what is a single case study

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base

Methodology

• What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

• Academic style
• Vague sentences
• Style consistency

See an example

Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

McCombes, S. (2023, November 20). What Is a Case Study? | Definition, Examples & Methods. Scribbr. Retrieved April 15, 2024, from https://www.scribbr.com/methodology/case-study/

Is this article helpful?

Shona McCombes

Other students also liked, primary vs. secondary sources | difference & examples, what is a theoretical framework | guide to organizing, what is action research | definition & examples, what is your plagiarism score.

• Privacy Policy

Buy Me a Coffee

Home » Case Study – Methods, Examples and Guide

Case Study – Methods, Examples and Guide

Table of Contents

A case study is a research method that involves an in-depth examination and analysis of a particular phenomenon or case, such as an individual, organization, community, event, or situation.

It is a qualitative research approach that aims to provide a detailed and comprehensive understanding of the case being studied. Case studies typically involve multiple sources of data, including interviews, observations, documents, and artifacts, which are analyzed using various techniques, such as content analysis, thematic analysis, and grounded theory. The findings of a case study are often used to develop theories, inform policy or practice, or generate new research questions.

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

A single-case study is an in-depth analysis of a single case. This type of case study is useful when the researcher wants to understand a specific phenomenon in detail.

For Example , A researcher might conduct a single-case study on a particular individual to understand their experiences with a particular health condition or a specific organization to explore their management practices. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a single-case study are often used to generate new research questions, develop theories, or inform policy or practice.

Multiple-Case Study

A multiple-case study involves the analysis of several cases that are similar in nature. This type of case study is useful when the researcher wants to identify similarities and differences between the cases.

For Example, a researcher might conduct a multiple-case study on several companies to explore the factors that contribute to their success or failure. The researcher collects data from each case, compares and contrasts the findings, and uses various techniques to analyze the data, such as comparative analysis or pattern-matching. The findings of a multiple-case study can be used to develop theories, inform policy or practice, or generate new research questions.

Exploratory Case Study

An exploratory case study is used to explore a new or understudied phenomenon. This type of case study is useful when the researcher wants to generate hypotheses or theories about the phenomenon.

For Example, a researcher might conduct an exploratory case study on a new technology to understand its potential impact on society. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as grounded theory or content analysis. The findings of an exploratory case study can be used to generate new research questions, develop theories, or inform policy or practice.

Descriptive Case Study

A descriptive case study is used to describe a particular phenomenon in detail. This type of case study is useful when the researcher wants to provide a comprehensive account of the phenomenon.

For Example, a researcher might conduct a descriptive case study on a particular community to understand its social and economic characteristics. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a descriptive case study can be used to inform policy or practice or generate new research questions.

Instrumental Case Study

An instrumental case study is used to understand a particular phenomenon that is instrumental in achieving a particular goal. This type of case study is useful when the researcher wants to understand the role of the phenomenon in achieving the goal.

For Example, a researcher might conduct an instrumental case study on a particular policy to understand its impact on achieving a particular goal, such as reducing poverty. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of an instrumental case study can be used to inform policy or practice or generate new research questions.

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

Interviews involve asking questions to individuals who have knowledge or experience relevant to the case study. Interviews can be structured (where the same questions are asked to all participants) or unstructured (where the interviewer follows up on the responses with further questions). Interviews can be conducted in person, over the phone, or through video conferencing.

Observations

Observations involve watching and recording the behavior and activities of individuals or groups relevant to the case study. Observations can be participant (where the researcher actively participates in the activities) or non-participant (where the researcher observes from a distance). Observations can be recorded using notes, audio or video recordings, or photographs.

Documents can be used as a source of information for case studies. Documents can include reports, memos, emails, letters, and other written materials related to the case study. Documents can be collected from the case study participants or from public sources.

Surveys involve asking a set of questions to a sample of individuals relevant to the case study. Surveys can be administered in person, over the phone, through mail or email, or online. Surveys can be used to gather information on attitudes, opinions, or behaviors related to the case study.

Artifacts are physical objects relevant to the case study. Artifacts can include tools, equipment, products, or other objects that provide insights into the case study phenomenon.

How to conduct Case Study Research

Conducting a case study research involves several steps that need to be followed to ensure the quality and rigor of the study. Here are the steps to conduct case study research:

• Define the research questions: The first step in conducting a case study research is to define the research questions. The research questions should be specific, measurable, and relevant to the case study phenomenon under investigation.
• Select the case: The next step is to select the case or cases to be studied. The case should be relevant to the research questions and should provide rich and diverse data that can be used to answer the research questions.
• Collect data: Data can be collected using various methods, such as interviews, observations, documents, surveys, and artifacts. The data collection method should be selected based on the research questions and the nature of the case study phenomenon.
• Analyze the data: The data collected from the case study should be analyzed using various techniques, such as content analysis, thematic analysis, or grounded theory. The analysis should be guided by the research questions and should aim to provide insights and conclusions relevant to the research questions.
• Draw conclusions: The conclusions drawn from the case study should be based on the data analysis and should be relevant to the research questions. The conclusions should be supported by evidence and should be clearly stated.
• Validate the findings: The findings of the case study should be validated by reviewing the data and the analysis with participants or other experts in the field. This helps to ensure the validity and reliability of the findings.
• Write the report: The final step is to write the report of the case study research. The report should provide a clear description of the case study phenomenon, the research questions, the data collection methods, the data analysis, the findings, and the conclusions. The report should be written in a clear and concise manner and should follow the guidelines for academic writing.

Examples of Case Study

Here are some examples of case study research:

• The Hawthorne Studies : Conducted between 1924 and 1932, the Hawthorne Studies were a series of case studies conducted by Elton Mayo and his colleagues to examine the impact of work environment on employee productivity. The studies were conducted at the Hawthorne Works plant of the Western Electric Company in Chicago and included interviews, observations, and experiments.
• The Stanford Prison Experiment: Conducted in 1971, the Stanford Prison Experiment was a case study conducted by Philip Zimbardo to examine the psychological effects of power and authority. The study involved simulating a prison environment and assigning participants to the role of guards or prisoners. The study was controversial due to the ethical issues it raised.
• The Challenger Disaster: The Challenger Disaster was a case study conducted to examine the causes of the Space Shuttle Challenger explosion in 1986. The study included interviews, observations, and analysis of data to identify the technical, organizational, and cultural factors that contributed to the disaster.
• The Enron Scandal: The Enron Scandal was a case study conducted to examine the causes of the Enron Corporation’s bankruptcy in 2001. The study included interviews, analysis of financial data, and review of documents to identify the accounting practices, corporate culture, and ethical issues that led to the company’s downfall.
• The Fukushima Nuclear Disaster : The Fukushima Nuclear Disaster was a case study conducted to examine the causes of the nuclear accident that occurred at the Fukushima Daiichi Nuclear Power Plant in Japan in 2011. The study included interviews, analysis of data, and review of documents to identify the technical, organizational, and cultural factors that contributed to the disaster.

Application of Case Study

Case studies have a wide range of applications across various fields and industries. Here are some examples:

Business and Management

Case studies are widely used in business and management to examine real-life situations and develop problem-solving skills. Case studies can help students and professionals to develop a deep understanding of business concepts, theories, and best practices.

Case studies are used in healthcare to examine patient care, treatment options, and outcomes. Case studies can help healthcare professionals to develop critical thinking skills, diagnose complex medical conditions, and develop effective treatment plans.

Case studies are used in education to examine teaching and learning practices. Case studies can help educators to develop effective teaching strategies, evaluate student progress, and identify areas for improvement.

Social Sciences

Case studies are widely used in social sciences to examine human behavior, social phenomena, and cultural practices. Case studies can help researchers to develop theories, test hypotheses, and gain insights into complex social issues.

Law and Ethics

Case studies are used in law and ethics to examine legal and ethical dilemmas. Case studies can help lawyers, policymakers, and ethical professionals to develop critical thinking skills, analyze complex cases, and make informed decisions.

Purpose of Case Study

The purpose of a case study is to provide a detailed analysis of a specific phenomenon, issue, or problem in its real-life context. A case study is a qualitative research method that involves the in-depth exploration and analysis of a particular case, which can be an individual, group, organization, event, or community.

The primary purpose of a case study is to generate a comprehensive and nuanced understanding of the case, including its history, context, and dynamics. Case studies can help researchers to identify and examine the underlying factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and detailed understanding of the case, which can inform future research, practice, or policy.

Case studies can also serve other purposes, including:

• Illustrating a theory or concept: Case studies can be used to illustrate and explain theoretical concepts and frameworks, providing concrete examples of how they can be applied in real-life situations.
• Developing hypotheses: Case studies can help to generate hypotheses about the causal relationships between different factors and outcomes, which can be tested through further research.
• Providing insight into complex issues: Case studies can provide insights into complex and multifaceted issues, which may be difficult to understand through other research methods.
• Informing practice or policy: Case studies can be used to inform practice or policy by identifying best practices, lessons learned, or areas for improvement.

Advantages of Case Study Research

There are several advantages of case study research, including:

• In-depth exploration: Case study research allows for a detailed exploration and analysis of a specific phenomenon, issue, or problem in its real-life context. This can provide a comprehensive understanding of the case and its dynamics, which may not be possible through other research methods.
• Rich data: Case study research can generate rich and detailed data, including qualitative data such as interviews, observations, and documents. This can provide a nuanced understanding of the case and its complexity.
• Holistic perspective: Case study research allows for a holistic perspective of the case, taking into account the various factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and comprehensive understanding of the case.
• Theory development: Case study research can help to develop and refine theories and concepts by providing empirical evidence and concrete examples of how they can be applied in real-life situations.
• Practical application: Case study research can inform practice or policy by identifying best practices, lessons learned, or areas for improvement.
• Contextualization: Case study research takes into account the specific context in which the case is situated, which can help to understand how the case is influenced by the social, cultural, and historical factors of its environment.

Limitations of Case Study Research

There are several limitations of case study research, including:

• Limited generalizability : Case studies are typically focused on a single case or a small number of cases, which limits the generalizability of the findings. The unique characteristics of the case may not be applicable to other contexts or populations, which may limit the external validity of the research.
• Biased sampling: Case studies may rely on purposive or convenience sampling, which can introduce bias into the sample selection process. This may limit the representativeness of the sample and the generalizability of the findings.
• Subjectivity: Case studies rely on the interpretation of the researcher, which can introduce subjectivity into the analysis. The researcher’s own biases, assumptions, and perspectives may influence the findings, which may limit the objectivity of the research.
• Limited control: Case studies are typically conducted in naturalistic settings, which limits the control that the researcher has over the environment and the variables being studied. This may limit the ability to establish causal relationships between variables.
• Time-consuming: Case studies can be time-consuming to conduct, as they typically involve a detailed exploration and analysis of a specific case. This may limit the feasibility of conducting multiple case studies or conducting case studies in a timely manner.
• Resource-intensive: Case studies may require significant resources, including time, funding, and expertise. This may limit the ability of researchers to conduct case studies in resource-constrained settings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

Questionnaire – Definition, Types, and Examples

Observational Research – Methods and Guide

Quantitative Research – Methods, Types and...

Qualitative Research Methods

Explanatory Research – Types, Methods, Guide

Survey Research – Types, Methods, Examples

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Methodology
• Case Study | Definition, Examples & Methods

Case Study | Definition, Examples & Methods

Published on 5 May 2022 by Shona McCombes . Revised on 30 January 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organisation, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating, and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyse the case.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

Prevent plagiarism, run a free check.

Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

Unlike quantitative or experimental research, a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

If you find yourself aiming to simultaneously investigate and solve an issue, consider conducting action research . As its name suggests, action research conducts research and takes action at the same time, and is highly iterative and flexible. 

However, you can also choose a more common or representative case to exemplify a particular category, experience, or phenomenon.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews, observations, and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data .

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis, with separate sections or chapters for the methods , results , and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyse its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

McCombes, S. (2023, January 30). Case Study | Definition, Examples & Methods. Scribbr. Retrieved 15 April 2024, from https://www.scribbr.co.uk/research-methods/case-studies/

Is this article helpful?

Shona McCombes

Other students also liked, correlational research | guide, design & examples, a quick guide to experimental design | 5 steps & examples, descriptive research design | definition, methods & examples.

Research Writing and Analysis

• NVivo Group and Study Sessions
• SPSS This link opens in a new window
• Statistical Analysis Group sessions
• Using Qualtrics
• Dissertation and Data Analysis Group Sessions
• Defense Schedule - Commons Calendar This link opens in a new window
• Research Process Flow Chart
• Research Alignment This link opens in a new window
• Step 1: Seek Out Evidence
• Step 2: Explain
• Step 3: The Big Picture
• Step 4: Own It
• Step 5: Illustrate
• Annotated Bibliography
• Literature Review This link opens in a new window
• Systematic Reviews & Meta-Analyses
• How to Synthesize and Analyze
• Synthesis and Analysis Practice
• Synthesis and Analysis Group Sessions
• Problem Statement
• Purpose Statement
• Quantitative Research Questions
• Qualitative Research Questions
• Trustworthiness of Qualitative Data
• Analysis and Coding Example- Qualitative Data
• Thematic Data Analysis in Qualitative Design
• Dissertation to Journal Article This link opens in a new window
• International Journal of Online Graduate Education (IJOGE) This link opens in a new window
• Journal of Research in Innovative Teaching & Learning (JRIT&L) This link opens in a new window

Writing a Case Study

What is a case study?

A Case study is: 

• An in-depth research design that primarily uses a qualitative methodology but sometimes​​ includes quantitative methodology.
• Used to examine an identifiable problem confirmed through research.
• Used to investigate an individual, group of people, organization, or event.
• Used to mostly answer "how" and "why" questions.

What are the different types of case studies?

Note: These are the primary case studies. As you continue to research and learn

about case studies you will begin to find a robust list of different types. 

Who are your case study participants?

What is triangulation ? 

Validity and credibility are an essential part of the case study. Therefore, the researcher should include triangulation to ensure trustworthiness while accurately reflecting what the researcher seeks to investigate.

How to write a Case Study?

When developing a case study, there are different ways you could present the information, but remember to include the five parts for your case study.

Was this resource helpful?

• << Previous: Thematic Data Analysis in Qualitative Design
• Next: Journal Article Reporting Standards (JARS) >>
• Last Updated: Apr 12, 2024 11:40 AM
• URL: https://resources.nu.edu/researchtools

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Perspective
• Published: 22 November 2022

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

• Lyndsey Nickels   ORCID: orcid.org/0000-0002-0311-3524 1 , 2 ,
• Simon Fischer-Baum   ORCID: orcid.org/0000-0002-6067-0538 3 &
• Wendy Best   ORCID: orcid.org/0000-0001-8375-5916 4  

Nature Reviews Psychology volume  1 ,  pages 733–747 ( 2022 ) Cite this article

642 Accesses

5 Citations

26 Altmetric

Metrics details

• Neurological disorders

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.

This is a preview of subscription content, access via your institution

Access options

Subscribe to this journal

Receive 12 digital issues and online access to articles

55,14 € per year

only 4,60 € per issue

Buy this article

• Purchase on Springer Link
• Instant access to full article PDF

Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others

A systematic review and multivariate meta-analysis of the physical and mental health benefits of touch interventions

Julian Packheiser, Helena Hartmann, … Frédéric Michon

Worldwide divergence of values

Joshua Conrad Jackson & Danila Medvedev

The process and mechanisms of personality change

Joshua J. Jackson & Amanda J. Wright

Corkin, S. Permanent Present Tense: The Unforgettable Life Of The Amnesic Patient, H. M . Vol. XIX, 364 (Basic Books, 2013).

Lilienfeld, S. O. Psychology: From Inquiry To Understanding (Pearson, 2019).

Schacter, D. L., Gilbert, D. T., Nock, M. K. & Wegner, D. M. Psychology (Worth Publishers, 2019).

Eysenck, M. W. & Brysbaert, M. Fundamentals Of Cognition (Routledge, 2018).

Squire, L. R. Memory and brain systems: 1969–2009. J. Neurosci. 29 , 12711–12716 (2009).

Article   PubMed   PubMed Central   Google Scholar  

Corkin, S. What’s new with the amnesic patient H.M.? Nat. Rev. Neurosci. 3 , 153–160 (2002).

Article   PubMed   Google Scholar  

Schubert, T. M. et al. Lack of awareness despite complex visual processing: evidence from event-related potentials in a case of selective metamorphopsia. Proc. Natl Acad. Sci. USA 117 , 16055–16064 (2020).

Behrmann, M. & Plaut, D. C. Bilateral hemispheric processing of words and faces: evidence from word impairments in prosopagnosia and face impairments in pure alexia. Cereb. Cortex 24 , 1102–1118 (2014).

Plaut, D. C. & Behrmann, M. Complementary neural representations for faces and words: a computational exploration. Cogn. Neuropsychol. 28 , 251–275 (2011).

Haxby, J. V. et al. Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science 293 , 2425–2430 (2001).

Hirshorn, E. A. et al. Decoding and disrupting left midfusiform gyrus activity during word reading. Proc. Natl Acad. Sci. USA 113 , 8162–8167 (2016).

Kosakowski, H. L. et al. Selective responses to faces, scenes, and bodies in the ventral visual pathway of infants. Curr. Biol. 32 , 265–274.e5 (2022).

Harlow, J. Passage of an iron rod through the head. Boston Med. Surgical J . https://doi.org/10.1176/jnp.11.2.281 (1848).

Broca, P. Remarks on the seat of the faculty of articulated language, following an observation of aphemia (loss of speech). Bull. Soc. Anat. 6 , 330–357 (1861).

Google Scholar  

Dejerine, J. Contribution A L’étude Anatomo-pathologique Et Clinique Des Différentes Variétés De Cécité Verbale: I. Cécité Verbale Avec Agraphie Ou Troubles Très Marqués De L’écriture; II. Cécité Verbale Pure Avec Intégrité De L’écriture Spontanée Et Sous Dictée (Société de Biologie, 1892).

Liepmann, H. Das Krankheitsbild der Apraxie (“motorischen Asymbolie”) auf Grund eines Falles von einseitiger Apraxie (Fortsetzung). Eur. Neurol. 8 , 102–116 (1900).

Article   Google Scholar  

Basso, A., Spinnler, H., Vallar, G. & Zanobio, M. E. Left hemisphere damage and selective impairment of auditory verbal short-term memory. A case study. Neuropsychologia 20 , 263–274 (1982).

Humphreys, G. W. & Riddoch, M. J. The fractionation of visual agnosia. In Visual Object Processing: A Cognitive Neuropsychological Approach 281–306 (Lawrence Erlbaum, 1987).

Whitworth, A., Webster, J. & Howard, D. A Cognitive Neuropsychological Approach To Assessment And Intervention In Aphasia (Psychology Press, 2014).

Caramazza, A. On drawing inferences about the structure of normal cognitive systems from the analysis of patterns of impaired performance: the case for single-patient studies. Brain Cogn. 5 , 41–66 (1986).

Caramazza, A. & McCloskey, M. The case for single-patient studies. Cogn. Neuropsychol. 5 , 517–527 (1988).

Shallice, T. Cognitive neuropsychology and its vicissitudes: the fate of Caramazza’s axioms. Cogn. Neuropsychol. 32 , 385–411 (2015).

Shallice, T. From Neuropsychology To Mental Structure (Cambridge Univ. Press, 1988).

Coltheart, M. Assumptions and methods in cognitive neuropscyhology. In The Handbook Of Cognitive Neuropsychology: What Deficits Reveal About The Human Mind (ed. Rapp, B.) 3–22 (Psychology Press, 2001).

McCloskey, M. & Chaisilprungraung, T. The value of cognitive neuropsychology: the case of vision research. Cogn. Neuropsychol. 34 , 412–419 (2017).

McCloskey, M. The future of cognitive neuropsychology. In The Handbook Of Cognitive Neuropsychology: What Deficits Reveal About The Human Mind (ed. Rapp, B.) 593–610 (Psychology Press, 2001).

Lashley, K. S. In search of the engram. In Physiological Mechanisms in Animal Behavior 454–482 (Academic Press, 1950).

Squire, L. R. & Wixted, J. T. The cognitive neuroscience of human memory since H.M. Annu. Rev. Neurosci. 34 , 259–288 (2011).

Stone, G. O., Vanhoy, M. & Orden, G. C. V. Perception is a two-way street: feedforward and feedback phonology in visual word recognition. J. Mem. Lang. 36 , 337–359 (1997).

Perfetti, C. A. The psycholinguistics of spelling and reading. In Learning To Spell: Research, Theory, And Practice Across Languages 21–38 (Lawrence Erlbaum, 1997).

Nickels, L. The autocue? self-generated phonemic cues in the treatment of a disorder of reading and naming. Cogn. Neuropsychol. 9 , 155–182 (1992).

Rapp, B., Benzing, L. & Caramazza, A. The autonomy of lexical orthography. Cogn. Neuropsychol. 14 , 71–104 (1997).

Bonin, P., Roux, S. & Barry, C. Translating nonverbal pictures into verbal word names. Understanding lexical access and retrieval. In Past, Present, And Future Contributions Of Cognitive Writing Research To Cognitive Psychology 315–522 (Psychology Press, 2011).

Bonin, P., Fayol, M. & Gombert, J.-E. Role of phonological and orthographic codes in picture naming and writing: an interference paradigm study. Cah. Psychol. Cogn./Current Psychol. Cogn. 16 , 299–324 (1997).

Bonin, P., Fayol, M. & Peereman, R. Masked form priming in writing words from pictures: evidence for direct retrieval of orthographic codes. Acta Psychol. 99 , 311–328 (1998).

Bentin, S., Allison, T., Puce, A., Perez, E. & McCarthy, G. Electrophysiological studies of face perception in humans. J. Cogn. Neurosci. 8 , 551–565 (1996).

Jeffreys, D. A. Evoked potential studies of face and object processing. Vis. Cogn. 3 , 1–38 (1996).

Laganaro, M., Morand, S., Michel, C. M., Spinelli, L. & Schnider, A. ERP correlates of word production before and after stroke in an aphasic patient. J. Cogn. Neurosci. 23 , 374–381 (2011).

Indefrey, P. & Levelt, W. J. M. The spatial and temporal signatures of word production components. Cognition 92 , 101–144 (2004).

Valente, A., Burki, A. & Laganaro, M. ERP correlates of word production predictors in picture naming: a trial by trial multiple regression analysis from stimulus onset to response. Front. Neurosci. 8 , 390 (2014).

Kittredge, A. K., Dell, G. S., Verkuilen, J. & Schwartz, M. F. Where is the effect of frequency in word production? Insights from aphasic picture-naming errors. Cogn. Neuropsychol. 25 , 463–492 (2008).

Domdei, N. et al. Ultra-high contrast retinal display system for single photoreceptor psychophysics. Biomed. Opt. Express 9 , 157 (2018).

Poldrack, R. A. et al. Long-term neural and physiological phenotyping of a single human. Nat. Commun. 6 , 8885 (2015).

Coltheart, M. The assumptions of cognitive neuropsychology: reflections on Caramazza (1984, 1986). Cogn. Neuropsychol. 34 , 397–402 (2017).

Badecker, W. & Caramazza, A. A final brief in the case against agrammatism: the role of theory in the selection of data. Cognition 24 , 277–282 (1986).

Fischer-Baum, S. Making sense of deviance: Identifying dissociating cases within the case series approach. Cogn. Neuropsychol. 30 , 597–617 (2013).

Nickels, L., Howard, D. & Best, W. On the use of different methodologies in cognitive neuropsychology: drink deep and from several sources. Cogn. Neuropsychol. 28 , 475–485 (2011).

Dell, G. S. & Schwartz, M. F. Who’s in and who’s out? Inclusion criteria, model evaluation, and the treatment of exceptions in case series. Cogn. Neuropsychol. 28 , 515–520 (2011).

Schwartz, M. F. & Dell, G. S. Case series investigations in cognitive neuropsychology. Cogn. Neuropsychol. 27 , 477–494 (2010).

Cohen, J. A power primer. Psychol. Bull. 112 , 155–159 (1992).

Martin, R. C. & Allen, C. Case studies in neuropsychology. In APA Handbook Of Research Methods In Psychology Vol. 2 Research Designs: Quantitative, Qualitative, Neuropsychological, And Biological (eds Cooper, H. et al.) 633–646 (American Psychological Association, 2012).

Leivada, E., Westergaard, M., Duñabeitia, J. A. & Rothman, J. On the phantom-like appearance of bilingualism effects on neurocognition: (how) should we proceed? Bilingualism 24 , 197–210 (2021).

Arnett, J. J. The neglected 95%: why American psychology needs to become less American. Am. Psychol. 63 , 602–614 (2008).

Stolz, J. A., Besner, D. & Carr, T. H. Implications of measures of reliability for theories of priming: activity in semantic memory is inherently noisy and uncoordinated. Vis. Cogn. 12 , 284–336 (2005).

Cipora, K. et al. A minority pulls the sample mean: on the individual prevalence of robust group-level cognitive phenomena — the instance of the SNARC effect. Preprint at psyArXiv https://doi.org/10.31234/osf.io/bwyr3 (2019).

Andrews, S., Lo, S. & Xia, V. Individual differences in automatic semantic priming. J. Exp. Psychol. Hum. Percept. Perform. 43 , 1025–1039 (2017).

Tan, L. C. & Yap, M. J. Are individual differences in masked repetition and semantic priming reliable? Vis. Cogn. 24 , 182–200 (2016).

Olsson-Collentine, A., Wicherts, J. M. & van Assen, M. A. L. M. Heterogeneity in direct replications in psychology and its association with effect size. Psychol. Bull. 146 , 922–940 (2020).

Gratton, C. & Braga, R. M. Editorial overview: deep imaging of the individual brain: past, practice, and promise. Curr. Opin. Behav. Sci. 40 , iii–vi (2021).

