what is a single study research article

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10.1 Overview of Single-Subject Research

Learning objectives.

• Explain what single-subject research is, including how it differs from other types of psychological research.
• Explain what case studies are, including some of their strengths and weaknesses.
• Explain who uses single-subject research and why.

What Is Single-Subject Research?

Single-subject research is a type of quantitative research that involves studying in detail the behavior of each of a small number of participants. Note that the term single-subject does not mean that only one participant is studied; it is more typical for there to be somewhere between two and 10 participants. (This is why single-subject research designs are sometimes called small- n designs, where n is the statistical symbol for the sample size.) Single-subject research can be contrasted with group research , which typically involves studying large numbers of participants and examining their behavior primarily in terms of group means, standard deviations, and so on. The majority of this book is devoted to understanding group research, which is the most common approach in psychology. But single-subject research is an important alternative, and it is the primary approach in some areas of psychology.

Before continuing, it is important to distinguish single-subject research from two other approaches, both of which involve studying in detail a small number of participants. One is qualitative research, which focuses on understanding people’s subjective experience by collecting relatively unstructured data (e.g., detailed interviews) and analyzing those data using narrative rather than quantitative techniques. Single-subject research, in contrast, focuses on understanding objective behavior through experimental manipulation and control, collecting highly structured data, and analyzing those data quantitatively.

It is also important to distinguish single-subject research from case studies. A case study is a detailed description of an individual, which can include both qualitative and quantitative analyses. (Case studies that include only qualitative analyses can be considered a type of qualitative research.) The history of psychology is filled with influential cases studies, such as Sigmund Freud’s description of “Anna O.” (see Note 10.5 “The Case of “Anna O.”” ) and John Watson and Rosalie Rayner’s description of Little Albert (Watson & Rayner, 1920), who learned to fear a white rat—along with other furry objects—when the researchers made a loud noise while he was playing with the rat. Case studies can be useful for suggesting new research questions and for illustrating general principles. They can also help researchers understand rare phenomena, such as the effects of damage to a specific part of the human brain. As a general rule, however, case studies cannot substitute for carefully designed group or single-subject research studies. One reason is that case studies usually do not allow researchers to determine whether specific events are causally related, or even related at all. For example, if a patient is described in a case study as having been sexually abused as a child and then as having developed an eating disorder as a teenager, there is no way to determine whether these two events had anything to do with each other. A second reason is that an individual case can always be unusual in some way and therefore be unrepresentative of people more generally. Thus case studies have serious problems with both internal and external validity.

The Case of “Anna O.”

Sigmund Freud used the case of a young woman he called “Anna O.” to illustrate many principles of his theory of psychoanalysis (Freud, 1961). (Her real name was Bertha Pappenheim, and she was an early feminist who went on to make important contributions to the field of social work.) Anna had come to Freud’s colleague Josef Breuer around 1880 with a variety of odd physical and psychological symptoms. One of them was that for several weeks she was unable to drink any fluids. According to Freud,

She would take up the glass of water that she longed for, but as soon as it touched her lips she would push it away like someone suffering from hydrophobia.…She lived only on fruit, such as melons, etc., so as to lessen her tormenting thirst (p. 9).

But according to Freud, a breakthrough came one day while Anna was under hypnosis.

[S]he grumbled about her English “lady-companion,” whom she did not care for, and went on to describe, with every sign of disgust, how she had once gone into this lady’s room and how her little dog—horrid creature!—had drunk out of a glass there. The patient had said nothing, as she had wanted to be polite. After giving further energetic expression to the anger she had held back, she asked for something to drink, drank a large quantity of water without any difficulty, and awoke from her hypnosis with the glass at her lips; and thereupon the disturbance vanished, never to return.

Freud’s interpretation was that Anna had repressed the memory of this incident along with the emotion that it triggered and that this was what had caused her inability to drink. Furthermore, her recollection of the incident, along with her expression of the emotion she had repressed, caused the symptom to go away.

As an illustration of Freud’s theory, the case study of Anna O. is quite effective. As evidence for the theory, however, it is essentially worthless. The description provides no way of knowing whether Anna had really repressed the memory of the dog drinking from the glass, whether this repression had caused her inability to drink, or whether recalling this “trauma” relieved the symptom. It is also unclear from this case study how typical or atypical Anna’s experience was.

Figure 10.2

“Anna O.” was the subject of a famous case study used by Freud to illustrate the principles of psychoanalysis.

Wikimedia Commons – public domain.

Assumptions of Single-Subject Research

Again, single-subject research involves studying a small number of participants and focusing intensively on the behavior of each one. But why take this approach instead of the group approach? There are several important assumptions underlying single-subject research, and it will help to consider them now.

First and foremost is the assumption that it is important to focus intensively on the behavior of individual participants. One reason for this is that group research can hide individual differences and generate results that do not represent the behavior of any individual. For example, a treatment that has a positive effect for half the people exposed to it but a negative effect for the other half would, on average, appear to have no effect at all. Single-subject research, however, would likely reveal these individual differences. A second reason to focus intensively on individuals is that sometimes it is the behavior of a particular individual that is primarily of interest. A school psychologist, for example, might be interested in changing the behavior of a particular disruptive student. Although previous published research (both single-subject and group research) is likely to provide some guidance on how to do this, conducting a study on this student would be more direct and probably more effective.

A second assumption of single-subject research is that it is important to discover causal relationships through the manipulation of an independent variable, the careful measurement of a dependent variable, and the control of extraneous variables. For this reason, single-subject research is often considered a type of experimental research with good internal validity. Recall, for example, that Hall and his colleagues measured their dependent variable (studying) many times—first under a no-treatment control condition, then under a treatment condition (positive teacher attention), and then again under the control condition. Because there was a clear increase in studying when the treatment was introduced, a decrease when it was removed, and an increase when it was reintroduced, there is little doubt that the treatment was the cause of the improvement.

A third assumption of single-subject research is that it is important to study strong and consistent effects that have biological or social importance. Applied researchers, in particular, are interested in treatments that have substantial effects on important behaviors and that can be implemented reliably in the real-world contexts in which they occur. This is sometimes referred to as social validity (Wolf, 1976). The study by Hall and his colleagues, for example, had good social validity because it showed strong and consistent effects of positive teacher attention on a behavior that is of obvious importance to teachers, parents, and students. Furthermore, the teachers found the treatment easy to implement, even in their often chaotic elementary school classrooms.

Who Uses Single-Subject Research?

Single-subject research has been around as long as the field of psychology itself. In the late 1800s, one of psychology’s founders, Wilhelm Wundt, studied sensation and consciousness by focusing intensively on each of a small number of research participants. Herman Ebbinghaus’s research on memory and Ivan Pavlov’s research on classical conditioning are other early examples, both of which are still described in almost every introductory psychology textbook.

In the middle of the 20th century, B. F. Skinner clarified many of the assumptions underlying single-subject research and refined many of its techniques (Skinner, 1938). He and other researchers then used it to describe how rewards, punishments, and other external factors affect behavior over time. This work was carried out primarily using nonhuman subjects—mostly rats and pigeons. This approach, which Skinner called the experimental analysis of behavior —remains an important subfield of psychology and continues to rely almost exclusively on single-subject research. For excellent examples of this work, look at any issue of the Journal of the Experimental Analysis of Behavior . By the 1960s, many researchers were interested in using this approach to conduct applied research primarily with humans—a subfield now called applied behavior analysis (Baer, Wolf, & Risley, 1968). Applied behavior analysis plays an especially important role in contemporary research on developmental disabilities, education, organizational behavior, and health, among many other areas. Excellent examples of this work (including the study by Hall and his colleagues) can be found in the Journal of Applied Behavior Analysis .

Although most contemporary single-subject research is conducted from the behavioral perspective, it can in principle be used to address questions framed in terms of any theoretical perspective. For example, a studying technique based on cognitive principles of learning and memory could be evaluated by testing it on individual high school students using the single-subject approach. The single-subject approach can also be used by clinicians who take any theoretical perspective—behavioral, cognitive, psychodynamic, or humanistic—to study processes of therapeutic change with individual clients and to document their clients’ improvement (Kazdin, 1982).

Key Takeaways

• Single-subject research—which involves testing a small number of participants and focusing intensively on the behavior of each individual—is an important alternative to group research in psychology.
• Single-subject studies must be distinguished from case studies, in which an individual case is described in detail. Case studies can be useful for generating new research questions, for studying rare phenomena, and for illustrating general principles. However, they cannot substitute for carefully controlled experimental or correlational studies because they are low in internal and external validity.
• Single-subject research has been around since the beginning of the field of psychology. Today it is most strongly associated with the behavioral theoretical perspective, but it can in principle be used to study behavior from any perspective.
• Practice: Find and read a published article in psychology that reports new single-subject research. (A good source of articles published in the Journal of Applied Behavior Analysis can be found at http://seab.envmed.rochester.edu/jaba/jabaMostPop-2011.html .) Write a short summary of the study.

Practice: Find and read a published case study in psychology. (Use case study as a key term in a PsycINFO search.) Then do the following:

• Describe one problem related to internal validity.
• Describe one problem related to external validity.
• Generate one hypothesis suggested by the case study that might be interesting to test in a systematic single-subject or group study.

Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis , 1 , 91–97.

Freud, S. (1961). Five lectures on psycho-analysis . New York, NY: Norton.

Kazdin, A. E. (1982). Single-case research designs: Methods for clinical and applied settings . New York, NY: Oxford University Press.

Skinner, B. F. (1938). The behavior of organisms: An experimental analysis . New York, NY: Appleton-Century-Crofts.

Watson, J. B., & Rayner, R. (1920). Conditioned emotional reactions. Journal of Experimental Psychology , 3 , 1–14.

Wolf, M. (1976). Social validity: The case for subjective measurement or how applied behavior analysis is finding its heart. Journal of Applied Behavior Analysis, 11 , 203–214.

Research Methods in Psychology Copyright © 2016 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Answered By: Last Updated: Feb 17, 2024     Views: 1671

What is an original research or single study article, and how do i find it in the library databases.

Original research, also known as a single study, primary study or empirical study, is one that reports results of a scientific study rather than summarizing other articles. Basically, original research is where the researchers do the study and report their findings.

Find an Original Research Article in the Library

• Start your search from the Search Everything box on the library homepage.
• Enter your keywords, and select  Search . 
• Under the Filter Results section on the left-hand side of the search results, select Peer-Reviewed Journals and Articles , and change the Publication Date range to reflect your assignment requirements. 
• Read the abstract of the article(s) to determine if it is original research. The abstract of the article usually contains subdivision headings where each of the key sections are summarized individually such as Literature Review or Background, Methods, Results, Conclusions and Discussion. The methodology section will tell you what they are doing in the study. 

Note!  There is no way to limit the results to only show original research articles in this search system. If you are having trouble identifying the type of study, please contact your professor.

For more information on types of research, see our  Finding Types of Research guide .

Watch the Tutorial Video

Select the image below to watch a video on how to determine if an article is original research.

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Neag School of Education

Educational Research Basics by Del Siegle

Single subject research.

“ Single subject research (also known as single case experiments) is popular in the fields of special education and counseling. This research design is useful when the researcher is attempting to change the behavior of an individual or a small group of individuals and wishes to document that change. Unlike true experiments where the researcher randomly assigns participants to a control and treatment group, in single subject research the participant serves as both the control and treatment group. The researcher uses line graphs to show the effects of a particular intervention or treatment.  An important factor of single subject research is that only one variable is changed at a time. Single subject research designs are “weak when it comes to external validity….Studies involving single-subject designs that show a particular treatment to be effective in changing behavior must rely on replication–across individuals rather than groups–if such results are be found worthy of generalization” (Fraenkel & Wallen, 2006, p. 318).

Suppose a researcher wished to investigate the effect of praise on reducing disruptive behavior over many days. First she would need to establish a baseline of how frequently the disruptions occurred. She would measure how many disruptions occurred each day for several days. In the example below, the target student was disruptive seven times on the first day, six times on the second day, and seven times on the third day. Note how the sequence of time is depicted on the x-axis (horizontal axis) and the dependent variable (outcome variable) is depicted on the y-axis (vertical axis).

Once a baseline of behavior has been established (when a consistent pattern emerges with at least three data points), the intervention begins. The researcher continues to plot the frequency of behavior while implementing the intervention of praise.

In this example, we can see that the frequency of disruptions decreased once praise began. The design in this example is known as an A-B design. The baseline period is referred to as A and the intervention period is identified as B.

Another design is the A-B-A design. An A-B-A design (also known as a reversal design) involves discontinuing the intervention and returning to a nontreatment condition.

Sometimes an individual’s behavior is so severe that the researcher cannot wait to establish a baseline and must begin with an intervention. In this case, a B-A-B design is used. The intervention is implemented immediately (before establishing a baseline). This is followed by a measurement without the intervention and then a repeat of the intervention.

Multiple-Baseline Design

Sometimes, a researcher may be interested in addressing several issues for one student or a single issue for several students. In this case, a multiple-baseline design is used.

“In a multiple baseline across subjects design, the researcher introduces the intervention to different persons at different times. The significance of this is that if a behavior changes only after the intervention is presented, and this behavior change is seen successively in each subject’s data, the effects can more likely be credited to the intervention itself as opposed to other variables. Multiple-baseline designs do not require the intervention to be withdrawn. Instead, each subject’s own data are compared between intervention and nonintervention behaviors, resulting in each subject acting as his or her own control (Kazdin, 1982). An added benefit of this design, and all single-case designs, is the immediacy of the data. Instead of waiting until postintervention to take measures on the behavior, single-case research prescribes continuous data collection and visual monitoring of that data displayed graphically, allowing for immediate instructional decision-making. Students, therefore, do not linger in an intervention that is not working for them, making the graphic display of single-case research combined with differentiated instruction responsive to the needs of students.” (Geisler, Hessler, Gardner, & Lovelace, 2009)

Regardless of the research design, the line graphs used to illustrate the data contain a set of common elements.

Generally, in single subject research we count the number of times something occurs in a given time period and see if it occurs more or less often in that time period after implementing an intervention. For example, we might measure how many baskets someone makes while shooting for 2 minutes. We would repeat that at least three times to get our baseline. Next, we would test some intervention. We might play music while shooting, give encouragement while shooting, or video the person while shooting to see if our intervention influenced the number of shots made. After the 3 baseline measurements (3 sets of 2 minute shooting), we would measure several more times (sets of 2 minute shooting) after the intervention and plot the time points (number of baskets made in 2 minutes for each of the measured time points). This works well for behaviors that are distinct and can be counted.

Sometimes behaviors come and go over time (such as being off task in a classroom or not listening during a coaching session). The way we can record these is to select a period of time (say 5 minutes) and mark down every 10 seconds whether our participant is on task. We make a minimum of three sets of 5 minute observations for a baseline, implement an intervention, and then make more sets of 5 minute observations with the intervention in place. We use this method rather than counting how many times someone is off task because one could continually be off task and that would only be a count of 1 since the person was continually off task. Someone who might be off task twice for 15 second would be off task twice for a score of 2. However, the second person is certainly not off task twice as much as the first person. Therefore, recording whether the person is off task at 10-second intervals gives a more accurate picture. The person continually off task would have a score of 30 (off task at every second interval for 5 minutes) and the person off task twice for a short time would have a score of 2 (off task only during 2 of the 10 second interval measures.

I also have additional information about how to record single-subject research data .

I hope this helps you better understand single subject research.

I have created a PowerPoint on Single Subject Research , which also available below as a video.

I have also created instructions for creating single-subject research design graphs with Excel .

Fraenkel, J. R., & Wallen, N. E. (2006). How to design and evaluate research in education (6th ed.). Boston, MA: McGraw Hill.

Geisler, J. L., Hessler, T., Gardner, R., III, & Lovelace, T. S. (2009). Differentiated writing interventions for high-achieving urban African American elementary students. Journal of Advanced Academics, 20, 214–247.

Del Siegle, Ph.D. University of Connecticut [email protected] www.delsiegle.info

Revised 02/02/2024

Applied Behavior Analysis

• Find Articles on a Topic

Two Ways to Find Single Subject Research Design (SSRD) Articles

Finding ssrd articles via the browsing method, finding ssrd articles via the searching method.

• Search by Article Citation in OneSearch
• Find Reading Lists (AKA 'Course Reserves')
• Get Articles We Don't Have through Interlibrary Loan
• Browse ABA Journals
• APA citation style
• Install LibKey Nomad

Types of Single Subject Research Design

 Types of SSRDs to look for as you skim abstracts:

• reversal design
• withdrawal design
• ABAB design
• A-B-A-B design
• A-B-C design
• A-B-A design
• multiple baseline
• alternating treatments design
• multi-element design
• changing criterion design
• single case design
• single subject design
• single case series

Behavior analysts recognize the advantages of single-subject design for establishing intervention efficacy.  Much of the research performed by behavior analysts will use SSRD methods.

