. Retreived from http://www.nytimes.com/2014/03/06/education/major-changes-in-sat-announced-by-college-board.html.

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grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing

well-developed set of ideas that propose an explanation for observed phenomena

(plural: hypotheses) tentative and testable statement about the relationship between two or more variables

an experiment must be replicable by another researcher

implies that a theory should enable us to make predictions about future events

able to be disproven by experimental results

implies that all data must be considered when evaluating a hypothesis

committee of administrators, scientists, and community members that reviews proposals for research involving human participants

process of informing a research participant about what to expect during an experiment, any risks involved, and the implications of the research, and then obtaining the person’s consent to participate

purposely misleading experiment participants in order to maintain the integrity of the experiment

when an experiment involved deception, participants are told complete and truthful information about the experiment at its conclusion

committee of administrators, scientists, veterinarians, and community members that reviews proposals for research involving non-human animals

research studies that do not test specific relationships between variables

research investigating the relationship between two or more variables

research method that uses hypothesis testing to make inferences about how one variable impacts and causes another

observation of behavior in its natural setting

inferring that the results for a sample apply to the larger population

when observations may be skewed to align with observer expectations

measure of agreement among observers on how they record and classify a particular event

observational research study focusing on one or a few people

list of questions to be answered by research participants—given as paper-and-pencil questionnaires, administered electronically, or conducted verbally—allowing researchers to collect data from a large number of people

subset of individuals selected from the larger population

overall group of individuals that the researchers are interested in

method of research using past records or data sets to answer various research questions, or to search for interesting patterns or relationships

studies in which the same group of individuals is surveyed or measured repeatedly over an extended period of time

compares multiple segments of a population at a single time

reduction in number of research participants as some drop out of the study over time

relationship between two or more variables; when two variables are correlated, one variable changes as the other does

number from -1 to +1, indicating the strength and direction of the relationship between variables, and usually represented by r

two variables change in the same direction, both becoming either larger or smaller

two variables change in different directions, with one becoming larger as the other becomes smaller; a negative correlation is not the same thing as no correlation

changes in one variable cause the changes in the other variable; can be determined only through an experimental research design

unanticipated outside factor that affects both variables of interest, often giving the false impression that changes in one variable causes changes in the other variable, when, in actuality, the outside factor causes changes in both variables

seeing relationships between two things when in reality no such relationship exists

tendency to ignore evidence that disproves ideas or beliefs

group designed to answer the research question; experimental manipulation is the only difference between the experimental and control groups, so any differences between the two are due to experimental manipulation rather than chance

serves as a basis for comparison and controls for chance factors that might influence the results of the study—by holding such factors constant across groups so that the experimental manipulation is the only difference between groups

description of what actions and operations will be used to measure the dependent variables and manipulate the independent variables

researcher expectations skew the results of the study

experiment in which the researcher knows which participants are in the experimental group and which are in the control group

experiment in which both the researchers and the participants are blind to group assignments

people's expectations or beliefs influencing or determining their experience in a given situation

variable that is influenced or controlled by the experimenter; in a sound experimental study, the independent variable is the only important difference between the experimental and control group

variable that the researcher measures to see how much effect the independent variable had

subjects of psychological research

subset of a larger population in which every member of the population has an equal chance of being selected

method of experimental group assignment in which all participants have an equal chance of being assigned to either group

consistency and reproducibility of a given result

accuracy of a given result in measuring what it is designed to measure

determines how likely any difference between experimental groups is due to chance

statistical probability that represents the likelihood that experimental results happened by chance

Psychological Science is the scientific study of mind, brain, and behavior. We will explore what it means to be human in this class. It has never been more important for us to understand what makes people tick, how to evaluate information critically, and the importance of history. Psychology can also help you in your future career; indeed, there are very little jobs out there with no human interaction!

Because psychology is a science, we analyze human behavior through the scientific method. There are several ways to investigate human phenomena, such as observation, experiments, and more. We will discuss the basics, pros and cons of each! We will also dig deeper into the important ethical guidelines that psychologists must follow in order to do research. Lastly, we will briefly introduce ourselves to statistics, the language of scientific research. While reading the content in these chapters, try to find examples of material that can fit with the themes of the course.

To get us started:

• The study of the mind moved away Introspection to reaction time studies as we learned more about empiricism
• Psychologists work in careers outside of the typical "clinician" role. We advise in human factors, education, policy, and more!
• While completing an observation study, psychologists will work to aggregate common themes to explain the behavior of the group (sample) as a whole. In doing so, we still allow for normal variation from the group!
• The IRB and IACUC are important in ensuring ethics are maintained for both human and animal subjects

Psychological Science: Understanding Human Behavior Copyright © by Karenna Malavanti is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Psychological Research

Ethics in Research

Learning objectives.

• Explain how research involving humans and animals is regulated

Today, scientists agree that good research is ethical in nature and is guided by a basic respect for human dignity and safety. However, as you will read in the Tuskegee Syphilis Study, this has not always been the case. Modern researchers must demonstrate that the research they perform is ethically sound. This section presents how ethical considerations affect the design and implementation of research conducted today.

Research Involving Human Participants

Any experiment involving the participation of human subjects is governed by extensive, strict guidelines designed to ensure that the experiment does not result in harm. Any research institution that receives federal support for research involving human participants must have access to an institutional review board (IRB) . The IRB is a committee of individuals often made up of members of the institution’s administration, scientists, and community members (Figure 1). The purpose of the IRB is to review proposals for research that involves human participants. The IRB reviews these proposals with the principles mentioned above in mind, and generally, approval from the IRB is required in order for the experiment to proceed.

An institution’s IRB requires several components in any experiment it approves. For one, each participant must sign an informed consent form before they can participate in the experiment. An informed consent form provides a written description of what participants can expect during the experiment, including potential risks and implications of the research. It also lets participants know that their involvement is completely voluntary and can be discontinued without penalty at any time. Furthermore, the informed consent guarantees that any data collected in the experiment will remain completely confidential. In cases where research participants are under the age of 18, the parents or legal guardians are required to sign the informed consent form.

While the informed consent form should be as honest as possible in describing exactly what participants will be doing, sometimes deception is necessary to prevent participants’ knowledge of the exact research question from affecting the results of the study. Deception involves purposely misleading experiment participants in order to maintain the integrity of the experiment, but not to the point where the deception could be considered harmful. For example, if we are interested in how our opinion of someone is affected by their attire, we might use deception in describing the experiment to prevent that knowledge from affecting participants’ responses. In cases where deception is involved, participants must receive a full debriefing upon conclusion of the study—complete, honest information about the purpose of the experiment, how the data collected will be used, the reasons why deception was necessary, and information about how to obtain additional information about the study.