Fedorenko, E. The early origins and the growing popularity of the individual-subject analytic approach in human neuroscience. Curr. Opin. Behav. Sci. 40 , 105–112 (2021).

Xue, A. et al. The detailed organization of the human cerebellum estimated by intrinsic functional connectivity within the individual. J. Neurophysiol. 125 , 358–384 (2021).

Petit, S. et al. Toward an individualized neural assessment of receptive language in children. J. Speech Lang. Hear. Res. 63 , 2361–2385 (2020).

Jung, K.-H. et al. Heterogeneity of cerebral white matter lesions and clinical correlates in older adults. Stroke 52 , 620–630 (2021).

Falcon, M. I., Jirsa, V. & Solodkin, A. A new neuroinformatics approach to personalized medicine in neurology: the virtual brain. Curr. Opin. Neurol. 29 , 429–436 (2016).

Duncan, G. J., Engel, M., Claessens, A. & Dowsett, C. J. Replication and robustness in developmental research. Dev. Psychol. 50 , 2417–2425 (2014).

Open Science Collaboration. Estimating the reproducibility of psychological science. Science 349 , aac4716 (2015).

Tackett, J. L., Brandes, C. M., King, K. M. & Markon, K. E. Psychology’s replication crisis and clinical psychological science. Annu. Rev. Clin. Psychol. 15 , 579–604 (2019).

Munafò, M. R. et al. A manifesto for reproducible science. Nat. Hum. Behav. 1 , 0021 (2017).

Oldfield, R. C. & Wingfield, A. The time it takes to name an object. Nature 202 , 1031–1032 (1964).

Oldfield, R. C. & Wingfield, A. Response latencies in naming objects. Q. J. Exp. Psychol. 17 , 273–281 (1965).

Brysbaert, M. How many participants do we have to include in properly powered experiments? A tutorial of power analysis with reference tables. J. Cogn. 2 , 16 (2019).

Brysbaert, M. Power considerations in bilingualism research: time to step up our game. Bilingualism https://doi.org/10.1017/S1366728920000437 (2020).

Machery, E. What is a replication? Phil. Sci. 87 , 545–567 (2020).

Nosek, B. A. & Errington, T. M. What is replication? PLoS Biol. 18 , e3000691 (2020).

Li, X., Huang, L., Yao, P. & Hyönä, J. Universal and specific reading mechanisms across different writing systems. Nat. Rev. Psychol. 1 , 133–144 (2022).

Rapp, B. (Ed.) The Handbook Of Cognitive Neuropsychology: What Deficits Reveal About The Human Mind (Psychology Press, 2001).

Code, C. et al. Classic Cases In Neuropsychology (Psychology Press, 1996).

Patterson, K., Marshall, J. C. & Coltheart, M. Surface Dyslexia: Neuropsychological And Cognitive Studies Of Phonological Reading (Routledge, 2017).

Marshall, J. C. & Newcombe, F. Patterns of paralexia: a psycholinguistic approach. J. Psycholinguist. Res. 2 , 175–199 (1973).

Castles, A. & Coltheart, M. Varieties of developmental dyslexia. Cognition 47 , 149–180 (1993).

Khentov-Kraus, L. & Friedmann, N. Vowel letter dyslexia. Cogn. Neuropsychol. 35 , 223–270 (2018).

Winskel, H. Orthographic and phonological parafoveal processing of consonants, vowels, and tones when reading Thai. Appl. Psycholinguist. 32 , 739–759 (2011).

Hepner, C., McCloskey, M. & Rapp, B. Do reading and spelling share orthographic representations? Evidence from developmental dysgraphia. Cogn. Neuropsychol. 34 , 119–143 (2017).

Hanley, J. R. & Sotiropoulos, A. Developmental surface dysgraphia without surface dyslexia. Cogn. Neuropsychol. 35 , 333–341 (2018).

Zihl, J. & Heywood, C. A. The contribution of single case studies to the neuroscience of vision: single case studies in vision neuroscience. Psych. J. 5 , 5–17 (2016).

Bouvier, S. E. & Engel, S. A. Behavioral deficits and cortical damage loci in cerebral achromatopsia. Cereb. Cortex 16 , 183–191 (2006).

Zihl, J. & Heywood, C. A. The contribution of LM to the neuroscience of movement vision. Front. Integr. Neurosci. 9 , 6 (2015).

Dotan, D. & Friedmann, N. Separate mechanisms for number reading and word reading: evidence from selective impairments. Cortex 114 , 176–192 (2019).

McCloskey, M. & Schubert, T. Shared versus separate processes for letter and digit identification. Cogn. Neuropsychol. 31 , 437–460 (2014).

Fayol, M. & Seron, X. On numerical representations. Insights from experimental, neuropsychological, and developmental research. In Handbook of Mathematical Cognition (ed. Campbell, J.) 3–23 (Psychological Press, 2005).

Bornstein, B. & Kidron, D. P. Prosopagnosia. J. Neurol. Neurosurg. Psychiat. 22 , 124–131 (1959).

Kühn, C. D., Gerlach, C., Andersen, K. B., Poulsen, M. & Starrfelt, R. Face recognition in developmental dyslexia: evidence for dissociation between faces and words. Cogn. Neuropsychol. 38 , 107–115 (2021).

Barton, J. J. S., Albonico, A., Susilo, T., Duchaine, B. & Corrow, S. L. Object recognition in acquired and developmental prosopagnosia. Cogn. Neuropsychol. 36 , 54–84 (2019).

Renault, B., Signoret, J.-L., Debruille, B., Breton, F. & Bolgert, F. Brain potentials reveal covert facial recognition in prosopagnosia. Neuropsychologia 27 , 905–912 (1989).

Bauer, R. M. Autonomic recognition of names and faces in prosopagnosia: a neuropsychological application of the guilty knowledge test. Neuropsychologia 22 , 457–469 (1984).

Haan, E. H. F., de, Young, A. & Newcombe, F. Face recognition without awareness. Cogn. Neuropsychol. 4 , 385–415 (1987).

Ellis, H. D. & Lewis, M. B. Capgras delusion: a window on face recognition. Trends Cogn. Sci. 5 , 149–156 (2001).

Ellis, H. D., Young, A. W., Quayle, A. H. & De Pauw, K. W. Reduced autonomic responses to faces in Capgras delusion. Proc. R. Soc. Lond. B 264 , 1085–1092 (1997).

Collins, M. N., Hawthorne, M. E., Gribbin, N. & Jacobson, R. Capgras’ syndrome with organic disorders. Postgrad. Med. J. 66 , 1064–1067 (1990).

Enoch, D., Puri, B. K. & Ball, H. Uncommon Psychiatric Syndromes 5th edn (Routledge, 2020).

Tranel, D., Damasio, H. & Damasio, A. R. Double dissociation between overt and covert face recognition. J. Cogn. Neurosci. 7 , 425–432 (1995).

Brighetti, G., Bonifacci, P., Borlimi, R. & Ottaviani, C. “Far from the heart far from the eye”: evidence from the Capgras delusion. Cogn. Neuropsychiat. 12 , 189–197 (2007).

Coltheart, M., Langdon, R. & McKay, R. Delusional belief. Annu. Rev. Psychol. 62 , 271–298 (2011).

Coltheart, M. Cognitive neuropsychiatry and delusional belief. Q. J. Exp. Psychol. 60 , 1041–1062 (2007).

Coltheart, M. & Davies, M. How unexpected observations lead to new beliefs: a Peircean pathway. Conscious. Cogn. 87 , 103037 (2021).

Coltheart, M. & Davies, M. Failure of hypothesis evaluation as a factor in delusional belief. Cogn. Neuropsychiat. 26 , 213–230 (2021).

McCloskey, M. et al. A developmental deficit in localizing objects from vision. Psychol. Sci. 6 , 112–117 (1995).

McCloskey, M., Valtonen, J. & Cohen Sherman, J. Representing orientation: a coordinate-system hypothesis and evidence from developmental deficits. Cogn. Neuropsychol. 23 , 680–713 (2006).

McCloskey, M. Spatial representations and multiple-visual-systems hypotheses: evidence from a developmental deficit in visual location and orientation processing. Cortex 40 , 677–694 (2004).

Gregory, E. & McCloskey, M. Mirror-image confusions: implications for representation and processing of object orientation. Cognition 116 , 110–129 (2010).

Gregory, E., Landau, B. & McCloskey, M. Representation of object orientation in children: evidence from mirror-image confusions. Vis. Cogn. 19 , 1035–1062 (2011).

Laine, M. & Martin, N. Cognitive neuropsychology has been, is, and will be significant to aphasiology. Aphasiology 26 , 1362–1376 (2012).

Howard, D. & Patterson, K. The Pyramids And Palm Trees Test: A Test Of Semantic Access From Words And Pictures (Thames Valley Test Co., 1992).

Kay, J., Lesser, R. & Coltheart, M. PALPA: Psycholinguistic Assessments Of Language Processing In Aphasia. 2: Picture & Word Semantics, Sentence Comprehension (Erlbaum, 2001).

Franklin, S. Dissociations in auditory word comprehension; evidence from nine fluent aphasic patients. Aphasiology 3 , 189–207 (1989).

Howard, D., Swinburn, K. & Porter, G. Putting the CAT out: what the comprehensive aphasia test has to offer. Aphasiology 24 , 56–74 (2010).

Conti-Ramsden, G., Crutchley, A. & Botting, N. The extent to which psychometric tests differentiate subgroups of children with SLI. J. Speech Lang. Hear. Res. 40 , 765–777 (1997).

Bishop, D. V. M. & McArthur, G. M. Individual differences in auditory processing in specific language impairment: a follow-up study using event-related potentials and behavioural thresholds. Cortex 41 , 327–341 (2005).

Bishop, D. V. M., Snowling, M. J., Thompson, P. A. & Greenhalgh, T., and the CATALISE-2 consortium. Phase 2 of CATALISE: a multinational and multidisciplinary Delphi consensus study of problems with language development: terminology. J. Child. Psychol. Psychiat. 58 , 1068–1080 (2017).

Wilson, A. J. et al. Principles underlying the design of ‘the number race’, an adaptive computer game for remediation of dyscalculia. Behav. Brain Funct. 2 , 19 (2006).

Basso, A. & Marangolo, P. Cognitive neuropsychological rehabilitation: the emperor’s new clothes? Neuropsychol. Rehabil. 10 , 219–229 (2000).

Murad, M. H., Asi, N., Alsawas, M. & Alahdab, F. New evidence pyramid. Evidence-based Med. 21 , 125–127 (2016).

Greenhalgh, T., Howick, J. & Maskrey, N., for the Evidence Based Medicine Renaissance Group. Evidence based medicine: a movement in crisis? Br. Med. J. 348 , g3725–g3725 (2014).

Best, W., Ping Sze, W., Edmundson, A. & Nickels, L. What counts as evidence? Swimming against the tide: valuing both clinically informed experimentally controlled case series and randomized controlled trials in intervention research. Evidence-based Commun. Assess. Interv. 13 , 107–135 (2019).

Best, W. et al. Understanding differing outcomes from semantic and phonological interventions with children with word-finding difficulties: a group and case series study. Cortex 134 , 145–161 (2021).

OCEBM Levels of Evidence Working Group. The Oxford Levels of Evidence 2. CEBM https://www.cebm.ox.ac.uk/resources/levels-of-evidence/ocebm-levels-of-evidence (2011).

Holler, D. E., Behrmann, M. & Snow, J. C. Real-world size coding of solid objects, but not 2-D or 3-D images, in visual agnosia patients with bilateral ventral lesions. Cortex 119 , 555–568 (2019).

Duchaine, B. C., Yovel, G., Butterworth, E. J. & Nakayama, K. Prosopagnosia as an impairment to face-specific mechanisms: elimination of the alternative hypotheses in a developmental case. Cogn. Neuropsychol. 23 , 714–747 (2006).

Hartley, T. et al. The hippocampus is required for short-term topographical memory in humans. Hippocampus 17 , 34–48 (2007).

Pishnamazi, M. et al. Attentional bias towards and away from fearful faces is modulated by developmental amygdala damage. Cortex 81 , 24–34 (2016).

Rapp, B., Fischer-Baum, S. & Miozzo, M. Modality and morphology: what we write may not be what we say. Psychol. Sci. 26 , 892–902 (2015).

Yong, K. X. X., Warren, J. D., Warrington, E. K. & Crutch, S. J. Intact reading in patients with profound early visual dysfunction. Cortex 49 , 2294–2306 (2013).

Rockland, K. S. & Van Hoesen, G. W. Direct temporal–occipital feedback connections to striate cortex (V1) in the macaque monkey. Cereb. Cortex 4 , 300–313 (1994).

Haynes, J.-D., Driver, J. & Rees, G. Visibility reflects dynamic changes of effective connectivity between V1 and fusiform cortex. Neuron 46 , 811–821 (2005).

Tanaka, K. Mechanisms of visual object recognition: monkey and human studies. Curr. Opin. Neurobiol. 7 , 523–529 (1997).

Fischer-Baum, S., McCloskey, M. & Rapp, B. Representation of letter position in spelling: evidence from acquired dysgraphia. Cognition 115 , 466–490 (2010).

Houghton, G. The problem of serial order: a neural network model of sequence learning and recall. In Current Research In Natural Language Generation (eds Dale, R., Mellish, C. & Zock, M.) 287–319 (Academic Press, 1990).

Fieder, N., Nickels, L., Biedermann, B. & Best, W. From “some butter” to “a butter”: an investigation of mass and count representation and processing. Cogn. Neuropsychol. 31 , 313–349 (2014).

Fieder, N., Nickels, L., Biedermann, B. & Best, W. How ‘some garlic’ becomes ‘a garlic’ or ‘some onion’: mass and count processing in aphasia. Neuropsychologia 75 , 626–645 (2015).

Schröder, A., Burchert, F. & Stadie, N. Training-induced improvement of noncanonical sentence production does not generalize to comprehension: evidence for modality-specific processes. Cogn. Neuropsychol. 32 , 195–220 (2015).

Stadie, N. et al. Unambiguous generalization effects after treatment of non-canonical sentence production in German agrammatism. Brain Lang. 104 , 211–229 (2008).

Schapiro, A. C., Gregory, E., Landau, B., McCloskey, M. & Turk-Browne, N. B. The necessity of the medial temporal lobe for statistical learning. J. Cogn. Neurosci. 26 , 1736–1747 (2014).

Schapiro, A. C., Kustner, L. V. & Turk-Browne, N. B. Shaping of object representations in the human medial temporal lobe based on temporal regularities. Curr. Biol. 22 , 1622–1627 (2012).

Baddeley, A., Vargha-Khadem, F. & Mishkin, M. Preserved recognition in a case of developmental amnesia: implications for the acaquisition of semantic memory? J. Cogn. Neurosci. 13 , 357–369 (2001).

Snyder, J. J. & Chatterjee, A. Spatial-temporal anisometries following right parietal damage. Neuropsychologia 42 , 1703–1708 (2004).

Ashkenazi, S., Henik, A., Ifergane, G. & Shelef, I. Basic numerical processing in left intraparietal sulcus (IPS) acalculia. Cortex 44 , 439–448 (2008).

Lebrun, M.-A., Moreau, P., McNally-Gagnon, A., Mignault Goulet, G. & Peretz, I. Congenital amusia in childhood: a case study. Cortex 48 , 683–688 (2012).

Vannuscorps, G., Andres, M. & Pillon, A. When does action comprehension need motor involvement? Evidence from upper limb aplasia. Cogn. Neuropsychol. 30 , 253–283 (2013).

Jeannerod, M. Neural simulation of action: a unifying mechanism for motor cognition. NeuroImage 14 , S103–S109 (2001).

Blakemore, S.-J. & Decety, J. From the perception of action to the understanding of intention. Nat. Rev. Neurosci. 2 , 561–567 (2001).

Rizzolatti, G. & Craighero, L. The mirror-neuron system. Annu. Rev. Neurosci. 27 , 169–192 (2004).

Forde, E. M. E., Humphreys, G. W. & Remoundou, M. Disordered knowledge of action order in action disorganisation syndrome. Neurocase 10 , 19–28 (2004).

Mazzi, C. & Savazzi, S. The glamor of old-style single-case studies in the neuroimaging era: insights from a patient with hemianopia. Front. Psychol. 10 , 965 (2019).

Coltheart, M. What has functional neuroimaging told us about the mind (so far)? (Position Paper Presented to the European Cognitive Neuropsychology Workshop, Bressanone, 2005). Cortex 42 , 323–331 (2006).

Page, M. P. A. What can’t functional neuroimaging tell the cognitive psychologist? Cortex 42 , 428–443 (2006).

Blank, I. A., Kiran, S. & Fedorenko, E. Can neuroimaging help aphasia researchers? Addressing generalizability, variability, and interpretability. Cogn. Neuropsychol. 34 , 377–393 (2017).

Niv, Y. The primacy of behavioral research for understanding the brain. Behav. Neurosci. 135 , 601–609 (2021).

Crawford, J. R. & Howell, D. C. Comparing an individual’s test score against norms derived from small samples. Clin. Neuropsychol. 12 , 482–486 (1998).

Crawford, J. R., Garthwaite, P. H. & Ryan, K. Comparing a single case to a control sample: testing for neuropsychological deficits and dissociations in the presence of covariates. Cortex 47 , 1166–1178 (2011).

McIntosh, R. D. & Rittmo, J. Ö. Power calculations in single-case neuropsychology: a practical primer. Cortex 135 , 146–158 (2021).

Patterson, K. & Plaut, D. C. “Shallow draughts intoxicate the brain”: lessons from cognitive science for cognitive neuropsychology. Top. Cogn. Sci. 1 , 39–58 (2009).

Lambon Ralph, M. A., Patterson, K. & Plaut, D. C. Finite case series or infinite single-case studies? Comments on “Case series investigations in cognitive neuropsychology” by Schwartz and Dell (2010). Cogn. Neuropsychol. 28 , 466–474 (2011).

Horien, C., Shen, X., Scheinost, D. & Constable, R. T. The individual functional connectome is unique and stable over months to years. NeuroImage 189 , 676–687 (2019).

Epelbaum, S. et al. Pure alexia as a disconnection syndrome: new diffusion imaging evidence for an old concept. Cortex 44 , 962–974 (2008).

Fischer-Baum, S. & Campana, G. Neuroplasticity and the logic of cognitive neuropsychology. Cogn. Neuropsychol. 34 , 403–411 (2017).

Paul, S., Baca, E. & Fischer-Baum, S. Cerebellar contributions to orthographic working memory: a single case cognitive neuropsychological investigation. Neuropsychologia 171 , 108242 (2022).

Feinstein, J. S., Adolphs, R., Damasio, A. & Tranel, D. The human amygdala and the induction and experience of fear. Curr. Biol. 21 , 34–38 (2011).

Crawford, J., Garthwaite, P. & Gray, C. Wanted: fully operational definitions of dissociations in single-case studies. Cortex 39 , 357–370 (2003).

McIntosh, R. D. Simple dissociations for a higher-powered neuropsychology. Cortex 103 , 256–265 (2018).

McIntosh, R. D. & Brooks, J. L. Current tests and trends in single-case neuropsychology. Cortex 47 , 1151–1159 (2011).

Best, W., Schröder, A. & Herbert, R. An investigation of a relative impairment in naming non-living items: theoretical and methodological implications. J. Neurolinguistics 19 , 96–123 (2006).

Franklin, S., Howard, D. & Patterson, K. Abstract word anomia. Cogn. Neuropsychol. 12 , 549–566 (1995).

Coltheart, M., Patterson, K. E. & Marshall, J. C. Deep Dyslexia (Routledge, 1980).

Nickels, L., Kohnen, S. & Biedermann, B. An untapped resource: treatment as a tool for revealing the nature of cognitive processes. Cogn. Neuropsychol. 27 , 539–562 (2010).

Download references

Acknowledgements

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.

Author information

Authors and affiliations.

School of Psychological Sciences & Macquarie University Centre for Reading, Macquarie University, Sydney, New South Wales, Australia

Lyndsey Nickels

NHMRC Centre of Research Excellence in Aphasia Recovery and Rehabilitation, Australia

Psychological Sciences, Rice University, Houston, TX, USA

Simon Fischer-Baum

Psychology and Language Sciences, University College London, London, UK

You can also search for this author in PubMed   Google Scholar

Contributions

L.N. led and was primarily responsible for the structuring and writing of the manuscript. All authors contributed to all aspects of the article.

Corresponding author

Correspondence to Lyndsey Nickels .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Peer review

Peer review information.

Nature Reviews Psychology thanks Yanchao Bi, Rob McIntosh, and the other, anonymous, reviewer for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Cite this article.

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

Download citation

Accepted : 13 October 2022

Published : 22 November 2022

Issue Date : December 2022

DOI : https://doi.org/10.1038/s44159-022-00127-y

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Organizing Your Social Sciences Research Assignments

• Annotated Bibliography
• Analyzing a Scholarly Journal Article
• Group Presentations
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• Types of Structured Group Activities
• Group Project Survival Skills
• Leading a Class Discussion
• Multiple Book Review Essay
• Reviewing Collected Works
• Writing a Case Analysis Paper
• Writing a Case Study
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Reflective Paper
• Writing a Research Proposal
• Generative AI and Writing
• Acknowledgments

A case study research paper examines a person, place, event, condition, phenomenon, or other type of subject of analysis in order to extrapolate  key themes and results that help predict future trends, illuminate previously hidden issues that can be applied to practice, and/or provide a means for understanding an important research problem with greater clarity. A case study research paper usually examines a single subject of analysis, but case study papers can also be designed as a comparative investigation that shows relationships between two or more subjects. The methods used to study a case can rest within a quantitative, qualitative, or mixed-method investigative paradigm.

Case Studies. Writing@CSU. Colorado State University; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010 ; “What is a Case Study?” In Swanborn, Peter G. Case Study Research: What, Why and How? London: SAGE, 2010.

How to Approach Writing a Case Study Research Paper

General information about how to choose a topic to investigate can be found under the " Choosing a Research Problem " tab in the Organizing Your Social Sciences Research Paper writing guide. Review this page because it may help you identify a subject of analysis that can be investigated using a case study design.

However, identifying a case to investigate involves more than choosing the research problem . A case study encompasses a problem contextualized around the application of in-depth analysis, interpretation, and discussion, often resulting in specific recommendations for action or for improving existing conditions. As Seawright and Gerring note, practical considerations such as time and access to information can influence case selection, but these issues should not be the sole factors used in describing the methodological justification for identifying a particular case to study. Given this, selecting a case includes considering the following:

• The case represents an unusual or atypical example of a research problem that requires more in-depth analysis? Cases often represent a topic that rests on the fringes of prior investigations because the case may provide new ways of understanding the research problem. For example, if the research problem is to identify strategies to improve policies that support girl's access to secondary education in predominantly Muslim nations, you could consider using Azerbaijan as a case study rather than selecting a more obvious nation in the Middle East. Doing so may reveal important new insights into recommending how governments in other predominantly Muslim nations can formulate policies that support improved access to education for girls.
• The case provides important insight or illuminate a previously hidden problem? In-depth analysis of a case can be based on the hypothesis that the case study will reveal trends or issues that have not been exposed in prior research or will reveal new and important implications for practice. For example, anecdotal evidence may suggest drug use among homeless veterans is related to their patterns of travel throughout the day. Assuming prior studies have not looked at individual travel choices as a way to study access to illicit drug use, a case study that observes a homeless veteran could reveal how issues of personal mobility choices facilitate regular access to illicit drugs. Note that it is important to conduct a thorough literature review to ensure that your assumption about the need to reveal new insights or previously hidden problems is valid and evidence-based.
• The case challenges and offers a counter-point to prevailing assumptions? Over time, research on any given topic can fall into a trap of developing assumptions based on outdated studies that are still applied to new or changing conditions or the idea that something should simply be accepted as "common sense," even though the issue has not been thoroughly tested in current practice. A case study analysis may offer an opportunity to gather evidence that challenges prevailing assumptions about a research problem and provide a new set of recommendations applied to practice that have not been tested previously. For example, perhaps there has been a long practice among scholars to apply a particular theory in explaining the relationship between two subjects of analysis. Your case could challenge this assumption by applying an innovative theoretical framework [perhaps borrowed from another discipline] to explore whether this approach offers new ways of understanding the research problem. Taking a contrarian stance is one of the most important ways that new knowledge and understanding develops from existing literature.
• The case provides an opportunity to pursue action leading to the resolution of a problem? Another way to think about choosing a case to study is to consider how the results from investigating a particular case may result in findings that reveal ways in which to resolve an existing or emerging problem. For example, studying the case of an unforeseen incident, such as a fatal accident at a railroad crossing, can reveal hidden issues that could be applied to preventative measures that contribute to reducing the chance of accidents in the future. In this example, a case study investigating the accident could lead to a better understanding of where to strategically locate additional signals at other railroad crossings so as to better warn drivers of an approaching train, particularly when visibility is hindered by heavy rain, fog, or at night.
• The case offers a new direction in future research? A case study can be used as a tool for an exploratory investigation that highlights the need for further research about the problem. A case can be used when there are few studies that help predict an outcome or that establish a clear understanding about how best to proceed in addressing a problem. For example, after conducting a thorough literature review [very important!], you discover that little research exists showing the ways in which women contribute to promoting water conservation in rural communities of east central Africa. A case study of how women contribute to saving water in a rural village of Uganda can lay the foundation for understanding the need for more thorough research that documents how women in their roles as cooks and family caregivers think about water as a valuable resource within their community. This example of a case study could also point to the need for scholars to build new theoretical frameworks around the topic [e.g., applying feminist theories of work and family to the issue of water conservation].