When you need to find SSRD articles, there are two methods you can use:

• Click on a title from the list of ABA Journal Titles .
• Scroll down on the resulting page to the View Online section.
• Choose a link which includes the date range you're interested in.
• Click on a link to an issue (date) you want to explore.
• From the resulting Table of Contents, explore titles of interest, reading the abstract carefully for signs that the research was carried out using a SSRD.  (To help, look for the box on this page with a list of SSRD types.)
• APA PsycInfo This link opens in a new window When you search in APA PsycInfo, you are searching through abstracts and descriptions of articles published in these ABA Journals in addition to thousands of other psychology-related journals. more... less... Description: PsycInfo is a key database in the field of psychology. Includes information of use to psychologists, students, and professionals in related fields such as psychiatry, management, business, and education, social science, neuroscience, law, medicine, and social work. Time Period: 1887 to present Sources: Indexes more than 2,500 journals. Subject Headings: Education, Mobile, Psychology, Social Sciences (Psychology) Scholarly or Popular: Scholarly Primary Materials: Journal Articles Information Included: Abstracts, Citations, Linked Full Text FindIt@BALL STATE: Yes Print Equivalent: None Publisher: American Psychological Association Updates: Monthly Number of Simultaneous Users: Unlimited

First , go to APA PsycInfo.

Second , copy and paste this set of terms describing different types of SSRDs into an APA PsycInfo search box, and choose "Abstract" in the drop-down menu.

Third , copy and paste this list of ABA journals into another search box in APA PsycInfo, and choose "SO Publication Name" in the drop-down menu.

Fourth , type in some keywords in another APA PsycInfo search box (or two) describing what you're researching.  Use OR and add synonyms or related words for the best results.

Hit SEARCH, and see what kind of results you get!

Here's an example of a search for SSRDs in ABA journals on the topic of fitness:

Note that the long list of terms in the top two boxes gets cut off in the screenshot - - but they're all there!

The reason this works:

• To find SSRD articles, we can't just search on the phrase "single subject research" because many studies which use SSRD do not include that phrase anywhere in the text of the article; instead such articles typically specify in the abstract (and "Methods" section) what type of SSRD method was used (ex. withdrawal design, multiple baseline, or ABA design).  That's why we string together all the possible descriptions of SSRD types with the word OR in between -- it enables us to search for any sort of SSRD, regardless of how it's described.  Choosing "Abstract" in the drop-down menu ensures that we're focusing on these terms being used in the abstract field (not just popping up in discussion in the full-text).
• To search specifically for studies carried out in the field of Applied Behavior Analysis, we enter in the titles of the ABA journals, strung together, with OR in between.  The quotation marks ensure each title is searched as a phrase.  Choosing "SO Publication Name" in the drop-down menu ensures that results will be from articles published in those journals (not just references to those journals).
• To limit the search to a topic we're interested in, we type in some keywords in another search box.  The more synonyms you can think of, the better; that ensures you'll have a decent pool of records to look through, including authors who may have described your topic differently.

Search ideas:

To limit your search to just the top ABA journals, you can use this shorter list in place of the long one above:

"Behavior Analysis in Practice" OR "Journal of Applied Behavior Analysis" OR "Journal of Behavioral Education" OR "Journal of Developmental and Physical Disabilities" OR "Journal of the Experimental Analysis of Behavior"

To get more specific, topic-wise, add another search box with another term (or set of terms), like in this example:

To search more broadly and include other psychology studies outside of ABA journals, simply remove the list of journal titles from the search, as shown here:

• << Previous: Find Articles on a Topic
• Next: Search by Article Citation in OneSearch >>
• Last Updated: Apr 24, 2024 10:40 AM
• URL: https://bsu.libguides.com/appliedbehavioranalysis

10.1 Overview of Single-Subject Research

Learning objectives.

• Explain what single-subject research is, including how it differs from other types of psychological research.
• Explain who uses single-subject research and why.

What Is Single-Subject Research?

Single-subject research  is a type of quantitative research that involves studying in detail the behavior of each of a small number of participants. Note that the term  single-subject  does not mean that only one participant is studied; it is more typical for there to be somewhere between two and 10 participants. (This is why single-subject research designs are sometimes called small- n designs, where  n  is the statistical symbol for the sample size.) Single-subject research can be contrasted with  group research , which typically involves studying large numbers of participants and examining their behavior primarily in terms of group means, standard deviations, and so on. The majority of this textbook is devoted to understanding group research, which is the most common approach in psychology. But single-subject research is an important alternative, and it is the primary approach in some more applied areas of psychology.

Before continuing, it is important to distinguish single-subject research from case studies and other more qualitative approaches that involve studying in detail a small number of participants. As described in Chapter 6, case studies involve an in-depth analysis and description of an individual, which is typically primarily qualitative in nature. More broadly speaking, qualitative research focuses on understanding people’s subjective experience by observing behavior and collecting relatively unstructured data (e.g., detailed interviews) and analyzing those data using narrative rather than quantitative techniques. Single-subject research, in contrast, focuses on understanding objective behavior through experimental manipulation and control, collecting highly structured data, and analyzing those data quantitatively.

Assumptions of Single-Subject Research

Again, single-subject research involves studying a small number of participants and focusing intensively on the behavior of each one. But why take this approach instead of the group approach? There are several important assumptions underlying single-subject research, and it will help to consider them now.

First and foremost is the assumption that it is important to focus intensively on the behavior of individual participants. One reason for this is that group research can hide individual differences and generate results that do not represent the behavior of any individual. For example, a treatment that has a positive effect for half the people exposed to it but a negative effect for the other half would, on average, appear to have no effect at all. Single-subject research, however, would likely reveal these individual differences. A second reason to focus intensively on individuals is that sometimes it is the behavior of a particular individual that is primarily of interest. A school psychologist, for example, might be interested in changing the behavior of a particular disruptive student. Although previous published research (both single-subject and group research) is likely to provide some guidance on how to do this, conducting a study on this student would be more direct and probably more effective.

A second assumption of single-subject research is that it is important to discover causal relationships through the manipulation of an independent variable, the careful measurement of a dependent variable, and the control of extraneous variables. For this reason, single-subject research is often considered a type of experimental research with good internal validity. Recall, for example, that Hall and his colleagues measured their dependent variable (studying) many times—first under a no-treatment control condition, then under a treatment condition (positive teacher attention), and then again under the control condition. Because there was a clear increase in studying when the treatment was introduced, a decrease when it was removed, and an increase when it was reintroduced, there is little doubt that the treatment was the cause of the improvement.

A third assumption of single-subject research is that it is important to study strong and consistent effects that have biological or social importance. Applied researchers, in particular, are interested in treatments that have substantial effects on important behaviors and that can be implemented reliably in the real-world contexts in which they occur. This is sometimes referred to as social validity  (Wolf, 1976) [1] . The study by Hall and his colleagues, for example, had good social validity because it showed strong and consistent effects of positive teacher attention on a behavior that is of obvious importance to teachers, parents, and students. Furthermore, the teachers found the treatment easy to implement, even in their often-chaotic elementary school classrooms.

Who Uses Single-Subject Research?

Single-subject research has been around as long as the field of psychology itself. In the late 1800s, one of psychology’s founders, Wilhelm Wundt, studied sensation and consciousness by focusing intensively on each of a small number of research participants. Herman Ebbinghaus’s research on memory and Ivan Pavlov’s research on classical conditioning are other early examples, both of which are still described in almost every introductory psychology textbook.

In the middle of the 20th century, B. F. Skinner clarified many of the assumptions underlying single-subject research and refined many of its techniques (Skinner, 1938) [2] . He and other researchers then used it to describe how rewards, punishments, and other external factors affect behavior over time. This work was carried out primarily using nonhuman subjects—mostly rats and pigeons. This approach, which Skinner called the experimental analysis of behavior —remains an important subfield of psychology and continues to rely almost exclusively on single-subject research. For excellent examples of this work, look at any issue of the  Journal of the Experimental Analysis of Behavior . By the 1960s, many researchers were interested in using this approach to conduct applied research primarily with humans—a subfield now called  applied behavior analysis  (Baer, Wolf, & Risley, 1968) [3] . Applied behavior analysis plays an especially important role in contemporary research on developmental disabilities, education, organizational behavior, and health, among many other areas. Excellent examples of this work (including the study by Hall and his colleagues) can be found in the  Journal of Applied Behavior Analysis .

Although most contemporary single-subject research is conducted from the behavioral perspective, it can in principle be used to address questions framed in terms of any theoretical perspective. For example, a studying technique based on cognitive principles of learning and memory could be evaluated by testing it on individual high school students using the single-subject approach. The single-subject approach can also be used by clinicians who take any theoretical perspective—behavioral, cognitive, psychodynamic, or humanistic—to study processes of therapeutic change with individual clients and to document their clients’ improvement (Kazdin, 1982) [4] .

Key Takeaways

• Single-subject research—which involves testing a small number of participants and focusing intensively on the behavior of each individual—is an important alternative to group research in psychology.
• Single-subject studies must be distinguished from qualitative research on a single person or small number of individuals. Unlike more qualitative research, single-subject research focuses on understanding objective behavior through experimental manipulation and control, collecting highly structured data, and analyzing those data quantitatively.
• Single-subject research has been around since the beginning of the field of psychology. Today it is most strongly associated with the behavioral theoretical perspective, but it can in principle be used to study behavior from any perspective.
• Practice: Find and read a published article in psychology that reports new single-subject research. (An archive of articles published in the Journal of Applied Behavior Analysis can be found at http://www.ncbi.nlm.nih.gov/pmc/journals/309/ ) Write a short summary of the study.
• Wolf, M. (1976). Social validity: The case for subjective measurement or how applied behavior analysis is finding its heart.  Journal of Applied Behavior Analysis, 11 , 203–214. ↵
• Skinner, B. F. (1938). T he behavior of organisms: An experimental analysis . New York, NY: Appleton-Century-Crofts. ↵
• Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis.  Journal of Applied Behavior Analysis, 1 , 91–97. ↵
• Kazdin, A. E. (1982).  Single-case research designs: Methods for clinical and applied settings . New York, NY: Oxford University Press. ↵

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Single-Subject Research

45 Single-Subject Research Designs

Learning objectives.

• Describe the basic elements of a single-subject research design.
• Design simple single-subject studies using reversal and multiple-baseline designs.
• Explain how single-subject research designs address the issue of internal validity.
• Interpret the results of simple single-subject studies based on the visual inspection of graphed data.

General Features of Single-Subject Designs

Before looking at any specific single-subject research designs, it will be helpful to consider some features that are common to most of them. Many of these features are illustrated in Figure 10.1, which shows the results of a generic single-subject study. First, the dependent variable (represented on the  y -axis of the graph) is measured repeatedly over time (represented by the  x -axis) at regular intervals. Second, the study is divided into distinct phases, and the participant is tested under one condition per phase. The conditions are often designated by capital letters: A, B, C, and so on. Thus Figure 10.1 represents a design in which the participant was tested first in one condition (A), then tested in another condition (B), and finally retested in the original condition (A). (This is called a reversal design and will be discussed in more detail shortly.)

Another important aspect of single-subject research is that the change from one condition to the next does not usually occur after a fixed amount of time or number of observations. Instead, it depends on the participant’s behavior. Specifically, the researcher waits until the participant’s behavior in one condition becomes fairly consistent from observation to observation before changing conditions. This is sometimes referred to as the steady state strategy  (Sidman, 1960) [1] . The idea is that when the dependent variable has reached a steady state, then any change across conditions will be relatively easy to detect. Recall that we encountered this same principle when discussing experimental research more generally. The effect of an independent variable is easier to detect when the “noise” in the data is minimized.

Reversal Designs

The most basic single-subject research design is the  reversal design , also called the  ABA design . During the first phase, A, a  baseline  is established for the dependent variable. This is the level of responding before any treatment is introduced, and therefore the baseline phase is a kind of control condition. When steady state responding is reached, phase B begins as the researcher introduces the treatment. There may be a period of adjustment to the treatment during which the behavior of interest becomes more variable and begins to increase or decrease. Again, the researcher waits until that dependent variable reaches a steady state so that it is clear whether and how much it has changed. Finally, the researcher removes the treatment and again waits until the dependent variable reaches a steady state. This basic reversal design can also be extended with the reintroduction of the treatment (ABAB), another return to baseline (ABABA), and so on.

The study by Hall and his colleagues employed an ABAB reversal design. Figure 10.2 approximates the data for Robbie. The percentage of time he spent studying (the dependent variable) was low during the first baseline phase, increased during the first treatment phase until it leveled off, decreased during the second baseline phase, and again increased during the second treatment phase.

Why is the reversal—the removal of the treatment—considered to be necessary in this type of design? Why use an ABA design, for example, rather than a simpler AB design? Notice that an AB design is essentially an interrupted time-series design applied to an individual participant. Recall that one problem with that design is that if the dependent variable changes after the treatment is introduced, it is not always clear that the treatment was responsible for the change. It is possible that something else changed at around the same time and that this extraneous variable is responsible for the change in the dependent variable. But if the dependent variable changes with the introduction of the treatment and then changes  back  with the removal of the treatment (assuming that the treatment does not create a permanent effect), it is much clearer that the treatment (and removal of the treatment) is the cause. In other words, the reversal greatly increases the internal validity of the study.

There are close relatives of the basic reversal design that allow for the evaluation of more than one treatment. In a  multiple-treatment reversal design , a baseline phase is followed by separate phases in which different treatments are introduced. For example, a researcher might establish a baseline of studying behavior for a disruptive student (A), then introduce a treatment involving positive attention from the teacher (B), and then switch to a treatment involving mild punishment for not studying (C). The participant could then be returned to a baseline phase before reintroducing each treatment—perhaps in the reverse order as a way of controlling for carryover effects. This particular multiple-treatment reversal design could also be referred to as an ABCACB design.

In an  alternating treatments design , two or more treatments are alternated relatively quickly on a regular schedule. For example, positive attention for studying could be used one day and mild punishment for not studying the next, and so on. Or one treatment could be implemented in the morning and another in the afternoon. The alternating treatments design can be a quick and effective way of comparing treatments, but only when the treatments are fast acting.

Multiple-Baseline Designs

There are two potential problems with the reversal design—both of which have to do with the removal of the treatment. One is that if a treatment is working, it may be unethical to remove it. For example, if a treatment seemed to reduce the incidence of self-injury in a child with an intellectual delay, it would be unethical to remove that treatment just to show that the incidence of self-injury increases. The second problem is that the dependent variable may not return to baseline when the treatment is removed. For example, when positive attention for studying is removed, a student might continue to study at an increased rate. This could mean that the positive attention had a lasting effect on the student’s studying, which of course would be good. But it could also mean that the positive attention was not really the cause of the increased studying in the first place. Perhaps something else happened at about the same time as the treatment—for example, the student’s parents might have started rewarding him for good grades. One solution to these problems is to use a  multiple-baseline design , which is represented in Figure 10.3. There are three different types of multiple-baseline designs which we will now consider.

Multiple-Baseline Design Across Participants

In one version of the design, a baseline is established for each of several participants, and the treatment is then introduced for each one. In essence, each participant is tested in an AB design. The key to this design is that the treatment is introduced at a different  time  for each participant. The idea is that if the dependent variable changes when the treatment is introduced for one participant, it might be a coincidence. But if the dependent variable changes when the treatment is introduced for multiple participants—especially when the treatment is introduced at different times for the different participants—then it is unlikely to be a coincidence.

As an example, consider a study by Scott Ross and Robert Horner (Ross & Horner, 2009) [2] . They were interested in how a school-wide bullying prevention program affected the bullying behavior of particular problem students. At each of three different schools, the researchers studied two students who had regularly engaged in bullying. During the baseline phase, they observed the students for 10-minute periods each day during lunch recess and counted the number of aggressive behaviors they exhibited toward their peers. After 2 weeks, they implemented the program at one school. After 2 more weeks, they implemented it at the second school. And after 2 more weeks, they implemented it at the third school. They found that the number of aggressive behaviors exhibited by each student dropped shortly after the program was implemented at the student’s school. Notice that if the researchers had only studied one school or if they had introduced the treatment at the same time at all three schools, then it would be unclear whether the reduction in aggressive behaviors was due to the bullying program or something else that happened at about the same time it was introduced (e.g., a holiday, a television program, a change in the weather). But with their multiple-baseline design, this kind of coincidence would have to happen three separate times—a very unlikely occurrence—to explain their results.

Multiple-Baseline Design Across Behaviors

In another version of the multiple-baseline design, multiple baselines are established for the same participant but for different dependent variables, and the treatment is introduced at a different time for each dependent variable. Imagine, for example, a study on the effect of setting clear goals on the productivity of an office worker who has two primary tasks: making sales calls and writing reports. Baselines for both tasks could be established. For example, the researcher could measure the number of sales calls made and reports written by the worker each week for several weeks. Then the goal-setting treatment could be introduced for one of these tasks, and at a later time the same treatment could be introduced for the other task. The logic is the same as before. If productivity increases on one task after the treatment is introduced, it is unclear whether the treatment caused the increase. But if productivity increases on both tasks after the treatment is introduced—especially when the treatment is introduced at two different times—then it seems much clearer that the treatment was responsible.

Multiple-Baseline Design Across Settings

In yet a third version of the multiple-baseline design, multiple baselines are established for the same participant but in different settings. For example, a baseline might be established for the amount of time a child spends reading during his free time at school and during his free time at home. Then a treatment such as positive attention might be introduced first at school and later at home. Again, if the dependent variable changes after the treatment is introduced in each setting, then this gives the researcher confidence that the treatment is, in fact, responsible for the change.

Data Analysis in Single-Subject Research

In addition to its focus on individual participants, single-subject research differs from group research in the way the data are typically analyzed. As we have seen throughout the book, group research involves combining data across participants. Group data are described using statistics such as means, standard deviations, correlation coefficients, and so on to detect general patterns. Finally, inferential statistics are used to help decide whether the result for the sample is likely to generalize to the population. Single-subject research, by contrast, relies heavily on a very different approach called  visual inspection . This means plotting individual participants’ data as shown throughout this chapter, looking carefully at those data, and making judgments about whether and to what extent the independent variable had an effect on the dependent variable. Inferential statistics are typically not used.