Dig Deeper: Ethics and the Tuskegee Syphilis Study

Unfortunately, the ethical guidelines that exist for research today were not always applied in the past. In 1932, poor, rural, black, male sharecroppers from Tuskegee, Alabama, were recruited to participate in an experiment conducted by the U.S. Public Health Service, with the aim of studying syphilis in black men (Figure 2). In exchange for free medical care, meals, and burial insurance, 600 men agreed to participate in the study. A little more than half of the men tested positive for syphilis, and they served as the experimental group (given that the researchers could not randomly assign participants to groups, this represents a quasi-experiment). The remaining syphilis-free individuals served as the control group. However, those individuals that tested positive for syphilis were never informed that they had the disease.

While there was no treatment for syphilis when the study began, by 1947 penicillin was recognized as an effective treatment for the disease. Despite this, no penicillin was administered to the participants in this study, and the participants were not allowed to seek treatment at any other facilities if they continued in the study. Over the course of 40 years, many of the participants unknowingly spread syphilis to their wives (and subsequently their children born from their wives) and eventually died because they never received treatment for the disease. This study was discontinued in 1972 when the experiment was discovered by the national press (Tuskegee University, n.d.). The resulting outrage over the experiment led directly to the National Research Act of 1974 and the strict ethical guidelines for research on humans described in this chapter. Why is this study unethical? How were the men who participated and their families harmed as a function of this research?

Learn more about the Tuskegee Syphilis Study on the CDC website .

Research Involving Animal Subjects

This does not mean that animal researchers are immune to ethical concerns. Indeed, the humane and ethical treatment of animal research subjects is a critical aspect of this type of research. Researchers must design their experiments to minimize any pain or distress experienced by animals serving as research subjects.

Whereas IRBs review research proposals that involve human participants, animal experimental proposals are reviewed by an Institutional Animal Care and Use Committee (IACUC) . An IACUC consists of institutional administrators, scientists, veterinarians, and community members. This committee is charged with ensuring that all experimental proposals require the humane treatment of animal research subjects. It also conducts semi-annual inspections of all animal facilities to ensure that the research protocols are being followed. No animal research project can proceed without the committee’s approval.

CC licensed content, Shared previously

• Ethics. Authored by : OpenStax College. Located at : https://openstax.org/books/psychology-2e/pages/2-4-ethics . License : CC BY: Attribution . License Terms : Download for free at https://openstax.org/books/psychology-2e/pages/1-introduction.

committee of administrators, scientists, and community members that reviews proposals for research involving human participants

process of informing a research participant about what to expect during an experiment, any risks involved, and the implications of the research, and then obtaining the person’s consent to participate

purposely misleading experiment participants in order to maintain the integrity of the experiment

when an experiment involved deception, participants are told complete and truthful information about the experiment at its conclusion

General Psychology Copyright © by OpenStax and Lumen Learning is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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Ethical review of research involving human subjects: when and why is IRB review necessary?

Affiliation.

• 1 Human Subjects Protection Program, Committee on Human Research, University of California San Francisco, San Francisco, California 94143-0962, USA. [email protected]
• PMID: 12811770
• DOI: 10.1002/mus.10398

Requirements for ethical review of research involving human subjects are based on widely accepted international standards that are implemented by various national regulations and institutional policies. In the United States, most human research is reviewed by institutional review boards (IRBs) applying federal standards. Researchers may not realize the variety of studies that should be submitted for review. Studies involving interventions must be reviewed regardless of whether these are standard interventions, nonmedical interventions, or retrospective studies. Quality improvement activities require IRB review if the results may be published. Research use of information from medical records or of biomedical specimens requires review unless no identifiers are recorded. Review must be sought at least annually and whenever the research changes. Even human research that is technically exempt from Federal regulations usually needs to have that exemption certified by someone other than the researcher.

Copyright 2003 Wiley Periodicals, Inc.

Publication types

• Ethics Committees, Research / ethics*
• Ethics Committees, Research / legislation & jurisprudence
• Ethics, Research*
• Research / standards
• Terminology as Topic

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Lesson 2: What is Human Subjects Research?

Please note: This lesson will take approximately 1 hour and 35 minutes to complete. Use the next and previous buttons to advance through the course. You will be able to print a completion certificate for your records at the end of this training. OHRP does not collect information about who accesses it.

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Purpose of this Lesson

This lesson will explain how the Common Rule regulations define “research” and “human subjects” and explain what it means to be exempt from the regulations. This lesson focuses on the Revised Common Rule (or 2018 Requirements) that became effective in 2018.

Lesson Overview

This lesson contains four parts:

Part 1: Background of Human Subjects Research

Part 2: is the activity research, part 3: does the research involve human subjects, part 4: is the human subjects research exempt.

You will answer quiz questions throughout each part to test your knowledge. A correct response is required to advance in the lesson.

Learning Objectives

After completing this lesson, you will be able to:

• Identify if a certain activity meets the regulatory definition of research.
• Identify if research involves human subjects based on the regulatory definition.
• Determine whether a particular project is non-exempt human subjects research under the Common Rule.

Go to Section: Introduction > The Concept of Non-exempt Human Subjects Research > Identifying Non-Exempt Human Subjects Research > Quiz Questions

Introduction

The Common Rule applies to human subjects research that is supported or conducted by a Common Rule agency. For research supported or conducted by the Department of Health and Human Services (HHS), the Office for Human Research Protections (OHRP) is the office with the authority to enforce the regulations. Many research institutions choose to apply the Common Rule to all of their human subjects research regardless of funding source.

This lesson focuses on the Revised Common Rule that became effective in 2018.

The Concept of Non-exempt Human Subjects Research

Even when funded by a Common Rule agency, not all research involving humans is required to follow the Common Rule. The Rule only applies to activities that qualify as human subjects research under the regulation and that do not qualify for an exemption. This is commonly referred to as non-exempt human subjects research.

Note that, in addition to the Common Rule (subpart A), non-exempt human subjects research funded by HHS must also comply with subparts B, C, & D of the regulations at 45 CFR 46. These subparts provide additional protections for certain special populations involved in research.

This lesson explains how the regulations define research and human subjects and explains what it means to be exempt from the regulations. Understanding these concepts is important to knowing when the regulations apply and when they do not.

Identifying Non-Exempt Human Subjects Research

To figure out whether a particular activity is non-exempt human subjects research under the Common Rule, ask the following three questions, in this order :

• Is the activity research according to the regulations?
• Does the research involve human subjects based on the definition in the regulations?
• Is the human subjects research exempt?

The determination of whether a research study is non-exempt human subjects research is usually made by an institution’s Human Research Protection Program (HRPP) or IRB office. In addition to applying the Common Rule’s basic protections for human subjects in research, the HRPP or IRB office also may ensure that the activity aligns with institutional policies, ethical guidelines, and other regulations and policies that might be relevant.

What is non-exempt human subjects research?

All research involving human volunteers in the United States is required to follow the Common Rule. True or false?

An investigator plans to do a research project involving human subjects that is not funded by the Federal government. Can she proceed with her proposed project without IRB review?

In an institution, who usually determines whether a research study is non-exempt human subjects? (Select all that apply)

In deciding whether a project is non-exempt human subjects research under the Common Rule, what is the first question you should ask?