Eisenhardt, Kathleen M. “Building Theories from Case Study Research.” Academy of Management Review 14 (October 1989): 532-550; Emmel, Nick. Sampling and Choosing Cases in Qualitative Research: A Realist Approach . Thousand Oaks, CA: SAGE Publications, 2013; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Seawright, Jason and John Gerring. "Case Selection Techniques in Case Study Research." Political Research Quarterly 61 (June 2008): 294-308.

Structure and Writing Style

The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case studies may also be used to reveal best practices, highlight key programs, or investigate interesting aspects of professional work.

In general, the structure of a case study research paper is not all that different from a standard college-level research paper. However, there are subtle differences you should be aware of. Here are the key elements to organizing and writing a case study research paper.

I.  Introduction

As with any research paper, your introduction should serve as a roadmap for your readers to ascertain the scope and purpose of your study . The introduction to a case study research paper, however, should not only describe the research problem and its significance, but you should also succinctly describe why the case is being used and how it relates to addressing the problem. The two elements should be linked. With this in mind, a good introduction answers these four questions:

• What is being studied? Describe the research problem and describe the subject of analysis [the case] you have chosen to address the problem. Explain how they are linked and what elements of the case will help to expand knowledge and understanding about the problem.
• Why is this topic important to investigate? Describe the significance of the research problem and state why a case study design and the subject of analysis that the paper is designed around is appropriate in addressing the problem.
• What did we know about this topic before I did this study? Provide background that helps lead the reader into the more in-depth literature review to follow. If applicable, summarize prior case study research applied to the research problem and why it fails to adequately address the problem. Describe why your case will be useful. If no prior case studies have been used to address the research problem, explain why you have selected this subject of analysis.
• How will this study advance new knowledge or new ways of understanding? Explain why your case study will be suitable in helping to expand knowledge and understanding about the research problem.

Each of these questions should be addressed in no more than a few paragraphs. Exceptions to this can be when you are addressing a complex research problem or subject of analysis that requires more in-depth background information.

II.  Literature Review

The literature review for a case study research paper is generally structured the same as it is for any college-level research paper. The difference, however, is that the literature review is focused on providing background information and  enabling historical interpretation of the subject of analysis in relation to the research problem the case is intended to address . This includes synthesizing studies that help to:

• Place relevant works in the context of their contribution to understanding the case study being investigated . This would involve summarizing studies that have used a similar subject of analysis to investigate the research problem. If there is literature using the same or a very similar case to study, you need to explain why duplicating past research is important [e.g., conditions have changed; prior studies were conducted long ago, etc.].
• Describe the relationship each work has to the others under consideration that informs the reader why this case is applicable . Your literature review should include a description of any works that support using the case to investigate the research problem and the underlying research questions.
• Identify new ways to interpret prior research using the case study . If applicable, review any research that has examined the research problem using a different research design. Explain how your use of a case study design may reveal new knowledge or a new perspective or that can redirect research in an important new direction.
• Resolve conflicts amongst seemingly contradictory previous studies . This refers to synthesizing any literature that points to unresolved issues of concern about the research problem and describing how the subject of analysis that forms the case study can help resolve these existing contradictions.
• Point the way in fulfilling a need for additional research . Your review should examine any literature that lays a foundation for understanding why your case study design and the subject of analysis around which you have designed your study may reveal a new way of approaching the research problem or offer a perspective that points to the need for additional research.
• Expose any gaps that exist in the literature that the case study could help to fill . Summarize any literature that not only shows how your subject of analysis contributes to understanding the research problem, but how your case contributes to a new way of understanding the problem that prior research has failed to do.
• Locate your own research within the context of existing literature [very important!] . Collectively, your literature review should always place your case study within the larger domain of prior research about the problem. The overarching purpose of reviewing pertinent literature in a case study paper is to demonstrate that you have thoroughly identified and synthesized prior studies in relation to explaining the relevance of the case in addressing the research problem.

III.  Method

In this section, you explain why you selected a particular case [i.e., subject of analysis] and the strategy you used to identify and ultimately decide that your case was appropriate in addressing the research problem. The way you describe the methods used varies depending on the type of subject of analysis that constitutes your case study.

If your subject of analysis is an incident or event . In the social and behavioral sciences, the event or incident that represents the case to be studied is usually bounded by time and place, with a clear beginning and end and with an identifiable location or position relative to its surroundings. The subject of analysis can be a rare or critical event or it can focus on a typical or regular event. The purpose of studying a rare event is to illuminate new ways of thinking about the broader research problem or to test a hypothesis. Critical incident case studies must describe the method by which you identified the event and explain the process by which you determined the validity of this case to inform broader perspectives about the research problem or to reveal new findings. However, the event does not have to be a rare or uniquely significant to support new thinking about the research problem or to challenge an existing hypothesis. For example, Walo, Bull, and Breen conducted a case study to identify and evaluate the direct and indirect economic benefits and costs of a local sports event in the City of Lismore, New South Wales, Australia. The purpose of their study was to provide new insights from measuring the impact of a typical local sports event that prior studies could not measure well because they focused on large "mega-events." Whether the event is rare or not, the methods section should include an explanation of the following characteristics of the event: a) when did it take place; b) what were the underlying circumstances leading to the event; and, c) what were the consequences of the event in relation to the research problem.

If your subject of analysis is a person. Explain why you selected this particular individual to be studied and describe what experiences they have had that provide an opportunity to advance new understandings about the research problem. Mention any background about this person which might help the reader understand the significance of their experiences that make them worthy of study. This includes describing the relationships this person has had with other people, institutions, and/or events that support using them as the subject for a case study research paper. It is particularly important to differentiate the person as the subject of analysis from others and to succinctly explain how the person relates to examining the research problem [e.g., why is one politician in a particular local election used to show an increase in voter turnout from any other candidate running in the election]. Note that these issues apply to a specific group of people used as a case study unit of analysis [e.g., a classroom of students].

If your subject of analysis is a place. In general, a case study that investigates a place suggests a subject of analysis that is unique or special in some way and that this uniqueness can be used to build new understanding or knowledge about the research problem. A case study of a place must not only describe its various attributes relevant to the research problem [e.g., physical, social, historical, cultural, economic, political], but you must state the method by which you determined that this place will illuminate new understandings about the research problem. It is also important to articulate why a particular place as the case for study is being used if similar places also exist [i.e., if you are studying patterns of homeless encampments of veterans in open spaces, explain why you are studying Echo Park in Los Angeles rather than Griffith Park?]. If applicable, describe what type of human activity involving this place makes it a good choice to study [e.g., prior research suggests Echo Park has more homeless veterans].

If your subject of analysis is a phenomenon. A phenomenon refers to a fact, occurrence, or circumstance that can be studied or observed but with the cause or explanation to be in question. In this sense, a phenomenon that forms your subject of analysis can encompass anything that can be observed or presumed to exist but is not fully understood. In the social and behavioral sciences, the case usually focuses on human interaction within a complex physical, social, economic, cultural, or political system. For example, the phenomenon could be the observation that many vehicles used by ISIS fighters are small trucks with English language advertisements on them. The research problem could be that ISIS fighters are difficult to combat because they are highly mobile. The research questions could be how and by what means are these vehicles used by ISIS being supplied to the militants and how might supply lines to these vehicles be cut off? How might knowing the suppliers of these trucks reveal larger networks of collaborators and financial support? A case study of a phenomenon most often encompasses an in-depth analysis of a cause and effect that is grounded in an interactive relationship between people and their environment in some way.

NOTE:   The choice of the case or set of cases to study cannot appear random. Evidence that supports the method by which you identified and chose your subject of analysis should clearly support investigation of the research problem and linked to key findings from your literature review. Be sure to cite any studies that helped you determine that the case you chose was appropriate for examining the problem.

IV.  Discussion

The main elements of your discussion section are generally the same as any research paper, but centered around interpreting and drawing conclusions about the key findings from your analysis of the case study. Note that a general social sciences research paper may contain a separate section to report findings. However, in a paper designed around a case study, it is common to combine a description of the results with the discussion about their implications. The objectives of your discussion section should include the following:

Reiterate the Research Problem/State the Major Findings Briefly reiterate the research problem you are investigating and explain why the subject of analysis around which you designed the case study were used. You should then describe the findings revealed from your study of the case using direct, declarative, and succinct proclamation of the study results. Highlight any findings that were unexpected or especially profound.

Explain the Meaning of the Findings and Why They are Important Systematically explain the meaning of your case study findings and why you believe they are important. Begin this part of the section by repeating what you consider to be your most important or surprising finding first, then systematically review each finding. Be sure to thoroughly extrapolate what your analysis of the case can tell the reader about situations or conditions beyond the actual case that was studied while, at the same time, being careful not to misconstrue or conflate a finding that undermines the external validity of your conclusions.

Relate the Findings to Similar Studies No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your case study results to those found in other studies, particularly if questions raised from prior studies served as the motivation for choosing your subject of analysis. This is important because comparing and contrasting the findings of other studies helps support the overall importance of your results and it highlights how and in what ways your case study design and the subject of analysis differs from prior research about the topic.

Consider Alternative Explanations of the Findings Remember that the purpose of social science research is to discover and not to prove. When writing the discussion section, you should carefully consider all possible explanations revealed by the case study results, rather than just those that fit your hypothesis or prior assumptions and biases. Be alert to what the in-depth analysis of the case may reveal about the research problem, including offering a contrarian perspective to what scholars have stated in prior research if that is how the findings can be interpreted from your case.

Acknowledge the Study's Limitations You can state the study's limitations in the conclusion section of your paper but describing the limitations of your subject of analysis in the discussion section provides an opportunity to identify the limitations and explain why they are not significant. This part of the discussion section should also note any unanswered questions or issues your case study could not address. More detailed information about how to document any limitations to your research can be found here .

Suggest Areas for Further Research Although your case study may offer important insights about the research problem, there are likely additional questions related to the problem that remain unanswered or findings that unexpectedly revealed themselves as a result of your in-depth analysis of the case. Be sure that the recommendations for further research are linked to the research problem and that you explain why your recommendations are valid in other contexts and based on the original assumptions of your study.

V.  Conclusion

As with any research paper, you should summarize your conclusion in clear, simple language; emphasize how the findings from your case study differs from or supports prior research and why. Do not simply reiterate the discussion section. Provide a synthesis of key findings presented in the paper to show how these converge to address the research problem. If you haven't already done so in the discussion section, be sure to document the limitations of your case study and any need for further research.

The function of your paper's conclusion is to: 1) reiterate the main argument supported by the findings from your case study; 2) state clearly the context, background, and necessity of pursuing the research problem using a case study design in relation to an issue, controversy, or a gap found from reviewing the literature; and, 3) provide a place to persuasively and succinctly restate the significance of your research problem, given that the reader has now been presented with in-depth information about the topic.

Consider the following points to help ensure your conclusion is appropriate:

• If the argument or purpose of your paper is complex, you may need to summarize these points for your reader.
• If prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the conclusion of your paper to describe your main points and explain their significance.
• Move from a detailed to a general level of consideration of the case study's findings that returns the topic to the context provided by the introduction or within a new context that emerges from your case study findings.

Note that, depending on the discipline you are writing in or the preferences of your professor, the concluding paragraph may contain your final reflections on the evidence presented as it applies to practice or on the essay's central research problem. However, the nature of being introspective about the subject of analysis you have investigated will depend on whether you are explicitly asked to express your observations in this way.

Problems to Avoid

Overgeneralization One of the goals of a case study is to lay a foundation for understanding broader trends and issues applied to similar circumstances. However, be careful when drawing conclusions from your case study. They must be evidence-based and grounded in the results of the study; otherwise, it is merely speculation. Looking at a prior example, it would be incorrect to state that a factor in improving girls access to education in Azerbaijan and the policy implications this may have for improving access in other Muslim nations is due to girls access to social media if there is no documentary evidence from your case study to indicate this. There may be anecdotal evidence that retention rates were better for girls who were engaged with social media, but this observation would only point to the need for further research and would not be a definitive finding if this was not a part of your original research agenda.

Failure to Document Limitations No case is going to reveal all that needs to be understood about a research problem. Therefore, just as you have to clearly state the limitations of a general research study , you must describe the specific limitations inherent in the subject of analysis. For example, the case of studying how women conceptualize the need for water conservation in a village in Uganda could have limited application in other cultural contexts or in areas where fresh water from rivers or lakes is plentiful and, therefore, conservation is understood more in terms of managing access rather than preserving access to a scarce resource.

Failure to Extrapolate All Possible Implications Just as you don't want to over-generalize from your case study findings, you also have to be thorough in the consideration of all possible outcomes or recommendations derived from your findings. If you do not, your reader may question the validity of your analysis, particularly if you failed to document an obvious outcome from your case study research. For example, in the case of studying the accident at the railroad crossing to evaluate where and what types of warning signals should be located, you failed to take into consideration speed limit signage as well as warning signals. When designing your case study, be sure you have thoroughly addressed all aspects of the problem and do not leave gaps in your analysis that leave the reader questioning the results.

Case Studies. Writing@CSU. Colorado State University; Gerring, John. Case Study Research: Principles and Practices . New York: Cambridge University Press, 2007; Merriam, Sharan B. Qualitative Research and Case Study Applications in Education . Rev. ed. San Francisco, CA: Jossey-Bass, 1998; Miller, Lisa L. “The Use of Case Studies in Law and Social Science Research.” Annual Review of Law and Social Science 14 (2018): TBD; Mills, Albert J., Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Putney, LeAnn Grogan. "Case Study." In Encyclopedia of Research Design , Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE Publications, 2010), pp. 116-120; Simons, Helen. Case Study Research in Practice . London: SAGE Publications, 2009;  Kratochwill,  Thomas R. and Joel R. Levin, editors. Single-Case Research Design and Analysis: New Development for Psychology and Education .  Hilldsale, NJ: Lawrence Erlbaum Associates, 1992; Swanborn, Peter G. Case Study Research: What, Why and How? London : SAGE, 2010; Yin, Robert K. Case Study Research: Design and Methods . 6th edition. Los Angeles, CA, SAGE Publications, 2014; Walo, Maree, Adrian Bull, and Helen Breen. “Achieving Economic Benefits at Local Events: A Case Study of a Local Sports Event.” Festival Management and Event Tourism 4 (1996): 95-106.

Writing Tip

At Least Five Misconceptions about Case Study Research

Social science case studies are often perceived as limited in their ability to create new knowledge because they are not randomly selected and findings cannot be generalized to larger populations. Flyvbjerg examines five misunderstandings about case study research and systematically "corrects" each one. To quote, these are:

Misunderstanding 1 :  General, theoretical [context-independent] knowledge is more valuable than concrete, practical [context-dependent] knowledge. Misunderstanding 2 :  One cannot generalize on the basis of an individual case; therefore, the case study cannot contribute to scientific development. Misunderstanding 3 :  The case study is most useful for generating hypotheses; that is, in the first stage of a total research process, whereas other methods are more suitable for hypotheses testing and theory building. Misunderstanding 4 :  The case study contains a bias toward verification, that is, a tendency to confirm the researcher’s preconceived notions. Misunderstanding 5 :  It is often difficult to summarize and develop general propositions and theories on the basis of specific case studies [p. 221].

While writing your paper, think introspectively about how you addressed these misconceptions because to do so can help you strengthen the validity and reliability of your research by clarifying issues of case selection, the testing and challenging of existing assumptions, the interpretation of key findings, and the summation of case outcomes. Think of a case study research paper as a complete, in-depth narrative about the specific properties and key characteristics of your subject of analysis applied to the research problem.

Flyvbjerg, Bent. “Five Misunderstandings About Case-Study Research.” Qualitative Inquiry 12 (April 2006): 219-245.

• << Previous: Writing a Case Analysis Paper
• Next: Writing a Field Report >>
• Last Updated: Mar 6, 2024 1:00 PM
• URL: https://libguides.usc.edu/writingguide/assignments

• Bipolar Disorder
• Therapy Center
• When To See a Therapist
• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Guided Meditations
• Verywell Mind Insights
• 2023 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

What Is a Case Study?

Weighing the pros and cons of this method of research

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Cara Lustik is a fact-checker and copywriter.

Verywell / Colleen Tighe

• Pros and Cons

What Types of Case Studies Are Out There?

Where do you find data for a case study, how do i write a psychology case study.

A case study is an in-depth study of one person, group, or event. In a case study, nearly every aspect of the subject's life and history is analyzed to seek patterns and causes of behavior. Case studies can be used in many different fields, including psychology, medicine, education, anthropology, political science, and social work.

The point of a case study is to learn as much as possible about an individual or group so that the information can be generalized to many others. Unfortunately, case studies tend to be highly subjective, and it is sometimes difficult to generalize results to a larger population.

While case studies focus on a single individual or group, they follow a format similar to other types of psychology writing. If you are writing a case study, we got you—here are some rules of APA format to reference.  

At a Glance

A case study, or an in-depth study of a person, group, or event, can be a useful research tool when used wisely. In many cases, case studies are best used in situations where it would be difficult or impossible for you to conduct an experiment. They are helpful for looking at unique situations and allow researchers to gather a lot of˜ information about a specific individual or group of people. However, it's important to be cautious of any bias we draw from them as they are highly subjective.

What Are the Benefits and Limitations of Case Studies?

A case study can have its strengths and weaknesses. Researchers must consider these pros and cons before deciding if this type of study is appropriate for their needs.

One of the greatest advantages of a case study is that it allows researchers to investigate things that are often difficult or impossible to replicate in a lab. Some other benefits of a case study:

• Allows researchers to capture information on the 'how,' 'what,' and 'why,' of something that's implemented
• Gives researchers the chance to collect information on why one strategy might be chosen over another
• Permits researchers to develop hypotheses that can be explored in experimental research

On the other hand, a case study can have some drawbacks:

• It cannot necessarily be generalized to the larger population
• Cannot demonstrate cause and effect
• It may not be scientifically rigorous
• It can lead to bias

Researchers may choose to perform a case study if they want to explore a unique or recently discovered phenomenon. Through their insights, researchers develop additional ideas and study questions that might be explored in future studies.

It's important to remember that the insights from case studies cannot be used to determine cause-and-effect relationships between variables. However, case studies may be used to develop hypotheses that can then be addressed in experimental research.

Case Study Examples

There have been a number of notable case studies in the history of psychology. Much of  Freud's work and theories were developed through individual case studies. Some great examples of case studies in psychology include:

• Anna O : Anna O. was a pseudonym of a woman named Bertha Pappenheim, a patient of a physician named Josef Breuer. While she was never a patient of Freud's, Freud and Breuer discussed her case extensively. The woman was experiencing symptoms of a condition that was then known as hysteria and found that talking about her problems helped relieve her symptoms. Her case played an important part in the development of talk therapy as an approach to mental health treatment.
• Phineas Gage : Phineas Gage was a railroad employee who experienced a terrible accident in which an explosion sent a metal rod through his skull, damaging important portions of his brain. Gage recovered from his accident but was left with serious changes in both personality and behavior.
• Genie : Genie was a young girl subjected to horrific abuse and isolation. The case study of Genie allowed researchers to study whether language learning was possible, even after missing critical periods for language development. Her case also served as an example of how scientific research may interfere with treatment and lead to further abuse of vulnerable individuals.

Such cases demonstrate how case research can be used to study things that researchers could not replicate in experimental settings. In Genie's case, her horrific abuse denied her the opportunity to learn a language at critical points in her development.

This is clearly not something researchers could ethically replicate, but conducting a case study on Genie allowed researchers to study phenomena that are otherwise impossible to reproduce.

There are a few different types of case studies that psychologists and other researchers might use:

• Collective case studies : These involve studying a group of individuals. Researchers might study a group of people in a certain setting or look at an entire community. For example, psychologists might explore how access to resources in a community has affected the collective mental well-being of those who live there.
• Descriptive case studies : These involve starting with a descriptive theory. The subjects are then observed, and the information gathered is compared to the pre-existing theory.
• Explanatory case studies : These   are often used to do causal investigations. In other words, researchers are interested in looking at factors that may have caused certain things to occur.
• Exploratory case studies : These are sometimes used as a prelude to further, more in-depth research. This allows researchers to gather more information before developing their research questions and hypotheses .
• Instrumental case studies : These occur when the individual or group allows researchers to understand more than what is initially obvious to observers.
• Intrinsic case studies : This type of case study is when the researcher has a personal interest in the case. Jean Piaget's observations of his own children are good examples of how an intrinsic case study can contribute to the development of a psychological theory.

The three main case study types often used are intrinsic, instrumental, and collective. Intrinsic case studies are useful for learning about unique cases. Instrumental case studies help look at an individual to learn more about a broader issue. A collective case study can be useful for looking at several cases simultaneously.

The type of case study that psychology researchers use depends on the unique characteristics of the situation and the case itself.

There are a number of different sources and methods that researchers can use to gather information about an individual or group. Six major sources that have been identified by researchers are:

• Archival records : Census records, survey records, and name lists are examples of archival records.
• Direct observation : This strategy involves observing the subject, often in a natural setting . While an individual observer is sometimes used, it is more common to utilize a group of observers.
• Documents : Letters, newspaper articles, administrative records, etc., are the types of documents often used as sources.
• Interviews : Interviews are one of the most important methods for gathering information in case studies. An interview can involve structured survey questions or more open-ended questions.
• Participant observation : When the researcher serves as a participant in events and observes the actions and outcomes, it is called participant observation.
• Physical artifacts : Tools, objects, instruments, and other artifacts are often observed during a direct observation of the subject.

If you have been directed to write a case study for a psychology course, be sure to check with your instructor for any specific guidelines you need to follow. If you are writing your case study for a professional publication, check with the publisher for their specific guidelines for submitting a case study.

Here is a general outline of what should be included in a case study.

Section 1: A Case History

This section will have the following structure and content:

Background information : The first section of your paper will present your client's background. Include factors such as age, gender, work, health status, family mental health history, family and social relationships, drug and alcohol history, life difficulties, goals, and coping skills and weaknesses.

Description of the presenting problem : In the next section of your case study, you will describe the problem or symptoms that the client presented with.

Describe any physical, emotional, or sensory symptoms reported by the client. Thoughts, feelings, and perceptions related to the symptoms should also be noted. Any screening or diagnostic assessments that are used should also be described in detail and all scores reported.

Your diagnosis : Provide your diagnosis and give the appropriate Diagnostic and Statistical Manual code. Explain how you reached your diagnosis, how the client's symptoms fit the diagnostic criteria for the disorder(s), or any possible difficulties in reaching a diagnosis.

Section 2: Treatment Plan

This portion of the paper will address the chosen treatment for the condition. This might also include the theoretical basis for the chosen treatment or any other evidence that might exist to support why this approach was chosen.

• Cognitive behavioral approach : Explain how a cognitive behavioral therapist would approach treatment. Offer background information on cognitive behavioral therapy and describe the treatment sessions, client response, and outcome of this type of treatment. Make note of any difficulties or successes encountered by your client during treatment.
• Humanistic approach : Describe a humanistic approach that could be used to treat your client, such as client-centered therapy . Provide information on the type of treatment you chose, the client's reaction to the treatment, and the end result of this approach. Explain why the treatment was successful or unsuccessful.
• Psychoanalytic approach : Describe how a psychoanalytic therapist would view the client's problem. Provide some background on the psychoanalytic approach and cite relevant references. Explain how psychoanalytic therapy would be used to treat the client, how the client would respond to therapy, and the effectiveness of this treatment approach.
• Pharmacological approach : If treatment primarily involves the use of medications, explain which medications were used and why. Provide background on the effectiveness of these medications and how monotherapy may compare with an approach that combines medications with therapy or other treatments.

This section of a case study should also include information about the treatment goals, process, and outcomes.

When you are writing a case study, you should also include a section where you discuss the case study itself, including the strengths and limitiations of the study. You should note how the findings of your case study might support previous research. 

In your discussion section, you should also describe some of the implications of your case study. What ideas or findings might require further exploration? How might researchers go about exploring some of these questions in additional studies?

Need More Tips?

Here are a few additional pointers to keep in mind when formatting your case study:

• Never refer to the subject of your case study as "the client." Instead, use their name or a pseudonym.
• Read examples of case studies to gain an idea about the style and format.
• Remember to use APA format when citing references .

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach .  BMC Med Res Methodol . 2011;11:100.

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach . BMC Med Res Methodol . 2011 Jun 27;11:100. doi:10.1186/1471-2288-11-100

Gagnon, Yves-Chantal.  The Case Study as Research Method: A Practical Handbook . Canada, Chicago Review Press Incorporated DBA Independent Pub Group, 2010.

Yin, Robert K. Case Study Research and Applications: Design and Methods . United States, SAGE Publications, 2017.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

• Subject List
• Take a Tour
• For Authors
• Subscriber Services
• Publications
• African American Studies
• African Studies
• American Literature
• Anthropology
• Architecture Planning and Preservation
• Art History
• Atlantic History
• Biblical Studies
• British and Irish Literature
• Childhood Studies
• Chinese Studies
• Cinema and Media Studies
• Communication
• Criminology
• Environmental Science
• Evolutionary Biology
• International Law
• International Relations
• Islamic Studies
• Jewish Studies
• Latin American Studies
• Latino Studies
• Linguistics
• Literary and Critical Theory
• Medieval Studies
• Military History
• Political Science
• Public Health
• Renaissance and Reformation
• Social Work
• Urban Studies
• Victorian Literature
• Browse All Subjects

How to Subscribe

• Free Trials

In This Article Expand or collapse the "in this article" section Single-Case Experimental Designs

Introduction, general overviews and primary textbooks.

• Textbooks in Applied Behavior Analysis
• Types of Single-Case Experimental Designs
• Model Building and Randomization in Single-Case Experimental Designs
• Visual Analysis of Single-Case Experimental Designs
• Effect Size Estimates in Single-Case Experimental Designs
• Reporting Single-Case Design Intervention Research

Related Articles Expand or collapse the "related articles" section about

About related articles close popup.