In visually inspecting their data, single-subject researchers take several factors into account. One of them is changes in the level of the dependent variable from condition to condition. If the dependent variable is much higher or much lower in one condition than another, this suggests that the treatment had an effect. A second factor is trend , which refers to gradual increases or decreases in the dependent variable across observations. If the dependent variable begins increasing or decreasing with a change in conditions, then again this suggests that the treatment had an effect. It can be especially telling when a trend changes directions—for example, when an unwanted behavior is increasing during baseline but then begins to decrease with the introduction of the treatment. A third factor is latency , which is the time it takes for the dependent variable to begin changing after a change in conditions. In general, if a change in the dependent variable begins shortly after a change in conditions, this suggests that the treatment was responsible.

In the top panel of Figure 10.4, there are fairly obvious changes in the level and trend of the dependent variable from condition to condition. Furthermore, the latencies of these changes are short; the change happens immediately. This pattern of results strongly suggests that the treatment was responsible for the changes in the dependent variable. In the bottom panel of Figure 10.4, however, the changes in level are fairly small. And although there appears to be an increasing trend in the treatment condition, it looks as though it might be a continuation of a trend that had already begun during baseline. This pattern of results strongly suggests that the treatment was not responsible for any changes in the dependent variable—at least not to the extent that single-subject researchers typically hope to see.

The results of single-subject research can also be analyzed using statistical procedures—and this is becoming more common. There are many different approaches, and single-subject researchers continue to debate which are the most useful. One approach parallels what is typically done in group research. The mean and standard deviation of each participant’s responses under each condition are computed and compared, and inferential statistical tests such as the  t  test or analysis of variance are applied (Fisch, 2001) [3] . (Note that averaging  across  participants is less common.) Another approach is to compute the  percentage of non-overlapping data  (PND) for each participant (Scruggs & Mastropieri, 2001) [4] . This is the percentage of responses in the treatment condition that are more extreme than the most extreme response in a relevant control condition. In the study of Hall and his colleagues, for example, all measures of Robbie’s study time in the first treatment condition were greater than the highest measure in the first baseline, for a PND of 100%. The greater the percentage of non-overlapping data, the stronger the treatment effect. Still, formal statistical approaches to data analysis in single-subject research are generally considered a supplement to visual inspection, not a replacement for it.

Image Description

Figure 10.2 long description:  Line graph showing the results of a study with an ABAB reversal design. The dependent variable was low during first baseline phase; increased during the first treatment; decreased during the second baseline, but was still higher than during the first baseline; and was highest during the second treatment phase.  [Return to Figure 10.2]

Figure 10.3 long description:  Three line graphs showing the results of a generic multiple-baseline study, in which different baselines are established and treatment is introduced to participants at different times.

For Baseline 1, treatment is introduced one-quarter of the way into the study. The dependent variable ranges between 12 and 16 units during the baseline, but drops down to 10 units with treatment and mostly decreases until the end of the study, ranging between 4 and 10 units.

For Baseline 2, treatment is introduced halfway through the study. The dependent variable ranges between 10 and 15 units during the baseline, then has a sharp decrease to 7 units when treatment is introduced. However, the dependent variable increases to 12 units soon after the drop and ranges between 8 and 10 units until the end of the study.

For Baseline 3, treatment is introduced three-quarters of the way into the study. The dependent variable ranges between 12 and 16 units for the most part during the baseline, with one drop down to 10 units. When treatment is introduced, the dependent variable drops down to 10 units and then ranges between 8 and 9 units until the end of the study.  [Return to Figure 10.3]

Figure 10.4 long description:  Two graphs showing the results of a generic single-subject study with an ABA design. In the first graph, under condition A, level is high and the trend is increasing. Under condition B, level is much lower than under condition A and the trend is decreasing. Under condition A again, level is about as high as the first time and the trend is increasing. For each change, latency is short, suggesting that the treatment is the reason for the change.

In the second graph, under condition A, level is relatively low and the trend is increasing. Under condition B, level is a little higher than during condition A and the trend is increasing slightly. Under condition A again, level is a little lower than during condition B and the trend is decreasing slightly. It is difficult to determine the latency of these changes, since each change is rather minute, which suggests that the treatment is ineffective.  [Return to Figure 10.4]

• Sidman, M. (1960). Tactics of scientific research: Evaluating experimental data in psychology . Boston, MA: Authors Cooperative. ↵
• Ross, S. W., & Horner, R. H. (2009). Bully prevention in positive behavior support. Journal of Applied Behavior Analysis, 42 , 747–759. ↵
• Fisch, G. S. (2001). Evaluating data from behavioral analysis: Visual inspection or statistical models. Behavioral Processes, 54 , 137–154. ↵
• Scruggs, T. E., & Mastropieri, M. A. (2001). How to summarize single-participant research: Ideas and applications.  Exceptionality, 9 , 227–244. ↵

When the researcher waits until the participant’s behavior in one condition becomes fairly consistent from observation to observation before changing conditions.

The most basic single-subject research design in which the researcher measures the dependent variable in three phases: Baseline, before a treatment is introduced (A); after the treatment is introduced (B); and then a return to baseline after removing the treatment (A). It is often called an ABA design.

Another term for reversal design.

The beginning phase of an ABA design which acts as a kind of control condition in which the level of responding before any treatment is introduced.

In this design the baseline phase is followed by separate phases in which different treatments are introduced.

In this design two or more treatments are alternated relatively quickly on a regular schedule.

In this design, multiple baselines are either established for one participant or one baseline is established for many participants.

This means plotting individual participants’ data, looking carefully at those plots, and making judgments about whether and to what extent the independent variable had an effect on the dependent variable.

This is the percentage of responses in the treatment condition that are more extreme than the most extreme response in a relevant control condition.

Research Methods in Psychology Copyright © 2019 by Rajiv S. Jhangiani, I-Chant A. Chiang, Carrie Cuttler, & Dana C. Leighton is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Single Subject Research Design

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Single-case research design ; Single-participant experimental design ; Time-series design

Single subject research design refers to a unique type of research methodology that facilitates intervention evaluation through an individual case.

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Single subject research design is a type of research methodology characterized by repeated assessment of a particular phenomenon (often a behavior) over time and is generally used to evaluate interventions [ 2 ]. Repeated measurement across time differentiates single subject research design from case studies and group designs, as it facilitates the examination of client change in response to an intervention. Although the use of single subject research design has generally been limited to research, it is also appropriate and useful in applied practice.

Single subject research designs differ in structure and purpose and typically fall into one of three categories: within-series designs, between-series designs and...

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Hayes, S. C., Barlow, D. H., & Nelson-Gray, R. O. (1999). The scientist practitioner: Research and accountability in the age of managed care (2nd ed.). Boston, MA: Allyn & Bacon.

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Herrera, G. C., & Kratochwill, T. R. (2005). Single-case experimental design. In S. W. Lee (Ed.), Encyclopedia of School Psychology (pp. 501–504). Thousand Oaks, CA: Sage Publications.

Kazdin, A. E. (1982). Single-case research designs: Methods for clinical and applied settings . New York, NY: Oxford Press University.

Kratochwill, T. R., & Levin, J. R. (1992). Single-case research design and analysis: New directions for psychology and education . Hillsdale, NJ: Lawrence Erlbaum Associates.

Kratochwill, T. R., Mott, S. E., & Dodson, C. L. (1984). Case study and single case research in clinical and applied psychology. In A. S. Bellack & M. Hersen (Eds.), Research methods in clinical psychology (pp. 55–99). New York, NY: Pergamon Press.

Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi- experimental designs for generalized causal inference . Boston, MA: Houghton Mifflin Company.

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Identifying Primary and Secondary Research Articles

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Primary research articles report on a single study. In the health sciences, primary research articles generally describe the following aspects of the study:

• The study's hypothesis or research question
• Some articles will include information on how participants were recruited or identified, as well as additional information about participants' sex, age, or race/ethnicity
• A "methods" or "methodology" section that describes how the study was performed and what the researchers did
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Secondary Research Articles

Review articles are the most common type of secondary research article in the health sciences. A review article is a summary of previously published research on a topic. Authors who are writing a review article will search databases for previously completed research and summarize or synthesize those articles,  as opposed to recruiting participants and performing a new research study.

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Single case studies are a powerful tool for developing, testing and extending theories

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Psychology embraces a diverse range of methodologies. However, most rely on averaging group data to draw conclusions. In this Perspective, we argue that single case methodology is a valuable tool for developing and extending psychological theories. We stress the importance of single case and case series research, drawing on classic and contemporary cases in which cognitive and perceptual deficits provide insights into typical cognitive processes in domains such as memory, delusions, reading and face perception. We unpack the key features of single case methodology, describe its strengths, its value in adjudicating between theories, and outline its benefits for a better understanding of deficits and hence more appropriate interventions. The unique insights that single case studies have provided illustrate the value of in-depth investigation within an individual. Single case methodology has an important place in the psychologist’s toolkit and it should be valued as a primary research tool.

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The authors thank all of those pioneers of and advocates for single case study research who have mentored, inspired and encouraged us over the years, and the many other colleagues with whom we have discussed these issues.

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Nickels, L., Fischer-Baum, S. & Best, W. Single case studies are a powerful tool for developing, testing and extending theories. Nat Rev Psychol 1 , 733–747 (2022). https://doi.org/10.1038/s44159-022-00127-y

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Single-Subject Experimental Design: An Overview

Cred library, julie wambaugh, and ralf schlosser.

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Single-subject experimental designs – also referred to as within-subject or single case experimental designs – are among the most prevalent designs used in CSD treatment research. These designs provide a framework for a quantitative, scientifically rigorous approach where each participant provides his or her own experimental control.

An Overview of Single-Subject Experimental Design

What is single-subject design.

Transcript of the video Q&A with Julie Wambaugh. The essence of single-subject design is using repeated measurements to really understand an individual’s variability, so that we can use our understanding of that variability to determine what the effects of our treatment are. For me, one of the first steps in developing a treatment is understanding what an individual does. So, if I were doing a group treatment study, I would not necessarily be able to see or to understand what was happening with each individual patient, so that I could make modifications to my treatment and understand all the details of what’s happening in terms of the effects of my treatment. For me it’s a natural first step in the progression of developing a treatment. Also with the disorders that we deal with, it’s very hard to get the number of participants that we would need for the gold standard randomized controlled trial. Using single-subject designs works around the possible limiting factor of not having enough subjects in a particular area of study. My mentor was Dr. Cynthia Thompson, who was trained by Leija McReynolds from the University of Kansas, which was where a lot of single-subject design in our field originated, and so I was fortunate to be on the cutting edge of this being implemented in our science back in the late ’70s early ’80s. We saw, I think, a nice revolution in terms of attention to these types of designs, giving credit to the type of data that could be obtained from these types of designs, and a flourishing of these designs really through the 1980s into the 1990s and into the 2000s. But I think — I’ve talked with other single-subject design investigators, and now we’re seeing maybe a little bit of a lapse of attention, and a lack of training again among our young folks. Maybe people assume that people understand the foundation, but they really don’t. And more problems are occurring with the science. I think we need to re-establish the foundations in our young scientists. And this project, I think, will be a big plus toward moving us in that direction.

What is the Role of Single-Subject Design?

Transcript of the video Q&A with Ralf Schlosser. So what has happened recently, is with the onset of evidence-based practice and the adoption of the common hierarchy of evidence in terms of designs. As you noted the randomized controlled trial and meta-analyses of randomized controlled trials are on top of common hierarchies. And that’s fine. But it doesn’t mean that single-subject cannot play a role. For example, single-subject design can be implemented prior to implementing a randomized controlled trial to get a better handle on the magnitude of the effects, the workings of the active ingredients, and all of that. It is very good to prepare that prior to developing a randomized controlled trial. After you have implemented the randomized controlled trial, and then you want to implement the intervention in a more naturalistic setting, it becomes very difficult to do that in a randomized form or at the group level. So again, single-subject design lends itself to more practice-oriented implementation. So I see it as a crucial methodology among several. What we can do to promote what single-subject design is good for is to speak up. It is important that it is being recognized for what it can do and what it cannot do.

Basic Features and Components of Single-Subject Experimental Designs

Defining Features Single-subject designs are defined by the following features:

• An individual “case” is the unit of intervention and unit of data analysis.
• The case provides its own control for purposes of comparison. For example, the case’s series of outcome variables are measured prior to the intervention and compared with measurements taken during (and after) the intervention.
• The outcome variable is measured repeatedly within and across different conditions or levels of the independent variable.

See Kratochwill, et al. (2010)

Structure and Phases of the Design Single-subject designs are typically described according to the arrangement of baseline and treatment phases.

The conditions in a single-subject experimental study are often assigned letters such as the A phase and the B phase, with A being the baseline, or no-treatment phase, and B the experimental, or treatment phase. (Other letters are sometimes used to designate other experimental phases.) Generally, the A phase serves as a time period in which the behavior or behaviors of interest are counted or scored prior to introducing treatment. In the B phase, the same behavior of the individual is counted over time under experimental conditions while treatment is administered. Decisions regarding the effect of treatment are then made by comparing an individual’s performance during the treatment, B phase, and the no-treatment. McReynolds and Thompson (1986)

Basic Components Important primary components of a single-subject study include the following:

• The participant is the unit of analysis, where a participant may be an individual or a unit such as a class or school.
• Participant and setting descriptions are provided with sufficient detail to allow another researcher to recruit similar participants in similar settings.
• Dependent variables are (a) operationally defined and (b) measured repeatedly.
• An independent variable is actively manipulated, with the fidelity of implementation documented.
• A baseline condition demonstrates a predictable pattern which can be compared with the intervention condition(s).
• Experimental control is achieved through introduction and withdrawal/reversal, staggered introduction, or iterative manipulation of the independent variable.
• Visual analysis is used to interpret the level, trend, and variability of the data within and across phases.
• External validity of results is accomplished through replication of the effects.
• Social validity is established by documenting that interventions are functionally related to change in socially important outcomes.

See Horner, et al. (2005)

Common Misconceptions

Single-Subject Experimental Designs versus Case Studies

Transcript of the video Q&A with Julie Wambaugh. One of the biggest mistakes, that is a huge problem, is misunderstanding that a case study is not a single-subject experimental design. There are controls that need to be implemented, and a case study does not equate to a single-subject experimental design. People misunderstand or they misinterpret the term “multiple baseline” to mean that because you are measuring multiple things, that that gives you the experimental control. You have to be demonstrating, instead, that you’ve measured multiple behaviors and that you’ve replicated your treatment effect across those multiple behaviors. So, one instance of one treatment being implemented with one behavior is not sufficient, even if you’ve measured other things. That’s a very common mistake that I see. There’s a design — an ABA design — that’s a very strong experimental design where you measure the behavior, you implement treatment, and you then to get experimental control need to see that treatment go back down to baseline, for you to have evidence of experimental control. It’s a hard behavior to implement in our field because we want our behaviors to stay up! We don’t want to see them return back to baseline. Oftentimes people will say they did an ABA. But really, in effect, all they did was an AB. They measured, they implemented treatment, and the behavior changed because the treatment was successful. That does not give you experimental control. They think they did an experimentally sound design, but because the behavior didn’t do what the design requires to get experimental control, they really don’t have experimental control with their design.

Single-subject studies should not be confused with case studies or other non-experimental designs.

In case study reports, procedures used in treatment of a particular client’s behavior are documented as carefully as possible, and the client’s progress toward habilitation or rehabilitation is reported. These investigations provide useful descriptions. . . .However, a demonstration of treatment effectiveness requires an experimental study. A better role for case studies is description and identification of potential variables to be evaluated in experimental studies. An excellent discussion of this issue can be found in the exchange of letters to the editor by Hoodin (1986) [Article] and Rubow and Swift (1986) [Article]. McReynolds and Thompson (1986)

Other Single-Subject Myths

Transcript of the video Q&A with Ralf Schlosser. Myth 1: Single-subject experiments only have one participant. Obviously, it requires only one subject, one participant. But that’s a misnomer to think that single-subject is just about one participant. You can have as many as twenty or thirty. Myth 2: Single-subject experiments only require one pre-test/post-test. I think a lot of students in the clinic are used to the measurement of one pre-test and one post-test because of the way the goals are written, and maybe there’s not enough time to collect continuous data.But single-case experimental designs require ongoing data collection. There’s this misperception that one baseline data point is enough. But for single-case experimental design you want to see at least three data points, because it allows you to see a trend in the data. So there’s a myth about the number of data points needed. The more data points we have, the better. Myth 3: Single-subject experiments are easy to do. Single-subject design has its own tradition of methodology. It seems very easy to do when you read up on one design. But there are lots of things to consider, and lots of things can go wrong.It requires quite a bit of training. It takes at least one three-credit course that you take over the whole semester.

Further Reading: Components of Single-Subject Designs

Kratochwill, T. R., Hitchcock, J., Horner, R. H., Levin, J. R., Odom, S. L., Rindskopf, D. M. & Shadish, W. R. (2010). Single-case designs technical documentation. From the What Works Clearinghouse. http://ies.ed.gov/ncee/wwc/documentsum.aspx?sid=229

Further Reading: Single-Subject Design Textbooks

Kazdin, A. E. (2011). Single-case research designs: Methods for clinical and applied settings. Oxford University Press.