Go to Section: Defining Research > Categories of Activities Deemed Not to Be Research > Quiz Questions > Determining When the Common Rule Requirements Apply

Defining Research

Let’s start with the first question: Is the activity research according to the regulations?

Not all work that we would colloquially call ‘research’ is considered to be research under the Common Rule. The Common Rule defines research as:

“a systematic investigation, including research development, testing, and evaluation, designed to develop or contribute to generalizable knowledge.”

To decide if a certain activity meets the regulatory definition of research, consider:

• It would likely involve a hypothesis, research question, and a plan to systematically collect and analyze data.
• The systematic investigation adds information and contributes to generalizable knowledge in the field.
• For example, lots of information is published that comes from activities that do not meet the Common Rule’s definition of research. And sometimes results from research that meets the Common Rule definition never get published.

Categories of Activities Deemed Not to Be Research

The revised Common Rule also lists four specific types of activities that are deemed not to be research:

• Scholarly and journalistic activities that focus on information specifically about certain individuals.
• Certain public health surveillance activities.
• Certain activities solely for criminal justice or criminal investigative purposes.
• Certain operational activities in support of national security missions.

Review the regulatory descriptions of these four categories of activities deemed to be not research under §46.102(l).

Watch the video to learn more.

The Common Rule defines research as “a systematic investigation, including research development, testing, and evaluation, designed to develop or contribute to generalize knowledge.” True or false?

What are the criteria for the regulatory definition of research? (Select all that apply)

Select all activities deemed not to be research under the Common Rule. (Select all that apply)

Determining When the Common Rule Regulatory Requirements Apply

So, when deciding if a specific activity comes under the Common Rule,

First, ask whether it meets the regulatory definition for research—and remember to consider the four categories of activities deemed not to be research.

If the answer is “No,” then the Common Rule does not apply and, as a result, the activity does not have to be reviewed and approved by an IRB before starting. However , investigators should always check with their institution’s HRPP or IRB office to see whether there are institutional policies to follow even if the regulations don’t apply.

If, however, the answer to the first question is “ Yes ” – the activity does meet the regulatory definition of research, THEN ask the second question: Does the research involve human subjects?

Go to Section: Defining Human Subject > Living Individuals > Identifying the Subject > Interaction and Intervention > Identifiable Private Information > Quiz Questions > Determining When the Common Rule Requirements Apply

Defining Human Subject

The revised Common Rule defines human subject as:

“a living individual about whom an investigator (whether professional or student) conducting research: (i) Obtains information or biospecimens through intervention or interaction with the individual, and uses studies, or analyzes the information or biospecimens; or (ii) Obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens.”

While there is a lot of detail in the definition of human subject, it generally boils down to this:

It is important to understand the key terms in this definition to determine when a research study involves human subjects according to the regulations.

Living Individuals

Human Subject: “ a living individual about whom an investigator (whether professional or student) conducting research: (i) Obtains information or biospecimens through intervention or interaction with the individual, and uses studies, or analyzes the information or biospecimens; or (ii) Obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens.”

First of all, notice that it specifies living individuals. Therefore, for the purpose of the Common Rule, research that only involves information or biospecimens from deceased persons would not be considered human subjects research.

Identifying the Subject

Human Subject: “a living individual about whom an investigator (whether professional or student) conducting research: (i) Obtains information or biospecimens through intervention or interaction with the individual, and uses studies, or analyzes the information or biospecimens; or (ii) Obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens.”

The phrase ‘about whom’ is important. A human subject is the person that the information is about, not necessarily the person providing the information. In the case of biospecimens, the human subject is the person from whom the specimen was taken.

For example:

Interaction and Intervention

• Interactions occur when investigators communicate or have interpersonal contact with research participants, for example verbally, in writing, or electronically, to obtain information about them for the research.
• Interventions , on the other hand, include both physical procedures by which investigators collect information or biospecimens and manipulations of the subjects or the subjects’ environment for the purpose of the research.
• Examples of interventions include assigning subjects to take a particular drug in a clinical trial, asking subjects to complete a certain task for research purposes, and changing the background noise level to study how subjects’ stress levels vary.

Identifiable Private Information

Human Subject: “a living individual about whom an investigator (whether professional or student) conducting research: (i) Obtains information or biospecimens through intervention or interaction with the individual, and uses studies, or analyzes the information or biospecimens; or (ii) Obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens .”

Note, also, that the researchers may or may not have interacted or intervened with the subject at all – for example, they might use leftover blood samples from clinical tests; but if the blood sample is identifiable, then the person is considered to be a human subject.

A proposed research project involves studying tissue samples from cadavers being used in a local medical school to train students. Personal information about the deceased individuals will be used in the research. Is this human subjects research?

Question 10

A proposed research project involves asking participants to complete a task and answer questions on a computer. No identifiable information will be recorded about participants. Is this human subjects research?

Question 11

A proposed research project will use leftover blood samples from clinical tests to check for levels of a certain metabolite. Investigators will also review patients’ identifiable medical records to obtain other necessary health information. Is this human subjects research?

Question 12

Which of the following activities, when carried out for the purpose of research, would constitute research involving human subjects under the Common Rule? (Select all that apply)

Question 13

Research that only involves specimens from deceased persons would not be considered human subjects research. True or false?

Apply this definition of “human subjects” to your research to determine whether your research study constitutes human subjects research under the Common Rule. If the answer is “no,” then the Common Rule does not apply.

If, on the other hand, the answer to this second question is “yes,” and it is human subjects research, then you go on to the third question: Is it exempt?

Go to Section: Could the Human Subjects Research Be Exempt? > Exempt Human Subjects Research > Quiz Questions > Determining When the Common Rule Requirements Apply

Could the Human Subjects Research Be Exempt?

There are eight exemption categories listed in the revised Common Rule. If all of the activities in a human subjects research study meet the criteria for one or more of these exemption categories, the study is exempt from the Common Rule requirements for oversight. This means, for example, that the research does not need to undergo initial or continuing IRB review for approval as required by the regulations.

The Common Rule does not specify who can make determinations about exemptions. Most institutions require that investigators submit proposed research to the institution’s HRPP or IRB office for the determination about whether it meets the criteria for an exemption. Additionally, certain exemptions require a “limited IRB review” to determine that specific conditions are met for the exemption to apply.

Exempt Human Subjects Research

An entire human subjects research projects that has been determined to meet the conditions for one or more exemption categories in the Common Rule can generally proceed without having to comply with the regulatory requirements.

One thing to remember, however, is that if investigators make changes to the research at a later time, they should check with their institution’s HRPP or IRB office to make sure that the research still meets the exemption criteria. If the changes cause the research study to no longer meet the criteria for exemption, then the research is no longer exempt and must comply with the regulatory requirements and undergo IRB review . Investigators should work closely with their HRPP or IRB office to avoid surprises like this that could affect the progress of their research.

Click here to watch a video explaining the exemption categories.