Lorem Ipsum Sit Dolor Amet

Vestibulum ante ipsum primis in faucibus orci luctus et ultrices posuere cubilia Curae; Aliquam ligula odio, euismod ut aliquam et, vestibulum nec risus. Nulla viverra, arcu et iaculis consequat, justo diam ornare tellus, semper ultrices tellus nunc eu tellus.

• Action Research
• Ambulatory Assessment in Behavioral Science
• Effect Size
• Mediation Analysis
• Path Models
• Research Methods for Studying Daily Life

Other Subject Areas

Forthcoming articles expand or collapse the "forthcoming articles" section.

• Data Visualization
• Remote Work
• Workforce Training Evaluation
• Find more forthcoming articles...
• Export Citations
• Share This Facebook LinkedIn Twitter

Single-Case Experimental Designs by S. Andrew Garbacz , Thomas R. Kratochwill LAST MODIFIED: 29 July 2020 DOI: 10.1093/obo/9780199828340-0265

Single-case experimental designs are a family of experimental designs that are characterized by researcher manipulation of an independent variable and repeated measurement of a dependent variable before (i.e., baseline) and after (i.e., intervention phase) introducing the independent variable. In single-case experimental designs a case is the unit of intervention and analysis (e.g., a child, a school). Because measurement within each case is conducted before and after manipulation of the independent variable, the case typically serves as its own control. Experimental variants of single-case designs provide a basis for determining a causal relation by replication of the intervention through (a) introducing and withdrawing the independent variable, (b) manipulating the independent variable across different phases, and (c) introducing the independent variable in a staggered fashion across different points in time. Due to their economy of resources, single-case designs may be useful during development activities and allow for rapid replication across studies.

Several sources provide overviews of single-case experimental designs. Barlow, et al. 2009 includes an overview for the development of single-case experimental designs, describes key considerations for designing and conducting single-case experimental design research, and reviews procedural elements, assessment strategies, and replication considerations. Kazdin 2011 provides detailed coverage of single-case experimental design variants as well as approaches for evaluating data in single-case experimental designs. Kratochwill and Levin 2014 describes key methodological features that underlie single-case experimental designs, including philosophical and statistical foundations and data evaluation. Ledford and Gast 2018 covers research conceptualization and writing, design variants within single-case experimental design, definitions of variables and associated measurement, and approaches to organize and evaluate data. Riley-Tillman and Burns 2009 provides a practical orientation to single-case experimental designs to facilitate uptake and use in applied settings.

Barlow, D. H., M. K. Nock, and M. Hersen, eds. 2009. Single case experimental designs: Strategies for studying behavior change . 3d ed. New York: Pearson.

A comprehensive reference about the process of designing and conducting single-case experimental design studies. Chapters are integrative but can stand alone.

Kazdin, A. E. 2011. Single-case research designs: Methods for clinical and applied settings . 2d ed. New York: Oxford Univ. Press.

A complete overview and description of single-case experimental design variants as well as information about data evaluation.

Kratochwill, T. R., and J. R. Levin, eds. 2014. Single-case intervention research: Methodological and statistical advances . New York: Routledge.

The authors describe in depth the methodological and analytic considerations necessary for designing and conducting research that uses a single-case experimental design. In addition, the text includes chapters from leaders in psychology and education who provide critical perspectives about the use of single-case experimental designs.

Ledford, J. R., and D. L. Gast, eds. 2018. Single case research methodology: Applications in special education and behavioral sciences . New York: Routledge.

Covers the research process from writing literature reviews, to designing, conducting, and evaluating single-case experimental design studies.

Riley-Tillman, T. C., and M. K. Burns. 2009. Evaluating education interventions: Single-case design for measuring response to intervention . New York: Guilford Press.

Focuses on accelerating uptake and use of single-case experimental designs in applied settings. This book provides a practical, “nuts and bolts” orientation to conducting single-case experimental design research.

back to top

Users without a subscription are not able to see the full content on this page. Please subscribe or login .

Oxford Bibliographies Online is available by subscription and perpetual access to institutions. For more information or to contact an Oxford Sales Representative click here .

• About Psychology »
• Meet the Editorial Board »
• Abnormal Psychology
• Academic Assessment
• Acculturation and Health
• Action Regulation Theory
• Addictive Behavior
• Adolescence
• Adoption, Social, Psychological, and Evolutionary Perspect...
• Advanced Theory of Mind
• Affective Forecasting
• Affirmative Action
• Ageism at Work
• Allport, Gordon
• Alzheimer’s Disease
• Analysis of Covariance (ANCOVA)
• Animal Behavior
• Animal Learning
• Anxiety Disorders
• Art and Aesthetics, Psychology of
• Artificial Intelligence, Machine Learning, and Psychology
• Assessment and Clinical Applications of Individual Differe...
• Attachment in Social and Emotional Development across the ...
• Attention-Deficit/Hyperactivity Disorder (ADHD) in Adults
• Attention-Deficit/Hyperactivity Disorder (ADHD) in Childre...
• Attitudinal Ambivalence
• Attraction in Close Relationships
• Attribution Theory
• Authoritarian Personality
• Bayesian Statistical Methods in Psychology
• Behavior Therapy, Rational Emotive
• Behavioral Economics
• Behavioral Genetics
• Belief Perseverance
• Bereavement and Grief
• Biological Psychology
• Birth Order
• Body Image in Men and Women
• Bystander Effect
• Categorical Data Analysis in Psychology
• Childhood and Adolescence, Peer Victimization and Bullying...
• Clark, Mamie Phipps
• Clinical Neuropsychology
• Clinical Psychology
• Cognitive Consistency Theories
• Cognitive Dissonance Theory
• Cognitive Neuroscience
• Communication, Nonverbal Cues and
• Comparative Psychology
• Competence to Stand Trial: Restoration Services
• Competency to Stand Trial
• Computational Psychology
• Conflict Management in the Workplace
• Conformity, Compliance, and Obedience
• Consciousness
• Coping Processes
• Correspondence Analysis in Psychology
• Counseling Psychology
• Creativity at Work
• Critical Thinking
• Cross-Cultural Psychology
• Cultural Psychology
• Daily Life, Research Methods for Studying
• Data Science Methods for Psychology
• Data Sharing in Psychology
• Death and Dying
• Deceiving and Detecting Deceit
• Defensive Processes
• Depressive Disorders
• Development, Prenatal
• Developmental Psychology (Cognitive)
• Developmental Psychology (Social)
• Diagnostic and Statistical Manual of Mental Disorders (DSM...
• Discrimination
• Dissociative Disorders
• Drugs and Behavior
• Eating Disorders
• Ecological Psychology
• Educational Settings, Assessment of Thinking in
• Embodiment and Embodied Cognition
• Emerging Adulthood
• Emotional Intelligence
• Empathy and Altruism
• Employee Stress and Well-Being
• Environmental Neuroscience and Environmental Psychology
• Ethics in Psychological Practice
• Event Perception
• Evolutionary Psychology
• Expansive Posture
• Experimental Existential Psychology
• Exploratory Data Analysis
• Eyewitness Testimony
• Eysenck, Hans
• Factor Analysis
• Festinger, Leon
• Five-Factor Model of Personality
• Flynn Effect, The
• Forensic Psychology
• Forgiveness
• Friendships, Children's
• Fundamental Attribution Error/Correspondence Bias
• Gambler's Fallacy
• Game Theory and Psychology
• Geropsychology, Clinical
• Global Mental Health
• Habit Formation and Behavior Change
• Health Psychology
• Health Psychology Research and Practice, Measurement in
• Heider, Fritz
• Heuristics and Biases
• History of Psychology
• Human Factors
• Humanistic Psychology
• Implicit Association Test (IAT)
• Industrial and Organizational Psychology
• Inferential Statistics in Psychology
• Insanity Defense, The
• Intelligence
• Intelligence, Crystallized and Fluid
• Intercultural Psychology
• Intergroup Conflict
• International Classification of Diseases and Related Healt...
• International Psychology
• Interviewing in Forensic Settings
• Intimate Partner Violence, Psychological Perspectives on
• Introversion–Extraversion
• Item Response Theory
• Law, Psychology and
• Lazarus, Richard
• Learned Helplessness
• Learning Theory
• Learning versus Performance
• LGBTQ+ Romantic Relationships
• Lie Detection in a Forensic Context
• Life-Span Development
• Locus of Control
• Loneliness and Health
• Mathematical Psychology
• Meaning in Life
• Mechanisms and Processes of Peer Contagion
• Media Violence, Psychological Perspectives on
• Memories, Autobiographical
• Memories, Flashbulb
• Memories, Repressed and Recovered
• Memory, False
• Memory, Human
• Memory, Implicit versus Explicit
• Memory in Educational Settings
• Memory, Semantic
• Meta-Analysis
• Metacognition
• Metaphor, Psychological Perspectives on
• Microaggressions
• Military Psychology
• Mindfulness
• Mindfulness and Education
• Minnesota Multiphasic Personality Inventory (MMPI)
• Money, Psychology of
• Moral Conviction
• Moral Development
• Moral Psychology
• Moral Reasoning
• Nature versus Nurture Debate in Psychology
• Neuroscience of Associative Learning
• Nonergodicity in Psychology and Neuroscience
• Nonparametric Statistical Analysis in Psychology
• Observational (Non-Randomized) Studies
• Obsessive-Complusive Disorder (OCD)
• Occupational Health Psychology
• Olfaction, Human
• Operant Conditioning
• Optimism and Pessimism
• Organizational Justice
• Parenting Stress
• Parenting Styles
• Parents' Beliefs about Children
• Peace Psychology
• Perception, Person
• Performance Appraisal
• Personality and Health
• Personality Disorders
• Personality Psychology
• Phenomenological Psychology
• Placebo Effects in Psychology
• Play Behavior
• Positive Psychological Capital (PsyCap)
• Positive Psychology
• Posttraumatic Stress Disorder (PTSD)
• Prejudice and Stereotyping
• Pretrial Publicity
• Prisoner's Dilemma
• Problem Solving and Decision Making
• Procrastination
• Prosocial Behavior
• Prosocial Spending and Well-Being
• Protocol Analysis
• Psycholinguistics
• Psychological Literacy
• Psychological Perspectives on Food and Eating
• Psychology, Political
• Psychoneuroimmunology
• Psychophysics, Visual
• Psychotherapy
• Psychotic Disorders
• Publication Bias in Psychology
• Reasoning, Counterfactual
• Rehabilitation Psychology
• Relationships
• Reliability–Contemporary Psychometric Conceptions
• Religion, Psychology and
• Replication Initiatives in Psychology
• Research Methods
• Risk Taking
• Role of the Expert Witness in Forensic Psychology, The
• Sample Size Planning for Statistical Power and Accurate Es...
• Schizophrenic Disorders
• School Psychology
• School Psychology, Counseling Services in
• Self, Gender and
• Self, Psychology of the
• Self-Construal
• Self-Control
• Self-Deception
• Self-Determination Theory
• Self-Efficacy
• Self-Esteem
• Self-Monitoring
• Self-Regulation in Educational Settings
• Self-Report Tests, Measures, and Inventories in Clinical P...
• Sensation Seeking
• Sex and Gender
• Sexual Minority Parenting
• Sexual Orientation
• Signal Detection Theory and its Applications
• Simpson's Paradox in Psychology
• Single People
• Single-Case Experimental Designs
• Skinner, B.F.
• Sleep and Dreaming
• Small Groups
• Social Class and Social Status
• Social Cognition
• Social Neuroscience
• Social Support
• Social Touch and Massage Therapy Research
• Somatoform Disorders
• Spatial Attention
• Sports Psychology
• Stanford Prison Experiment (SPE): Icon and Controversy
• Stereotype Threat
• Stereotypes
• Stress and Coping, Psychology of
• Student Success in College
• Subjective Wellbeing Homeostasis
• Taste, Psychological Perspectives on
• Teaching of Psychology
• Terror Management Theory
• Testing and Assessment
• The Concept of Validity in Psychological Assessment
• The Neuroscience of Emotion Regulation
• The Reasoned Action Approach and the Theories of Reasoned ...
• The Weapon Focus Effect in Eyewitness Memory
• Theory of Mind
• Therapies, Person-Centered
• Therapy, Cognitive-Behavioral
• Thinking Skills in Educational Settings
• Time Perception
• Trait Perspective
• Trauma Psychology
• Twin Studies
• Type A Behavior Pattern (Coronary Prone Personality)
• Unconscious Processes
• Video Games and Violent Content
• Virtues and Character Strengths
• Women and Science, Technology, Engineering, and Math (STEM...
• Women, Psychology of
• Work Well-Being
• Wundt, Wilhelm
• Privacy Policy
• Cookie Policy
• Legal Notice
• Accessibility

Powered by:

• [66.249.64.20|81.177.182.174]
• 81.177.182.174

Case Study Research Method in Psychology

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

Case studies are in-depth investigations of a person, group, event, or community. Typically, data is gathered from various sources using several methods (e.g., observations & interviews).

The case study research method originated in clinical medicine (the case history, i.e., the patient’s personal history). In psychology, case studies are often confined to the study of a particular individual.

The information is mainly biographical and relates to events in the individual’s past (i.e., retrospective), as well as to significant events that are currently occurring in his or her everyday life.

The case study is not a research method, but researchers select methods of data collection and analysis that will generate material suitable for case studies.

Freud (1909a, 1909b) conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

This makes it clear that the case study is a method that should only be used by a psychologist, therapist, or psychiatrist, i.e., someone with a professional qualification.

There is an ethical issue of competence. Only someone qualified to diagnose and treat a person can conduct a formal case study relating to atypical (i.e., abnormal) behavior or atypical development.

 Famous Case Studies

• Anna O – One of the most famous case studies, documenting psychoanalyst Josef Breuer’s treatment of “Anna O” (real name Bertha Pappenheim) for hysteria in the late 1800s using early psychoanalytic theory.
• Little Hans – A child psychoanalysis case study published by Sigmund Freud in 1909 analyzing his five-year-old patient Herbert Graf’s house phobia as related to the Oedipus complex.
• Bruce/Brenda – Gender identity case of the boy (Bruce) whose botched circumcision led psychologist John Money to advise gender reassignment and raise him as a girl (Brenda) in the 1960s.
• Genie Wiley – Linguistics/psychological development case of the victim of extreme isolation abuse who was studied in 1970s California for effects of early language deprivation on acquiring speech later in life.
• Phineas Gage – One of the most famous neuropsychology case studies analyzes personality changes in railroad worker Phineas Gage after an 1848 brain injury involving a tamping iron piercing his skull.

Clinical Case Studies

• Studying the effectiveness of psychotherapy approaches with an individual patient
• Assessing and treating mental illnesses like depression, anxiety disorders, PTSD
• Neuropsychological cases investigating brain injuries or disorders

Child Psychology Case Studies

• Studying psychological development from birth through adolescence
• Cases of learning disabilities, autism spectrum disorders, ADHD
• Effects of trauma, abuse, deprivation on development

Types of Case Studies

• Explanatory case studies : Used to explore causation in order to find underlying principles. Helpful for doing qualitative analysis to explain presumed causal links.
• Exploratory case studies : Used to explore situations where an intervention being evaluated has no clear set of outcomes. It helps define questions and hypotheses for future research.
• Descriptive case studies : Describe an intervention or phenomenon and the real-life context in which it occurred. It is helpful for illustrating certain topics within an evaluation.
• Multiple-case studies : Used to explore differences between cases and replicate findings across cases. Helpful for comparing and contrasting specific cases.
• Intrinsic : Used to gain a better understanding of a particular case. Helpful for capturing the complexity of a single case.
• Collective : Used to explore a general phenomenon using multiple case studies. Helpful for jointly studying a group of cases in order to inquire into the phenomenon.

Where Do You Find Data for a Case Study?

There are several places to find data for a case study. The key is to gather data from multiple sources to get a complete picture of the case and corroborate facts or findings through triangulation of evidence. Most of this information is likely qualitative (i.e., verbal description rather than measurement), but the psychologist might also collect numerical data.

1. Primary sources

• Interviews – Interviewing key people related to the case to get their perspectives and insights. The interview is an extremely effective procedure for obtaining information about an individual, and it may be used to collect comments from the person’s friends, parents, employer, workmates, and others who have a good knowledge of the person, as well as to obtain facts from the person him or herself.
• Observations – Observing behaviors, interactions, processes, etc., related to the case as they unfold in real-time.
• Documents & Records – Reviewing private documents, diaries, public records, correspondence, meeting minutes, etc., relevant to the case.

2. Secondary sources

• News/Media – News coverage of events related to the case study.
• Academic articles – Journal articles, dissertations etc. that discuss the case.
• Government reports – Official data and records related to the case context.
• Books/films – Books, documentaries or films discussing the case.

3. Archival records

Searching historical archives, museum collections and databases to find relevant documents, visual/audio records related to the case history and context.

Public archives like newspapers, organizational records, photographic collections could all include potentially relevant pieces of information to shed light on attitudes, cultural perspectives, common practices and historical contexts related to psychology.

4. Organizational records

Organizational records offer the advantage of often having large datasets collected over time that can reveal or confirm psychological insights.

Of course, privacy and ethical concerns regarding confidential data must be navigated carefully.

However, with proper protocols, organizational records can provide invaluable context and empirical depth to qualitative case studies exploring the intersection of psychology and organizations.

• Organizational/industrial psychology research : Organizational records like employee surveys, turnover/retention data, policies, incident reports etc. may provide insight into topics like job satisfaction, workplace culture and dynamics, leadership issues, employee behaviors etc.
• Clinical psychology : Therapists/hospitals may grant access to anonymized medical records to study aspects like assessments, diagnoses, treatment plans etc. This could shed light on clinical practices.
• School psychology : Studies could utilize anonymized student records like test scores, grades, disciplinary issues, and counseling referrals to study child development, learning barriers, effectiveness of support programs, and more.

How do I Write a Case Study in Psychology?

Follow specified case study guidelines provided by a journal or your psychology tutor. General components of clinical case studies include: background, symptoms, assessments, diagnosis, treatment, and outcomes. Interpreting the information means the researcher decides what to include or leave out. A good case study should always clarify which information is the factual description and which is an inference or the researcher’s opinion.

1. Introduction

• Provide background on the case context and why it is of interest, presenting background information like demographics, relevant history, and presenting problem.
• Compare briefly to similar published cases if applicable. Clearly state the focus/importance of the case.

2. Case Presentation

• Describe the presenting problem in detail, including symptoms, duration,and impact on daily life.
• Include client demographics like age and gender, information about social relationships, and mental health history.
• Describe all physical, emotional, and/or sensory symptoms reported by the client.
• Use patient quotes to describe the initial complaint verbatim. Follow with full-sentence summaries of relevant history details gathered, including key components that led to a working diagnosis.
• Summarize clinical exam results, namely orthopedic/neurological tests, imaging, lab tests, etc. Note actual results rather than subjective conclusions. Provide images if clearly reproducible/anonymized.
• Clearly state the working diagnosis or clinical impression before transitioning to management.

3. Management and Outcome

• Indicate the total duration of care and number of treatments given over what timeframe. Use specific names/descriptions for any therapies/interventions applied.
• Present the results of the intervention,including any quantitative or qualitative data collected.
• For outcomes, utilize visual analog scales for pain, medication usage logs, etc., if possible. Include patient self-reports of improvement/worsening of symptoms. Note the reason for discharge/end of care.

4. Discussion

• Analyze the case, exploring contributing factors, limitations of the study, and connections to existing research.
• Analyze the effectiveness of the intervention,considering factors like participant adherence, limitations of the study, and potential alternative explanations for the results.
• Identify any questions raised in the case analysis and relate insights to established theories and current research if applicable. Avoid definitive claims about physiological explanations.
• Offer clinical implications, and suggest future research directions.

5. Additional Items

• Thank specific assistants for writing support only. No patient acknowledgments.
• References should directly support any key claims or quotes included.
• Use tables/figures/images only if substantially informative. Include permissions and legends/explanatory notes.
• Provides detailed (rich qualitative) information.
• Provides insight for further research.
• Permitting investigation of otherwise impractical (or unethical) situations.

Case studies allow a researcher to investigate a topic in far more detail than might be possible if they were trying to deal with a large number of research participants (nomothetic approach) with the aim of ‘averaging’.

Because of their in-depth, multi-sided approach, case studies often shed light on aspects of human thinking and behavior that would be unethical or impractical to study in other ways.

Research that only looks into the measurable aspects of human behavior is not likely to give us insights into the subjective dimension of experience, which is important to psychoanalytic and humanistic psychologists.

Case studies are often used in exploratory research. They can help us generate new ideas (that might be tested by other methods). They are an important way of illustrating theories and can help show how different aspects of a person’s life are related to each other.

The method is, therefore, important for psychologists who adopt a holistic point of view (i.e., humanistic psychologists ).

Limitations

• Lacking scientific rigor and providing little basis for generalization of results to the wider population.
• Researchers’ own subjective feelings may influence the case study (researcher bias).
• Difficult to replicate.
• Time-consuming and expensive.
• The volume of data, together with the time restrictions in place, impacted the depth of analysis that was possible within the available resources.

Because a case study deals with only one person/event/group, we can never be sure if the case study investigated is representative of the wider body of “similar” instances. This means the conclusions drawn from a particular case may not be transferable to other settings.

Because case studies are based on the analysis of qualitative (i.e., descriptive) data , a lot depends on the psychologist’s interpretation of the information she has acquired.

This means that there is a lot of scope for Anna O , and it could be that the subjective opinions of the psychologist intrude in the assessment of what the data means.

For example, Freud has been criticized for producing case studies in which the information was sometimes distorted to fit particular behavioral theories (e.g., Little Hans ).

This is also true of Money’s interpretation of the Bruce/Brenda case study (Diamond, 1997) when he ignored evidence that went against his theory.

Breuer, J., & Freud, S. (1895).  Studies on hysteria . Standard Edition 2: London.

Curtiss, S. (1981). Genie: The case of a modern wild child .

Diamond, M., & Sigmundson, K. (1997). Sex Reassignment at Birth: Long-term Review and Clinical Implications. Archives of Pediatrics & Adolescent Medicine , 151(3), 298-304

Freud, S. (1909a). Analysis of a phobia of a five year old boy. In The Pelican Freud Library (1977), Vol 8, Case Histories 1, pages 169-306

Freud, S. (1909b). Bemerkungen über einen Fall von Zwangsneurose (Der “Rattenmann”). Jb. psychoanal. psychopathol. Forsch ., I, p. 357-421; GW, VII, p. 379-463; Notes upon a case of obsessional neurosis, SE , 10: 151-318.

Harlow J. M. (1848). Passage of an iron rod through the head.  Boston Medical and Surgical Journal, 39 , 389–393.

Harlow, J. M. (1868).  Recovery from the Passage of an Iron Bar through the Head .  Publications of the Massachusetts Medical Society. 2  (3), 327-347.

Money, J., & Ehrhardt, A. A. (1972).  Man & Woman, Boy & Girl : The Differentiation and Dimorphism of Gender Identity from Conception to Maturity. Baltimore, Maryland: Johns Hopkins University Press.

Money, J., & Tucker, P. (1975). Sexual signatures: On being a man or a woman.

Further Information

• Case Study Approach
• Case Study Method
• Enhancing the Quality of Case Studies in Health Services Research
• “We do things together” A case study of “couplehood” in dementia
• Using mixed methods for evaluating an integrative approach to cancer care: a case study

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• HHS Author Manuscripts

Single-Case Experimental Designs: A Systematic Review of Published Research and Current Standards

Justin d. smith.

Child and Family Center, University of Oregon

This article systematically reviews the research design and methodological characteristics of single-case experimental design (SCED) research published in peer-reviewed journals between 2000 and 2010. SCEDs provide researchers with a flexible and viable alternative to group designs with large sample sizes. However, methodological challenges have precluded widespread implementation and acceptance of the SCED as a viable complementary methodology to the predominant group design. This article includes a description of the research design, measurement, and analysis domains distinctive to the SCED; a discussion of the results within the framework of contemporary standards and guidelines in the field; and a presentation of updated benchmarks for key characteristics (e.g., baseline sampling, method of analysis), and overall, it provides researchers and reviewers with a resource for conducting and evaluating SCED research. The results of the systematic review of 409 studies suggest that recently published SCED research is largely in accordance with contemporary criteria for experimental quality. Analytic method emerged as an area of discord. Comparison of the findings of this review with historical estimates of the use of statistical analysis indicates an upward trend, but visual analysis remains the most common analytic method and also garners the most support amongst those entities providing SCED standards. Although consensus exists along key dimensions of single-case research design and researchers appear to be practicing within these parameters, there remains a need for further evaluation of assessment and sampling techniques and data analytic methods.

The single-case experiment has a storied history in psychology dating back to the field’s founders: Fechner (1889) , Watson (1925) , and Skinner (1938) . It has been used to inform and develop theory, examine interpersonal processes, study the behavior of organisms, establish the effectiveness of psychological interventions, and address a host of other research questions (for a review, see Morgan & Morgan, 2001 ). In recent years the single-case experimental design (SCED) has been represented in the literature more often than in past decades, as is evidenced by recent reviews ( Hammond & Gast, 2010 ; Shadish & Sullivan, 2011 ), but it still languishes behind the more prominent group design in nearly all subfields of psychology. Group designs are often professed to be superior because they minimize, although do not necessarily eliminate, the major internal validity threats to drawing scientifically valid inferences from the results ( Shadish, Cook, & Campbell, 2002 ). SCEDs provide a rigorous, methodologically sound alternative method of evaluation (e.g., Barlow, Nock, & Hersen, 2008 ; Horner et al., 2005 ; Kazdin, 2010 ; Kratochwill & Levin, 2010 ; Shadish et al., 2002 ) but are often overlooked as a true experimental methodology capable of eliciting legitimate inferences (e.g., Barlow et al., 2008 ; Kazdin, 2010 ). Despite a shift in the zeitgeist from single-case experiments to group designs more than a half century ago, recent and rapid methodological advancements suggest that SCEDs are poised for resurgence.