McReynolds, L. V. & Kearns, K. (1983). Single-subject experimental designs in communicative disorders. Baltimore: University Park Press.

Further Reading: Foundational Articles

Julie Wambaugh University of Utah

Ralf Schlosser Northeastern University

The content of this page is based on selected clips from video interviews conducted at the ASHA National Office.

Additional digested resources and references for further reading were selected and implemented by CREd Library staff.

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Q. How do I identify a research study?

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Answered by: david hisle last updated: aug 30, 2022     views: 65712.

These guidelines can help you identify a research study and distinguish an article that presents the findings of a research study from other types of articles.

• Ask a research question
• Identify a research population or group
• Describe a research method
• Test or measure something
• Summarize the results

Research studies are almost always published in peer-reviewed (scholarly) journals. The articles often contain headings similar to these: Literature Review, Method, Results, Discussion , and Conclusion .

Articles that review other studies without presenting new research results are not research studies. Examples of article types that are NOT research studies include:

• literature reviews
• meta-analyses
• case studies
• comments or letters relating to previously-published research studies

Some databases allow you to limit by publication type. Use this feature to help identify research studies. Here are tips for limiting by publication type in several popular databases:

• Click on the Advanced Search button.
• Type your search terms in the top boxes.
• In the area below the search boxes, find the box labeled "Publication Type".
• Select "Peer Reviewed Journal"
• empirical study
• follow-up study
• longitudinal study
• prospective study
• retrospective study
• treatment outcomes study

ERIC via EBSCO host :

• In the area below the search boxes, find the box labeled "Journal or Document".
• Select "Journal Articles" from the menu choices.
• Further down the screen, find the box labeled "Publication Type".
• Select "Reports - Research / Technical."
• Look carefully at the article abstracts to see if the article meets the requirements of a research study. Sometimes, you may have to look at the actual article to make this determination.

Some databases, like Sociological Abstracts , and Social Work Abstracts allow you to limit to "Articles" or "Abstracts of Journal Articles," but do not have more specific publication types. In Sociological Abstracts , a quick and dirty way to find research studies is to limit to "Articles" and then add "tables" to your search. This works because most research studies contain tables, and this is an indexed field in this database. For example, you might search for "gender and tables." This doesn't work well in Social Work Abstracts , though, because "tables" is not indexed. Instead, try something like "gender and research study" or even "gender and study." In all of these examples, you need to carefully examine the abstracts to see if the articles meet the requirements of a research study.

Many of the EBSCO host databases (e.g., Academic Search Complete , Health Source Nursing/Academic Edition, Sociological Collection ) allow you to limit to peer reviewed journals, but not by specific publication type. Be sure to click in the box to limit to peer reviewed journals. Then, add terms like "research study," "empirical," or "longitudinal" to your search. Again, carefully examine the abstracts to see if the articles meet the requirements of a research study.

Here is an example of an abstract of a research study from Sociological Collection . Phrases that help identify it as a research study are in bold:

Self-pity is a frequent response to stressful events. So far, however, empirical research has paid only scant attention to this subject. The present article aims at exploring personality characteristics associated with individual differences in feeling sorry for oneself . Two studies with N=5141 and N=5161 university students were conducted, employing multidimensional measures of personality, control beliefs, anger, loneliness, and adult attachment. With respect to personality, results showed strong associations of self-pity with neuroticism, particularly with the depression facet. With respect to control beliefs, individuals high in self-pity showed generalized externality beliefs, seeing themselves as controlled by both chance and powerful others. With respect to anger expression, self-pity was primarily related to anger-in. Strong connections with anger rumination were also found. Furthermore, individuals high in self-pity reported emotional loneliness and ambivalent-worrisome attachments. Finally, in both studies, a strong correlation with gender was found, with women reporting more self-pity reactions to stress than men. Findings are discussed with respect to how they support, extend, and qualify the previous literature on self-pity, and directions for future empirical research are pointed out.

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Vegetables and Fruits

• Vegetables and fruits are an important part of a healthy diet, and variety is as important as quantity.
• No single fruit or vegetable provides all of the nutrients you need to be healthy. Eat plenty every day.

A diet rich in vegetables and fruits can lower blood pressure, reduce the risk of heart disease and stroke, prevent some types of cancer, lower risk of eye and digestive problems, and have a positive effect upon blood sugar, which can help keep appetite in check. Eating non-starchy vegetables and fruits like apples, pears, and green leafy vegetables may even promote weight loss. [1] Their low glycemic loads prevent blood sugar spikes that can increase hunger.

At least nine different families of fruits and vegetables exist, each with potentially hundreds of different plant compounds that are beneficial to health. Eat a variety of types and colors of produce in order to give your body the mix of nutrients it needs. This not only ensures a greater diversity of beneficial plant chemicals but also creates eye-appealing meals.

Tips to eat more vegetables and fruits each day

• Keep fruit where you can see it . Place several ready-to-eat washed whole fruits in a bowl or store chopped colorful fruits in a glass bowl in the refrigerator to tempt a sweet tooth.
• Explore the produce aisle and choose something new . Variety and color are key to a healthy diet. On most days, try to get at least one serving from each of the following categories: dark green leafy vegetables; yellow or orange fruits and vegetables; red fruits and vegetables; legumes (beans) and peas; and citrus fruits.
• Skip the potatoes . Choose other vegetables that are packed with different nutrients and more slowly digested  carbohydrates .
• Make it a meal . Try cooking new  recipes that include more vegetables. Salads, soups, and stir-fries are just a few ideas for increasing the number of tasty vegetables in your meals.

5 common questions about fruits and vegetables.

Vegetables, fruits, and disease, cardiovascular disease.

There is compelling evidence that a diet rich in fruits and vegetables can lower the risk of heart disease and stroke.

• A meta-analysis of cohort studies following 469,551 participants found that a higher intake of fruits and vegetables is associated with a reduced risk of death from cardiovascular disease, with an average reduction in risk of 4% for each additional serving per day of fruit and vegetables. [2]
• The largest and longest study to date, done as part of the Harvard-based Nurses’ Health Study and Health Professionals Follow-up Study, included almost 110,000 men and women whose health and dietary habits were followed for 14 years.
• The higher the average daily intake of fruits and vegetables, the lower the chances of developing cardiovascular disease. Compared with those in the lowest category of fruit and vegetable intake (less than 1.5 servings a day), those who averaged 8 or more servings a day were 30% less likely to have had a heart attack or stroke. [3]
• Although all fruits and vegetables likely contributed to this benefit, green leafy vegetables, such as lettuce, spinach, Swiss chard, and mustard greens, were most strongly associated with decreased risk of cardiovascular disease. Cruciferous vegetables such as broccoli, cauliflower, cabbage, Brussels sprouts , bok choy, and kale ; and citrus fruits such as oranges, lemons, limes, and grapefruit (and their juices) also made important contributions. [3]
• When researchers combined findings from the Harvard studies with several other long-term studies in the U.S. and Europe, and looked at coronary heart disease and stroke separately, they found a similar protective effect: Individuals who ate more than 5 servings of fruits and vegetables per day had roughly a 20% lower risk of coronary heart disease [4] and stroke, [5] compared with individuals who ate less than 3 servings per day.

Blood pressure

• The  Dietary Approaches to Stop Hypertension (DASH) study [6] examined the effect on blood pressure of a diet that was rich in fruits, vegetables, and low-fat dairy products and that restricted the amount of saturated and total fat. The researchers found that people with high blood pressure who followed this diet reduced their systolic blood pressure (the upper number of a blood pressure reading) by about 11 mm Hg and their diastolic blood pressure (the lower number) by almost 6 mm Hg—as much as medications can achieve.
• A randomized trial known as the Optimal Macronutrient Intake Trial for Heart Health (OmniHeart) showed that this fruit and vegetable-rich diet lowered blood pressure even more when some of the carbohydrate was replaced with healthy unsaturated fat or protein. [7]
• In 2014 a meta-analysis of clinical trials and observational studies found that consumption of a vegetarian diet was associated with lower blood pressure. [8]

Numerous early studies revealed what appeared to be a strong link between eating fruits and vegetables and protection against cancer . Unlike case-control studies, cohort studies , which follow large groups of initially healthy individuals for years, generally provide more reliable information than case-control studies because they don’t rely on information from the past. And, in general, data from cohort studies have not consistently shown that a diet rich in fruits and vegetables prevents cancer.

• For example, over a 14-year period in the Nurses’ Health Study and the Health Professionals Follow-up Study, men and women with the highest intake of fruits and vegetables (8+ servings a day) were just as likely to have developed cancer as those who ate the fewest daily servings (under 1.5). [3]
• A meta-analysis of cohort studies found that a higher fruit and vegetable intake did not decrease the risk of deaths from cancer. [2]

A more likely possibility is that some types of fruits and vegetables may protect against certain cancers.

• A study by Farvid and colleagues followed a Nurses’ Health Study II cohort of 90,476 premenopausal women for 22 years and found that those who ate the most fruit during adolescence (about 3 servings a day) compared with those who ate the lowest intakes (0.5 servings a day) had a 25% lower risk of developing breast cancer. There was a significant reduction in breast cancer in women who had eaten higher intakes of apples, bananas , grapes, and corn during adolescence, and oranges and kale during early adulthood. No protection was found from drinking fruit juices at younger ages. [9]
• Farvid and colleagues followed 90, 534 premenopausal women from the Nurses’ Health Study II over 20 years and found that higher fiber intakes during adolescence and early adulthood were associated with a reduced risk of breast cancer later in life. When comparing the highest and lowest fiber intakes from fruits and vegetables, women with the highest fruit fiber intake had a 12% reduced risk of breast cancer; those with the highest vegetable fiber intake had an 11% reduced risk. [10]
• After following 182,145 women in the Nurses’ Health Study I and II for 30 years, Farvid’s team also found that women who ate more than 5.5 servings of fruits and vegetables each day (especially cruciferous and yellow/orange vegetables) had an 11% lower risk of breast cancer than those who ate 2.5 or fewer servings. Vegetable intake was strongly associated with a 15% lower risk of estrogen-receptor-negative tumors for every two additional servings of vegetables eaten daily. A higher intake of fruits and vegetables was associated with a lower risk of other aggressive tumors including HER2-enriched and basal-like tumors. [11]
• A report by the World Cancer Research Fund and the American Institute for Cancer Research suggests that non-starchy vegetables—such as lettuce and other leafy greens, broccoli, bok choy, cabbage, as well as garlic, onions, and the like—and fruits “probably” protect against several types of cancers, including those of the mouth, throat, voice box, esophagus, and stomach. Fruit probably also protects against lung cancer. [12]

Specific components of fruits and vegetables may also be protective against cancer. For example:

• A line of research stemming from a finding from the Health Professionals Follow-up Study suggests that tomatoes may help protect men against prostate cancer, especially aggressive forms of it. [12] One of the pigments that give tomatoes their red hue—lycopene—could be involved in this protective effect. Although several studies other than the Health Professionals Study have also demonstrated a link between tomatoes or lycopene and prostate cancer, others have not or have found only a weak connection. [14]
• Taken as a whole, however, these studies suggest that increased consumption of tomato-based products (especially cooked tomato products) and other lycopene-containing foods may reduce the occurrence of prostate cancer. [12] Lycopene is one of several carotenoids (compounds that the body can turn into vitamin A) found in brightly colored fruits and vegetables, and research suggests that foods containing carotenoids may protect against lung, mouth, and throat cancer. [12] But more research is needed to understand the exact relationship between fruits and vegetables, carotenoids, and cancer.

Some research looks specifically at whether individual fruits are associated with risk of type 2 diabetes. While there isn’t an abundance of research into this area yet, preliminary results are compelling.

• A study of over 66,000 women in the Nurses’ Health Study, 85,104 women from the Nurses’ Health Study II, and 36,173 men from the Health Professionals Follow-up Study—who were free of major chronic diseases—found that greater consumption of whole fruits—especially blueberries, grapes, and apples—was associated with a lower risk of type 2 diabetes. Another important finding was that greater consumption of fruit juice was associated with a higher risk of type 2 diabetes. [15]
• Additionally a study of over 70,000 female nurses aged 38-63 years, who were free of cardiovascular disease, cancer, and diabetes, showed that consumption of green leafy vegetables and fruit was associated with a lower risk of diabetes. While not conclusive, research also indicated that consumption of fruit juices may be associated with an increased risk among women. (16)
• A study of over 2,300 Finnish men showed that vegetables and fruits, especially berries, may reduce the risk of type 2 diabetes. [17]

Data from the Nurses’ Health Studies and the Health Professional’s Follow-up Study show that women and men who increased their intakes of fruits and vegetables over a 24-year period were more likely to have lost weight than those who ate the same amount or those who decreased their intake. Berries, apples, pears, soy, and cauliflower were associated with weight loss while starchier vegetables like potatoes, corn, and peas were linked with weight gain. [1] However, keep in mind that adding more produce into the diet won’t necessarily help with weight loss unless it replaces another food, such as refined carbohydrates of white bread and crackers.

Gastrointestinal health

Fruits and vegetables contain indigestible fiber, which absorbs water and expands as it passes through the digestive system. This can calm symptoms of an irritable bowel and, by triggering regular bowel movements, can relieve or prevent constipation. [18] The bulking and softening action of insoluble fiber also decreases pressure inside the intestinal tract and may help prevent diverticulosis. [19]

Eating fruits and vegetables can also keep your eyes healthy, and may help prevent two common aging-related eye diseases—cataracts and macular degeneration—which afflict millions of Americans over age 65. [20-23] Lutein and zeaxanthin, in particular, seem to reduce risk of cataracts. [24]

• Bertoia ML, Mukamal KJ, Cahill LE, Hou T, Ludwig DS, Mozaffarian D, Willett WC, Hu FB, Rimm EB. Changes in intake of fruits and vegetables and weight change in United States men and women followed for up to 24 years: analysis from three prospective cohort studies. PLoS medicine . 2015 Sep 22;12(9):e1001878.
• Wang X, Ouyang Y, Liu J, Zhu M, Zhao G, Bao W, Hu FB. Fruit and vegetable consumption and mortality from all causes, cardiovascular disease, and cancer: systematic review and dose-response meta-analysis of prospective cohort studies. BMJ . 2014 Jul 29;349:g4490.
• Hung HC, Joshipura KJ, Jiang R, Hu FB, Hunter D, Smith-Warner SA, Colditz GA, Rosner B, Spiegelman D, Willett WC. Fruit and vegetable intake and risk of major chronic disease. Journal of the National Cancer Institute . 2004 Nov 3;96(21):1577-84.
• He FJ, Nowson CA, Lucas M, MacGregor GA. Increased consumption of fruit and vegetables is related to a reduced risk of coronary heart disease: meta-analysis of cohort studies. Journal of human hypertension . 2007 Sep;21(9):717.
• He FJ, Nowson CA, MacGregor GA. Fruit and vegetable consumption and stroke: meta-analysis of cohort studies. The Lancet . 2006 Jan 28;367(9507):320-6.
• Appel LJ, Moore TJ, Obarzanek E, Vollmer WM, Svetkey LP, Sacks FM, Bray GA, Vogt TM, Cutler JA, Windhauser MM, Lin PH. A clinical trial of the effects of dietary patterns on blood pressure. New England Journal of Medicine . 1997 Apr 17;336(16):1117-24.
• Appel LJ, Sacks FM, Carey VJ, Obarzanek E, Swain JF, Miller ER, Conlin PR, Erlinger TP, Rosner BA, Laranjo NM, Charleston J. Effects of protein, monounsaturated fat, and carbohydrate intake on blood pressure and serum lipids: results of the OmniHeart randomized trial. JAMA . 2005 Nov 16;294(19):2455-64.
• Yokoyama Y, Nishimura K, Barnard ND, Takegami M, Watanabe M, Sekikawa A, Okamura T, Miyamoto Y. Vegetarian diets and blood pressure: a meta-analysis. JAMA internal medicine. 2014 Apr 1;174(4):577-87.
• Farvid MS, Chen WY, Michels KB, Cho E, Willett WC, Eliassen AH. Fruit and vegetable consumption in adolescence and early adulthood and risk of breast cancer: population based cohort study. BMJ . 2016 May 11;353:i2343.
• Farvid MS, Eliassen AH, Cho E, Liao X, Chen WY, Willett WC. Dietary fiber intake in young adults and breast cancer risk. Pediatrics . 2016 Mar 1;137(3):e20151226.
• Farvid MS, Chen WY, Rosner BA, Tamimi RM, Willett WC, Eliassen AH. Fruit and vegetable consumption and breast cancer incidence: Repeated measures over 30 years of follow‐up. International journal of cancer . 2018 Jul 6.
• Wiseman M. The Second World Cancer Research Fund/American Institute for Cancer Research Expert Report. Food, Nutrition, Physical Activity, and the Prevention of Cancer: A Global Perspective: Nutrition Society and BAPEN Medical Symposium on ‘Nutrition support in cancer therapy’. Proceedings of the Nutrition Society . 2008 Aug;67(3):253-6.
• Giovannucci E, Liu Y, Platz EA, Stampfer MJ, Willett WC. Risk factors for prostate cancer incidence and progression in the health professionals follow‐up study. International journal of cancer . 2007 Oct 1;121(7):1571-8.
• Kavanaugh CJ, Trumbo PR, Ellwood KC. The US Food and Drug Administration’s evidence-based review for qualified health claims: tomatoes, lycopene, and cancer. Journal of the National Cancer Institute . 2007 Jul 18;99(14):1074-85.
• Muraki I, Imamura F, Manson JE, Hu FB, Willett WC, van Dam RM, Sun Q. Fruit consumption and risk of type 2 diabetes: results from three prospective longitudinal cohort studies. BMJ . 2013 Aug 29;347:f5001.
• Bazzano LA, Li TY, Joshipura KJ, Hu FB. Intake of fruit, vegetables, and fruit juices and risk of diabetes in women. Diabetes Care . 2008 Apr 3.
• Mursu J, Virtanen JK, Tuomainen TP, Nurmi T, Voutilainen S. Intake of fruit, berries, and vegetables and risk of type 2 diabetes in Finnish men: the Kuopio Ischaemic Heart Disease Risk Factor Study–. The American journal of clinical nutrition . 2013 Nov 20;99(2):328-33.
• Lembo A, Camilleri M. Chronic constipation. New England Journal of Medicine . 2003 Oct 2;349(14):1360-8.
• Aldoori WH, Giovannucci EL, Rockett HR, Sampson L, Rimm EB, Willett AW. A prospective study of dietary fiber types and symptomatic diverticular disease in men. The Journal of nutrition . 1998 Oct 1;128(4):714-9.
• Brown L, Rimm EB, Seddon JM, Giovannucci EL, Chasan-Taber L, Spiegelman D, Willett WC, Hankinson SE. A prospective study of carotenoid intake and risk of cataract extraction in US men–. The American journal of clinical nutrition . 1999 Oct 1;70(4):517-24.
• Christen WG, Liu S, Schaumberg DA, Buring JE. Fruit and vegetable intake and the risk of cataract in women–. The American journal of clinical nutrition . 2005 Jun 1;81(6):1417-22.
• Moeller SM, Taylor A, Tucker KL, McCullough ML, Chylack Jr LT, Hankinson SE, Willett WC, Jacques PF. Overall adherence to the dietary guidelines for Americans is associated with reduced prevalence of early age-related nuclear lens opacities in women. The Journal of nutrition . 2004 Jul 1;134(7):1812-9.
• Cho E, Seddon JM, Rosner B, Willett WC, Hankinson SE. Prospective study of intake of fruits, vegetables, vitamins, and carotenoidsand risk of age-related maculopathy. Archives of Ophthalmology . 2004 Jun 1;122(6):883-92.
• Christen WG, Liu S, Glynn RJ, Gaziano JM, Buring JE. Dietary carotenoids, vitamins C and E, and risk of cataract in women: a prospective study. Archives of Ophthalmology . 2008 Jan 1;126(1):102-9.