Question 14

What does it mean for a research project to be exempt?

Question 15

The Common Rule specifies who should make determinations about exemptions. True or false?

Question 16

Where should a researcher go to inquire whether something qualifies as an exemption? (Select all that could apply)

Question 17

Once a research study is determined to be exempt, it will always be exempt regardless of any subsequent changes that might be made to it. True or false?

Human subjects research studies that do not qualify for an exemption are referred to as non-exempt human subjects research. Unless there is a Secretarial waiver, they must comply with the Common Rule regulatory requirements, including IRB review and approval, before the research can begin. For non-exempt cooperative research studies involving multiple institutions, the review would generally be done by a single IRB.

Go to Section: Wrap Up > Completion Certificate

This lesson explained the process of determining whether a research project meets the criteria for being non-exempt human subjects research under the Common Rule. Remember that if it doesn’t satisfy the regulatory definition of either research or human subject, or if all of the activities in the human subjects research meet the criteria for one or more of the exemptions, then the Common Rule regulatory requirements do not apply to the project, but investigators may still be subject to any institutional policies that are in place. Investigators should work with their institution’s Human Research Protection Program (HRPP) or IRB office to find answers and determine how to proceed.

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Human Participation

Human participants.

Researchers conducting research that involves human participants must ensure human participants are treated fairly and their welfare and rights are protected.  Newcastle University’s guidelines on the use of humans in research are based on those established by the HRA’s Research Ethics Service , the Declaration of Helsinki and the Human Rights Act (1998) .  

The following good practice should be considered at the project proposal stage , as part of the development of the research design and methodology:

Researchers should seek informed and voluntary consent from participants

Any research or impact and engagement activity which involves working with human participants should follow the best practice set out in the University's ‌.  This includes internal activities in which University staff and students act as participants.  

Please see the sections below for more information regarding informing participants and seeking consent.

Informing participants

Participants should be fully informed about the purpose, methods and intended use of the research.  They should be provided with sufficient information about the study to be able to make an appropriate decision about taking part. 

Typically, this information is provided in a Participant Information Sheet (PIS) , but a member of the research team should also explain this information in a conversation with the potential participant.  Additionally, participants should be given the opportunity to ask questions and have these answered satisfactorily. 

The information and level of detail that you provide in the PIS will depend on the nature of the  study .  The document should include the following information as a minimum:

• The title of the project and the research aims
• Details of who is carrying out the research 
• An invitation to participate in the study
• The terms for withdrawing from the study

A more detailed PIS should also address the following:

• What does taking part involve?
• What information will be collected and who will have access to the information collected?
• How will the data be used and stored during and after the study?
• Any limitations of confidentiality (e.g. where researchers have a legal duty to report safety concerns)
• Why has the participant been invited to take part? (What are the inclusion/exclusion criteria?)
• What are the possible benefits of taking part?
• What are the possible disadvantages and risks of taking part?
• What procedures are in place to minimise any disadvantages and risks?
• Who is the sponsor and the data controller for the research?
• Has the study received ethical approval?
• Who should the participant contact for further information relating to the research?
• Who should the participant contact to file a complaint?

For more tips on writing a PIS, see the  HRA website .  A number of Example Documents are also provided on the Ethics Toolkit.

Acquiring voluntary consent

Participants should take part voluntarily in the research, free from any coercion or undue influence. On receiving the information (and PIS) about the research study, potential participants should be allowed time to consider whether or not to take part and should be given the opportunity to discuss their potential participation with others if they wish to. Typically participants will sign a ‘Consent Form’*, (see  Example consent form ‌).  

As a minimum, the consent form should allow the participant to confirm each of the following:

• That they have read the information sheet, had the opportunity to consider the information and ask questions, and had their questions answered satisfactorily.
• That they understand their participation is voluntary, that they are free to withdraw at any time without giving any reason, without any penalty, and that they understand what will happen to any data collected prior to their withdrawal.
• That they consent to their [anonymised/pseudonymised] research data being stored and used by others for future research.
• That they understand their research data may be published as a report.
• (If applicable) That they consent to the processing of their personal information for the purposes of the research study and (if applicable) that they consent to the retention of their personal information for [insert period time and purpose].
• That they agree to take part in the research project.

Note that, in longitudinal research studies, consent may need to be obtained on more than one occasion.

Informed consent should also be taken from any staff or students who are participating in the study. 

The signature of an independent witness is also recommended for high-risk projects involving invasive procedures and / or vulnerable groups. 

*Providing written information is not always the best format to use. Instead of a PIS, other media e.g. a video, an audio recording, or a script to be read aloud by a researcher may be more appropriate. Similarly, instead of a written consent form, it may be more appropriate to use a recording device to record the obtaining of oral consent and have this witnessed. However, please be aware that providing written information and obtaining written consent is preferred. Therefore, where possible (i.e. where reading information and/or writing is not problematic), researchers should always provide a written information sheet and request written consent.

Research involving deception/covert observation

Researchers should always aim to conduct research studies for which participants are fully informed about the study before taking part.  However, sometimes providing participants with full information about the study is not possible, because doing so could significantly influence the outcome, and be at odds with the aims of the research. 

Whilst Newcastle University strongly encourages researchers to attain fully informed consent from all participants, the University’s Ethics Committees will consider applications for research where the only possible way to conduct the research involves deception/covert observation*.  The researcher must clearly explain and justify the reasons for the lack of fully informed consent in their research ethics application.  If there is an alternative way to investigate the research aims, which would allow participants to provide fully informed consent, this should be pursued instead. 

*Note observational research is only acceptable in situations where those observed would expect to be observed by strangers. 

Research involving vulnerable participants

Vulnerability may arise as a result of:

• Potential marginalisation
• Financial circumstances
• Being in an abusive relationship
• Disadvantageous imbalance of power within personal/professional roles

Where research involves potentially vulnerable groups, researchers should make every effort to:

• attain fully informed and voluntary consent,
• ensure participants have had the opportunity to discuss the research invitation with others,  and
• develop methods of seeking consent that are appropriate.

Other considerations:

• Where researchers are in a position of authority/influence over potential participants, they must ensure that their relationship (e.g. as a teacher, employer) does not influence any decision to take part.  This also applies to participants who are staff and students at Newcastle University.
• Where a payment is offered to participants for their taking part, the payment must not be used to induce participants to risk harm beyond that which they risk without payment in their normal life style.

Please note researchers working with vulnerable groups may need to undergo a Disclosure & Barring Service (DBS) check.  For further information, please contact Newcastle University’s  Human Resources  team.

Research involving child participants

16 years and older:  In clinical practice, young people aged 16 years and above are able to give their own consent. 

Younger children:  Where the potential participants are younger children (i.e. under 16 years), , Newcastle University expects researchers to make every effort to inform children about the research study, by talking to them about the study and using age-appropriate language and participant information sheets.  Children should be asked if they want to participate in the research and, where possible, should provide their consent to do so.  In addition, however, researchers must fully inform the children’s parents/guardians about the study, provide them with a PIS and ask them to provide their consent for their child’s participation.