Single case refers to the participant or cluster of participants (e.g., a classroom, hospital, or neighborhood) under investigation. In contrast to an experimental group design in which one group is compared with another, participants in a single-subject experiment research provide their own control data for the purpose of comparison in a within-subject rather than a between-subjects design. SCEDs typically involve a comparison between two experimental time periods, known as phases. This approach typically includes collecting a representative baseline phase to serve as a comparison with subsequent phases. In studies examining single subjects that are actually groups (i.e., classroom, school), there are additional threats to internal validity of the results, as noted by Kratochwill and Levin (2010) , which include setting or site effects.

The central goal of the SCED is to determine whether a causal or functional relationship exists between a researcher-manipulated independent variable (IV) and a meaningful change in the dependent variable (DV). SCEDs generally involve repeated, systematic assessment of one or more IVs and DVs over time. The DV is measured repeatedly across and within all conditions or phases of the IV. Experimental control in SCEDs includes replication of the effect either within or between participants ( Horner et al., 2005 ). Randomization is another way in which threats to internal validity can be experimentally controlled. Kratochwill and Levin (2010) recently provided multiple suggestions for adding a randomization component to SCEDs to improve the methodological rigor and internal validity of the findings.

Examination of the effectiveness of interventions is perhaps the area in which SCEDs are most well represented ( Morgan & Morgan, 2001 ). Researchers in behavioral medicine and in clinical, health, educational, school, sport, rehabilitation, and counseling psychology often use SCEDs because they are particularly well suited to examining the processes and outcomes of psychological and behavioral interventions (e.g., Borckardt et al., 2008 ; Kazdin, 2010 ; Robey, Schultz, Crawford, & Sinner, 1999 ). Skepticism about the clinical utility of the randomized controlled trial (e.g., Jacobsen & Christensen, 1996 ; Wachtel, 2010 ; Westen & Bradley, 2005 ; Westen, Novotny, & Thompson-Brenner, 2004 ) has renewed researchers’ interest in SCEDs as a means to assess intervention outcomes (e.g., Borckardt et al., 2008 ; Dattilio, Edwards, & Fishman, 2010 ; Horner et al., 2005 ; Kratochwill, 2007 ; Kratochwill & Levin, 2010 ). Although SCEDs are relatively well represented in the intervention literature, it is by no means their sole home: Examples appear in nearly every subfield of psychology (e.g., Bolger, Davis, & Rafaeli, 2003 ; Piasecki, Hufford, Solham, & Trull, 2007 ; Reis & Gable, 2000 ; Shiffman, Stone, & Hufford, 2008 ; Soliday, Moore, & Lande, 2002 ). Aside from the current preference for group-based research designs, several methodological challenges have repressed the proliferation of the SCED.

Methodological Complexity

SCEDs undeniably present researchers with a complex array of methodological and research design challenges, such as establishing a representative baseline, managing the nonindependence of sequential observations (i.e., autocorrelation, serial dependence), interpreting single-subject effect sizes, analyzing the short data streams seen in many applications, and appropriately addressing the matter of missing observations. In the field of intervention research for example, Hser et al. (2001) noted that studies using SCEDs are “rare” because of the minimum number of observations that are necessary (e.g., 3–5 data points in each phase) and the complexity of available data analysis approaches. Advances in longitudinal person-based trajectory analysis (e.g., Nagin, 1999 ), structural equation modeling techniques (e.g., Lubke & Muthén, 2005 ), time-series forecasting (e.g., autoregressive integrated moving averages; Box & Jenkins, 1970 ), and statistical programs designed specifically for SCEDs (e.g., Simulation Modeling Analysis; Borckardt, 2006 ) have provided researchers with robust means of analysis, but they might not be feasible methods for the average psychological scientist.

Application of the SCED has also expanded. Today, researchers use variants of the SCED to examine complex psychological processes and the relationship between daily and momentary events in peoples’ lives and their psychological correlates. Research in nearly all subfields of psychology has begun to use daily diary and ecological momentary assessment (EMA) methods in the context of the SCED, opening the door to understanding increasingly complex psychological phenomena (see Bolger et al., 2003 ; Shiffman et al., 2008 ). In contrast to the carefully controlled laboratory experiment that dominated research in the first half of the twentieth century (e.g., Skinner, 1938 ; Watson, 1925 ), contemporary proponents advocate application of the SCED in naturalistic studies to increase the ecological validity of empirical findings (e.g., Bloom, Fisher, & Orme, 2003 ; Borckardt et al., 2008 ; Dattilio et al., 2010 ; Jacobsen & Christensen, 1996 ; Kazdin, 2008 ; Morgan & Morgan, 2001 ; Westen & Bradley, 2005 ; Westen et al., 2004 ). Recent advancements and expanded application of SCEDs indicate a need for updated design and reporting standards.

Many current benchmarks in the literature concerning key parameters of the SCED were established well before current advancements and innovations, such as the suggested minimum number of data points in the baseline phase(s), which remains a disputed area of SCED research (e.g., Center, Skiba, & Casey, 1986 ; Huitema, 1985 ; R. R. Jones, Vaught, & Weinrott, 1977 ; Sharpley, 1987 ). This article comprises (a) an examination of contemporary SCED methodological and reporting standards; (b) a systematic review of select design, measurement, and statistical characteristics of published SCED research during the past decade; and (c) a broad discussion of the critical aspects of this research to inform methodological improvements and study reporting standards. The reader will garner a fundamental understanding of what constitutes appropriate methodological soundness in single-case experimental research according to the established standards in the field, which can be used to guide the design of future studies, improve the presentation of publishable empirical findings, and inform the peer-review process. The discussion begins with the basic characteristics of the SCED, including an introduction to time-series, daily diary, and EMA strategies, and describes how current reporting and design standards apply to each of these areas of single-case research. Interweaved within this presentation are the results of a systematic review of SCED research published between 2000 and 2010 in peer-reviewed outlets and a discussion of the way in which these findings support, or differ from, existing design and reporting standards and published SCED benchmarks.

Review of Current SCED Guidelines and Reporting Standards

In contrast to experimental group comparison studies, which conform to generally well agreed upon methodological design and reporting guidelines, such as the CONSORT ( Moher, Schulz, Altman, & the CONSORT Group, 2001 ) and TREND ( Des Jarlais, Lyles, & Crepaz, 2004 ) statements for randomized and nonrandomized trials, respectively, there is comparatively much less consensus when it comes to the SCED. Until fairly recently, design and reporting guidelines for single-case experiments were almost entirely absent in the literature and were typically determined by the preferences of a research subspecialty or a particular journal’s editorial board. Factions still exist within the larger field of psychology, as can be seen in the collection of standards presented in this article, particularly in regard to data analytic methods of SCEDs, but fortunately there is budding agreement about certain design and measurement characteristics. A number of task forces, professional groups, and independent experts in the field have recently put forth guidelines; each has a relatively distinct purpose, which likely accounts for some of the discrepancies between them. In what is to be a central theme of this article, researchers are ultimately responsible for thoughtfully and synergistically combining research design, measurement, and analysis aspects of a study.

This review presents the more prominent, comprehensive, and recently established SCED standards. Six sources are discussed: (1) Single-Case Design Technical Documentation from the What Works Clearinghouse (WWC; Kratochwill et al., 2010 ); (2) the APA Division 12 Task Force on Psychological Interventions, with contributions from the Division 12 Task Force on Promotion and Dissemination of Psychological Procedures and the APA Task Force for Psychological Intervention Guidelines (DIV12; presented in Chambless & Hollon, 1998 ; Chambless & Ollendick, 2001 ), adopted and expanded by APA Division 53, the Society for Clinical Child and Adolescent Psychology ( Weisz & Hawley, 1998 , 1999 ); (3) the APA Division 16 Task Force on Evidence-Based Interventions in School Psychology (DIV16; Members of the Task Force on Evidence-Based Interventions in School Psychology. Chair: T. R. Kratochwill, 2003); (4) the National Reading Panel (NRP; National Institute of Child Health and Human Development, 2000 ); (5) the Single-Case Experimental Design Scale ( Tate et al., 2008 ); and (6) the reporting guidelines for EMA put forth by Stone & Shiffman (2002) . Although the specific purposes of each source differ somewhat, the overall aim is to provide researchers and reviewers with agreed-upon criteria to be used in the conduct and evaluation of SCED research. The standards provided by WWC, DIV12, DIV16, and the NRP represent the efforts of task forces. The Tate et al. scale was selected for inclusion in this review because it represents perhaps the only psychometrically validated tool for assessing the rigor of SCED methodology. Stone and Shiffman’s (2002) standards were intended specifically for EMA methods, but many of their criteria also apply to time-series, daily diary, and other repeated-measurement and sampling methods, making them pertinent to this article. The design, measurement, and analysis standards are presented in the later sections of this article and notable concurrences, discrepancies, strengths, and deficiencies are summarized.

Systematic Review Search Procedures and Selection Criteria

Search strategy.

A comprehensive search strategy of SCEDs was performed to identify studies published in peer-reviewed journals meeting a priori search and inclusion criteria. First, a computer-based PsycINFO search of articles published between 2000 and 2010 (search conducted in July 2011) was conducted that used the following primary key terms and phrases that appeared anywhere in the article (asterisks denote that any characters/letters can follow the last character of the search term): alternating treatment design, changing criterion design, experimental case*, multiple baseline design, replicated single-case design, simultaneous treatment design, time-series design. The search was limited to studies published in the English language and those appearing in peer-reviewed journals within the specified publication year range. Additional limiters of the type of article were also used in PsycINFO to increase specificity: The search was limited to include methodologies indexed as either quantitative study OR treatment outcome/randomized clinical trial and NOT field study OR interview OR focus group OR literature review OR systematic review OR mathematical model OR qualitative study.

Study selection

The author used a three-phase study selection, screening, and coding procedure to select the highest number of applicable studies. Phase 1 consisted of the initial systematic review conducted using PsycINFO, which resulted in 571 articles. In Phase 2, titles and abstracts were screened: Articles appearing to use a SCED were retained (451) for Phase 3, in which the author and a trained research assistant read each full-text article and entered the characteristics of interest into a database. At each phase of the screening process, studies that did not use a SCED or that either self-identified as, or were determined to be, quasi-experimental were dropped. Of the 571 original studies, 82 studies were determined to be quasi-experimental. The definition of a quasi-experimental design used in the screening procedure conforms to the descriptions provided by Kazdin (2010) and Shadish et al. (2002) regarding the necessary components of an experimental design. For example, reversal designs require a minimum of four phases (e.g., ABAB), and multiple baseline designs must demonstrate replication of the effect across at least three conditions (e.g., subjects, settings, behaviors). Sixteen studies were unavailable in full text in English, and five could not be obtained in full text and were thus dropped. The remaining articles that were not retained for review (59) were determined not to be SCED studies meeting our inclusion criteria, but had been identified in our PsycINFO search using the specified keyword and methodology terms. For this review, 409 studies were selected. The sources of the 409 reviewed studies are summarized in Table 1 . A complete bibliography of the 571 studies appearing in the initial search, with the included studies marked, is available online as an Appendix or from the author.

Journal Sources of Studies Included in the Systematic Review (N = 409)

Note: Each of the following journal titles contributed 1 study unless otherwise noted in parentheses: Augmentative and Alternative Communication; Acta Colombiana de Psicología; Acta Comportamentalia; Adapted Physical Activity Quarterly (2); Addiction Research and Theory; Advances in Speech Language Pathology; American Annals of the Deaf; American Journal of Education; American Journal of Occupational Therapy; American Journal of Speech-Language Pathology; The American Journal on Addictions; American Journal on Mental Retardation; Applied Ergonomics; Applied Psychophysiology and Biofeedback; Australian Journal of Guidance & Counseling; Australian Psychologist; Autism; The Behavior Analyst; The Behavior Analyst Today; Behavior Analysis in Practice (2); Behavior and Social Issues (2); Behaviour Change (2); Behavioural and Cognitive Psychotherapy; Behaviour Research and Therapy (3); Brain and Language (2); Brain Injury (2); Canadian Journal of Occupational Therapy (2); Canadian Journal of School Psychology; Career Development for Exceptional Individuals; Chinese Mental Health Journal; Clinical Linguistics and Phonetics; Clinical Psychology & Psychotherapy; Cognitive and Behavioral Practice; Cognitive Computation; Cognitive Therapy and Research; Communication Disorders Quarterly; Developmental Medicine & Child Neurology (2); Developmental Neurorehabilitation (2); Disability and Rehabilitation: An International, Multidisciplinary Journal (3); Disability and Rehabilitation: Assistive Technology; Down Syndrome: Research & Practice; Drug and Alcohol Dependence (2); Early Childhood Education Journal (2); Early Childhood Services: An Interdisciplinary Journal of Effectiveness; Educational Psychology (2); Education and Training in Autism and Developmental Disabilities; Electronic Journal of Research in Educational Psychology; Environment and Behavior (2); European Eating Disorders Review; European Journal of Sport Science; European Review of Applied Psychology; Exceptional Children; Exceptionality; Experimental and Clinical Psychopharmacology; Family & Community Health: The Journal of Health Promotion & Maintenance; Headache: The Journal of Head and Face Pain; International Journal of Behavioral Consultation and Therapy (2); International Journal of Disability; Development and Education (2); International Journal of Drug Policy; International Journal of Psychology; International Journal of Speech-Language Pathology; International Psychogeriatrics; Japanese Journal of Behavior Analysis (3); Japanese Journal of Special Education; Journal of Applied Research in Intellectual Disabilities (2); Journal of Applied Sport Psychology (3); Journal of Attention Disorders (2); Journal of Behavior Therapy and Experimental Psychiatry; Journal of Child Psychology and Psychiatry; Journal of Clinical Psychology in Medical Settings; Journal of Clinical Sport Psychology; Journal of Cognitive Psychotherapy; Journal of Consulting and Clinical Psychology (2); Journal of Deaf Studies and Deaf Education; Journal of Educational & Psychological Consultation (2); Journal of Evidence-Based Practices for Schools (2); Journal of the Experimental Analysis of Behavior (2); Journal of General Internal Medicine; Journal of Intellectual and Developmental Disabilities; Journal of Intellectual Disability Research (2); Journal of Medical Speech-Language Pathology; Journal of Neurology, Neurosurgery & Psychiatry; Journal of Paediatrics and Child Health; Journal of Prevention and Intervention in the Community; Journal of Safety Research; Journal of School Psychology (3); The Journal of Socio-Economics; The Journal of Special Education; Journal of Speech, Language, and Hearing Research (2); Journal of Sport Behavior; Journal of Substance Abuse Treatment; Journal of the International Neuropsychological Society; Journal of Traumatic Stress; The Journals of Gerontology: Series B: Psychological Sciences and Social Sciences; Language, Speech, and Hearing Services in Schools; Learning Disabilities Research & Practice (2); Learning Disability Quarterly (2); Music Therapy Perspectives; Neurorehabilitation and Neural Repair; Neuropsychological Rehabilitation (2); Pain; Physical Education and Sport Pedagogy (2); Preventive Medicine: An International Journal Devoted to Practice and Theory; Psychological Assessment; Psychological Medicine: A Journal of Research in Psychiatry and the Allied Sciences; The Psychological Record; Reading and Writing; Remedial and Special Education (3); Research and Practice for Persons with Severe Disabilities (2); Restorative Neurology and Neuroscience; School Psychology International; Seminars in Speech and Language; Sleep and Hypnosis; School Psychology Quarterly; Social Work in Health Care; The Sport Psychologist (3); Therapeutic Recreation Journal (2); The Volta Review; Work: Journal of Prevention, Assessment & Rehabilitation.

Coding criteria amplifications

A comprehensive description of the coding criteria for each category in this review is available from the author by request. The primary coding criteria are described here and in later sections of this article.

• Research design was classified into one of the types discussed later in the section titled Predominant Single-Case Experimental Designs on the basis of the authors’ stated design type. Secondary research designs were then coded when applicable (i.e., mixed designs). Distinctions between primary and secondary research designs were made based on the authors’ description of their study. For example, if an author described the study as a “multiple baseline design with time-series measurement,” the primary research design would be coded as being multiple baseline, and time-series would be coded as the secondary research design.
• Observer ratings were coded as present when observational coding procedures were described and/or the results of a test of interobserver agreement were reported.
• Interrater reliability for observer ratings was coded as present in any case in which percent agreement, alpha, kappa, or another appropriate statistic was reported, regardless of the amount of the total data that were examined for agreement.
• Daily diary, daily self-report, and EMA codes were given when authors explicitly described these procedures in the text by name. Coders did not infer the use of these measurement strategies.
• The number of baseline observations was either taken directly from the figures provided in text or was simply counted in graphical displays of the data when this was determined to be a reliable approach. In some cases, it was not possible to reliably determine the number of baseline data points from the graphical display of data, in which case, the “unavailable” code was assigned. Similarly, the “unavailable” code was assigned when the number of observations was either unreported or ambiguous, or only a range was provided and thus no mean could be determined. Similarly, the mean number of baseline observations was calculated for each study prior to further descriptive statistical analyses because a number of studies reported means only.
• The coding of the analytic method used in the reviewed studies is discussed later in the section titled Discussion of Review Results and Coding of Analytic Methods .

Results of the Systematic Review

Descriptive statistics of the design, measurement, and analysis characteristics of the reviewed studies are presented in Table 2 . The results and their implications are discussed in the relevant sections throughout the remainder of the article.

Descriptive Statistics of Reviewed SCED Characteristics

Note. % refers to the proportion of reviewed studies that satisfied criteria for this code: For example, the percent of studies reporting observer ratings.

Discussion of the Systematic Review Results in Context

The SCED is a very flexible methodology and has many variants. Those mentioned here are the building blocks from which other designs are then derived. For those readers interested in the nuances of each design, Barlow et al., (2008) ; Franklin, Allison, and Gorman (1997) ; Kazdin (2010) ; and Kratochwill and Levin (1992) , among others, provide cogent, in-depth discussions. Identifying the appropriate SCED depends upon many factors, including the specifics of the IV, the setting in which the study will be conducted, participant characteristics, the desired or hypothesized outcomes, and the research question(s). Similarly, the researcher’s selection of measurement and analysis techniques is determined by these factors.

Predominant Single-Case Experimental Designs

Alternating/simultaneous designs (6%; primary design of the studies reviewed).

Alternating and simultaneous designs involve an iterative manipulation of the IV(s) across different phases to show that changes in the DV vary systematically as a function of manipulating the IV(s). In these multielement designs, the researcher has the option to alternate the introduction of two or more IVs or present two or more IVs at the same time. In the alternating variation, the researcher is able to determine the relative impact of two different IVs on the DV, when all other conditions are held constant. Another variation of this design is to alternate IVs across various conditions that could be related to the DV (e.g., class period, interventionist). Similarly, the simultaneous design would occur when the IVs were presented at the same time within the same phase of the study.

Changing criterion design (4%)

Changing criterion designs are used to demonstrate a gradual change in the DV over the course of the phase involving the active manipulation of the IV. Criteria indicating that a change has occurred happen in a step-wise manner, in which the criterion shifts as the participant responds to the presence of the manipulated IV. The changing criterion design is particularly useful in applied intervention research for a number of reasons. The IV is continuous and never withdrawn, unlike the strategy used in a reversal design. This is particularly important in situations where removal of a psychological intervention would be either detrimental or dangerous to the participant, or would be otherwise unfeasible or unethical. The multiple baseline design also does not withdraw intervention, but it requires replicating the effects of the intervention across participants, settings, or situations. A changing criterion design can be accomplished with one participant in one setting without withholding or withdrawing treatment.

Multiple baseline/combined series design (69%)

The multiple baseline or combined series design can be used to test within-subject change across conditions and often involves multiple participants in a replication context. The multiple baseline design is quite simple in many ways, essentially consisting of a number of repeated, miniature AB experiments or variations thereof. Introduction of the IV is staggered temporally across multiple participants or across multiple within-subject conditions, which allows the researcher to demonstrate that changes in the DV reliably occur only when the IV is introduced, thus controlling for the effects of extraneous factors. Multiple baseline designs can be used both within and across units (i.e., persons or groups of persons). When the baseline phase of each subject begins simultaneously, it is called a concurrent multiple baseline design. In a nonconcurrent variation, baseline periods across subjects begin at different points in time. The multiple baseline design is useful in many settings in which withdrawal of the IV would not be appropriate or when introduction of the IV is hypothesized to result in permanent change that would not reverse when the IV is withdrawn. The major drawback of this design is that the IV must be initially withheld for a period of time to ensure different starting points across the different units in the baseline phase. Depending upon the nature of the research questions, withholding an IV, such as a treatment, could be potentially detrimental to participants.

Reversal designs (17%)

Reversal designs are also known as introduction and withdrawal and are denoted as ABAB designs in their simplest form. As the name suggests, the reversal design involves collecting a baseline measure of the DV (the first A phase), introducing the IV (the first B phase), removing the IV while continuing to assess the DV (the second A phase), and then reintroducing the IV (the second B phase). This pattern can be repeated as many times as is necessary to demonstrate an effect or otherwise address the research question. Reversal designs are useful when the manipulation is hypothesized to result in changes in the DV that are expected to reverse or discontinue when the manipulation is not present. Maintenance of an effect is often necessary to uphold the findings of reversal designs. The demonstration of an effect is evident in reversal designs when improvement occurs during the first manipulation phase, compared to the first baseline phase, then reverts to or approaches original baseline levels during the second baseline phase when the manipulation has been withdrawn, and then improves again when the manipulation in then reinstated. This pattern of reversal, when the manipulation is introduced and then withdrawn, is essential to attributing changes in the DV to the IV. However, maintenance of the effects in a reversal design, in which the DV is hypothesized to reverse when the IV is withdrawn, is not incompatible ( Kazdin, 2010 ). Maintenance is demonstrated by repeating introduction–withdrawal segments until improvement in the DV becomes permanent even when the IV is withdrawn. There is not always a need to demonstrate maintenance in all applications, nor is it always possible or desirable, but it is paramount in the learning and intervention research contexts.

Mixed designs (10%)

Mixed designs include a combination of more than one SCED (e.g., a reversal design embedded within a multiple baseline) or an SCED embedded within a group design (i.e., a randomized controlled trial comparing two groups of multiple baseline experiments). Mixed designs afford the researcher even greater flexibility in designing a study to address complex psychological hypotheses, but also capitalize on the strengths of the various designs. See Kazdin (2010) for a discussion of the variations and utility of mixed designs.

Related Nonexperimental Designs

Quasi-experimental designs.

In contrast to the designs previously described, all of which constitute “true experiments” ( Kazdin, 2010 ; Shadish et al., 2002 ), in quasi-experimental designs the conditions of a true experiment (e.g., active manipulation of the IV, replication of the effect) are approximated and are not readily under the control of the researcher. Because the focus of this article is on experimental designs, quasi-experiments are not discussed in detail; instead the reader is referred to Kazdin (2010) and Shadish et al. (2002) .

Ecological and naturalistic single-case designs

For a single-case design to be experimental, there must be active manipulation of the IV, but in some applications, such as those that might be used in social and personality psychology, the researcher might be interested in measuring naturally occurring phenomena and examining their temporal relationships. Thus, the researcher will not use a manipulation. An example of this type of research might be a study about the temporal relationship between alcohol consumption and depressed mood, which can be measured reliably using EMA methods. Psychotherapy process researchers also use this type of design to assess dyadic relationship dynamics between therapists and clients (e.g., Tschacher & Ramseyer, 2009 ).

Research Design Standards

Each of the reviewed standards provides some degree of direction regarding acceptable research designs. The WWC provides the most detailed and specific requirements regarding design characteristics. Those guidelines presented in Tables 3 , ​ ,4, 4 , and ​ and5 5 are consistent with the methodological rigor necessary to meet the WWC distinction “meets standards.” The WWC also provides less-stringent standards for a “meets standards with reservations” distinction. When minimum criteria in the design, measurement, or analysis sections of a study are not met, it is rated “does not meet standards” ( Kratochwill et al., 2010 ). Many SCEDs are acceptable within the standards of DIV12, DIV16, NRP, and in the Tate et al. SCED scale. DIV12 specifies that replication occurs across a minimum of three successive cases, which differs from the WWC specifications, which allow for three replications within a single-subject design but does not necessarily need to be across multiple subjects. DIV16 does not require, but seems to prefer, a multiple baseline design with a between-subject replication. Tate et al. state that the “design allows for the examination of cause and effect relationships to demonstrate efficacy” (p. 400, 2008). Determining whether or not a design meets this requirement is left up to the evaluator, who might then refer to one of the other standards or another source for direction.

Research Design Standards and Guidelines

Measurement and Assessment Standards and Guidelines

Analysis Standards and Guidelines

The Stone and Shiffman (2002) standards for EMA are concerned almost entirely with the reporting of measurement characteristics and less so with research design. One way in which these standards differ from those of other sources is in the active manipulation of the IV. Many research questions in EMA, daily diary, and time-series designs are concerned with naturally occurring phenomena, and a researcher manipulation would run counter to this aim. The EMA standards become important when selecting an appropriate measurement strategy within the SCED. In EMA applications, as is also true in some other time-series and daily diary designs, researcher manipulation occurs as a function of the sampling interval in which DVs of interest are measured according to fixed time schedules (e.g., reporting occurs at the end of each day), random time schedules (e.g., the data collection device prompts the participant to respond at random intervals throughout the day), or on an event-based schedule (e.g., reporting occurs after a specified event takes place).