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• These plant variations are called cultivars

Cannabis-derived compounds

• Compounds occurring naturally in the plant – like CBD and THC
• These compounds are extracted directly from the plant
• Can be used to manufacture drug products
• Example: highly-purified CBD extracted from the plant

Cannabis-related compounds

• These synthetic compounds are created in a laboratory
• Can be used to manufacture drug products 
• Some synthetic compounds may also occur naturally in the plant and some may not
• Examples: synthetically-derived dronabinol (also naturally occurring) and nabilone (not naturally occurring) 

FDA has approved Epidiolex, which contains a purified form of the drug substance cannabidiol (CBD) for the treatment of seizures associated with Lennox-Gastaut syndrome or Dravet syndrome in patients 2 years of age and older. That means FDA has concluded that this particular drug product is safe and effective for its intended use.

The agency also has approved Marinol and Syndros for therapeutic uses in the United States, including for nausea associated with cancer chemotherapy and for the treatment of anorexia associated with weight loss in AIDS patients. Marinol and Syndros include the active ingredient dronabinol, a synthetic delta-9- tetrahydrocannabinol (THC) which is considered the psychoactive intoxicating component of cannabis (i.e., the component responsible for the “high” people may experience from using cannabis). Another FDA-approved drug, Cesamet, contains the active ingredient nabilone, which has a chemical structure similar to THC and is synthetically derived. Cesamet, like dronabinol-containing products, is indicated for nausea associated with cancer chemotherapy.

FDA is aware that unapproved cannabis and/or unapproved cannabis-derived products are being used to treat a number of medical conditions including, AIDS wasting, epilepsy, neuropathic pain, spasticity associated with multiple sclerosis, and cancer and chemotherapy-induced nausea. Caregivers and patients can be confident that FDA-approved drugs have been carefully evaluated for safety, efficacy, and quality, and are monitored by the FDA once they are on the market. However, the use of unapproved cannabis and cannabis-derived products can have unpredictable and unintended consequences, including serious safety risks. Also, there has been no FDA review of data from rigorous clinical trials to support that these unapproved products are safe and efficacious for the various therapeutic uses for which they are being used.

FDA understands the need to develop therapies for patients with unmet medical needs, and does everything it can to facilitate this process. FDA has programs such as Fast Track, Breakthrough Therapy, Accelerated Approval and Priority Review that are designed to facilitate the development of and expedite the approval of drug products. In addition, the FDA’s expanded access (sometimes called “compassionate use”) statutory and regulatory provisions are designed to facilitate the availability of investigational products to patients with serious diseases or conditions when there is no comparable or satisfactory alternative therapy available, either because the patients have exhausted treatment with or are intolerant of approved therapies, or when the patients are not eligible for an ongoing clinical trial. Through these programs and the drug approval process, FDA supports sound, scientifically-based research into the medicinal uses of drug products containing cannabis or cannabis-derived compounds and will continue to work with companies interested in bringing safe, effective, and quality products to market.

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The FDA has an important role to play in supporting scientific research into the medical uses of cannabis and its constituents in scientifically valid investigations as part of the agency’s drug review and approval process. As a part of this role, the FDA supports those in the medical research community who intend to study cannabis by:

• Providing information on the process needed to conduct clinical research using cannabis.
• Providing information on the specific requirements needed to develop a human drug that is derived from a plant such as cannabis. In December 2016, the FDA updated its Guidance for Industry: Botanical Drug Development , which provides sponsors with guidance on submitting investigational new drug (IND) applications for botanical drug products. The FDA also has issued “ Cannabis and Cannabis-Derived Compounds: Quality Considerations for Clinical Research, Draft Guidance for Industry .”
• Providing specific support for investigators interested in conducting clinical research using cannabis and its constituents as a part of the IND or investigational new animal drug (INAD) process through meetings and regular interactions throughout the drug development process.
• Providing general support to investigators to help them understand and follow the procedures to conduct clinical research through the FDA Center for Drug Evaluation and Research (CDER) Small Business and Industry Assistance group .

To conduct clinical research that can lead to an approved new drug, including research using materials from plants such as cannabis, researchers need to work with the FDA and submit an IND application to CDER. The IND application process gives researchers a path to follow that includes regular interactions with the FDA to support efficient drug development while protecting the patients who are enrolled in the trials. An IND includes protocols describing proposed studies, the qualifications of the investigators who will conduct the clinical studies, and assurances of informed consent and protection of the rights, safety, and welfare of the human subjects. The FDA reviews the IND to ensure that the proposed studies, generally referred to as “clinical trials,” do not place human subjects at an unreasonable risk of harm. The FDA also requires obtaining the informed consent of trial subjects and human subject protection in the conduct of the clinical trials. For research intending to develop an animal drug product, researchers would establish an INAD file with the Center for Veterinary Medicine (CVM) to conduct their research, rather than an IND with CDER.

FDA is committed to encouraging the development of cannabis-related drug products, including CBD. Those interested in cannabis-derived and cannabis-related drug development are encouraged to contact the relevant CDER review division and CDER’s Botanical Review Team (BRT) to answer questions related to their specific drug development program. The BRT serves as an expert resource on botanical issues and has developed the Botanical Drug Development Guidance for Industry to assist those pursuing drug development in this area. FDA encourages researchers to request a Pre-Investigational New Drug application (PIND) meeting to discuss questions related to the development of a specific cannabis-derived and cannabis-related drug product.

Please note that certain cultivars and parts of the Cannabis sativa L. plant are controlled under the Controlled Substances Act (CSA) since 1970 under the drug class "Marihuana" (commonly referred to as "marijuana") [21 U.S.C. 802(16)]. "Marihuana" is listed in Schedule I of the CSA due to its high potential for abuse, which is attributable in large part to the psychoactive intoxicating effects of THC, and the absence of a currently accepted medical use in the United States. From 1970 until December of 2018, the definition of “marihuana” included all types of Cannabis Sativa L. , regardless of THC content.  However, in December 2018, the Agriculture Improvement Act of 2018 (also known as the Farm Bill) removed hemp, a type of cannabis that is very low in THC (cannabis or cannabis derivatives containing no more than 0.3% THC on a dry weight basis), from controls under the CSA. This change in the law may result in a more streamlined process for researchers to study cannabis and its derivatives, including CBD, that fall under the definition of hemp, a result which could speed the development of new drugs containing hemp. 

Conducting clinical research using cannabis-derived substances that are considered controlled substances under the CSA often involves interactions with several federal agencies. For example:

• Protocols to conduct research with controlled substances listed in Schedule I are required to be conducted under a site-specific DEA investigator registration. For more information, see 21 CFR 1301.18 .
• National Institute on Drug Abuse (NIDA) Drug Supply Program provides research-grade marijuana for scientific study. Through registration issued by DEA, NIDA is responsible for overseeing the cultivation of marijuana for medical research and has contracted with the University of Mississippi to grow marijuana for research at a secure facility. Marijuana of varying potencies and compositions along with marijuana-derived compounds are available. DEA also may allow additional growers to register with the DEA to produce and distribute marijuana for research purposes. DEA that, as the result of a recent amendment to federal law, certain forms of cannabis no longer require DEA registration to grow or manufacture.
• Researchers work with the FDA and submit an IND or INAD application to the appropriate CDER divisions or other center offices depending on the therapeutic indication or population. If the research is intended to support the approval of an animal drug product, an INAD file should be established with CVM. Based on the results obtained in studies conducted at the IND or INAD stage, sponsors may submit a marketing application for formal approval of the drug.

Cannabis Study Drugs Controlled Under Schedule I of the CSA (greater than 0.3% THC on a dry weight basis)

Sponsor obtains pre-IND number through CDER review division to request a pre-IND meeting. For new animal drug research, a sponsor may engage with CVM to establish an INAD file. A pre-IND meeting with CDER is optional, and an opportunity to obtain FDA guidance on sponsor research plans and required content for an IND submission .

The sponsor contacts NIDA or another DEA-registered source of cannabis and/or cannabis-derived substances to obtain information on the specific cultivars available, so that all necessary chemistry, manufacturing, and controls (CMC) and botanical raw material (BRM) information can be included in the IND. Importation of products controlled under the CSA are subject to DEA authorization.

The sponsor may contact DEA to discuss Schedule I drug research plans that may require DEA inspection for an investigator and study site Schedule I license.

Step 4: If the selected BRM or drug substance manufacturer holds a Drug Master File (DMF) , the sponsor must obtain a Letter of Authorization (LOA) to reference CMC and BRM information. Alternatively, an IND submission would need to contain all necessary CMC data characterizing their study drug and ensuring it is safe for use in humans.

The sponsor sends a copy of the IND and clinical protocol, including a LOA (if applicable), to FDA.

FDA reviews the submitted IND. The sponsor must wait 30 calendar days following IND submission before initiating any clinical trials, unless FDA notifies the sponsor that the trials may proceed sooner. During this time, FDA has an opportunity to review the submission for safety to assure that research subjects will not be subjected to unreasonable risk.

If the IND is authorized by FDA as “safe to proceed” the sponsor may then submit their clinical protocol registration application, including referenced IND number, to DEA to obtain the protocol registration. Once this is received, the sponsor contacts NIDA or another DEA-registered source to obtain the cannabis and/or cannabis-derived substances and they can then begin the study.

For nonclinical research, including research conducted under an INAD file submitted established with CVM, there is no requirement of prior authorization of the protocol by FDA before the investigators may proceed with a protocol registration application submitted to DEA. For these nonclinical protocols, investigators may immediately pursue investigator and study site licensure, and protocol registration with DEA, so they may then obtain their Schedule I cannabis-derived study drug from supplier.

Cannabis Study Drugs Containing Hemp (no more than 0.3% THC on a dry weight basis)

Sponsor provides all applicable chemistry, manufacturing, and controls (CMC) and botanical raw material (BRM) information in the IND for review by FDA, including hemp cultivars.

If the selected hemp manufacturer holds a Drug Master File (DMF) , the sponsor must obtain a Letter of Authorization (LOA) to reference CMC and BRM information. Alternatively, an IND submission would need to contain all necessary CMC data characterizing their study drug and ensuring it is safe for use in humans.

FDA’s Role in the Drug Approval Process

The FDA’s role in the regulation of drugs, including cannabis and cannabis-derived products, also includes review of applications to market drugs to determine whether proposed drug products are safe and effective for their intended indications. The FDA’s drug approval process requires that clinical trials be designed and conducted in a way that provides the agency with the necessary scientific data upon which the FDA can make its approval decisions. Without this review, the FDA cannot determine whether a drug product is safe and effective. It also cannot ensure that a drug product meets appropriate quality standards. For certain drugs that have not been approved by the FDA, the lack of FDA approval and oversight means the safety, effectiveness, and quality of the drug – including how potent it is, how pure it is, and whether the labeling is accurate or false – may vary considerably.

• Product-Specific Guidance for Generic Drug Development: Draft Guidance on Cannabidiol Oral Solution (PDF - 42KB)
• Cannabis Clinical Research: Drug Master Files (DMFs) & Quality Considerations Webinar
• Cannabis and Cannabis-Derived Compounds: Quality Considerations for Clinical Research, Draft Guidance for Industry
• FDA Regulation of Cannabis and Cannabis-Derived Products, Including Cannabidiol (CBD): Questions and Answers
• Development & Approval Process (Drugs)
• From an Idea to the Marketplace: The Journey of an Animal Drug through the Approval Process
• FDA Center for Drug Evaluation and Research Small Business and Industry Assistance group
• CVM Small Business Assistance
• National Institutes of Health (NIH): Guidance on Procedures for Provision of Marijuana for Medical Research
• National Institute on Drug Abuse's (NIDA) Role in Providing Marijuana for Research
• Drug Enforcement Administration - Registration of Manufacturers, Distributors, and Dispensers of Controlled Substances
• International Narcotics Control Board: Single Convention on Narcotic Drugs (1961)
• National Institute on Drug Abuse (NIDA): Ordering Guidelines for Marijuana and Marijuana Cigarettes

What is omnichannel marketing?

Picture this: you’re browsing online for some new work clothes, and you add something to your virtual cart but ultimately decide not to buy it. Then later, you see an ad on social media for the abandoned garment. Some scratch their heads at this, but it’s actually an example of omnichannel marketing.

The prefix “omni” means “all,” and “channel” is a reference to the many ways customers might interact with a company—in physical stores, by surfing the web, on social media, and in emails, apps, SMS, and other digital spaces. And this omnichannel approach can be a powerful way to meet your customers where they are, providing them good service in line with their preferences and needs. (Note that, in this article, we use the terms “customers,” “consumers,” and “shoppers” interchangeably in referring to omnichannel marketing in both B2B and B2C contexts.)

More and more, customers move across all channels—in person, online, and beyond—to get what they want. But not every customer is looking for the same thing, and omnichannel marketing acknowledges that. Some people want more services for certain transactions; others prefer low-touch, 24/7 interactions. Effective omnichannel marketing , then, happens when companies provide a set of seamlessly integrated channels, catering to customer preferences, and steer them to the most efficient solutions.

So why is omnichannel marketing important? Research on the omnichannel experience  shows more than half of B2C customers engage with three to five channels each time they make a purchase or resolve a request. And the average customer looking to make a single reservation for accommodations (like a hotel room) online switched nearly six times between websites and mobile channels. If these customers encounter inconsistent information or can’t get what they need, they may lose interest in a brand’s products or services.

And this can translate into business outcomes. Omnichannel customers shop 1.7 times more than shoppers who use a single channel. They also spend more.

Sometimes the term omnichannel is used in the context of customer service or customer experience . And it’s also used as a descriptor of other elements that go into supporting an organization’s omnichannel efforts—for instance, omnichannel supply chains , which is shorthand for an approach in which companies ensure that their supply chains are optimally set up to support omnichannel marketing efforts.

What are examples of omnichannel?

Omnichannel approaches are commonly used in retail  (both B2B  and B2C ), but you’ll also find it in healthcare and other spaces. Medtech companies , for instance, use a variety of channels including digital marketing, inside sales, portal and e-commerce, and hybrid sales-rep interactions to engage with healthcare professionals.

Several omnichannel examples  can illustrate various approaches:

• Best Buy typically focuses on commerce (both in store and online), but boosted its in-store experience by creating offerings for customers to explore smart home-technology solutions, pairing them with free in-home advisory services. And its mobile app lets customers “scan to shop” from catalogs and curbside, or buy online and pick up merchandise in the store itself, smoothing the end-to-end journey for customers with the 24/7 tech support from its Geek Squad. Best Buy’s Totaltech support offer was compelling to customers—it launched with 200,000 memberships in 2018, which climbed to two million within a year.
• Beauty retailer Sephora emphasizes omnichannel personalization, relying on rich in-app messaging, personalized push notifications, and easy ways for customers to book in-person consultations. Its in-store technology is a powerful complement that allows employees to access customer favorites and suggest products they might try next. Its loyalty program also plays an important role. The efforts are already driving value for Sephora: data showed that customers visiting the retail website within 24 hours of visiting a store were three times more likely to make a purchase, and orders were 13 percent higher than for other customers.
• Nike takes an ecosystems view of omnichannel, extending the brand experience and offering customers an ever-growing platform of content, offers, and community interactions. Its SNKRS and Run Club apps, for example, facilitate in-person meetups, running groups, and events. It also has an app for delivering individual workouts and fitness programs, creating experiences that go far beyond shoe and apparel lines to meet customers in their day-to-day routines.