Infants:  Researchers must fully inform the infant’s parents/guardians about the study, provide them with a PIS and ask them to provide their consent for their child’s participation.

The HRA provides some example documentation .   

Please note researchers working with children will need to undergo a Disclosure & Barring Service (DBS) check.  For further information, please contact Newcastle University’s Human Resources team.

Research involving participants who lack the capacity to consent

The Mental Capacity Act (2005) is an Act of Parliament of the UK, applying to England and Wales.  It provides a legal framework for making decision on behalf of adults (defined in this case as 16 years and above) who lack the capacity to make decisions.

Section 2 (1&2) of the Act defines a person who lacks capacity as follows:

• A person lacks capacity in relation to a matter if at the material time he is unable to make a decision for himself in relation to the matter because of an impairment of, or a disturbance in the functioning of, the mind or brain.
• It does not matter whether the impairment or disturbance is permanent or temporary.

A person’s lack of capacity may be due to various reasons including, for example, dementia, mental illness, learning disability, brain damage, intoxication.

The researcher is responsible for deciding whether a potential participant has the capacity to consent for themselves, and is able to consult other care professionals, if appropriate.  In order to assess capacity, the researcher must consider:

• Is there an impairment of, or disturbance to, the functioning of the mind or brain?
• If so, is the impairment or disturbance sufficient that the person is unable to make the decision to consent?

Research that involves recruitment of adults who lack the capacity to consent must undergo approval through an NHS or Social Care REC (see NHS & Social Care ). 

Using a gatekeeper

Researchers may require permission from a gatekeeper to acquire initial or continued access to potential participants.  A gatekeeper is an individual/organisation that controls the initial or continued access to an individual or group of individuals. 

Examples of situations in which researchers may require a gatekeeper to access a potential participant include:

• Research involving employees recruited through their employer (gatekeeper = employer).
• Research involving NHS service users recruited through an NHS service provider (gatekeeper = NHS service provider).
• Research involving social care service users recruited through a social care provider (gatekeeper = social care provider).
• Research involving children recruited through their school (gatekeeper = school head).
• Research involving minority groups recruited through their community centres (gatekeepers = community centres).

If a researcher intends to access participants by using a gatekeeper, the researcher must acquire the necessary permission and consent from the gatekeeper to approach the potential participants.  Researchers will still need to fully inform potential participants about the research and acquire their voluntary consent.   

Research involving questionnaires

It is strongly recommended that researchers acquire fully informed written consent from all participants.  However, for questionnaires where personal data, sensitive data and/or confidential data are not collected, implied consent may be sufficient.  In this case, prior to completing the questionnaire, participants should be fully informed about the study (see 'Informing participants' section above) and within this information it should be stated that consent for using their data for the specified purposes is implied from their participation.  

Accessing security sensitive materials online

In addition to obtaining ethical approval, colleagues and students conducting security sensitive research should also ensure that they follow the University's Prevent Guidance .  Researchers should:

• Complete Prevent training.  All colleagues are expected to complete the mandatory e-learning programme   via the University's Learning Management System (internal login required). Further online training is available to colleagues and students via the Home Office website . 
• Not use their personal or work laptop to access security sensitive materials online .  Contact a member of the Prevent Team  or IT Helpdesk to arrange access to a University PC or laptop which can be used for this purpose.  
• Not store any security sensitive materials on their personal or work laptop .  Contact the University's Research Data Service for advice on developing an appropriate Research Data Management Plan.  
• Consider their own mental health and wellbeing .  Students can access support through the University's dedicated counselling service .  Staff can access support through the  Colleague Health and Wellbeing Hub (internal login required).
• Refer to the UUK Report on Oversight of Security Sensitive Research Material in UK Universities for further best practice guidance.  

Video Recording of Online Interviews

The global pandemic had an impact on how we collect data for research. Some communication technologies offer new opportunities to conduct qualitative research. For example, Zoom, Microsoft Teams, Skype and Google Hangout allow researchers to conduct interviews using videoconferencing platforms.

A number of features of these technologies, such as automatic transcription, along with their cost-effectiveness, data management features, and security options are potentially appealing to qualitative researchers. These technologies can be more convenient for the research participants, too. A recent research that explored the feasibility and acceptability of using Zoom to collect qualitative interview data shows that most participants found their interview experience as highly satisfactory. They generally rated Zoom above alternative interviewing mediums such as face-to-face, telephone, and other videoconferencing services (Archibald et al 2019).

Before conducting online interviews the researchers should consider carefully whether the topic is appropriate for an online interview. For example, if the interview is on a sensitive or intrusive topic, conducting an online interview might not be the best approach.

The videoconferencing tools allow the researchers to video record the interaction in a specific drive or Cloud. Video recording is not a common practice during the face-to-face interviews, unless the research is designed that way, and the researcher has a particular reason for making a video of the session. Arguably, making a video of someone is more intrusive than recording their voice, and protecting that data also involves more risk (eg facial recognition technologies can easily match someone’s face with their personal identity). Hence, it is preferable to use phone rather than Zoom, to discuss  strictly confidential or sensitive  topics.

Even if the interview topic is not sensitive, it is important to obtain consent from the participants to record their video. Some participants may not be aware of the fact that the research does not necessarily require a video recording. The researcher should communicate this openly with the participant and remind the participant that turning off the video camera would not affect the quality of the research.

Most video conferencing software allows you or the participant to disable the camera. The participants can also be reminded that they can cover the camera with a cloth or a piece of paper. It is also worth reminding them at the start of the interaction that the session is being recorded. 

In summary, the participants should be aware of the fact that giving an interview using a videoconferencing software does not necessarily involve being audio/video recorded. The Participant Consent forms should include an explicit statement consenting to interview via the named platform (eg Zoom) and to the audio (and video, if necessary) recording of the conversation.

Data recorded from remote or online interactions with participants should be transferred as soon as possible from the recording location (eg Zoom Cloud) to a password protected folder. The original file in the recording location should be deleted once it is transferred. The researchers should also keep in mind that some video conferencing software deletes the files automatically (eg Zoom deletes the files in 30 days). 

Dr Ilke Turkmendag

Senior Lecturer, Newcastle Law School

Archibald MM, Ambagtsheer RC, Casey MG, Lawless M. Using Zoom Videoconferencing for Qualitative Data Collection: Perceptions and Experiences of Researchers and Participants. International Journal of Qualitative Methods. January 2019. doi:10.1177/1609406919874596

Researchers should ensure participants are aware of their right to withdraw

Researchers must inform participants of their right to withdraw from the research study at any time, without giving any reason, without any penalty (and irrespective of whether or not payment or other inducement has been offered).  Researchers must inform participants of what will happen to any data collected from the participant prior to their withdrawal of consent.  Participants have a right to request that their data be destroyed, but where research data is anonymised it can no longer be identified to be excluded.  Accordingly, participants need to be informed if any research data provided by them, prior to any withdrawal, will be excluded/included.