Measurement

The basic measurement requirement of the SCED is a repeated assessment of the DV across each phase of the design in order to draw valid inferences regarding the effect of the IV on the DV. In other applications, such as those used by personality and social psychology researchers to study various human phenomena ( Bolger et al., 2003 ; Reis & Gable, 2000 ), sampling strategies vary widely depending on the topic area under investigation. Regardless of the research area, SCEDs are most typically concerned with within-person change and processes and involve a time-based strategy, most commonly to assess global daily averages or peak daily levels of the DV. Many sampling strategies, such as time-series, in which reporting occurs at uniform intervals or on event-based, fixed, or variable schedules, are also appropriate measurement methods and are common in psychological research (see Bolger et al., 2003 ).

Repeated-measurement methods permit the natural, even spontaneous, reporting of information ( Reis, 1994 ), which reduces the biases of retrospection by minimizing the amount of time elapsed between an experience and the account of this experience ( Bolger et al., 2003 ). Shiffman et al. (2008) aptly noted that the majority of research in the field of psychology relies heavily on retrospective assessment measures, even though retrospective reports have been found to be susceptible to state-congruent recall (e.g., Bower, 1981 ) and a tendency to report peak levels of the experience instead of giving credence to temporal fluctuations ( Redelmeier & Kahneman, 1996 ; Stone, Broderick, Kaell, Deles-Paul, & Porter, 2000 ). Furthermore, Shiffman et al. (1997) demonstrated that subjective aggregate accounts were a poor fit to daily reported experiences, which can be attributed to reductions in measurement error resulting in increased validity and reliability of the daily reports.

The necessity of measuring at least one DV repeatedly means that the selected assessment method, instrument, and/or construct must be sensitive to change over time and be capable of reliably and validly capturing change. Horner et al. (2005) discusses the important features of outcome measures selected for use in these types of designs. Kazdin (2010) suggests that measures be dimensional, which can more readily detect effects than categorical and binary measures. Although using an established measure or scale, such as the Outcome Questionnaire System ( M. J. Lambert, Hansen, & Harmon, 2010 ), provides empirically validated items for assessing various outcomes, most measure validation studies conducted on this type of instrument involve between-subject designs, which is no guarantee that these measures are reliable and valid for assessing within-person variability. Borsboom, Mellenbergh, and van Heerden (2003) suggest that researchers adapting validated measures should consider whether the items they propose using have a factor structure within subjects similar to that obtained between subjects. This is one of the reasons that SCEDs often use observational assessments from multiple sources and report the interrater reliability of the measure. Self-report measures are acceptable practice in some circles, but generally additional assessment methods or informants are necessary to uphold the highest methodological standards. The results of this review indicate that the majority of studies include observational measurement (76.0%). Within those studies, nearly all (97.1%) reported interrater reliability procedures and results. The results within each design were similar, with the exception of time-series designs, which used observer ratings in only half of the reviewed studies.

Time-series

Time-series designs are defined by repeated measurement of variables of interest over a period of time ( Box & Jenkins, 1970 ). Time-series measurement most often occurs in uniform intervals; however, this is no longer a constraint of time-series designs (see Harvey, 2001 ). Although uniform interval reporting is not necessary in SCED research, repeated measures often occur at uniform intervals, such as once each day or each week, which constitutes a time-series design. The time-series design has been used in various basic science applications ( Scollon, Kim-Pietro, & Diener, 2003 ) across nearly all subspecialties in psychology (e.g., Bolger et al., 2003 ; Piasecki et al., 2007 ; for a review, see Reis & Gable, 2000 ; Soliday et al., 2002 ). The basic time-series formula for a two-phase (AB) data stream is presented in Equation 1 . In this formula α represents the step function of the data stream; S represents the change between the first and second phases, which is also the intercept in a two-phase data stream and a step function being 0 at times i = 1, 2, 3…n1 and 1 at times i = n1+1, n1+2, n1+3…n; n 1 is the number of observations in the baseline phase; n is the total number of data points in the data stream; i represents time; and ε i = ρε i −1 + e i , which indicates the relationship between the autoregressive function (ρ) and the distribution of the data in the stream.

Time-series formulas become increasingly complex when seasonality and autoregressive processes are modeled in the analytic procedures, but these are rarely of concern for short time-series data streams in SCEDs. For a detailed description of other time-series design and analysis issues, see Borckardt et al. (2008) , Box and Jenkins (1970) , Crosbie (1993) , R. R. Jones et al. (1977) , and Velicer and Fava (2003) .

Time-series and other repeated-measures methodologies also enable examination of temporal effects. Borckardt et al. (2008) and others have noted that time-series designs have the potential to reveal how change occurs, not simply if it occurs. This distinction is what most interested Skinner (1938) , but it often falls below the purview of today’s researchers in favor of group designs, which Skinner felt obscured the process of change. In intervention and psychopathology research, time-series designs can assess mediators of change ( Doss & Atkins, 2006 ), treatment processes ( Stout, 2007 ; Tschacher & Ramseyer, 2009 ), and the relationship between psychological symptoms (e.g., Alloy, Just, & Panzarella, 1997 ; Hanson & Chen, 2010 ; Oslin, Cary, Slaymaker, Colleran, & Blow, 2009 ), and might be capable of revealing mechanisms of change ( Kazdin, 2007 , 2009 , 2010 ). Between- and within-subject SCED designs with repeated measurements enable researchers to examine similarities and differences in the course of change, both during and as a result of manipulating an IV. Temporal effects have been largely overlooked in many areas of psychological science ( Bolger et al., 2003 ): Examining temporal relationships is sorely needed to further our understanding of the etiology and amplification of numerous psychological phenomena.

Time-series studies were very infrequently found in this literature search (2%). Time-series studies traditionally occur in subfields of psychology in which single-case research is not often used (e.g., personality, physiological/biological). Recent advances in methods for collecting and analyzing time-series data (e.g., Borckardt et al., 2008 ) could expand the use of time-series methodology in the SCED community. One problem with drawing firm conclusions from this particular review finding is a semantic factor: Time-series is a specific term reserved for measurement occurring at a uniform interval. However, SCED research appears to not yet have adopted this language when referring to data collected in this fashion. When time-series data analytic methods are not used, the matter of measurement interval is of less importance and might not need to be specified or described as a time-series. An interesting extension of this work would be to examine SCED research that used time-series measurement strategies but did not label it as such. This is important because then it could be determined how many SCEDs could be analyzed with time-series statistical methods.

Daily diary and ecological momentary assessment methods

EMA and daily diary approaches represent methodological procedures for collecting repeated measurements in time-series and non-time-series experiments, which are also known as experience sampling. Presenting an in-depth discussion of the nuances of these sampling techniques is well beyond the scope of this paper. The reader is referred to the following review articles: daily diary ( Bolger et al., 2003 ; Reis & Gable, 2000 ; Thiele, Laireiter, & Baumann, 2002 ), and EMA ( Shiffman et al., 2008 ). Experience sampling in psychology has burgeoned in the past two decades as technological advances have permitted more precise and immediate reporting by participants (e.g., Internet-based, two-way pagers, cellular telephones, handheld computers) than do paper and pencil methods (for reviews see Barrett & Barrett, 2001 ; Shiffman & Stone, 1998 ). Both methods have practical limitations and advantages. For example, electronic methods are more costly and may exclude certain subjects from participating in the study, either because they do not have access to the necessary technology or they do not have the familiarity or savvy to successfully complete reporting. Electronic data collection methods enable the researcher to prompt responses at random or predetermined intervals and also accurately assess compliance. Paper and pencil methods have been criticized for their inability to reliably track respondents’ compliance: Palermo, Valenzuela, and Stork (2004) found better compliance with electronic diaries than with paper and pencil. On the other hand, Green, Rafaeli, Bolger, Shrout, & Reis (2006) demonstrated the psychometric data structure equivalence between these two methods, suggesting that the data collected in either method will yield similar statistical results given comparable compliance rates.

Daily diary/daily self-report and EMA measurement were somewhat rarely represented in this review, occurring in only 6.1% of the total studies. EMA methods had been used in only one of the reviewed studies. The recent proliferation of EMA and daily diary studies in psychology reported by others ( Bolger et al., 2003 ; Piasecki et al., 2007 ; Shiffman et al., 2008 ) suggests that these methods have not yet reached SCED researchers, which could in part have resulted from the long-held supremacy of observational measurement in fields that commonly practice single-case research.

Measurement Standards

As was previously mentioned, measurement in SCEDs requires the reliable assessment of change over time. As illustrated in Table 4 , DIV16 and the NRP explicitly require that reliability of all measures be reported. DIV12 provides little direction in the selection of the measurement instrument, except to require that three or more clinically important behaviors with relative independence be assessed. Similarly, the only item concerned with measurement on the Tate et al. scale specifies assessing behaviors consistent with the target of the intervention. The WWC and the Tate et al. scale require at least two independent assessors of the DV and that interrater reliability meeting minimum established thresholds be reported. Furthermore, WWC requires that interrater reliability be assessed on at least 20% of the data in each phase and in each condition. DIV16 expects that assessment of the outcome measures will be multisource and multimethod, when applicable. The interval of measurement is not specified by any of the reviewed sources. The WWC and the Tate et al. scale require that DVs be measured repeatedly across phases (e.g., baseline and treatment), which is a typical requirement of a SCED. The NRP asks that the time points at which DV measurement occurred be reported.

The baseline measurement represents one of the most crucial design elements of the SCED. Because subjects provide their own data for comparison, gathering a representative, stable sampling of behavior before manipulating the IV is essential to accurately inferring an effect. Some researchers have reported the typical length of the baseline period to range from 3 to 12 observations in intervention research applications (e.g., Center et al., 1986 ; Huitema, 1985 ; R. R. Jones et al., 1977 ; Sharpley, 1987 ); Huitema’s (1985) review of 881 experiments published in the Journal of Applied Behavior Analysis resulted in a modal number of three to four baseline points. Center et al. (1986) suggested five as the minimum number of baseline measurements needed to accurately estimate autocorrelation. Longer baseline periods suggest a greater likelihood of a representative measurement of the DVs, which has been found to increase the validity of the effects and reduce bias resulting from autocorrelation ( Huitema & McKean, 1994 ). The results of this review are largely consistent with those of previous researchers: The mean number of baseline observations was found to be 10.22 ( SD = 9.59), and 6 was the modal number of observations. Baseline data were available in 77.8% of the reviewed studies. Although the baseline assessment has tremendous bearing on the results of a SCED study, it was often difficult to locate the exact number of data points. Similarly, the number of data points assessed across all phases of the study were not easily identified.

The WWC, DIV12, and DIV16 agree that a minimum of three data points during the baseline is necessary. However, to receive the highest rating by the WWC, five data points are necessary in each phase, including the baseline and any subsequent withdrawal baselines as would occur in a reversal design. DIV16 explicitly states that more than three points are preferred and further stipulates that the baseline must demonstrate stability (i.e., limited variability), absence of overlap between the baseline and other phases, absence of a trend, and that the level of the baseline measurement is severe enough to warrant intervention; each of these aspects of the data is important in inferential accuracy. Detrending techniques can be used to address baseline data trend. The integration option in ARIMA-based modeling and the empirical mode decomposition method ( Wu, Huang, Long, & Peng, 2007 ) are two sophisticated detrending techniques. In regression-based analytic methods, detrending can be accomplished by simply regressing each variable in the model on time (i.e., the residuals become the detrended series), which is analogous to adding a linear, exponential, or quadratic term to the regression equation.

NRP does not provide a minimum for data points, nor does the Tate et al. scale, which requires only a sufficient sampling of baseline behavior. Although the mean and modal number of baseline observations is well within these parameters, seven (1.7%) studies reported mean baselines of less than three data points.

Establishing a uniform minimum number of required baseline observations would provide researchers and reviewers with only a starting guide. The baseline phase is important in SCED research because it establishes a trend that can then be compared with that of subsequent phases. Although a minimum number of observations might be required to meet standards, many more might be necessary to establish a trend when there is variability and trends in the direction of the expected effect. The selected data analytic approach also has some bearing on the number of necessary baseline observations. This is discussed further in the Analysis section.

Reporting of repeated measurements

Stone and Shiffman (2002) provide a comprehensive set of guidelines for the reporting of EMA data, which can also be applied to other repeated-measurement strategies. Because the application of EMA is widespread and not confined to specific research designs, Stone and Shiffman intentionally place few restraints on researchers regarding selection of the DV and the reporter, which is determined by the research question under investigation. The methods of measurement, however, are specified in detail: Descriptions of prompting, recording of responses, participant-initiated entries, and the data acquisition interface (e.g., paper and pencil diary, PDA, cellular telephone) ought to be provided with sufficient detail for replication. Because EMA specifically, and time-series/daily diary methods similarly, are primarily concerned with the interval of assessment, Stone and Shiffman suggest reporting the density and schedule of assessment. The approach is generally determined by the nature of the research question and pragmatic considerations, such as access to electronic data collection devices at certain times of the day and participant burden. Compliance and missing data concerns are present in any longitudinal research design, but they are of particular importance in repeated-measurement applications with frequent measurement. When the research question pertains to temporal effects, compliance becomes paramount, and timely, immediate responding is necessary. For this reason, compliance decisions, rates of missing data, and missing data management techniques must be reported. The effect of missing data in time-series data streams has been the topic of recent research in the social sciences (e.g., Smith, Borckardt, & Nash, in press ; Velicer & Colby, 2005a , 2005b ). The results and implications of these and other missing data studies are discussed in the next section.

Analysis of SCED Data

Visual analysis.

Experts in the field generally agree about the majority of critical single-case experiment design and measurement characteristics. Analysis, on the other hand, is an area of significant disagreement, yet it has also received extensive recent attention and advancement. Debate regarding the appropriateness and accuracy of various methods for analyzing SCED data, the interpretation of single-case effect sizes, and other concerns vital to the validity of SCED results has been ongoing for decades, and no clear consensus has been reached. Visual analysis, following systematic procedures such as those provided by Franklin, Gorman, Beasley, and Allison (1997) and Parsonson and Baer (1978) , remains the standard by which SCED data are most commonly analyzed ( Parker, Cryer, & Byrns, 2006 ). Visual analysis can arguably be applied to all SCEDs. However, a number of baseline data characteristics must be met for effects obtained through visual analysis to be valid and reliable. The baseline phase must be relatively stable; free of significant trend, particularly in the hypothesized direction of the effect; have minimal overlap of data with subsequent phases; and have a sufficient sampling of behavior to be considered representative ( Franklin, Gorman, et al., 1997 ; Parsonson & Baer, 1978 ). The effect of baseline trend on visual analysis, and a technique to control baseline trend, are offered by Parker et al. (2006) . Kazdin (2010) suggests using statistical analysis when a trend or significant variability appears in the baseline phase, two conditions that ought to preclude the use of visual analysis techniques. Visual analysis methods are especially adept at determining intervention effects and can be of particular relevance in real-world applications (e.g., Borckardt et al., 2008 ; Kratochwill, Levin, Horner, & Swoboda, 2011 ).

However, visual analysis has its detractors. It has been shown to be inconsistent, can be affected by autocorrelation, and results in overestimation of effect (e.g., Matyas & Greenwood, 1990 ). Visual analysis as a means of estimating an effect precludes the results of SCED research from being included in meta-analysis, and also makes it very difficult to compare results to the effect sizes generated by other statistical methods. Yet, visual analysis proliferates in large part because SCED researchers are familiar with these methods and are not only generally unfamiliar with statistical approaches, but lack agreement about their appropriateness. Still, top experts in single-case analysis champion the use of statistical methods alongside visual analysis whenever it is appropriate to do so ( Kratochwill et al., 2011 ).

Statistical analysis

Statistical analysis of SCED data consists generally of an attempt to address one or more of three broad research questions: (1) Does introduction/manipulation of the IV result in statistically significant change in the level of the DV (level-change or phase-effect analysis)? (2) Does introduction/manipulation of the IV result in statistically significant change in the slope of the DV over time (slope-change analysis)? and (3) Do meaningful relationships exist between the trajectory of the DV and other potential covariates? Level- and slope-change analyses are relevant to intervention effectiveness studies and other research questions in which the IV is expected to result in changes in the DV in a particular direction. Visual analysis methods are most adept at addressing research questions pertaining to changes in level and slope (Questions 1 and 2), most often using some form of graphical representation and standardized computation of a mean level or trend line within and between each phase of interest (e.g., Horner & Spaulding, 2010 ; Kratochwill et al., 2011 ; Matyas & Greenwood, 1990 ). Research questions in other areas of psychological science might address the relationship between DVs or the slopes of DVs (Question 3). A number of sophisticated modeling approaches (e.g., cross-lag, multilevel, panel, growth mixture, latent class analysis) may be used for this type of question, and some are discussed in greater detail later in this section. However, a discussion about the nuances of this type of analysis and all their possible methods is well beyond the scope of this article.

The statistical analysis of SCEDs is a contentious issue in the field. Not only is there no agreed-upon statistical method, but the practice of statistical analysis in the context of the SCED is viewed by some as unnecessary (see Shadish, Rindskopf, & Hedges, 2008 ). Traditional trends in the prevalence of statistical analysis usage by SCED researchers are revealing: Busk & Marascuilo (1992) found that only 10% of the published single-case studies they reviewed used statistical analysis; Brossart, Parker, Olson, & Mahadevan (2006) estimated that this figure had roughly doubled by 2006. A range of concerns regarding single-case effect size calculation and interpretation is discussed in significant detail elsewhere (e.g., Campbell, 2004 ; Cohen, 1994 ; Ferron & Sentovich, 2002 ; Ferron & Ware, 1995 ; Kirk, 1996 ; Manolov & Solanas, 2008 ; Olive & Smith, 2005 ; Parker & Brossart, 2003 ; Robey et al., 1999 ; Smith et al., in press ; Velicer & Fava, 2003 ). One concern is the lack of a clearly superior method across datasets. Although statistical methods for analyzing SCEDs abound, few studies have examined their comparative performance with the same dataset. The most recent studies of this kind, performed by Brossart et al. (2006) , Campbell (2004) , Parker and Brossart (2003) , and Parker and Vannest (2009) , found that the more promising available statistical analysis methods yielded moderately different results on the same data series, which led them to conclude that each available method is equipped to adequately address only a relatively narrow spectrum of data. Given these findings, analysts need to select an appropriate model for the research questions and data structure, being mindful of how modeling results can be influenced by extraneous factors.

The current standards unfortunately provide little guidance in the way of statistical analysis options. This article presents an admittedly cursory introduction to available statistical methods; many others are not covered in this review. The following articles provide more in-depth discussion and description of other methods: Barlow et al. (2008) ; Franklin et al., (1997) ; Kazdin (2010) ; and Kratochwill and Levin (1992 , 2010 ). Shadish et al. (2008) summarize more recently developed methods. Similarly, a Special Issue of Evidence-Based Communication Assessment and Intervention (2008, Volume 2) provides articles and discussion of the more promising statistical methods for SCED analysis. An introduction to autocorrelation and its implications for statistical analysis is necessary before specific analytic methods can be discussed. It is also pertinent at this time to discuss the implications of missing data.

Autocorrelation

Many repeated measurements within a single subject or unit create a situation that most psychological researchers are unaccustomed to dealing with: autocorrelated data, which is the nonindependence of sequential observations, also known as serial dependence. Basic and advanced discussions of autocorrelation in single-subject data can be found in Borckardt et al. (2008) , Huitema (1985) , and Marshall (1980) , and discussions of autocorrelation in multilevel models can be found in Snijders and Bosker (1999) and Diggle and Liang (2001) . Along with trend and seasonal variation, autocorrelation is one example of the internal structure of repeated measurements. In the social sciences, autocorrelated data occur most naturally in the fields of physiological psychology, econometrics, and finance, where each phase of interest has potentially hundreds or even thousands of observations that are tightly packed across time (e.g., electroencephalography actuarial data, financial market indices). Applied SCED research in most areas of psychology is more likely to have measurement intervals of day, week, or hour.

Autocorrelation is a direct result of the repeated-measurement requirements of the SCED, but its effect is most noticeable and problematic when one is attempting to analyze these data. Many commonly used data analytic approaches, such as analysis of variance, assume independence of observations and can produce spurious results when the data are nonindependent. Even statistically insignificant autocorrelation estimates are generally viewed as sufficient to cause inferential bias when conventional statistics are used (e.g., Busk & Marascuilo, 1988 ; R. R. Jones et al., 1977 ; Matyas & Greenwood, 1990 ). The effect of autocorrelation on statistical inference in single-case applications has also been known for quite some time (e.g., R. R. Jones et al., 1977 ; Kanfer, 1970 ; Kazdin, 1981 ; Marshall, 1980 ). The findings of recent simulation studies of single-subject data streams indicate that autocorrelation is a nontrivial matter. For example, Manolov and Solanas (2008) determined that calculated effect sizes were linearly related to the autocorrelation of the data stream, and Smith et al. (in press) demonstrated that autocorrelation estimates in the vicinity of 0.80 negatively affect the ability to correctly infer a significant level-change effect using a standardized mean differences method. Huitema and colleagues (e.g., Huitema, 1985 ; Huitema & McKean, 1994 ) argued that autocorrelation is rarely a concern in applied research. Huitema’s methods and conclusions have been questioned and opposing data have been published (e.g., Allison & Gorman, 1993 ; Matyas & Greenwood, 1990 ; Robey et al., 1999 ), resulting in abandonment of the position that autocorrelation can be conscionably ignored without compromising the validity of the statistical procedures. Procedures for removing autocorrelation in the data stream prior to calculating effect sizes are offered as one option: One of the more promising analysis methods, autoregressive integrated moving averages (discussed later in this article), was specifically designed to remove the internal structure of time-series data, such as autocorrelation, trend, and seasonality ( Box & Jenkins, 1970 ; Tiao & Box, 1981 ).

Missing observations

Another concern inherent in repeated-measures designs is missing data. Daily diary and EMA methods are intended to reduce the risk of retrospection error by eliciting accurate, real-time information ( Bolger et al., 2003 ). However, these methods are subject to missing data as a result of honest forgetfulness, not possessing the diary collection tool at the specified time of collection, and intentional or systematic noncompliance. With paper and pencil diaries and some electronic methods, subjects might be able to complete missed entries retrospectively, defeating the temporal benefits of these assessment strategies ( Bolger et al., 2003 ). Methods of managing noncompliance through the study design and measurement methods include training the subject to use the data collection device appropriately, using technology to prompt responding and track the time of response, and providing incentives to participants for timely compliance (for additional discussion of this topic, see Bolger et al., 2003 ; Shiffman & Stone, 1998 ).

Even when efforts are made to maximize compliance during the conduct of the research, the problem of missing data is often unavoidable. Numerous approaches exist for handling missing observations in group multivariate designs (e.g., Horton & Kleinman, 2007 ; Ibrahim, Chen, Lipsitz, & Herring, 2005 ). Ragunathan (2004) and others concluded that full information and raw data maximum likelihood methods are preferable. Velicer and Colby (2005a , 2005b ) established the superiority of maximum likelihood methods over listwise deletion, mean of adjacent observations, and series mean substitution in the estimation of various critical time-series data parameters. Smith et al. (in press) extended these findings regarding the effect of missing data on inferential precision. They found that managing missing data with the EM procedure ( Dempster, Laird, & Rubin, 1977 ), a maximum likelihood algorithm, did not affect one’s ability to correctly infer a significant effect. However, lag-1 autocorrelation estimates in the vicinity of 0.80 resulted in insufficient power sensitivity (< 0.80), regardless of the proportion of missing data (10%, 20%, 30%, or 40%). 1 Although maximum likelihood methods have garnered some empirical support, methodological strategies that minimize missing data, particularly systematically missing data, are paramount to post-hoc statistical remedies.

Nonnormal distribution of data

In addition to the autocorrelated nature of SCED data, typical measurement methods also present analytic challenges. Many statistical methods, particularly those involving model finding, assume that the data are normally distributed. This is often not satisfied in SCED research when measurements involve count data, observer-rated behaviors, and other, similar metrics that result in skewed distributions. Techniques are available to manage nonnormal distributions in regression-based analysis, such as zero-inflated Poisson regression ( D. Lambert, 1992 ) and negative binomial regression ( Gardner, Mulvey, & Shaw, 1995 ), but many other statistical analysis methods do not include these sophisticated techniques. A skewed data distribution is perhaps one of the reasons Kazdin (2010) suggests not using count, categorical, or ordinal measurement methods.

Available statistical analysis methods

Following is a basic introduction to the more promising and prevalent analytic methods for SCED research. Because there is little consensus regarding the superiority of any single method, the burden unfortunately falls on the researcher to select a method capable of addressing the research question and handling the data involved in the study. Some indications and contraindications are provided for each method presented here.

Multilevel and structural equation modeling

Multilevel modeling (MLM; e.g., Schmidt, Perels, & Schmitz, 2010 ) techniques represent the state of the art among parametric approaches to SCED analysis, particularly when synthesizing SCED results ( Shadish et al., 2008 ). MLM and related latent growth curve and factor mixture methods in structural equation modeling (SEM; e.g., Lubke & Muthén, 2005 ; B. O. Muthén & Curran, 1997 ) are particularly effective for evaluating trajectories and slopes in longitudinal data and relating changes to potential covariates. MLM and related hierarchical linear models (HLM) can also illuminate the relationship between the trajectories of different variables under investigation and clarify whether or not these relationships differ amongst the subjects in the study. Time-series and cross-lag analyses can also be used in MLM and SEM ( Chow, Ho, Hamaker, & Dolan, 2010 ; du Toit & Browne, 2007 ). However, they generally require sophisticated model-fitting techniques, making them difficult for many social scientists to implement. The structure (autocorrelation) and trend of the data can also complicate many MLM methods. The common, short data streams in SCED research and the small number of subjects also present problems to MLM and SEM approaches, which were developed for data with significantly greater numbers of observations when the number of subjects is fewer, and for a greater number of participants for model-fitting purposes, particularly when there are fewer data points. Still, MLM and related techniques arguably represent the most promising analytic methods.