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How has omnichannel been affected by the COVID-19 pandemic?

Omnichannel rose during the COVID-19 pandemic as more consumers turned to e-commerce. Due to the increased demand for contactless shopping during the height of the pandemic, US grocery stores saw 20 to 30 percent of their business shift to online . Before the pandemic, e-commerce accounted for just 3 to 4 percent of total sales for grocers.

The shifts made during the pandemic are likely to persist . In the pandemic, people gravitated to curbside pickup, “buy online, pay in store” models, and self-checkout at higher rates than in the past. And recent research indicates these behaviors are “sticky”—indeed, about 70 percent of people who first tried self-checkout in the pandemic say they’ll use it again.

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What do customers want out of the omnichannel experience.

Customers want a compelling and personalized omnichannel user experience with robust digital capabilities, both online and offline. About 60 to 70 percent of consumers research and shop both in stores and online . More concretely, over one-third of Americans  made omnichannel features—think buying online and picking up in store or curbside—part of their regular shopping routines since the COVID-19 pandemic emerged. Nearly two-thirds of those individuals plan to continue doing so. And younger buyers, like Gen Zers, embrace omnichannel enthusiastically; these customers don’t think in terms of traditional channel boundaries, and they expect brands and retailers to provide a seamless experience, no matter where they are.

In a sense, all customers are omnichannel customers now, McKinsey partner Tiffany Burns  explains in an episode of the McKinsey on Consumer and Retail podcast :

“Many retailers still think, ‘There are omnichannel interactions and store interactions, and I’m optimizing those two things separately. I have two different teams working on and thinking about those experiences.’ But as a consumer, when I go on the retailer’s website or app, I expect to see availability, a connection to what’s in the store, and a way to order things that I can pick up in store. I also expect to be able to stand in the aisle in the store and research a product. Today, consumers are figuring out workarounds to do all those things: they’re switching over from the app to Google, looking up the product, and searching for reviews.”

Organizations that make shopping a seamless omnichannel experience , or provide an app that helps customers find their way or see what’s in stock in the store, are already creating experiences that are a win for omnichannel customers .

Is omnichannel the same thing as phygital? And what is phygital, anyway?

Omnichannel is a business strategy, while “phygital” (a portmanteau that combines the word “physical” and “digital”) refers to the integration of the physical and digital worlds.

The term suggests a completely connected world that is both physical and digital at the same time . While fewer consumers are visiting brick-and-mortar stores and choosing to use e-commerce instead, more than 80 percent of retail sales still occur in a physical location . By 2030, the shopping experience will be highly personalized , and some activities may even take place in the metaverse . According to a recent survey, 80 percent of US adults  want personalization from retailers with multiple, personalized touchpoints , which can include a mobile app, digital displays, interactive screens, tech-enabled associates, and point of sale.

What about omnichannel vs multichannel?

When it comes to omnichannel vs multichannel, the key difference is the focus at the center of all efforts. Omnichannel is a customer-centric approach in which all channels are integrated so the customer has a unified and consistent experience whether they are at a physical store, using an app, or on a website. Multichannel, in contrast, tends to revolve around products instead of customers. It aims to inform as many people as possible about the product or brand, and the channels are not linked, so the customer experience is often different for each channel.

An interview with an insurance executive, Eric Gewirtzman of BOLT , makes that distinction relatable: “Insurance customers are already moving between various channels,” Gewirtzman says. “But there’s a big difference between being multichannel and being omnichannel. Just because carriers have, say, an exclusive agent channel, an independent agent channel, and a website, doesn’t mean they’re omnichannel. Too often, consumers will get a different experience and different results depending on which channel they use. This has to change. If there is no awareness between the channels, sales are lost.”

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What is omnichannel personalization?

Omnichannel personalization refers to the way organizations might tailor the customer experience for individuals across physical and digital channels. This includes multiple touchpoints that cater to the customer’s preferences pre-visit, during the visit, and post-visit. Customers receive products, offers, and communications that are unique to them as individuals.

Efforts to personalize the omnichannel market can have a big payoff. Indeed, getting omnichannel personalization right  could help companies increase revenue by 5 to 15 percent across the full customer base.

While companies recognize the power of omnichannel personalization, they may face roadblocks in implementing these efforts for a variety of reasons:

• Omnichannel personalization requires a lot of investment in technology  (both software and hardware). Personalizing physical spaces often starts from scratch because it requires enabling digital touchpoints such as screens, kiosks, or tablets for store associates, which may not exist.
• It is difficult to deliver a seamless customer experience and train employees. The front line needs training to understand and reinforce the customer journey.
• Traditionally, companies operate their digital and physical channels independently. Omnichannel personalization requires companies to rethink their organizational structure across both the digital and physical parts of the business .

These barriers, however, can be overcome. Five steps can help companies achieve omnichannel personalization :

• Define the omnichannel personalization strategy and learning agenda. It’s crucial to develop a clear view on key moments of influence in the customer journey , and then identify what outcomes are desired at each step of that journey. Finally, an organization needs to prioritize use cases to test, looking at their ability to deliver business benefits and value to customers.
• Address five digital touchpoints to activate personalized experiences in physical environments. Companies need to connect digital and physical footprints to drive omnichannel personalization, especially at touchpoints where these worlds converge. Five are particularly important: mobile apps, digital displays, interactive screens, tech-enabled associates, and point of sale.
• Use an omnichannel “ decisioning engine ” to deliver experiences and measure performance. This can help organizations identify, quickly and accurately, the next best action to take with each customer.
• Implement agile operating practices. Personalized marketing goes beyond mere technology; it requires new ways of working, and agile marketing teams  can help in this regard.
• Activate omnichannel personalization in the field. To bring all these elements together, a company’s sales force must be fully aligned and well trained. In-person teams could make your customer’s day, so frontline personnel need to support personalization efforts, understand their value, and use digital tools to deliver the complete experience.

What is omnichannel strategy?

An omnichannel strategy for marketing is a way of ensuring that your efforts drive tangible business value. Rather than rushing blindly into the space, or haphazardly approaching it, organizations should step back and think about underlying business value drivers. Excelling in omnichannel depends on a laser focus on value creation, looking at both strategic and customer priorities to craft the omnichannel strategy that will be most effective for their unique circumstances.

The most successful companies set their omnichannel strategy by leading with their strategic ambition and aspirations for customer experience. There are three primary omnichannel strategies :

• Commerce. This prioritizes cross-channel shopping experience both in store and online.
• Personalization. This strategy focuses on tailored, targeted, and relevant cross-channel engagement at scale.
• Ecosystem. Here, the strategy aims to provide rich cross-channel platforms integrated with consumer needs and lifestyles.

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What’s involved in omnichannel operations?

Organizations can build leading omnichannel operations , spanning a variety of areas. By strengthening the foundation of your omnichannel operations and focusing on strategy, structure, and processes, you could gain a performance edge.

Topics to explore include mastering omnichannel supply chains , creating a customer-centric supply chain strategy , designing the omnichannel distribution network of the future , reimagining the role of physical stores , and more.

What should I know about B2B omnichannel?

Omnichannel has become a permanent part of B2B sales , with e-commerce, face-to-face, and remote videoconference sales all a necessary part of buyers’ experience. According to a 2021 McKinsey survey of US-based B2B decision makers, 94 percent of respondents view today’s B2B omnichannel reality  as being as effective or more effective than before COVID-19. The findings also revealed that B2B customers regularly use ten or more channels to interact with suppliers, up from five in 2016.

B2B omnichannel efforts can be a path to grow an organization’s market share, but loyalty is up for grabs, with customers more willing than ever to switch suppliers for a better omnichannel experience. B2B decision makers use more channels than ever before to interact with suppliers, and being attuned to those channels will be important.

There are five must-dos for B2B companies seeking to retain customer loyalty and succeed in omnichannel:

• offer a performance guarantee (nearly 80 percent of B2B customers say it’s crucial)
• show product availability online
• enable purchases over any channel
• provide customer service in real time
• ensure the customer experience is consistent as buyers toggle between channels

While B2C omnichannel efforts might be the first to spring to mind, omnichannel experience is crucial to giving all customers a better and more seamless journey.

For more in-depth exploration of these topics, see McKinsey’s insights on marketing and sales —and check out omnichannel-related job opportunities if you’re interested in working at McKinsey.

Articles referenced include:

• “ The new B2B growth equation ,” February 23, 2022, Arun Arora , Liz Harrison , Max Magni, Candace Lun Plotkin , and Jennifer Stanley
• “ Omnichannel: The path to value ,” April 30, 2021, Holly Briedis, Brian Gregg , Kevin Heidenreich, and Wei Wei Liu
• “ Omnichannel shopping in 2030 ,” April 9, 2021, Praveen Adhi , Eric Hazan , Sajal Kohli , and Kelsey Robinson
• “ Redefine the omnichannel approach: Focus on what truly matters ,” June 22, 2020, Jorge Amar , Raelyn Jacobson , Becca Kleinstein, and Allison Shi
• “ The end of shopping’s boundaries: Omnichannel personalization ,” February 10, 2020, Gal Gitter, Meg Raymond, Kelsey Robinson , and Jamie Wilkie

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Related articles.

Omnichannel: The path to value

The new B2B growth equation

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The benefits of single-subject research designs and multi-methodological approaches for neuroscience research

1. introduction.

The scientific method is neither singular nor fixed; it is an evolving, plural set of processes. It develops and improves through time as methodology rises to meet new challenges (Lakatos, 1978 ; Hull, 1988 ; Kuhn and Hacking, 2012 ). “It would be wrong to assume that one must stay with a research programme until it has exhausted all its heuristic power, that one must not introduce a rival programme before everybody agrees that the point of degeneration has probably been reached” (Lakatos, 1978 ). These insights apply not least to experimental design approaches.

For better and for worse, no experimental design comes without limitation. We must accept that the realities of the world cannot be simplistically verified against universal standard procedures; we are free instead to explore how the progressive evolution of experimental design enables new advancement. This paper proposes support for a shift of focus in the methodology of experimental research in neuroscience toward an increased utilization of single-subject experimental designs. I will highlight several supports for this suggestion. Most importantly, single-subject methods can complement group methodologies in two ways: by addressing important points of internal validity and by enabling the inductive process characteristic of quality early research. The power of these approaches has already been somewhat established by key historical neuroscience experiments. Additionally, the individuated nature of subject matter in behavioral neuroscience makes the single-subject approach particularly powerful, and single-subject phases in a research program can decrease time and resource costs in relation to scientific gains.

2. Complimentary research designs

Though the completely randomized group design is considered by many to be the gold standard of evidence (Meldrum, 2000 ), its limitations as well as ethical and logistical execution difficulties have been noted: e.g., blindness to group heterogeneity, problematic application to individual cases, and experimental weakness in the context of other often-neglected aspects of study design such as group size, randomization, and bias (Kravitz et al., 2004 ; Grossman and Mackenzie, 2005 ; Williams, 2010 ; Button et al., 2013 ). Thus, the concept of a “gold standard” results not from the uniform superiority of a method, but from an implicit valuing of its relative strengths compared to other designs, all things being equal (even though such things as context, randomization, group size, bias, heterogeneity, etc. are rarely equal). There is an alternative to this approach. Utilizing a wider array of methods across studies can help compensate for the limitations of each and provide flexibility in the face of unequal contexts. In a multi-methodological approach, different experimental designs can be evaluated in terms of complementarity rather than absolute strength. If one experimental design is limited in a particular way, adding another approach that is stronger in that aspect (but perhaps limited in another) can provide a more complete picture. This tactic also implicitly acknowledges that scientific rigor does not proceed only from the single study; replication, systematic replication, and convergent evidence may proceed from a progression of methods.

I suggest adding greater utilization of single-subject design to the already traditionally utilized between-subject and within-subject group designs in neuroscience to achieve this complementarity. The advantages and limitations of these designs are somewhat symmetrical. Overall, single-subject experiments carry with them more finely-focused internal validity because the same subject (together with their array of individual characteristics) serves in both the experimental and control conditions. Unlike in typical within-subject group comparisons, the repetition of comparisons in single-subject designs control for other confounding variables, rendering n = 1 into a true experiment. While an unreplicated single-subject experiment by itself cannot establish external validity, systematic replication of single-subject experiments over the relevant range of individual differences can. On the other hand, group designs cannot demonstrate an effect on an individual level, but within-individual group studies can characterize the generality of effects across large populations in a single properly sampled study, and may be particularly suited to analyzing combined effects of multiple variables (Kazdin, 1981 ). Single subject and group approaches can also be hybridized to fit a study's goals (Kazdin, 2011 ). In the following sections, I will describe aspects of each approach that illustrate how the addition of single-subject methodology to neuroscience could be of use. I do not mean to exhaustively describe either methodology, which would be outside the scope of this paper.

2.1. Group designs

Group experimental designs 1 interrogate the effect of an independent variable (IV) by applying that variable to a group of people, other organisms, or other biological units (e.g., neurons) and usually—but not always—comparing an aggregated population measure to that of one or more control groups. These designs require data from multiple individuals (people, animals, cells, etc.). Group experiments with between-group comparisons often assign these individuals to conditions (experimental or control) randomly. Other group experiments (such as a randomized block design) assign individuals to conditions systematically to explicitly balance the groups according to particular pre-considered individual factors. In both cases, the assumption is that if alternative variables influence the dependent variable (DV), they are unlikely to do so differentially across groups. Group experiments with within-subject comparisons expose each individual to both experimental and control conditions at different times and compare the grouped measures between conditions; this approach assures that the groups are truly identical since the same individuals are included in both conditions.

Because they involve multiple individuals, some group designs can provide important information about the generality of an effect across the included population, especially in the case of within-subject group designs. Unfortunately, some often-misused aspects of group designs tend to temper this advantage. For example, restricted inclusion criteria are often necessary to produce clear results. When desired generality involves only such a restricted population (e.g., only acute stroke patients, or only layer IV glutamatergic cortical neurons), this practice carries no disadvantage. However, if the study aims to identify more widely applicable processes, stringent inclusion criteria can produce cleaner but overly conditional results, limiting external validity (Henrich et al., 2010 ). Further, the analysis approach taken in many group designs that narrowly examines changes in central tendency (such as the mean) of groups can limit the assessment of generality within the sampled population since averaging will wash out heterogeneity of effects. Other aspects of rigor in group designs can also affect external validity (e.g., Kravitz et al., 2004 ; Grossman and Mackenzie, 2005 ; Williams, 2010 ; Button et al., 2013 ).

Another limitation of group design logic is the practical difficulty of balancing individual differences between groups. In the case of between-group comparisons, these difficulties arise from selection bias, mortality, etc. Even well controlled studies can still produce probabilistically imbalanced groups, especially in the small sample sizes often used in neuroscience research (Button et al., 2013 ). Deliberately balanced groups or post-hoc statistical control may help, but the former introduces a potential problem with true randomization, and the latter is weaker than true experimental control. Within-subject group comparisons implement both experimental and control conditions for each individual in a group and therefore better control for individual differences, however these designs still do not experimentally establish effects within the individual since single manipulations of experimental conditions can be confounded with other changes on an individual level.

The typical focus on parameters such as the mean in the analysis of group designs can also threaten internal as well as external validity, particularly if the experimental question concerns biological or behavioral variables that are highly individually contextualized or developmentally variant. 2 This problem extends from the fact that aggregate measures across populations do not necessarily reflect any of the underlying individuals (e.g., Williams, 2010 ); for example, average brain functional mapping tends not to apply to individual brains (Brett et al., 2002 ; Dworetsky et al., 2021 ; Fedorenko, 2021 ; Hanson, 2022 ). This kind of problem is particularly amplified in the study of human behavior and brain sciences, which both tend to be highly idiosyncratic. In these cases, aggregated measures can mask key heterogeneity including contradictory effects of IVs. This can complicate the application of results to individuals: an issue especially relevant in clinical research (Sidman, 1960 ; Williams, 2010 ). Relatedly, the estimation of population-based effect size provides scant information with which to estimate effects and relevance for an individual. Post-hoc statistical analysis may help to tease out these issues, but verification still requires new experimentation. True generality of a scientific insight requires not only that effects occur with reasonable replicability across individuals, but that a reasonable range of conditions that would alter the effect can be predicted: a difficult point to discern in group studies. Thus, while group designs carry advantages insofar as they can be used to characterize effects across a whole population in a single experiment, those advantages can be and often are subverted. Perhaps counter-intuitively, single-subject approaches can be ideal for methodically discovering the common processes that underlie diversity within a population, which have made it particularly powerful in producing generalizable results (see next section).

2.2. Single-subject designs

Single-subject designs compare experimental to control conditions repeatedly over time within the same individual. Like group designs with within-subject comparisons, single-subject designs can control for individual differences, which remain constant. However, single-subject designs take individual control to a new level. Since other confounding changes may coincide with a single change in the IV, single-subject designs also require multiple implementations of the same manipulation so that the comparison can be repeated within the individual, controlling for the coincidental confounds of a single condition change. Additionally, single-subject designs measure multiple data points through time within each condition before any experimental change occurs to assess pre-existing variation and trends in comparisons with the subsequent condition. Of course, a single-subject experiment without inter-individual replication has no generality—systematic replications across relevant individual characteristics and contexts are generally required to establish external validity. However, the typical group design also often requires similar replication to establish the same validity, and unlike group designs single-subject studies are also capable of rigorously interrogating even the rarest of effects.