Researchers should protect participants’ privacy and confidentiality

Researchers must protect the privacy of research participants and the confidentiality of their personal information. 

Participants must be informed of any limits to their privacy/confidentiality, and their consent for using their personal information must be attained.    

Researchers should also consider whether their research could potentially lead to any circumstances in which they might be required to divulge information to legal or other authorities.  If so, the limits of confidentiality should be clearly specified in the PIS:

'We [the researchers] will generally not disclose the information you [the participant] provide without your consent, but there may be circumstances where we have to because we have a legal requirement to do so (for example, under statute or a court order) and/or we have an overriding duty to the public (for example, the information concerns the commission of a criminal offence or relates to life-threatening circumstances)'. 

Research within the workplace:  Researchers should be aware of the possible existence of any confidentiality clauses in employment contracts.  Researchers may require consent from employers for any information given by employees within the workplace, during the course of their employment.

Research with children:  Researchers working with children should be familiar with the relevant child protection act (e.g. Child Protection Act 1989 for England and Wales) and consider what actions they would take in the event of a disclosure of child abuse.  

The benefits of the research must outweigh any potential risk/harm, and any potential risk/harm should be avoided/minimized.

Research should be worthwhile and provide value that outweighs any risk or harm to participants and/or researchers.  

Researchers must:

•      adequately assess the potential risks of their research study and
•      consider how these will be best managed to ensure that they are avoided/minimised. 

The table below provides a guide to the types of risks that research studies can pose, examples of these risks and of ways to manage these.  This is not an exhaustive list, and so researchers will need to carefully consider any other risks their research study may pose. 

If you have further examples that could be beneficial to other researchers, please contact [email protected] so that these can be added to the table.

If you wish to recommend any changes to the information above, please contact  [email protected] . 

Learning Objectives

By the end of this section, you will be able to:

• Discuss how research involving human subjects is regulated
• Summarize the processes of informed consent and debriefing
• Explain how research involving animal subjects is regulated

Today, scientists agree that good research is ethical in nature and is guided by a basic respect for human dignity and safety. However, as you will read in the feature box, this has not always been the case. Modern researchers must demonstrate that the research they perform is ethically sound. This section presents how ethical considerations affect the design and implementation of research conducted today.

Research Involving Human Participants

Any experiment involving the participation of human subjects is governed by extensive, strict guidelines designed to ensure that the experiment does not result in harm. Any research institution that receives federal support for research involving human participants must have access to an institutional review board (IRB) . The IRB is a committee of individuals often made up of members of the institution’s administration, scientists, and community members ( Figure 2.20 ). The purpose of the IRB is to review proposals for research that involves human participants. The IRB reviews these proposals with the principles mentioned above in mind, and generally, approval from the IRB is required in order for the experiment to proceed.

An institution’s IRB requires several components in any experiment it approves. For one, each participant must sign an informed consent form before they can participate in the experiment. An informed consent form provides a written description of what participants can expect during the experiment, including potential risks and implications of the research. It also lets participants know that their involvement is completely voluntary and can be discontinued without penalty at any time. Furthermore, the informed consent guarantees that any data collected in the experiment will remain completely confidential. In cases where research participants are under the age of 18, the parents or legal guardians are required to sign the informed consent form.

Link to Learning

View this example of a consent form to learn more.

While the informed consent form should be as honest as possible in describing exactly what participants will be doing, sometimes deception is necessary to prevent participants’ knowledge of the exact research question from affecting the results of the study. Deception involves purposely misleading experiment participants in order to maintain the integrity of the experiment, but not to the point where the deception could be considered harmful. For example, if we are interested in how our opinion of someone is affected by their attire, we might use deception in describing the experiment to prevent that knowledge from affecting participants’ responses. In cases where deception is involved, participants must receive a full debriefing upon conclusion of the study—complete, honest information about the purpose of the experiment, how the data collected will be used, the reasons why deception was necessary, and information about how to obtain additional information about the study.

Ethics and the Tuskegee Syphilis Study

Unfortunately, the ethical guidelines that exist for research today were not always applied in the past. In 1932, rural, Black men from Tuskegee, Alabama, were recruited to participate in an experiment conducted by the U.S. Public Health Service, with the aim of studying syphilis in Black men ( Figure 2.21 ). In exchange for free medical care, meals, and burial insurance, 600 men agreed to participate in the study. A little more than half of the men tested positive for syphilis, and they served as the experimental group (given that the researchers could not randomly assign participants to groups, this represents a quasi-experiment). The remaining syphilis-free individuals served as the control group. However, those individuals that tested positive for syphilis were never informed that they had the disease.

While there was no treatment for syphilis when the study began, by 1947 penicillin was recognized as an effective treatment for the disease. Despite this, no penicillin was administered to the participants in this study, and the participants were not allowed to seek treatment at any other facilities if they continued in the study. Over the course of 40 years, many of the participants unknowingly spread syphilis to their wives (and subsequently their children born from their wives) and eventually died because they never received treatment for the disease. This study was discontinued in 1972 when the experiment was discovered by the national press (Tuskegee University, n.d.). The resulting outrage over the experiment led directly to the National Research Act of 1974 and the strict ethical guidelines for research on humans described in this chapter. Why is this study unethical? How were the men who participated and their families harmed as a function of this research?

Visit this website about the Tuskegee Syphilis Study to learn more.

Research Involving Animal Subjects

Many psychologists conduct research involving animal subjects. Often, these researchers use rodents ( Figure 2.22 ) or birds as the subjects of their experiments—the APA estimates that 90% of all animal research in psychology uses these species (American Psychological Association, n.d.). Because many basic processes in animals are sufficiently similar to those in humans, these animals are acceptable substitutes for research that would be considered unethical in human participants.

This does not mean that animal researchers are immune to ethical concerns. Indeed, the humane and ethical treatment of animal research subjects is a critical aspect of this type of research. Researchers must design their experiments to minimize any pain or distress experienced by animals serving as research subjects.

Whereas IRBs review research proposals that involve human participants, animal experimental proposals are reviewed by an Institutional Animal Care and Use Committee (IACUC) . An IACUC consists of institutional administrators, scientists, veterinarians, and community members. This committee is charged with ensuring that all experimental proposals require the humane treatment of animal research subjects. It also conducts semi-annual inspections of all animal facilities to ensure that the research protocols are being followed. No animal research project can proceed without the committee’s approval.

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Office of the provost, use of human subjects in research, statement of policies and procedures governing the use of human subjects in research at harvard university.

As voted by the President and Fellows of Harvard College, September 22, 2003

Harvard University is guided by the ethical principles regarding research involving human subjects set forth in the report of the National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research (Ethical Principles and Guidelines for the Protection of Human Subjects of Research [the “Belmont Report”]). The minimum standard is set by the Department of Health and Human Services regulations at 45 CFR 46 (the “Common Rule”). Harvard University has additional provisions beyond that standard, which help to establish the highest expectations for performance and oversight by investigators, Institutional Review Boards (IRBs), and the University. The following policies and procedures outline these expectations.