A number of software options 2 exist for SEM. Popular statistical packages in the social sciences provide SEM options, such as PROC CALIS in SAS ( SAS Institute Inc., 2008 ), the AMOS module ( Arbuckle, 2006 ) of SPSS ( SPSS Statistics, 2011 ), and the sempackage for R ( R Development Core Team, 2005 ), the use of which is described by Fox ( Fox, 2006 ). A number of stand-alone software options are also available for SEM applications, including Mplus ( L. K. Muthén & Muthén, 2010 ) and Stata ( StataCorp., 2011 ). Each of these programs also provides options for estimating multilevel/hierarchical models (for a review of using these programs for MLM analysis see Albright & Marinova, 2010 ). Hierarchical linear and nonlinear modeling can also be accomplished using the HLM 7 program ( Raudenbush, Bryk, & Congdon, 2011 ).

Autoregressive moving averages (ARMA; e.g., Browne & Nesselroade, 2005 ; Liu & Hudack, 1995 ; Tiao & Box, 1981 )

Two primary points have been raised regarding ARMA modeling: length of the data stream and feasibility of the modeling technique. ARMA models generally require 30–50 observations in each phase when analyzing a single-subject experiment (e.g., Borckardt et al., 2008 ; Box & Jenkins, 1970 ), which is often difficult to satisfy in applied psychological research applications. However, ARMA models in an SEM framework, such as those described by du Toit & Browne (2001) , are well suited for longitudinal panel data with few observations and many subjects. Autoregressive SEM models are also applicable under similar conditions. Model-fitting options are available in SPSS, R, and SAS via PROC ARMA.

ARMA modeling also requires considerable training in the method and rather advanced knowledge about statistical methods (e.g., Kratochwill & Levin, 1992 ). However, Brossart et al. (2006) point out that ARMA-based approaches can produce excellent results when there is no “model finding” and a simple lag-1 model, with no differencing and no moving average, is used. This approach can be taken for many SCED applications when phase- or slope-change analyses are of interest with a single, or very few, subjects. As already mentioned, this method is particularly useful when one is seeking to account for autocorrelation or other over-time variations that are not directly related to the experimental or intervention effect of interest (i.e., detrending). ARMA and other time-series analysis methods require missing data to be managed prior to analysis by means of options such as full information maximum likelihood estimation, multiple imputation, or the Kalman filter (see Box & Jenkins, 1970 ; Hamilton, 1994 ; Shumway & Stoffer, 1982 ) because listwise deletion has been shown to result in inaccurate time-series parameter estimates ( Velicer & Colby, 2005a ).

Standardized mean differences

Standardized mean differences approaches include the common Cohen’s d , Glass’s Delta, and Hedge’s g that are used in the analysis of group designs. The computational properties of mean differences approaches to SCEDs are identical to those used for group comparisons, except that the results represent within-case variation instead of the variation between groups, which suggests that the obtained effect sizes are not interpretively equivalent. The advantage of the mean differences approach is its simplicity of calculation and also its familiarity to social scientists. The primary drawback of these approaches is that they were not developed to contend with autocorrelated data. However, Manolov and Solanas (2008) reported that autocorrelation least affected effect sizes calculated using standardized mean differences approaches. To the applied-research scientist this likely represents the most accessible analytic approach, because statistical software is not required to calculate these effect sizes. The resultant effect sizes of single subject standardized mean differences analysis must be interpreted cautiously because their relation to standard effect size benchmarks, such as those provided by Cohen (1988) , is unknown. Standardized mean differences approaches are appropriate only when examining significant differences between phases of the study and cannot illuminate trajectories or relationships between variables.

Other analytic approaches

Researchers have offered other analytic methods to deal with the characteristics of SCED data. A number of methods for analyzing N -of-1 experiments have been developed. Borckardt’s Simulation Modeling Analysis (2006) program provides a method for analyzing level- and slope-change in short (<30 observations per phase; see Borckardt et al., 2008 ), autocorrelated data streams that is statistically sophisticated, yet accessible and freely available to typical psychological scientists and clinicians. A replicated single-case time-series design conducted by Smith, Handler, & Nash (2010) provides an example of SMA application. The Singwin Package, described in Bloom et al., (2003) , is a another easy-to-use parametric approach for analyzing single-case experiments. A number of nonparametric approaches have also been developed that emerged from the visual analysis tradition: Some examples include percent nonoverlapping data ( Scruggs, Mastropieri, & Casto, 1987 ) and nonoverlap of all pairs ( Parker & Vannest, 2009 ); however, these methods have come under scrutiny, and Wolery, Busick, Reichow, and Barton (2010) have suggested abandoning them altogether. Each of these methods appears to be well suited for managing specific data characteristics, but they should not be used to analyze data streams beyond their intended purpose until additional empirical research is conducted.

Combining SCED Results

Beyond the issue of single-case analysis is the matter of integrating and meta-analyzing the results of single-case experiments. SCEDs have been given short shrift in the majority of meta-analytic literature ( Littell, Corcoran, & Pillai, 2008 ; Shadish et al., 2008 ), with only a few exceptions ( Carr et al., 1999 ; Horner & Spaulding, 2010 ). Currently, few proven methods exist for integrating the results of multiple single-case experiments. Allison and Gorman (1993) and Shadish et al. (2008) present the problems associated with meta-analyzing single-case effect sizes, and W. P. Jones (2003) , Manolov and Solanas (2008) , Scruggs and Mastropieri (1998) , and Shadish et al. (2008) offer four different potential statistical solutions for this problem, none of which appear to have received consensus amongst researchers. The ability to synthesize and compare single-case effect sizes, particularly effect sizes garnered through group design research, is undoubtedly necessary to increase SCED proliferation.

Discussion of Review Results and Coding of Analytic Methods

The coding criteria for this review were quite stringent in terms of what was considered to be either visual or statistical analysis. For visual analysis to be coded as present, it was necessary for the authors to self-identify as having used a visual analysis method. In many cases, it could likely be inferred that visual analysis had been used, but it was often not specified. Similarly, statistical analysis was reserved for analytic methods that produced an effect. 3 Analyses that involved comparing magnitude of change using raw count data or percentages were not considered rigorous enough. These two narrow definitions of visual and statistical analysis contributed to the high rate of unreported analytic method, shown in Table 1 (52.3%). A better representation of the use of visual and statistical analysis would likely be the percentage of studies within those that reported a method of analysis. Under these parameters, 41.5% used visual analysis and 31.3% used statistical analysis. Included in these figures are studies that included both visual and statistical methods (11%). These findings are slightly higher than those estimated by Brossart et al. (2006) , who estimated statistical analysis is used in about 20% of SCED studies. Visual analysis continues to undoubtedly be the most prevalent method, but there appears to be a trend for increased use of statistical approaches, which is likely to only gain momentum as innovations continue.

Analysis Standards

The standards selected for inclusion in this review offer minimal direction in the way of analyzing the results of SCED research. Table 5 summarizes analysis-related information provided by the six reviewed sources for SCED standards. Visual analysis is acceptable to DV12 and DIV16, along with unspecified statistical approaches. In the WWC standards, visual analysis is the acceptable method of determining an intervention effect, with statistical analyses and randomization tests permissible as a complementary or supporting method to the results of visual analysis methods. However, the authors of the WWC standards state, “As the field reaches greater consensus about appropriate statistical analyses and quantitative effect-size measures, new standards for effect demonstration will need to be developed” ( Kratochwill et al., 2010 , p.16). The NRP and DIV12 seem to prefer statistical methods when they are warranted. The Tate at al. scale accepts only statistical analysis with the reporting of an effect size. Only the WWC and DIV16 provide guidance in the use of statistical analysis procedures: The WWC “recommends” nonparametric and parametric approaches, multilevel modeling, and regression when statistical analysis is used. DIV16 refers the reader to Wilkinson and the Task Force on Statistical Inference of the APA Board of Scientific Affairs (1999) for direction in this matter. Statistical analysis of daily diary and EMA methods is similarly unsettled. Stone and Shiffman (2002) ask for a detailed description of the statistical procedures used, in order for the approach to be replicated and evaluated. They provide direction for analyzing aggregated and disaggregated data. They also aptly note that because many different modes of analysis exist, researchers must carefully match the analytic approach to the hypotheses being pursued.

Limitations and Future Directions

This review has a number of limitations that leave the door open for future study of SCED methodology. Publication bias is a concern in any systematic review. This is particularly true for this review because the search was limited to articles published in peer-reviewed journals. This strategy was chosen in order to inform changes in the practice of reporting and of reviewing, but it also is likely to have inflated the findings regarding the methodological rigor of the reviewed works. Inclusion of book chapters, unpublished studies, and dissertations would likely have yielded somewhat different results.

A second concern is the stringent coding criteria in regard to the analytic methods and the broad categorization into visual and statistical analytic approaches. The selection of an appropriate method for analyzing SCED data is perhaps the murkiest area of this type of research. Future reviews that evaluate the appropriateness of selected analytic strategies and provide specific decision-making guidelines for researchers would be a very useful contribution to the literature. Although six sources of standards apply to SCED research reviewed in this article, five of them were developed almost exclusively to inform psychological and behavioral intervention research. The principles of SCED research remain the same in different contexts, but there is a need for non–intervention scientists to weigh in on these standards.

Finally, this article provides a first step in the synthesis of the available SCED reporting guidelines. However, it does not resolve disagreements, nor does it purport to be a definitive source. In the future, an entity with the authority to construct such a document ought to convene and establish a foundational, adaptable, and agreed-upon set of guidelines that cuts across subspecialties but is applicable to many, if not all, areas of psychological research, which is perhaps an idealistic goal. Certain preferences will undoubtedly continue to dictate what constitutes acceptable practice in each subspecialty of psychology, but uniformity along critical dimensions will help advance SCED research.

Conclusions

The first decade of the twenty-first century has seen an upwelling of SCED research across nearly all areas of psychology. This article contributes updated benchmarks in terms of the frequency with which SCED design and methodology characteristics are used, including the number of baseline observations, assessment and measurement practices, and data analytic approaches, most of which are largely consistent with previously reported benchmarks. However, this review is much broader than those of previous research teams and also breaks down the characteristics of single-case research by the predominant design. With the recent SCED proliferation came a number of standards for the conduct and reporting of such research. This article also provides a much-needed synthesis of recent SCED standards that can inform the work of researchers, reviewers, and funding agencies conducting and evaluating single-case research, which reveals many areas of consensus as well as areas of significant disagreement. It appears that the question of where to go next is very relevant at this point in time. The majority of the research design and measurement characteristics of the SCED are reasonably well established, and the results of this review suggest general practice that is in accord with existing standards and guidelines, at least in regard to published peer-reviewed works. In general, the published literature appears to be meeting the basic design and measurement requirement to ensure adequate internal validity of SCED studies.

Consensus regarding the superiority of any one analytic method stands out as an area of divergence. Judging by the current literature and lack of consensus, researchers will need to carefully select a method that matches the research design, hypotheses, and intended conclusions of the study, while also considering the most up-to-date empirical support for the chosen analytic method, whether it be visual or statistical. In some cases the number of observations and subjects in the study will dictate which analytic methods can and cannot be used. In the case of the true N -of-1 experiment, there are relatively few sound analytic methods, and even fewer that are robust with shorter data streams (see Borckardt et al., 2008 ). As the number of observations and subjects increases, sophisticated modeling techniques, such as MLM, SEM, and ARMA, become applicable. Trends in the data and autocorrelation further obfuscate the development of a clear statistical analysis selection algorithm, which currently does not exist. Autocorrelation was rarely addressed or discussed in the articles reviewed, except when the selected statistical analysis dictated consideration. Given the empirical evidence regarding the effect of autocorrelation on visual and statistical analysis, researchers need to address this more explicitly. Missing-data considerations are similarly left out when they are unnecessary for analytic purposes. As newly devised statistical analysis approaches mature and are compared with one another for appropriateness in specific SCED applications, guidelines for statistical analysis will necessarily be revised. Similarly, empirically derived guidance, in the form of a decision tree, must be developed to ensure application of appropriate methods based on characteristics of the data and the research questions being addressed. Researchers could also benefit from tutorials and comparative reviews of different software packages: This is a needed area of future research. Powerful and reliable statistical analyses help move the SCED up the ladder of experimental designs and attenuate the view that the method applies primarily to pilot studies and idiosyncratic research questions and situations.

Another potential future advancement of SCED research comes in the area of measurement. Currently, SCED research gives significant weight to observer ratings and seems to discourage other forms of data collection methods. This is likely due to the origins of the SCED in behavioral assessment and applied behavior analysis, which remains a present-day stronghold. The dearth of EMA and diary-like sampling procedures within the SCED research reviewed, yet their ever-growing prevalence in the larger psychological research arena, highlights an area for potential expansion. Observational measurement, although reliable and valid in many contexts, is time and resource intensive and not feasible in all areas in which psychologists conduct research. It seems that numerous untapped research questions are stifled because of this measurement constraint. SCED researchers developing updated standards in the future should include guidelines for the appropriate measurement requirement of non-observer-reported data. For example, the results of this review indicate that reporting of repeated measurements, particularly the high-density type found in diary and EMA sampling strategies, ought to be more clearly spelled out, with specific attention paid to autocorrelation and trend in the data streams. In the event that SCED researchers adopt self-reported assessment strategies as viable alternatives to observation, a set of standards explicitly identifying the necessary psychometric properties of the measures and specific items used would be in order.

Along similar lines, SCED researchers could take a page from other areas of psychology that champion multimethod and multisource evaluation of primary outcomes. In this way, the long-standing tradition of observational assessment and the cutting-edge technological methods of EMA and daily diary could be married with the goal of strengthening conclusions drawn from SCED research and enhancing the validity of self-reported outcome assessment. The results of this review indicate that they rarely intersect today, and I urge SCED researchers to adopt other methods of assessment informed by time-series, daily diary, and EMA methods. The EMA standards could serve as a jumping-off point for refined measurement and assessment reporting standards in the context of multimethod SCED research.

One limitation of the current SCED standards is their relatively limited scope. To clarify, with the exception of the Stone & Shiffman EMA reporting guidelines, the other five sources of standards were developed in the context of designing and evaluating intervention research. Although this is likely to remain its patent emphasis, SCEDs are capable of addressing other pertinent research questions in the psychological sciences, and the current standards truly only roughly approximate salient crosscutting SCED characteristics. I propose developing broad SCED guidelines that address the specific design, measurement, and analysis issues in a manner that allows it to be useful across applications, as opposed to focusing solely on intervention effects. To accomplish this task, methodology experts across subspecialties in psychology would need to convene. Admittedly this is no small task.

Perhaps funding agencies will also recognize the fiscal and practical advantages of SCED research in certain areas of psychology. One example is in the field of intervention effectiveness, efficacy, and implementation research. A few exemplary studies using robust forms of SCED methodology are needed in the literature. Case-based methodologies will never supplant the group design as the gold standard in experimental applications, nor should that be the goal. Instead, SCEDs provide a viable and valid alternative experimental methodology that could stimulate new areas of research and answer questions that group designs cannot. With the astonishing number of studies emerging every year that use single-case designs and explore the methodological aspects of the design, we are poised to witness and be a part of an upsurge in the sophisticated application of the SCED. When federal grant-awarding agencies and journal editors begin to use formal standards while making funding and publication decisions, the field will benefit.

Last, for the practice of SCED research to continue and mature, graduate training programs must provide students with instruction in all areas of the SCED. This is particularly true of statistical analysis techniques that are not often taught in departments of psychology and education, where the vast majority of SCED studies seem to be conducted. It is quite the conundrum that the best available statistical analytic methods are often cited as being inaccessible to social science researchers who conduct this type of research. This need not be the case. To move the field forward, emerging scientists must be able to apply the most state-of-the-art research designs, measurement techniques, and analytic methods.

Acknowledgments

Research support for the author was provided by research training grant MH20012 from the National Institute of Mental Health, awarded to Elizabeth A. Stormshak. The author gratefully acknowledges Robert Horner and Laura Lee McIntyre, University of Oregon; Michael Nash, University of Tennessee; John Ferron, University of South Florida; the Action Editor, Lisa Harlow, and the anonymous reviewers for their thoughtful suggestions and guidance in shaping this article; Cheryl Mikkola for her editorial support; and Victoria Mollison for her assistance in the systematic review process.

Appendix. Results of Systematic Review Search and Studies Included in the Review

Psycinfo search conducted july 2011.

• Alternating treatment design
• Changing criterion design
• Experimental case*
• Multiple baseline design
• Replicated single-case design
• Simultaneous treatment design
• Time-series design
• Quantitative study OR treatment outcome/randomized clinical trial
• NOT field study OR interview OR focus group OR literature review OR systematic review OR mathematical model OR qualitative study
• Publication range: 2000–2010
• Published in peer-reviewed journals
• Available in the English Language

Bibliography

(* indicates inclusion in study: N = 409)

1 Autocorrelation estimates in this range can be caused by trends in the data streams, which creates complications in terms of detecting level-change effects. The Smith et al. (in press) study used a Monte Carlo simulation to control for trends in the data streams, but trends are likely to exist in real-world data with high lag-1 autocorrelation estimates.

2 The author makes no endorsement regarding the superiority of any statistical program or package over another by their mention or exclusion in this article. The author also has no conflicts of interest in this regard.

3 However, it should be noted that it was often very difficult to locate an actual effect size reported in studies that used statistical analysis. Although this issue would likely have added little to this review, it does inhibit the inclusion of the results in meta-analysis.