Because single-subject experiments deal well with individual effects, they are often used in clinical and closely applied disciplines, e.g., education (Alnahdi, 2015 ), rehabilitation and therapy (Tankersley et al., 2006 ), speech and language (Byiers et al., 2012 ), implementation science (Miller et al., 2020 ), neuropsychology (Perdices and Tate, 2009 ), biomedicine (Janosky et al., 2009 ), and behavior analysis (Perone, 1991 ). However, the single-subject design is not limited to clinical applications or to the study of rare effects; it can also be used for the study of generalizable individual processes via systematic replication. Serial replications often enable detailed distillation of both common and uncommon relevant factors across individuals, making the approach particularly powerful for identifying generalizable processes that account for within-population diversity (although this process can be challenging even on the single-subject level; see Kazdin, 1981 ). Single-subject methodology has historically established some of the most generalizable findings in psychology including the principles of Pavlovian and operant conditioning (Iversen, 2013 ). Establishing this generalizability requires a research program rather than a single study, however since each replication (and comparisons between them) can potentially add information about important contextual variables, systematic progression toward generality can be more efficient than in one-shot group studies.

Single-subject designs are sometimes confused with within-subject group comparisons or n-of-1 case studies, neither of which usually include multiple implementations of each condition for any one individual. N-of-1 case studies sometimes make no manipulation at all or may make a single comparison (as with an embedded AB design or pre-post observation), which can at best serve as a quasi-experiment (Kazdin and Tuma, 1982 ). A single subject design, in contrast, will include many repeated condition changes and collect multiple data points inside each condition (as in the ABABABAB design as well as many others, see Perone, 1991 ). As is the case for group designs, the quality of evidence in a single-subject experiment increases with the number of instances in which the experimental condition is compared to a control condition; the more comparisons occur, the less likely it is that an alternative explanation will have tracked with the manipulation. A strong single-subject design will require a minimum of three IV implementations for the same individual (i.e., ABABAB, with multiple data points for each A and each B), and a robust effect will require many more.

Because single-subject designs implement conditions across time, they are susceptible to some important limitations including sequence, maturation, and exposure effects. The need to consider within-condition stability, serial dependence in data sets, reversibility, carryover effects, and long experimental time courses can also complicate these designs. Still, manipulations common in neuroscience research is often amenable to these challenges (Soto, 2020 ). Single-subject designs for phenomena that are not reversable (such as skill acquisition) can also be studied using approaches such as the within-subject multiple baseline. Multiple baselines experiments across behaviors, across cell populations, or across homotopic brain regions may be reasonable if independence can be established (Soto, 2020 ). A variety of single-subject methods are available that can help to address the unique strengths and limitations in single-subject methodology; the reader is encouraged to explore the variety of designs that cannot be enumerated in the scope of the current paper (Horner and Baer, 1978 ; Hains and Baer, 1989 ; Perone, 1991 ; Holcombe et al., 1994 ; Edgington, 1996 ; Kratochwill et al., 2010 ; Ward-Horner and Sturmey, 2010 ).

2.3. A note about statistical methods

Issues relating to statistical analysis are commonly erroneously conflated with group experimental design per se . Problems with the frequentist statistical approach commonly used in group designs has greatly impacted its efficacy; frequentist statistical methods carry limitations that have been treated thoroughly elsewhere [e.g., the generic problems with null-hypothesis statistical testing NHST (Branch, 2014 ), the inappropriate use of frequentist statistics contrary to their best use and design (Moen et al., 2016 ; Wasserstein and Lazar, 2016 ), and the inappropriate reliance on p -values (Wasserstein and Lazar, 2016 )]. I do not expand on these issues in my summary of group design because such critiques need not apply to all between-group comparisons. The use and applicability of analysis techniques are separable from the experimental utility of group designs in general, which are not limited to inferential statistics. Group experiments can also be analyzed using alternative, less problematic statistical approaches such as the probability of replication statistic or P-rep (Killeen, 2015 ) and Bayesian approaches (Berry and Stangl, 2018 ). Well-considered statistical best practices for various forms of group analysis (e.g., Moen et al., 2016 ) can help a researcher to address limitations.

The conflation of statistical methods with group designs has also led to the misconception that single-subject designs cannot be analyzed statistically. Most scientists have less familiarity with statistical analyses appropriate for use in single-subject designs and the serially-dependent data sets that they produce. While pronounced effects uncovered in single-subject experiments can often be clearly detected using appropriate visual analysis, rigorous statistical methods applicable to single-subject designs are also available (e.g., Parker and Brossart, 2003 ; Scruggs and Mastropieri, 2013 ).

3. Single-subject design and the inductive process

The advantages highlighted above suggest not only compatibility between single-subject and group approaches, but a potential advantage conferred by an order of operations between methods. Early in the research process, inductive inference based on single-subject manipulations are ideal to generate likely and testable abstractions (Russell, 1962 ). Using single-subject approaches for this inductive phase requires fewer resources compared to fully powered group approaches and can be more rigorous than small-n group pilots. An effect can be isolated in one individual, then systematically replicated across relevant differences and contexts until it fails to replicate, at which time explanatory variables can be adjusted until replicated results are produced. The altered experiment can then be analyzed in comparison to previous experiments to form a more general understanding that can be tested in a new series of experiments. After sufficient systematic replication, hybrid and group designs can assess the extent to which inductively and contextually informed abstractions generalize across the widest relevant populations.

4. Precedent of within-subject methods

Although within-subject group experiments are common in human neuroscience and psychology, e.g., Greenwald ( 1976 ) and Crockett and Fehr ( 2014 ), full-fledged single-subject designs are virtually unknown in many subfields. Still, high-impact neuroscience experiments have occasionally either implicitly or deliberately implemented within-subject reversals, demonstrating the power of these approaches to advance the science. To name just a few high-impact examples, Hodgkin et al. ( 1952 ) classic work on voltage clamping utilizing the giant squid neuron involved multiple parametric IV implementations on single neurons. The discovery of circadian rhythms in humans also involved systematic single-subject experiments comparing circadian patterns at various light intensities, light-dark schedules, and control contexts, which allowed investigators to establish that outside entrainment overrode the cycle-altering effects of different light intensities (Aschoff, 1965 ). This fruitful precedent of single-subject-like experiments at the very foundation of historical neuroscience together with the well-established efficacy of single-subject design in other fields imply that the wider adoption of the full methodology can succeed.

5. Single-subject design and individuality in neuroscience

As suggested earlier in this paper, individual variation dominates the scene in behavioral and brain sciences and constitutes a basic part of the evolutionary selection processes that shaped them. In human neuroscience, individual developmental and experience-dependent variation are of particular importance. Human brains are so individuated that functional units across individuals cannot be discerned via typical anatomical landmarks, and even between-group designs often need to utilize individuated or normalized measures (Brett et al., 2002 ; Dworetsky et al., 2021 ; Fedorenko, 2021 ; Hanson, 2022 ). A shift toward including rigorous single-subject research therefore holds particular promise for the field. For example, systematically replicated individual analyses of functional brain networks and their dynamics may more easily lead to generalizable ideas about how they develop and change, and these purportedly general processes could in turn be tested across individual contexts.

6. Time and resource logistics

Group methodology often requires great time and resources in order to produce properly powered experiments. This can lead to problems with rigor, particularly in contexts of limited funding and publish-or-perish job demands (Bernard, 2016 ; Button, 2016 ). Especially in early stages of research, single-subject methodology enables experimenters to investigate effects more critically and rigorously for each subject, to more quickly answer and refine questions in individuals first before systematically exploring the generality of findings or the importance of context, and to do so in a cost-effective way. Thus, both cost and rigor could be served by conscientiously adding single-subject methodology to the neuroscience toolbelt.

7. Suggestions for neuroscience subfields that could benefit

Cognitive, behavioral, social, and developmental neuroscience each deal with individual variation in which later stages are often dependent on earlier stages and seek to identify generalizable processes that produce variant outcomes: a task for which the single-subject and multi-method approach is ideal. Neurology and clinical neuroscience also stand to benefit from a more rigorous tool for investigating clinical cases or rare phenomena. While I do not mean to suggest that the method's utility should be limited to these subfields, the potential benefit seems particularly pronounced.

8. Discussion

In summary, greater utilization of single-subject research in human neuroscience can complement current methods by balancing the progression toward internal and then external validity and enabling a low-cost and flexible inductive process that can strengthen subsequent between-group studies. These methods have already been incidentally utilized in important neuroscience research, and they could be an even more powerful, thorough, cost-efficient, rigorous, and deliberate ingredient of an ideal approach to studying the generalizable processes that account for the highly individuated human brain and the behavior that it enables.

Author contributions

AB conceived of and wrote this manuscript.

Acknowledgments

The author would like to thank Daniele Ortu, Ph.D. for helpful comments.

Funding Statement

AB was funded by the Beatrice H. Barrett endowment for research on neuro-operant relations.

1 This discussion intentionally excludes assignment to groups based on non-manipulable variables because of the qualitative difference between correlational approaches and true experimental approaches that manipulates the IV. The former carries a very different set of considerations outside the scope of this paper.

2 If the biological process under investigation actually occurs at the population level (e.g. natural selection), the population parameter precisely applies to the question at hand. However, group comparisons are more often used to study processes that function on the individual level.

Conflict of interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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What the data says about gun deaths in the U.S.

More Americans died of gun-related injuries in 2021 than in any other year on record, according to the latest available statistics from the Centers for Disease Control and Prevention (CDC). That included record numbers of both gun murders and gun suicides. Despite the increase in such fatalities, the rate of gun deaths – a statistic that accounts for the nation’s growing population – remained below the levels of earlier decades.

Here’s a closer look at gun deaths in the United States, based on a Pew Research Center analysis of data from the CDC, the FBI and other sources. You can also read key public opinion findings about U.S. gun violence and gun policy .

This Pew Research Center analysis examines the changing number and rate of gun deaths in the United States. It is based primarily on data from the Centers for Disease Control and Prevention (CDC) and the Federal Bureau of Investigation (FBI). The CDC’s statistics are based on information contained in official death certificates, while the FBI’s figures are based on information voluntarily submitted by thousands of police departments around the country.

For the number and rate of gun deaths over time, we relied on mortality statistics in the CDC’s WONDER database covering four distinct time periods:  1968 to 1978 ,  1979 to 1998 ,  1999 to 2020 , and 2021 . While these statistics are mostly comparable for the full 1968-2021 period, gun murders and suicides between 1968 and 1978 are classified by the CDC as involving firearms  and  explosives; those between 1979 and 2021 are classified as involving firearms only. Similarly, gun deaths involving law enforcement between 1968 and 1978 exclude those caused by “operations of war”; those between 1979 and 2021 include that category, which refers to gun deaths among military personnel or civilians  due to war or civil insurrection in the U.S . All CDC gun death estimates in this analysis are adjusted to account for age differences over time and across states.

The FBI’s statistics about the types of firearms used in gun murders in 2020 come from the bureau’s  Crime Data Explorer website . Specifically, they are drawn from the expanded homicide tables of the agency’s  2020 Crime in the United States report . The FBI’s statistics include murders and non-negligent manslaughters involving firearms.

How many people die from gun-related injuries in the U.S. each year?

In 2021, the most recent year for which complete data is available, 48,830 people died from gun-related injuries in the U.S., according to the CDC. That figure includes gun murders and gun suicides, along with three less common types of gun-related deaths tracked by the CDC: those that were accidental, those that involved law enforcement and those whose circumstances could not be determined. The total excludes deaths in which gunshot injuries played a contributing, but not principal, role. (CDC fatality statistics are based on information contained in official death certificates, which identify a single cause of death.)

What share of U.S. gun deaths are murders and what share are suicides?

Though they tend to get less public attention than gun-related murders, suicides have long accounted for the majority of U.S. gun deaths . In 2021, 54% of all gun-related deaths in the U.S. were suicides (26,328), while 43% were murders (20,958), according to the CDC. The remaining gun deaths that year were accidental (549), involved law enforcement (537) or had undetermined circumstances (458).

What share of all murders and suicides in the U.S. involve a gun?

About eight-in-ten U.S. murders in 2021 – 20,958 out of 26,031, or 81% – involved a firearm. That marked the highest percentage since at least 1968, the earliest year for which the CDC has online records. More than half of all suicides in 2021 – 26,328 out of 48,183, or 55% – also involved a gun, the highest percentage since 2001.

How has the number of U.S. gun deaths changed over time?

The record 48,830 total gun deaths in 2021 reflect a 23% increase since 2019, before the onset of the coronavirus pandemic .

Gun murders, in particular, have climbed sharply during the pandemic, increasing 45% between 2019 and 2021, while the number of gun suicides rose 10% during that span.

The overall increase in U.S. gun deaths since the beginning of the pandemic includes an especially stark rise in such fatalities among children and teens under the age of 18. Gun deaths among children and teens rose 50% in just two years , from 1,732 in 2019 to 2,590 in 2021.

How has the rate of U.S. gun deaths changed over time?

While 2021 saw the highest total number of gun deaths in the U.S., this statistic does not take into account the nation’s growing population. On a per capita basis, there were 14.6 gun deaths per 100,000 people in 2021 – the highest rate since the early 1990s, but still well below the peak of 16.3 gun deaths per 100,000 people in 1974.

The gun murder rate in the U.S. remains below its peak level despite rising sharply during the pandemic. There were 6.7 gun murders per 100,000 people in 2021, below the 7.2 recorded in 1974.

The gun suicide rate, on the other hand, is now on par with its historical peak. There were 7.5 gun suicides per 100,000 people in 2021, statistically similar to the 7.7 measured in 1977. (One caveat when considering the 1970s figures: In the CDC’s database, gun murders and gun suicides between 1968 and 1978 are classified as those caused by firearms and explosives. In subsequent years, they are classified as deaths involving firearms only.)

Which states have the highest and lowest gun death rates in the U.S.?

The rate of gun fatalities varies widely from state to state. In 2021, the states with the highest total rates of gun-related deaths – counting murders, suicides and all other categories tracked by the CDC – included Mississippi (33.9 per 100,000 people), Louisiana (29.1), New Mexico (27.8), Alabama (26.4) and Wyoming (26.1). The states with the lowest total rates included Massachusetts (3.4), Hawaii (4.8), New Jersey (5.2), New York (5.4) and Rhode Island (5.6).

The results are somewhat different when looking at gun murder and gun suicide rates separately. The places with the highest gun murder rates in 2021 included the District of Columbia (22.3 per 100,000 people), Mississippi (21.2), Louisiana (18.4), Alabama (13.9) and New Mexico (11.7). Those with the lowest gun murder rates included Massachusetts (1.5), Idaho (1.5), Hawaii (1.6), Utah (2.1) and Iowa (2.2). Rate estimates are not available for Maine, New Hampshire, Vermont or Wyoming.

The states with the highest gun suicide rates in 2021 included Wyoming (22.8 per 100,000 people), Montana (21.1), Alaska (19.9), New Mexico (13.9) and Oklahoma (13.7). The states with the lowest gun suicide rates were Massachusetts (1.7), New Jersey (1.9), New York (2.0), Hawaii (2.8) and Connecticut (2.9). Rate estimates are not available for the District of Columbia.

How does the gun death rate in the U.S. compare with other countries?

The gun death rate in the U.S. is much higher than in most other nations, particularly developed nations. But it is still far below the rates in several Latin American countries, according to a 2018 study of 195 countries and territories by researchers at the Institute for Health Metrics and Evaluation at the University of Washington.

The U.S. gun death rate was 10.6 per 100,000 people in 2016, the most recent year in the study, which used a somewhat different methodology from the CDC. That was far higher than in countries such as Canada (2.1 per 100,000) and Australia (1.0), as well as European nations such as France (2.7), Germany (0.9) and Spain (0.6). But the rate in the U.S. was much lower than in El Salvador (39.2 per 100,000 people), Venezuela (38.7), Guatemala (32.3), Colombia (25.9) and Honduras (22.5), the study found. Overall, the U.S. ranked 20th in its gun fatality rate that year .

How many people are killed in mass shootings in the U.S. every year?

This is a difficult question to answer because there is no single, agreed-upon definition of the term “mass shooting.” Definitions can vary depending on factors including the number of victims and the circumstances of the shooting.

The FBI collects data on “active shooter incidents,” which it defines as “one or more individuals actively engaged in killing or attempting to kill people in a populated area.” Using the FBI’s definition, 103 people – excluding the shooters – died in such incidents in 2021 .

The Gun Violence Archive, an online database of gun violence incidents in the U.S., defines mass shootings as incidents in which four or more people are shot, even if no one was killed (again excluding the shooters). Using this definition, 706 people died in these incidents in 2021 .

Regardless of the definition being used, fatalities in mass shooting incidents in the U.S. account for a small fraction of all gun murders that occur nationwide each year.

How has the number of mass shootings in the U.S. changed over time?

The same definitional issue that makes it challenging to calculate mass shooting fatalities comes into play when trying to determine the frequency of U.S. mass shootings over time. The unpredictability of these incidents also complicates matters: As Rand Corp. noted in a research brief , “Chance variability in the annual number of mass shooting incidents makes it challenging to discern a clear trend, and trend estimates will be sensitive to outliers and to the time frame chosen for analysis.”