Research that exposes human subjects to the unreasonable risk of harm shall not be conducted.

Subjects must not be exposed to any risk that can practicably be avoided without impairing the research design.

Individuals who propose to conduct research involving human subjects must be qualified by experience and/or training to safeguard the well-being of the subjects of their research.

Investigators under whose aegis research is to be conducted have primary responsibility for determining whether subjects might be exposed to a risk of harm. In making this determination, investigators shall seek advice from the appropriate IRB. Principal investigators also have primary responsibility for protecting subjects from being harmed by their participation in a study. All others involved in the study share this responsibility.

Each IRB shall be authorized to review and to approve or disapprove, and to state conditions for, the conduct of any research involving a human subject or subjects, in accordance with the policies outlined herein. In addition to membership requirements stipulated by federal laws and regulations, the membership of each IRB shall be chosen with a view to its ability to represent credibly the varying perspectives of subjects, investigators, and society at large. In appropriate circumstances, the IRB shall solicit advice from others who are especially qualified to represent the views of a particular subject population. IRB members shall not participate in the approval of projects in which they are involved or have a conflicting interest.

Although the typical issues dealt with by IRBs that oversee human subject research in different Faculties differ greatly, the Chairs of the IRBs shall confer as needed to assure that similar issues are treated similarly across the University.

Investigators shall explain to subjects, prior to their participation, the objectives of the research, the procedures to be followed, and the potential risks and benefits. Investigators shall not use individuals as subjects unless satisfied that they, or others legally responsible for their well-being, consent to participation freely and with understanding of the consequences. Ordinarily, investigators shall also obtain the assent of subjects who are not legally capable of consenting to participation. The IRB may waive some or all of these requirements only when persuaded that the research could not practicably be conducted otherwise, that the potential value of the research outweighs the indignity to the subject, and that the subject risks no other harm in participating. If appropriate, the IRB may also stipulate that additional information about the study will be provided to subjects after their participation.

Investigators shall respect the privacy of subjects. They shall protect confidential information given them, advising subjects in advance of any limits upon their ability to ensure that the information will remain confidential.

Subjects shall not be induced to participate by means or in circumstances that might affect their ability to decide freely.

Investigators shall address the equitable selection of subjects, taking into account the purposes of the research, the setting in which the research will be conducted, and any special vulnerabilities of the subject population.

It shall be made clear to subjects that they are free to withdraw from active participation in the research at any time and without prejudice to their legitimate interests. Subjects who indicate a desire to withdraw shall be allowed to do so promptly.

An investigator shall disclose to a subject, upon request, the source of support for the research.

Instructors who assign or supervise research projects and exercises conducted by students are responsible for ensuring that the student is qualified to safeguard adequately the well-being of the subjects.

Investigators may indicate their position at Harvard, but shall not represent that the research is sponsored by the University or a department within the University except by explicit arrangement with appropriate administrative authorities.

An investigator proposing to conduct, direct, or supervise research involving human subjects shall make certain that the research is consistent with the policies and procedures stated herein, and that the appropriate IRB has been informed of existing knowledge of any risks involved.

Regardless of funding source, all investigations that meet the definition of research involving human subjects as specified in the Common Rule shall be reviewed according to the standards therein, as well as any other applicable laws or regulations.

Whether or not the Common Rule mandates review, proposed research involving human subjects must be submitted to the IRB for review and approval, or determination of exemption, if the research presents more than minimal risk to subjects or if the research involves any of the following:

Procedures that might harm the subjects physically;

Procedures that deprive the subjects of necessary, or accustomed, resources;

Hypnosis or unusual degrees of mental stress;

The use of subjects who are not able to give free and informed consent, including minors, prisoners, and individuals of diminished mental capacity;

Explicit or implicit deception of the subjects in any aspect likely to be significant to them;

The use of subjects who are available because they need the investigator’s professional services;

Activities that may be illegal, or are likely to offend prevailing standards of morality.

Each IRB shall develop guidelines for investigations involving human subjects that do not meet the definition of research as specified in the Common Rule or the conditions elaborated in part C of these Procedures. The guidelines should provide procedures to be employed for the review and approval of such studies. Investigations in this category might include, for example, those designed to train individuals in research techniques, such as student exercises assigned during the course of classroom instruction or other pedagogical programs.

Investigators shall submit their plans for using human subjects to the appropriate IRB in the form, and according to the timetable, established by that IRB to ensure orderly handling of its business. IRB approval is ordinarily limited to the specific research plan submitted to the IRB. Approval shall be for a definite period of time up to one year. A new application must be approved for research continuing for more than a year. Extensions of the specified time that subjects participate, and changes in plan that subjects might consider significant, require further IRB approval.

If investigators detect an adverse change in the health or behavior of a subject that may be attributable to a study, or if they identify new risks that may result from subject participation in that study, they shall exercise judgment as to whether to suspend the study immediately. In any event, they shall immediately report the incident to the IRB. Regardless of the investigators’ decision about whether to suspend the study, the IRB independently shall determine whether suspension of the study is in order, and, if so, under what conditions it may be resumed. Study participants must be informed of any findings developed during the course of the research that may relate to their willingness to continue participation.

This Statement of Policies and Procedures shall be distributed annually to all faculty and administrative officers who might bear responsibility for studies involving human subjects. They, in turn, shall take appropriate steps to assure that their students and staff associates are aware of its contents.

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For the most up-to-date government policies and regulations that pertain to higher education, see the Harvard University Office of Federal Relations website .

Human Participants – General Guidance

For many researchers, an important strategy for gathering information and generating data is interacting with, and often speaking directly with, people. Through ethnography and participant observation, interviewing, carrying out focus groups, and conducting surveys or experiments, researchers involve human beings of all ages and backgrounds in their work. Those people become “human participants” (or, in legal parlance, “research subjects”) in those scholars’ research projects.

QDR offers a series of web pages addressing key topics in human participant research:

Principles of Human Participant Protection

Institutional review boards (irbs), informed consent, de-identification, access controls.

If your work involves human participants, there are important questions related to interacting with those individuals that you should begin to consider from the early planning stages of your project. We offer here and on the pages linked below general guidance for safely and ethically collecting information from human participants, and for managing and potentially sharing that information. The specific questions that arise when research involves human participants, and the answers to those questions, vary by project. We encourage you to contact the Institutional Review Board(s) (IRBs) with jurisdiction over your project, and/or QDR, early in the development of your project if you anticipate or encounter unusual circumstances or are unsure about some aspect of collecting data from human participants or managing those data.

Research with human participants should be guided by three ethical principles: respect, beneficence, and justice.

IRBs help to assure that research involving human participants protects those participants’ rights and welfare. If interacting with human beings is one of the strategies that you will employ to collect information for your research project, you need to seek approval for the project from the IRBs with jurisdiction over your work before you begin to conduct the research,

Seeking IRB approval entails evaluating the risk that participating in your project poses to all whom you may invite to participate. This risk often varies by participant. When the risk to all of the different types of human participants is minimal, you can request that your project be exempt from further IRB review. Note that declaring a project “exempt” from IRB supervision is not a decision that researchers can make on their own.

Strategies for Protecting Human Participants

Obtaining informed consent is crucial for conducting ethical research. You must inform those whom you invite to participate in your work what that participation will entail, what benefits it may bring to them, and what risks it may pose for them, and how you will manage, use, and share the information that they provide to you. You are required to obtain each participant’s written or oral consent to the arrangements you jointly decide upon.

Whenever you collect private and/or sensitive information from a project participant and that participant requests – or a law requires – that the information be kept confidential, you must make sure the information and the data generated from it are de-identified to protect the participant’s identity and privacy.

If you share your research data in a trusted digital repository, you can further protect participants’ privacy by restricting who may access the data and under what conditions they may do so.

Research data – even sensitive data – can be shared ethically and legally. The general guidance offered here is meant to help you think about how to design and carry out your research in ways that will facilitate such sharing. More specific guidance on conducting research ethically is provided by academic institutions, employers, funders, and professional organizations. We encourage you to become as informed as you can about the ethical conduct of research.

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Decision Tool: Am I Doing Human Subjects Research?

The Office of Extramural Research (OER) has developed a quick decision tool that should assist you with determining if your research involves human subjects, may be considered exempt from Federal regulations, or is not considered human subjects research. This tool should not be used as the sole determination of exemption.

This page last updated on: January 15, 2019

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Ethics in human research

Jharna mandal.

Department of Microbiology, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry - 605 006, India. E-mail: ni.oc.oohay@ajiraphsahbus

Srinivas Acharya

Subhash chandra parija.

‘Ethical conduct’ literally means simply doing the right thing, but in reality it means more. It involves acting in the right spirit, out of an abiding respect and concern for one's fellow creatures.

Human research is research conducted with or about people, or their data or tissues, with the sole intention to do good.

Human research involves significant risks and it is possible for things to go wrong. Despite the best of intentions and care in planning and practice, sometimes things go awry. Now and then mishaps may arise because of technical errors or an ethical insensitivity, neglect or disregard.

On rare occasions, the practice of research has even involved deliberate and appalling violation of human beings. Earlier, in the 1900s, there were no regulations regarding the ethical use of human subjects in research. There were no guidelines or any code drawn out for conduct and no Institutional Review Board (IRB). Here is a brief account of why rules and regulations were established and the need for all established research institutes to have an IRB became a necessity.[ 1 ]

THE NUREMBERG CODE

A well-known chapter in the history of research with human subjects opened on December 9, 1946, when an American military tribunal opened criminal proceedings against 23 leading German physicians and administrators for their willing participation in war crimes and crimes against humanity. Among the charges were that German physicians conducted medical experiments on thousands of concentration camp prisoners without their consent. Most of the subjects of these experiments died or were permanently crippled as a result.

As a direct result of the trial, the Nuremberg Code was established in 1948, stating that ‘The voluntary consent of the human subject is absolutely essential,’ making it clear that subjects should give consent and that the benefits of the research must outweigh the risks.

Although it did not carry the force of law, the Nuremberg Code was the first international document, which advocated voluntary participation and informed consent.[ 2 ]

THE DECLARATION OF HELSINKI

In 1964, the World Medical Association established recommendations guiding medical doctors in biomedical research involving human subjects. The Declaration governs international research ethics and defines rules for ‘research combined with clinical care’ and ‘non-therapeutic research.’ The Declaration of Helsinki was revised in 1975, 1983, 1989, and 1996, and is the basis for Good Clinical Practices used today.

Issues addressed in the declaration of Helsinki include:

• Research with humans should be based on the results from laboratory and animal experimentation
• Research protocols should be reviewed by an independent committee prior to initiation
• Informed consent from research participants is necessary
• Research should be conducted by medically / scientifically qualified individuals
• Risks should not exceed benefits

THE TUSKEGEE SYPHILIS STUDY (1932 – 1972)

One of the turning points in the development of a consensus for guidelines for ethical conduct in research was a project conducted by the US Public Health Service. Six hundred low-income, African-American males, 400 of whom were infected with syphilis, were monitored for 40 years. Free medical examinations were conducted; however, the subjects were not told about their disease. Even though a proven cure (penicillin) became available in the 1950s, the study continued until 1972, with participants being denied treatment. In some cases, when the subjects were diagnosed as having syphilis by other physicians, researchers intervened to prevent treatment. The study sparked off a wide-scale public outrage when it became publicly known, and the US government had to close it in 1973.

Due to the publicity from the Tuskegee Syphilis Study, a National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research was formed in the US, which was in charge of identifying the basic ethical principles that should underline the conduct of biomedical and behavioral research involving human subjects and to develop guidelines that should be followed, to assure that such research is conducted in accordance with those principles. The Commission drafted the Belmont Report, a foundational document for the ethics of human subjects’ research in the United States.[ 3 ]

THE BELMONT REPORT

The Belmont Report was published in 1979, with attempts to summarize the basic ethical principles identified by the Commission in the course of its deliberations. The Report is a statement of the basic ethical principles and guidelines that should assist in resolving the ethical problems that surround the conduct of research with human subjects. The three basic ethical principles and their corresponding applications according to the report are:

The Belmont Report established three basic ethical principles – respect for persons, beneficence, and justice – which are the cornerstones for the regulations involving human subjects.[ 3 ]

COMMON RULE

This is a set of regulations that have been adopted by many research agencies in the United States and elsewhere.

The main elements of the Common Rule include:[ 3 ]

• requirements for assuring compliance by research institutions
• requirements for researchers obtaining and documenting informed consent
• requirements for Institutional Review Board (IRB) membership, function, operations, review of research, and record keeping
• additional protection for certain vulnerable research subjects – pregnant women, prisoners, and children

Situation in India

As in the case of many other nations, India too has developed national guidelines for research involving human beings. In our country the guidelines, which are often cited and followed, are those issued by the Indian Council of Medical Research, New Delhi. The Indian Council of Medical research brought out the ‘Policy Statement on Ethical Considerations involved in Research on Human Subjects,’ in 1980, and revised these guidelines in 2000, as the ‘Ethical guidelines for Biomedical Research on Human Subjects’. Since then it has been revised and the latest version has been published in 2006.

In its general statement the document stresses on the fact that only such research should be undertaken whose purpose would be to advance the ‘betterment of all, especially the least advantaged’. The manner in which the research is conducted should not compromise the dignity and well-being of the subjects, and it should avoid the historical pitfalls of unethical research, To ensure sound scientific output ‘the research must be subjected to a strict regime of evaluation at all stages of the proposal’.[ 4 ]

All human beings are born free and equal in dignity and rights; it is the duty of each and every man related or unrelated to science to treat their fellow beings with love and respect.