The FBI found an increase in active shooter incidents between 2000 and 2021. There were three such incidents in 2000. By 2021, that figure had increased to 61.

Which types of firearms are most commonly used in gun murders in the U.S.?

In 2020, the most recent year for which the FBI has published data, handguns were involved in 59% of the 13,620 U.S. gun murders and non-negligent manslaughters for which data is available. Rifles – the category that includes guns sometimes referred to as “assault weapons” – were involved in 3% of firearm murders. Shotguns were involved in 1%. The remainder of gun homicides and non-negligent manslaughters (36%) involved other kinds of firearms or those classified as “type not stated.”

It’s important to note that the FBI’s statistics do not capture the details on all gun murders in the U.S. each year. The FBI’s data is based on information voluntarily submitted by police departments around the country, and not all agencies participate or provide complete information each year.

Note: This is an update of a post originally published on Aug. 16, 2019.

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John Gramlich is an associate director at Pew Research Center .

Cultural Issues and the 2024 Election

About 1 in 4 u.s. teachers say their school went into a gun-related lockdown in the last school year, striking findings from 2023, key facts about americans and guns, for most u.s. gun owners, protection is the main reason they own a gun, most popular.

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What is peer review?

Reviewers play a pivotal role in scholarly publishing. The peer review system exists to validate academic work, helps to improve the quality of published research, and increases networking possibilities within research communities. Despite criticisms, peer review is still the only widely accepted method for research validation and has continued successfully with relatively minor changes for some 350 years.

Elsevier relies on the peer review process to uphold the quality and validity of individual articles and the journals that publish them.

Peer review has been a formal part of scientific communication since the first scientific journals appeared more than 300 years ago. The Philosophical Transactions opens in new tab/window of the Royal Society is thought to be the first journal to formalize the peer review process opens in new tab/window under the editorship of Henry Oldenburg (1618- 1677).

Despite many criticisms about the integrity of peer review, the majority of the research community still believes peer review is the best form of scientific evaluation. This opinion was endorsed by the outcome of a survey Elsevier and Sense About Science conducted in 2009 opens in new tab/window and has since been further confirmed by other publisher and scholarly organization surveys. Furthermore, a  2015 survey by the Publishing Research Consortium opens in new tab/window , saw 82% of researchers agreeing that “without peer review there is no control in scientific communication.”

To learn more about peer review, visit Elsevier’s free e-learning platform  Researcher Academy opens in new tab/window and see our resources below.

The peer review process

Types of peer review.

Peer review comes in different flavours. Each model has its own advantages and disadvantages, and often one type of review will be preferred by a subject community. Before submitting or reviewing a paper, you must therefore check which type is employed by the journal so you are aware of the respective rules. In case of questions regarding the peer review model employed by the journal for which you have been invited to review, consult the journal’s homepage or contact the editorial office directly.  

Single anonymized review

In this type of review, the names of the reviewers are hidden from the author. This is the traditional method of reviewing and is the most common type by far. Points to consider regarding single anonymized review include:

Reviewer anonymity allows for impartial decisions , as the reviewers will not be influenced by potential criticism from the authors.

Authors may be concerned that reviewers in their field could delay publication, giving the reviewers a chance to publish first.

Reviewers may use their anonymity as justification for being unnecessarily critical or harsh when commenting on the authors’ work.

Double anonymized review

Both the reviewer and the author are anonymous in this model. Some advantages of this model are listed below.

Author anonymity limits reviewer bias, such as on author's gender, country of origin, academic status, or previous publication history.

Articles written by prestigious or renowned authors are considered based on the content of their papers, rather than their reputation.

But bear in mind that despite the above, reviewers can often identify the author through their writing style, subject matter, or self-citation – it is exceedingly difficult to guarantee total author anonymity. More information for authors can be found in our  double-anonymized peer review guidelines .

Triple anonymized review

With triple anonymized review, reviewers are anonymous to the author, and the author's identity is unknown to both the reviewers and the editor. Articles are anonymized at the submission stage and are handled in a way to minimize any potential bias towards the authors. However, it should be noted that: 

The complexities involved with anonymizing articles/authors to this level are considerable.

As with double anonymized review, there is still a possibility for the editor and/or reviewers to correctly identify the author(s) from their writing style, subject matter, citation patterns, or other methodologies.

Open review

Open peer review is an umbrella term for many different models aiming at greater transparency during and after the peer review process. The most common definition of open review is when both the reviewer and author are known to each other during the peer review process. Other types of open peer review consist of:

Publication of reviewers’ names on the article page 

Publication of peer review reports alongside the article, either signed or anonymous 

Publication of peer review reports (signed or anonymous) with authors’ and editors’ responses alongside the article 

Publication of the paper after pre-checks and opening a discussion forum to the community who can then comment (named or anonymous) on the article 

Many believe this is the best way to prevent malicious comments, stop plagiarism, prevent reviewers from following their own agenda, and encourage open, honest reviewing. Others see open review as a less honest process, in which politeness or fear of retribution may cause a reviewer to withhold or tone down criticism. For three years, five Elsevier journals experimented with publication of peer review reports (signed or anonymous) as articles alongside the accepted paper on ScienceDirect ( example opens in new tab/window ).

Read more about the experiment

More transparent peer review

Transparency is the key to trust in peer review and as such there is an increasing call towards more  transparency around the peer review process . In an effort to promote transparency in the peer review process, many Elsevier journals therefore publish the name of the handling editor of the published paper on ScienceDirect. Some journals also provide details about the number of reviewers who reviewed the article before acceptance. Furthermore, in order to provide updates and feedback to reviewers, most Elsevier journals inform reviewers about the editor’s decision and their peers’ recommendations. 

Article transfer service: sharing reviewer comments

Elsevier authors may be invited to  transfer  their article submission from one journal to another for free if their initial submission was not successful. 

As a referee, your review report (including all comments to the author and editor) will be transferred to the destination journal, along with the manuscript. The main benefit is that reviewers are not asked to review the same manuscript several times for different journals. 

Tools and resources

Interesting reads.

Chapter 2 of Academic and Professional Publishing, 2012, by Irene Hames in 2012 opens in new tab/window

"Is Peer Review in Crisis?" Perspectives in Publishing No 2, August 2004, by Adrian Mulligan opens in new tab/window

“The history of the peer-review process” Trends in Biotechnology, 2002, by Ray Spier opens in new tab/window

Reviewers’ Update articles

Peer review using today’s technology

Lifting the lid on publishing peer review reports: an interview with Bahar Mehmani and Flaminio Squazzoni

How face-to-face peer review can benefit authors and journals alike

Innovation in peer review: introducing “volunpeers”

Results masked review: peer review without publication bias

Elsevier Researcher Academy modules

The certified peer reviewer course opens in new tab/window

Transparency in peer review opens in new tab/window

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

Chapter 10: Single-Subject Research

Overview of Single-Subject Research

Learning Objectives

• Explain what single-subject research is, including how it differs from other types of psychological research.
• Explain what case studies are, including some of their strengths and weaknesses.
• Explain who uses single-subject research and why.

What Is Single-Subject Research?

Single-subject research  is a type of quantitative research that involves studying in detail the behaviour of each of a small number of participants. Note that the term  single-subject  does not mean that only one participant is studied; it is more typical for there to be somewhere between two and 10 participants. (This is why single-subject research designs are sometimes called small- n designs, where  n  is the statistical symbol for the sample size.) Single-subject research can be contrasted with  group research , which typically involves studying large numbers of participants and examining their behaviour primarily in terms of group means, standard deviations, and so on. The majority of this textbook is devoted to understanding group research, which is the most common approach in psychology. But single-subject research is an important alternative, and it is the primary approach in some areas of psychology.

Before continuing, it is important to distinguish single-subject research from two other approaches, both of which involve studying in detail a small number of participants. One is qualitative research, which focuses on understanding people’s subjective experience by collecting relatively unstructured data (e.g., detailed interviews) and analyzing those data using narrative rather than quantitative techniques. Single-subject research, in contrast, focuses on understanding objective behaviour through experimental manipulation and control, collecting highly structured data, and analyzing those data quantitatively.

It is also important to distinguish single-subject research from case studies. A case study  is a detailed description of an individual, which can include both qualitative and quantitative analyses. (Case studies that include only qualitative analyses can be considered a type of qualitative research.) The history of psychology is filled with influential cases studies, such as Sigmund Freud’s description of “Anna O.” (see Note 10.5 “The Case of “Anna O.””) and John Watson and Rosalie Rayner’s description of Little Albert (Watson & Rayner, 1920) [1] , who learned to fear a white rat—along with other furry objects—when the researchers made a loud noise while he was playing with the rat. Case studies can be useful for suggesting new research questions and for illustrating general principles. They can also help researchers understand rare phenomena, such as the effects of damage to a specific part of the human brain. As a general rule, however, case studies cannot substitute for carefully designed group or single-subject research studies. One reason is that case studies usually do not allow researchers to determine whether specific events are causally related, or even related at all. For example, if a patient is described in a case study as having been sexually abused as a child and then as having developed an eating disorder as a teenager, there is no way to determine whether these two events had anything to do with each other. A second reason is that an individual case can always be unusual in some way and therefore be unrepresentative of people more generally. Thus case studies have serious problems with both internal and external validity.

The Case of “Anna O.”

Sigmund Freud used the case of a young woman he called “Anna O.” to illustrate many principles of his theory of psychoanalysis (Freud, 1961) [2] . (Her real name was Bertha Pappenheim, and she was an early feminist who went on to make important contributions to the field of social work.) Anna had come to Freud’s colleague Josef Breuer around 1880 with a variety of odd physical and psychological symptoms. One of them was that for several weeks she was unable to drink any fluids. According to Freud,

She would take up the glass of water that she longed for, but as soon as it touched her lips she would push it away like someone suffering from hydrophobia.…She lived only on fruit, such as melons, etc., so as to lessen her tormenting thirst. (p. 9)

But according to Freud, a breakthrough came one day while Anna was under hypnosis.

[S]he grumbled about her English “lady-companion,” whom she did not care for, and went on to describe, with every sign of disgust, how she had once gone into this lady’s room and how her little dog—horrid creature!—had drunk out of a glass there. The patient had said nothing, as she had wanted to be polite. After giving further energetic expression to the anger she had held back, she asked for something to drink, drank a large quantity of water without any difficulty, and awoke from her hypnosis with the glass at her lips; and thereupon the disturbance vanished, never to return. (p.9)

Freud’s interpretation was that Anna had repressed the memory of this incident along with the emotion that it triggered and that this was what had caused her inability to drink. Furthermore, her recollection of the incident, along with her expression of the emotion she had repressed, caused the symptom to go away.

As an illustration of Freud’s theory, the case study of Anna O. is quite effective. As evidence for the theory, however, it is essentially worthless. The description provides no way of knowing whether Anna had really repressed the memory of the dog drinking from the glass, whether this repression had caused her inability to drink, or whether recalling this “trauma” relieved the symptom. It is also unclear from this case study how typical or atypical Anna’s experience was.

Assumptions of Single-Subject Research

Again, single-subject research involves studying a small number of participants and focusing intensively on the behaviour of each one. But why take this approach instead of the group approach? There are several important assumptions underlying single-subject research, and it will help to consider them now.

First and foremost is the assumption that it is important to focus intensively on the behaviour of individual participants. One reason for this is that group research can hide individual differences and generate results that do not represent the behaviour of any individual. For example, a treatment that has a positive effect for half the people exposed to it but a negative effect for the other half would, on average, appear to have no effect at all. Single-subject research, however, would likely reveal these individual differences. A second reason to focus intensively on individuals is that sometimes it is the behaviour of a particular individual that is primarily of interest. A school psychologist, for example, might be interested in changing the behaviour of a particular disruptive student. Although previous published research (both single-subject and group research) is likely to provide some guidance on how to do this, conducting a study on this student would be more direct and probably more effective.

A second assumption of single-subject research is that it is important to discover causal relationships through the manipulation of an independent variable, the careful measurement of a dependent variable, and the control of extraneous variables. For this reason, single-subject research is often considered a type of experimental research with good internal validity. Recall, for example, that Hall and his colleagues measured their dependent variable (studying) many times—first under a no-treatment control condition, then under a treatment condition (positive teacher attention), and then again under the control condition. Because there was a clear increase in studying when the treatment was introduced, a decrease when it was removed, and an increase when it was reintroduced, there is little doubt that the treatment was the cause of the improvement.

A third assumption of single-subject research is that it is important to study strong and consistent effects that have biological or social importance. Applied researchers, in particular, are interested in treatments that have substantial effects on important behaviours and that can be implemented reliably in the real-world contexts in which they occur. This is sometimes referred to as social validity  (Wolf, 1976) [3] . The study by Hall and his colleagues, for example, had good social validity because it showed strong and consistent effects of positive teacher attention on a behaviour that is of obvious importance to teachers, parents, and students. Furthermore, the teachers found the treatment easy to implement, even in their often-chaotic elementary school classrooms.

Who Uses Single-Subject Research?

Single-subject research has been around as long as the field of psychology itself. In the late 1800s, one of psychology’s founders, Wilhelm Wundt, studied sensation and consciousness by focusing intensively on each of a small number of research participants. Herman Ebbinghaus’s research on memory and Ivan Pavlov’s research on classical conditioning are other early examples, both of which are still described in almost every introductory psychology textbook.

In the middle of the 20th century, B. F. Skinner clarified many of the assumptions underlying single-subject research and refined many of its techniques (Skinner, 1938) [4] . He and other researchers then used it to describe how rewards, punishments, and other external factors affect behaviour over time. This work was carried out primarily using nonhuman subjects—mostly rats and pigeons. This approach, which Skinner called the experimental analysis of behaviour —remains an important subfield of psychology and continues to rely almost exclusively on single-subject research. For excellent examples of this work, look at any issue of the  Journal of the Experimental Analysis of Behaviour . By the 1960s, many researchers were interested in using this approach to conduct applied research primarily with humans—a subfield now called  applied behaviour analysis  (Baer, Wolf, & Risley, 1968) [5] . Applied behaviour analysis plays an especially important role in contemporary research on developmental disabilities, education, organizational behaviour, and health, among many other areas. Excellent examples of this work (including the study by Hall and his colleagues) can be found in the  Journal of Applied Behaviour Analysis .

Although most contemporary single-subject research is conducted from the behavioural perspective, it can in principle be used to address questions framed in terms of any theoretical perspective. For example, a studying technique based on cognitive principles of learning and memory could be evaluated by testing it on individual high school students using the single-subject approach. The single-subject approach can also be used by clinicians who take any theoretical perspective—behavioural, cognitive, psychodynamic, or humanistic—to study processes of therapeutic change with individual clients and to document their clients’ improvement (Kazdin, 1982) [6] .

Key Takeaways

• Single-subject research—which involves testing a small number of participants and focusing intensively on the behaviour of each individual—is an important alternative to group research in psychology.
• Single-subject studies must be distinguished from case studies, in which an individual case is described in detail. Case studies can be useful for generating new research questions, for studying rare phenomena, and for illustrating general principles. However, they cannot substitute for carefully controlled experimental or correlational studies because they are low in internal and external validity.
• Single-subject research has been around since the beginning of the field of psychology. Today it is most strongly associated with the behavioural theoretical perspective, but it can in principle be used to study behaviour from any perspective.
• Practice: Find and read a published article in psychology that reports new single-subject research. ( An archive of articles published in the Journal of Applied Behaviour Analysis can be found at http://www.ncbi.nlm.nih.gov/pmc/journals/309/) Write a short summary of the study.
• Describe one problem related to internal validity.
• Describe one problem related to external validity.
• Generate one hypothesis suggested by the case study that might be interesting to test in a systematic single-subject or group study.

Media Attributions

• Pappenheim 1882 by unknown is in the Public Domain .
• Watson, J. B., & Rayner, R. (1920). Conditioned emotional reactions.  Journal of Experimental Psychology, 3 , 1–14. ↵
• Freud, S. (1961).  Five lectures on psycho-analysis . New York, NY: Norton. ↵
• Wolf, M. (1976). Social validity: The case for subjective measurement or how applied behaviour analysis is finding its heart.  Journal of Applied Behaviour Analysis, 11 , 203–214. ↵
• Skinner, B. F. (1938). T he behaviour of organisms: An experimental analysis . New York, NY: Appleton-Century-Crofts. ↵
• Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behaviour analysis.  Journal of Applied Behaviour Analysis, 1 , 91–97. ↵
• Kazdin, A. E. (1982).  Single-case research designs: Methods for clinical and applied settings . New York, NY: Oxford University Press. ↵

A type of quantitative research that involves studying the behaviour of each small number of participants in detail.

The study of large numbers of participants and examining their behaviour primarily in terms of group means, standard deviations, and so on.

A detailed description of an individual, which can include both qualitative and quantitative analyses.

The study of strong and consistent effects that can be implemented reliably in the real-world contexts in which they occur.

Laboratory methods that rely on single-subject research; based upon B. F. Skinner’s philosophy of behaviourism which posits that everything organisms do is behaviour.

Starting in the 1960s, researchers began using single-subject techniques to conduct applied research with human subjects.

Research Methods in Psychology - 2nd Canadian Edition Copyright © 2015 by Paul C. Price, Rajiv Jhangiani, & I-Chant A. Chiang is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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