• Albright JJ, Marinova DM. Estimating multilevel modelsuUsing SPSS, Stata, and SAS. Indiana University; 2010. Retrieved from http://www.iub.edu/%7Estatmath/stat/all/hlm/hlm.pdf . [ Google Scholar ]
• Allison DB, Gorman BS. Calculating effect sizes for meta-analysis: The case of the single case. Behavior Research and Therapy. 1993; 31 (6):621–631. doi: 10.1016/0005-7967(93)90115-B. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Alloy LB, Just N, Panzarella C. Attributional style, daily life events, and hopelessness depression: Subtype validation by prospective variability and specificity of symptoms. Cognitive Therapy Research. 1997; 21 :321–344. doi: 10.1023/A:1021878516875. [ CrossRef ] [ Google Scholar ]
• Arbuckle JL. Amos (Version 7.0) Chicago, IL: SPSS, Inc; 2006. [ Google Scholar ]
• Barlow DH, Nock MK, Hersen M. Single case research designs: Strategies for studying behavior change. 3. New York, NY: Allyn and Bacon; 2008. [ Google Scholar ]
• Barrett LF, Barrett DJ. An introduction to computerized experience sampling in psychology. Social Science Computer Review. 2001; 19 (2):175–185. doi: 10.1177/089443930101900204. [ CrossRef ] [ Google Scholar ]
• Bloom M, Fisher J, Orme JG. Evaluating practice: Guidelines for the accountable professional. 4. Boston, MA: Allyn & Bacon; 2003. [ Google Scholar ]
• Bolger N, Davis A, Rafaeli E. Diary methods: Capturing life as it is lived. Annual Review of Psychology. 2003; 54 :579–616. doi: 10.1146/annurev.psych.54.101601.145030. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Borckardt JJ. Simulation Modeling Analysis: Time series analysis program for short time series data streams (Version 8.3.3) Charleston, SC: Medical University of South Carolina; 2006. [ Google Scholar ]
• Borckardt JJ, Nash MR, Murphy MD, Moore M, Shaw D, O’Neil P. Clinical practice as natural laboratory for psychotherapy research. American Psychologist. 2008; 63 :1–19. doi: 10.1037/0003-066X.63.2.77. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Borsboom D, Mellenbergh GJ, van Heerden J. The theoretical status of latent variables. Psychological Review. 2003; 110 (2):203–219. doi: 10.1037/0033-295X.110.2.203. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bower GH. Mood and memory. American Psychologist. 1981; 36 (2):129–148. doi: 10.1037/0003-066x.36.2.129. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Box GEP, Jenkins GM. Time-series analysis: Forecasting and control. San Francisco, CA: Holden-Day; 1970. [ Google Scholar ]
• Brossart DF, Parker RI, Olson EA, Mahadevan L. The relationship between visual analysis and five statistical analyses in a simple AB single-case research design. Behavior Modification. 2006; 30 (5):531–563. doi: 10.1177/0145445503261167. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Browne MW, Nesselroade JR. Representing psychological processes with dynamic factor models: Some promising uses and extensions of autoregressive moving average time series models. In: Maydeu-Olivares A, McArdle JJ, editors. Contemporary psychometrics: A festschrift for Roderick P McDonald. Mahwah, NJ: Lawrence Erlbaum Associates Publishers; 2005. pp. 415–452. [ Google Scholar ]
• Busk PL, Marascuilo LA. Statistical analysis in single-case research: Issues, procedures, and recommendations, with applications to multiple behaviors. In: Kratochwill TR, Levin JR, editors. Single-case research design and analysis: New directions for psychology and education. Hillsdale, NJ, England: Lawrence Erlbaum Associates, Inc; 1992. pp. 159–185. [ Google Scholar ]
• Busk PL, Marascuilo RC. Autocorrelation in single-subject research: A counterargument to the myth of no autocorrelation. Behavioral Assessment. 1988; 10 :229–242. [ Google Scholar ]
• Campbell JM. Statistical comparison of four effect sizes for single-subject designs. Behavior Modification. 2004; 28 (2):234–246. doi: 10.1177/0145445503259264. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Carr EG, Horner RH, Turnbull AP, Marquis JG, Magito McLaughlin D, McAtee ML, Doolabh A. Positive behavior support for people with developmental disabilities: A research synthesis. Washington, DC: American Association on Mental Retardation; 1999. [ Google Scholar ]
• Center BA, Skiba RJ, Casey A. A methodology for the quantitative synthesis of intra-subject design research. Journal of Educational Science. 1986; 19 :387–400. doi: 10.1177/002246698501900404. [ CrossRef ] [ Google Scholar ]
• Chambless DL, Hollon SD. Defining empirically supported therapies. Journal of Consulting and Clinical Psychology. 1998; 66 (1):7–18. doi: 10.1037/0022-006X.66.1.7. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Chambless DL, Ollendick TH. Empirically supported psychological interventions: Controversies and evidence. Annual Review of Psychology. 2001; 52 :685–716. doi: 10.1146/annurev.psych.52.1.685. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Chow S-M, Ho M-hR, Hamaker EL, Dolan CV. Equivalence and differences between structural equation modeling and state-space modeling techniques. Structural Equation Modeling. 2010; 17 (2):303–332. doi: 10.1080/10705511003661553. [ CrossRef ] [ Google Scholar ]
• Cohen J. Statistical power analysis for the bahavioral sciences. 2. Hillsdale, NJ: Erlbaum; 1988. [ Google Scholar ]
• Cohen J. The earth is round (p < .05) American Psychologist. 1994; 49 :997–1003. doi: 10.1037/0003-066X.49.12.997. [ CrossRef ] [ Google Scholar ]
• Crosbie J. Interrupted time-series analysis with brief single-subject data. Journal of Consulting and Clinical Psychology. 1993; 61 (6):966–974. doi: 10.1037/0022-006X.61.6.966. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Dattilio FM, Edwards JA, Fishman DB. Case studies within a mixed methods paradigm: Toward a resolution of the alienation between researcher and practitioner in psychotherapy research. Psychotherapy: Theory, Research, Practice, Training. 2010; 47 (4):427–441. doi: 10.1037/a0021181. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Dempster A, Laird N, Rubin DB. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, Series B. 1977; 39 (1):1–38. [ Google Scholar ]
• Des Jarlais DC, Lyles C, Crepaz N. Improving the reporting quality of nonrandomized evaluations of behavioral and public health interventions: the TREND statement. American Journal of Public Health. 2004; 94 (3):361–366. doi: 10.2105/ajph.94.3.361. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Diggle P, Liang KY. Analyses of longitudinal data. New York: Oxford University Press; 2001. [ Google Scholar ]
• Doss BD, Atkins DC. Investigating treatment mediators when simple random assignment to a control group is not possible. Clinical Psychology: Science and Practice. 2006; 13 (4):321–336. doi: 10.1111/j.1468-2850.2006.00045.x. [ CrossRef ] [ Google Scholar ]
• du Toit SHC, Browne MW. The covariance structure of a vector ARMA time series. In: Cudeck R, du Toit SHC, Sörbom D, editors. Structural equation modeling: Present and future. Lincolnwood, IL: Scientific Software International; 2001. pp. 279–314. [ Google Scholar ]
• du Toit SHC, Browne MW. Structural equation modeling of multivariate time series. Multivariate Behavioral Research. 2007; 42 :67–101. doi: 10.1080/00273170701340953. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Fechner GT. Elemente der psychophysik [Elements of psychophysics] Leipzig, Germany: Breitkopf & Hartel; 1889. [ Google Scholar ]
• Ferron J, Sentovich C. Statistical power of randomization tests used with multiple-baseline designs. The Journal of Experimental Education. 2002; 70 :165–178. doi: 10.1080/00220970209599504. [ CrossRef ] [ Google Scholar ]
• Ferron J, Ware W. Analyzing single-case data: The power of randomization tests. The Journal of Experimental Education. 1995; 63 :167–178. [ Google Scholar ]
• Fox J. TEACHER’S CORNER: Structural equation modeling with the sem package in R. Structural Equation Modeling: A Multidisciplinary Journal. 2006; 13 (3):465–486. doi: 10.1207/s15328007sem1303_7. [ CrossRef ] [ Google Scholar ]
• Franklin RD, Allison DB, Gorman BS, editors. Design and analysis of single-case research. Mahwah, NJ: Lawrence Erlbaum Associates; 1997. [ Google Scholar ]
• Franklin RD, Gorman BS, Beasley TM, Allison DB. Graphical display and visual analysis. In: Franklin RD, Allison DB, Gorman BS, editors. Design and analysis of single-case research. Mahway, NJ: Lawrence Erlbaum Associates, Publishers; 1997. pp. 119–158. [ Google Scholar ]
• Gardner W, Mulvey EP, Shaw EC. Regression analyses of counts and rates: Poisson, overdispersed Poisson, and negative binomial models. Psychological Bulletin. 1995; 118 (3):392–404. doi: 10.1037/0033-2909.118.3.392. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Green AS, Rafaeli E, Bolger N, Shrout PE, Reis HT. Paper or plastic? Data equivalence in paper and electronic diaries. Psychological Methods. 2006; 11 (1):87–105. doi: 10.1037/1082-989X.11.1.87. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hamilton JD. Time series analysis. Princeton, NJ: Princeton University Press; 1994. [ Google Scholar ]
• Hammond D, Gast DL. Descriptive analysis of single-subject research designs: 1983–2007. Education and Training in Autism and Developmental Disabilities. 2010; 45 :187–202. [ Google Scholar ]
• Hanson MD, Chen E. Daily stress, cortisol, and sleep: The moderating role of childhood psychosocial environments. Health Psychology. 2010; 29 (4):394–402. doi: 10.1037/a0019879. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Harvey AC. Forecasting, structural time series models and the Kalman filter. Cambridge, MA: Cambridge University Press; 2001. [ Google Scholar ]
• Horner RH, Carr EG, Halle J, McGee G, Odom S, Wolery M. The use of single-subject research to identify evidence-based practice in special education. Exceptional Children. 2005; 71 :165–179. [ Google Scholar ]
• Horner RH, Spaulding S. Single-case research designs. In: Salkind NJ, editor. Encyclopedia of research design. Thousand Oaks, CA: Sage Publications; 2010. [ Google Scholar ]
• Horton NJ, Kleinman KP. Much ado about nothing: A comparison of missing data methods and software to fit incomplete data regression models. The American Statistician. 2007; 61 (1):79–90. doi: 10.1198/000313007X172556. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hser Y, Shen H, Chou C, Messer SC, Anglin MD. Analytic approaches for assessing long-term treatment effects. Evaluation Review. 2001; 25 (2):233–262. doi: 10.1177/0193841X0102500206. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Huitema BE. Autocorrelation in applied behavior analysis: A myth. Behavioral Assessment. 1985; 7 (2):107–118. [ Google Scholar ]
• Huitema BE, McKean JW. Reduced bias autocorrelation estimation: Three jackknife methods. Educational and Psychological Measurement. 1994; 54 (3):654–665. doi: 10.1177/0013164494054003008. [ CrossRef ] [ Google Scholar ]
• Ibrahim JG, Chen M-H, Lipsitz SR, Herring AH. Missing-data methods for generalized linear models: A comparative review. Journal of the American Statistical Association. 2005; 100 (469):332–346. doi: 10.1198/016214504000001844. [ CrossRef ] [ Google Scholar ]
• Institute of Medicine. Reducing risks for mental disorders: Frontiers for preventive intervention research. Washington, DC: National Academy Press; 1994. [ PubMed ] [ Google Scholar ]
• Jacobsen NS, Christensen A. Studying the effectiveness of psychotherapy: How well can clinical trials do the job? American Psychologist. 1996; 51 :1031–1039. doi: 10.1037/0003-066X.51.10.1031. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Jones RR, Vaught RS, Weinrott MR. Time-series analysis in operant research. Journal of Behavior Analysis. 1977; 10 (1):151–166. doi: 10.1901/jaba.1977.10-151. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Jones WP. Single-case time series with Bayesian analysis: A practitioner’s guide. Measurement and Evaluation in Counseling and Development. 2003; 36 (28–39) [ Google Scholar ]
• Kanfer H. Self-monitoring: Methodological limitations and clinical applications. Journal of Consulting and Clinical Psychology. 1970; 35 (2):148–152. doi: 10.1037/h0029874. [ CrossRef ] [ Google Scholar ]
• Kazdin AE. Drawing valid inferences from case studies. Journal of Consulting and Clinical Psychology. 1981; 49 (2):183–192. doi: 10.1037/0022-006X.49.2.183. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kazdin AE. Mediators and mechanisms of change in psychotherapy research. Annual Review of Clinical Psychology. 2007; 3 :1–27. doi: 10.1146/annurev.clinpsy.3.022806.091432. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kazdin AE. Evidence-based treatment and practice: New opportunities to bridge clinical research and practice, enhance the knowledge base, and improve patient care. American Psychologist. 2008; 63 (3):146–159. doi: 10.1037/0003-066X.63.3.146. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kazdin AE. Understanding how and why psychotherapy leads to change. Psychotherapy Research. 2009; 19 (4):418–428. doi: 10.1080/10503300802448899. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kazdin AE. Single-case research designs: Methods for clinical and applied settings. 2. New York, NY: Oxford University Press; 2010. [ Google Scholar ]
• Kirk RE. Practical significance: A concept whose time has come. Educational and Psychological Measurement. 1996; 56 :746–759. doi: 10.1177/0013164496056005002. [ CrossRef ] [ Google Scholar ]
• Kratochwill TR. Preparing psychologists for evidence-based school practice: Lessons learned and challenges ahead. American Psychologist. 2007; 62 :829–843. doi: 10.1037/0003-066X.62.8.829. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kratochwill TR, Hitchcock J, Horner RH, Levin JR, Odom SL, Rindskopf DM, Shadish WR. Single-case designs technical documentation. 2010 Retrieved from What Works Clearinghouse website: http://ies.ed.gov/ncee/wwc/pdf/wwc_scd.pdf . Retrieved from http://ies.ed.gov/ncee/wwc/pdf/wwc_scd.pdf .
• Kratochwill TR, Levin JR. Single-case research design and analysis: New directions for psychology and education. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc; 1992. [ Google Scholar ]
• Kratochwill TR, Levin JR. Enhancing the scientific credibility of single-case intervention research: Randomization to the rescue. Psychological Methods. 2010; 15 (2):124–144. doi: 10.1037/a0017736. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kratochwill TR, Levin JR, Horner RH, Swoboda C. Visual analysis of single-case intervention research: Conceptual and methodological considerations (WCER Working Paper No. 2011-6) 2011 Retrieved from University of Wisconsin–Madison, Wisconsin Center for Education Research website: http://www.wcer.wisc.edu/publications/workingPapers/papers.php .
• Lambert D. Zero-inflated poisson regression, with an application to defects in manufacturing. Technometrics. 1992; 34 (1):1–14. [ Google Scholar ]
• Lambert MJ, Hansen NB, Harmon SC. Developing and Delivering Practice-Based Evidence. John Wiley & Sons, Ltd; 2010. Outcome Questionnaire System (The OQ System): Development and practical applications in healthcare settings; pp. 139–154. [ Google Scholar ]
• Littell JH, Corcoran J, Pillai VK. Systematic reviews and meta-analysis. New York: Oxford University Press; 2008. [ Google Scholar ]
• Liu LM, Hudack GB. The SCA statistical system. Vector ARMA modeling of multiple time series. Oak Brook, IL: Scientific Computing Associates Corporation; 1995. [ Google Scholar ]
• Lubke GH, Muthén BO. Investigating population heterogeneity with factor mixture models. Psychological Methods. 2005; 10 (1):21–39. doi: 10.1037/1082-989x.10.1.21. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Manolov R, Solanas A. Comparing N = 1 effect sizes in presence of autocorrelation. Behavior Modification. 2008; 32 (6):860–875. doi: 10.1177/0145445508318866. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Marshall RJ. Autocorrelation estimation of time series with randomly missing observations. Biometrika. 1980; 67 (3):567–570. doi: 10.1093/biomet/67.3.567. [ CrossRef ] [ Google Scholar ]
• Matyas TA, Greenwood KM. Visual analysis of single-case time series: Effects of variability, serial dependence, and magnitude of intervention effects. Journal of Applied Behavior Analysis. 1990; 23 (3):341–351. doi: 10.1901/jaba.1990.23-341. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kratochwill TR, Chair Members of the Task Force on Evidence-Based Interventions in School Psychology. Procedural and coding manual for review of evidence-based interventions. 2003 Retrieved July 18, 2011 from http://www.sp-ebi.org/documents/_workingfiles/EBImanual1.pdf .
• Moher D, Schulz KF, Altman DF the CONSORT Group. The CONSORT statement: Revised recommendations for improving the quality of reports of parallel-group randomized trials. Journal of the American Medical Association. 2001; 285 :1987–1991. doi: 10.1001/jama.285.15.1987. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Morgan DL, Morgan RK. Single-participant research design: Bringing science to managed care. American Psychologist. 2001; 56 (2):119–127. doi: 10.1037/0003-066X.56.2.119. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Muthén BO, Curran PJ. General longitudinal modeling of individual differences in experimental designs: A latent variable framework for analysis and power estimation. Psychological Methods. 1997; 2 (4):371–402. doi: 10.1037/1082-989x.2.4.371. [ CrossRef ] [ Google Scholar ]
• Muthén LK, Muthén BO. Mplus (Version 6.11) Los Angeles, CA: Muthén & Muthén; 2010. [ Google Scholar ]
• Nagin DS. Analyzing developmental trajectories: A semiparametric, group-based approach. Psychological Methods. 1999; 4 (2):139–157. doi: 10.1037/1082-989x.4.2.139. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• National Institute of Child Health and Human Development. Report of the National Reading Panel. Teaching children to read: An evidence-based assessment of the scientific research literature on reading and its implications for reading instruction (NIH Publication No. 00-4769) Washington, DC: U.S. Government Printing Office; 2000. [ Google Scholar ]
• Olive ML, Smith BW. Effect size calculations and single subject designs. Educational Psychology. 2005; 25 (2–3):313–324. doi: 10.1080/0144341042000301238. [ CrossRef ] [ Google Scholar ]
• Oslin DW, Cary M, Slaymaker V, Colleran C, Blow FC. Daily ratings measures of alcohol craving during an inpatient stay define subtypes of alcohol addiction that predict subsequent risk for resumption of drinking. Drug and Alcohol Dependence. 2009; 103 (3):131–136. doi: 10.1016/J.Drugalcdep.2009.03.009. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Palermo TP, Valenzuela D, Stork PP. A randomized trial of electronic versus paper pain diaries in children: Impact on compliance, accuracy, and acceptability. Pain. 2004; 107 (3):213–219. doi: 10.1016/j.pain.2003.10.005. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Parker RI, Brossart DF. Evaluating single-case research data: A comparison of seven statistical methods. Behavior Therapy. 2003; 34 (2):189–211. doi: 10.1016/S0005-7894(03)80013-8. [ CrossRef ] [ Google Scholar ]
• Parker RI, Cryer J, Byrns G. Controlling baseline trend in single case research. School Psychology Quarterly. 2006; 21 (4):418–440. doi: 10.1037/h0084131. [ CrossRef ] [ Google Scholar ]
• Parker RI, Vannest K. An improved effect size for single-case research: Nonoverlap of all pairs. Behavior Therapy. 2009; 40 (4):357–367. doi: 10.1016/j.beth.2008.10.006. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Parsonson BS, Baer DM. The analysis and presentation of graphic data. In: Kratochwill TR, editor. Single subject research. New York, NY: Academic Press; 1978. pp. 101–166. [ Google Scholar ]
• Parsonson BS, Baer DM. The visual analysis of data, and current research into the stimuli controlling it. In: Kratochwill TR, Levin JR, editors. Single-case research design and analysis: New directions for psychology and education. Hillsdale, NJ; England: Lawrence Erlbaum Associates, Inc; 1992. pp. 15–40. [ Google Scholar ]
• Piasecki TM, Hufford MR, Solham M, Trull TJ. Assessing clients in their natural environments with electronic diaries: Rationale, benefits, limitations, and barriers. Psychological Assessment. 2007; 19 (1):25–43. doi: 10.1037/1040-3590.19.1.25. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• R Development Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2005. [ Google Scholar ]
• Ragunathan TE. What do we do with missing data? Some options for analysis of incomplete data. Annual Review of Public Health. 2004; 25 :99–117. doi: 10.1146/annurev.publhealth.25.102802.124410. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Raudenbush SW, Bryk AS, Congdon R. HLM 7 Hierarchical Linear and Nonlinear Modeling. Scientific Software International, Inc; 2011. [ Google Scholar ]
• Redelmeier DA, Kahneman D. Patients’ memories of painful medical treatments: Real-time and retrospective evaluations of two minimally invasive procedures. Pain. 1996; 66 (1):3–8. doi: 10.1016/0304-3959(96)02994-6. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Reis HT. Domains of experience: Investigating relationship processes from three perspectives. In: Erber R, Gilmore R, editors. Theoretical frameworks in personal relationships. Mahwah, NJ: Erlbaum; 1994. pp. 87–110. [ Google Scholar ]
• Reis HT, Gable SL. Event sampling and other methods for studying everyday experience. In: Reis HT, Judd CM, editors. Handbook of research methods in social and personality psychology. New York, NY: Cambridge University Press; 2000. pp. 190–222. [ Google Scholar ]
• Robey RR, Schultz MC, Crawford AB, Sinner CA. Single-subject clinical-outcome research: Designs, data, effect sizes, and analyses. Aphasiology. 1999; 13 (6):445–473. doi: 10.1080/026870399402028. [ CrossRef ] [ Google Scholar ]
• Rossi PH, Freeman HE. Evaluation: A systematic approach. 5. Thousand Oaks, CA: Sage; 1993. [ Google Scholar ]
• SAS Institute Inc. The SAS system for Windows, Version 9. Cary, NC: SAS Institute Inc; 2008. [ Google Scholar ]
• Schmidt M, Perels F, Schmitz B. How to perform idiographic and a combination of idiographic and nomothetic approaches: A comparison of time series analyses and hierarchical linear modeling. Journal of Psychology. 2010; 218 (3):166–174. doi: 10.1027/0044-3409/a000026. [ CrossRef ] [ Google Scholar ]
• Scollon CN, Kim-Pietro C, Diener E. Experience sampling: Promises and pitfalls, strengths and weaknesses. Assessing Well-Being. 2003; 4 :5–35. doi: 10.1007/978-90-481-2354-4_8. [ CrossRef ] [ Google Scholar ]
• Scruggs TE, Mastropieri MA. Summarizing single-subject research: Issues and applications. Behavior Modification. 1998; 22 (3):221–242. doi: 10.1177/01454455980223001. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Scruggs TE, Mastropieri MA, Casto G. The quantitative synthesis of single-subject research. Remedial and Special Education. 1987; 8 (2):24–33. doi: 10.1177/074193258700800206. [ CrossRef ] [ Google Scholar ]
• Shadish WR, Cook TD, Campbell DT. Experimental and quasi-experimental designs for generalized causal inference. Boston, MA: Houghton Mifflin; 2002. [ Google Scholar ]
• Shadish WR, Rindskopf DM, Hedges LV. The state of the science in the meta-analysis of single-case experimental designs. Evidence-Based Communication Assessment and Intervention. 2008; 3 :188–196. doi: 10.1080/17489530802581603. [ CrossRef ] [ Google Scholar ]
• Shadish WR, Sullivan KJ. Characteristics of single-case designs used to assess treatment effects in 2008. Behavior Research Methods. 2011; 43 :971–980. doi: 10.3758/s13428-011-0111-y. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Sharpley CF. Time-series analysis of behavioural data: An update. Behaviour Change. 1987; 4 :40–45. [ Google Scholar ]
• Shiffman S, Hufford M, Hickcox M, Paty JA, Gnys M, Kassel JD. Remember that? A comparison of real-time versus retrospective recall of smoking lapses. Journal of Consulting and Clinical Psychology. 1997; 65 :292–300. doi: 10.1037/0022-006X.65.2.292.a. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Shiffman S, Stone AA. Ecological momentary assessment: A new tool for behavioral medicine research. In: Krantz DS, Baum A, editors. Technology and methods in behavioral medicine. Mahwah, NJ: Erlbaum; 1998. pp. 117–131. [ Google Scholar ]
• Shiffman S, Stone AA, Hufford MR. Ecological momentary assessment. Annual Review of Clinical Psychology. 2008; 4 :1–32. doi: 10.1146/annurev.clinpsy.3.022806.091415. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Shumway RH, Stoffer DS. An approach to time series smoothing and forecasting using the EM Algorithm. Journal of Time Series Analysis. 1982; 3 (4):253–264. doi: 10.1111/j.1467-9892.1982.tb00349.x. [ CrossRef ] [ Google Scholar ]
• Skinner BF. The behavior of organisms. New York, NY: Appleton-Century-Crofts; 1938. [ Google Scholar ]
• Smith JD, Borckardt JJ, Nash MR. Inferential precision in single-case time-series datastreams: How well does the EM Procedure perform when missing observations occur in autocorrelated data? Behavior Therapy. doi: 10.1016/j.beth.2011.10.001. (in press) [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Smith JD, Handler L, Nash MR. Therapeutic Assessment for preadolescent boys with oppositional-defiant disorder: A replicated single-case time-series design. Psychological Assessment. 2010; 22 (3):593–602. doi: 10.1037/a0019697. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Snijders TAB, Bosker RJ. Multilevel analysis: An introduction to basic and advanced multilevel modeling. Thousand Oaks, CA: Sage; 1999. [ Google Scholar ]
• Soliday E, Moore KJ, Lande MB. Daily reports and pooled time series analysis: Pediatric psychology applications. Journal of Pediatric Psychology. 2002; 27 (1):67–76. doi: 10.1093/jpepsy/27.1.67. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• SPSS Statistics. Chicago, IL: SPSS Inc; 2011. (Version 20.0.0) [ Google Scholar ]
• StataCorp. Stata Statistical Software: Release 12. College Station, TX: StataCorp LP; 2011. [ Google Scholar ]
• Stone AA, Broderick JE, Kaell AT, Deles-Paul PAEG, Porter LE. Does the peak-end phenomenon observed in laboratory pain studies apply to real-world pain in rheumatoid arthritics? Journal of Pain. 2000; 1 :212–217. doi: 10.1054/jpai.2000.7568. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Stone AA, Shiffman S. Capturing momentary, self-report data: A proposal for reporting guidelines. Annals of Behavioral Medicine. 2002; 24 :236–243. doi: 10.1207/S15324796ABM2403_09. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Stout RL. Advancing the analysis of treatment process. Addiction. 2007; 102 :1539–1545. doi: 10.1111/j.1360-0443.2007.01880.x. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Tate RL, McDonald S, Perdices M, Togher L, Schultz R, Savage S. Rating the methodological quality of single-subject designs and N-of-1 trials: Introducing the Single-Case Experimental Design (SCED) Scale. Neuropsychological Rehabilitation. 2008; 18 (4):385–401. doi: 10.1080/09602010802009201. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Thiele C, Laireiter A-R, Baumann U. Diaries in clinical psychology and psychotherapy: A selective review. Clinical Psychology & Psychotherapy. 2002; 9 (1):1–37. doi: 10.1002/cpp.302. [ CrossRef ] [ Google Scholar ]
• Tiao GC, Box GEP. Modeling multiple time series with applications. Journal of the American Statistical Association. 1981; 76 :802–816. [ Google Scholar ]
• Tschacher W, Ramseyer F. Modeling psychotherapy process by time-series panel analysis (TSPA) Psychotherapy Research. 2009; 19 (4):469–481. doi: 10.1080/10503300802654496. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Velicer WF, Colby SM. A comparison of missing-data procedures for ARIMA time-series analysis. Educational and Psychological Measurement. 2005a; 65 (4):596–615. doi: 10.1177/0013164404272502. [ CrossRef ] [ Google Scholar ]
• Velicer WF, Colby SM. Missing data and the general transformation approach to time series analysis. In: Maydeu-Olivares A, McArdle JJ, editors. Contemporary psychometrics. A festschrift to Roderick P McDonald. Hillsdale, NJ: Lawrence Erlbaum; 2005b. pp. 509–535. [ Google Scholar ]
• Velicer WF, Fava JL. Time series analysis. In: Schinka J, Velicer WF, Weiner IB, editors. Research methods in psychology. Vol. 2. New York, NY: John Wiley & Sons; 2003. [ Google Scholar ]
• Wachtel PL. Beyond “ESTs”: Problematic assumptions in the pursuit of evidence-based practice. Psychoanalytic Psychology. 2010; 27 (3):251–272. doi: 10.1037/a0020532. [ CrossRef ] [ Google Scholar ]
• Watson JB. Behaviorism. New York, NY: Norton; 1925. [ Google Scholar ]
• Weisz JR, Hawley KM. Finding, evaluating, refining, and applying empirically supported treatments for children and adolescents. Journal of Clinical Child Psychology. 1998; 27 :206–216. doi: 10.1207/s15374424jccp2702_7. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Weisz JR, Hawley KM. Procedural and coding manual for identification of beneficial treatments. Washinton, DC: American Psychological Association, Society for Clinical Psychology, Division 12, Committee on Science and Practice; 1999. [ Google Scholar ]
• Westen D, Bradley R. Empirically supported complexity. Current Directions in Psychological Science. 2005; 14 :266–271. doi: 10.1111/j.0963-7214.2005.00378.x. [ CrossRef ] [ Google Scholar ]
• Westen D, Novotny CM, Thompson-Brenner HK. The empirical status of empirically supported psychotherapies: Assumptions, findings, and reporting controlled clinical trials. Psychological Bulletin. 2004; 130 :631–663. doi: 10.1037/0033-2909.130.4.631. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Wilkinson L The Task Force on Statistical Inference. Statistical methods in psychology journals: Guidelines and explanations. American Psychologist. 1999; 54 :694–704. doi: 10.1037/0003-066X.54.8.594. [ CrossRef ] [ Google Scholar ]
• Wolery M, Busick M, Reichow B, Barton EE. Comparison of overlap methods for quantitatively synthesizing single-subject data. The Journal of Special Education. 2010; 44 (1):18–28. doi: 10.1177/0022466908328009. [ CrossRef ] [ Google Scholar ]
• Wu Z, Huang NE, Long SR, Peng C-K. On the trend, detrending, and variability of nonlinear and nonstationary time series. Proceedings of the National Academy of Sciences. 2007; 104 (38):14889–14894. doi: 10.1073/pnas.0701020104. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

The Advantages and Limitations of Single Case Study Analysis

As Andrew Bennett and Colin Elman have recently noted, qualitative research methods presently enjoy “an almost unprecedented popularity and vitality… in the international relations sub-field”, such that they are now “indisputably prominent, if not pre-eminent” (2010: 499). This is, they suggest, due in no small part to the considerable advantages that case study methods in particular have to offer in studying the “complex and relatively unstructured and infrequent phenomena that lie at the heart of the subfield” (Bennett and Elman, 2007: 171). Using selected examples from within the International Relations literature[1], this paper aims to provide a brief overview of the main principles and distinctive advantages and limitations of single case study analysis. Divided into three inter-related sections, the paper therefore begins by first identifying the underlying principles that serve to constitute the case study as a particular research strategy, noting the somewhat contested nature of the approach in ontological, epistemological, and methodological terms. The second part then looks to the principal single case study types and their associated advantages, including those from within the recent ‘third generation’ of qualitative International Relations (IR) research. The final section of the paper then discusses the most commonly articulated limitations of single case studies; while accepting their susceptibility to criticism, it is however suggested that such weaknesses are somewhat exaggerated. The paper concludes that single case study analysis has a great deal to offer as a means of both understanding and explaining contemporary international relations.

The term ‘case study’, John Gerring has suggested, is “a definitional morass… Evidently, researchers have many different things in mind when they talk about case study research” (2006a: 17). It is possible, however, to distil some of the more commonly-agreed principles. One of the most prominent advocates of case study research, Robert Yin (2009: 14) defines it as “an empirical enquiry that investigates a contemporary phenomenon in depth and within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident”. What this definition usefully captures is that case studies are intended – unlike more superficial and generalising methods – to provide a level of detail and understanding, similar to the ethnographer Clifford Geertz’s (1973) notion of ‘thick description’, that allows for the thorough analysis of the complex and particularistic nature of distinct phenomena. Another frequently cited proponent of the approach, Robert Stake, notes that as a form of research the case study “is defined by interest in an individual case, not by the methods of inquiry used”, and that “the object of study is a specific, unique, bounded system” (2008: 443, 445). As such, three key points can be derived from this – respectively concerning issues of ontology, epistemology, and methodology – that are central to the principles of single case study research.

First, the vital notion of ‘boundedness’ when it comes to the particular unit of analysis means that defining principles should incorporate both the synchronic (spatial) and diachronic (temporal) elements of any so-called ‘case’. As Gerring puts it, a case study should be “an intensive study of a single unit… a spatially bounded phenomenon – e.g. a nation-state, revolution, political party, election, or person – observed at a single point in time or over some delimited period of time” (2004: 342). It is important to note, however, that – whereas Gerring refers to a single unit of analysis – it may be that attention also necessarily be given to particular sub-units. This points to the important difference between what Yin refers to as an ‘holistic’ case design, with a single unit of analysis, and an ’embedded’ case design with multiple units of analysis (Yin, 2009: 50-52). The former, for example, would examine only the overall nature of an international organization, whereas the latter would also look to specific departments, programmes, or policies etc.

Secondly, as Tim May notes of the case study approach, “even the most fervent advocates acknowledge that the term has entered into understandings with little specification or discussion of purpose and process” (2011: 220). One of the principal reasons for this, he argues, is the relationship between the use of case studies in social research and the differing epistemological traditions – positivist, interpretivist, and others – within which it has been utilised. Philosophy of science concerns are obviously a complex issue, and beyond the scope of much of this paper. That said, the issue of how it is that we know what we know – of whether or not a single independent reality exists of which we as researchers can seek to provide explanation – does lead us to an important distinction to be made between so-called idiographic and nomothetic case studies (Gerring, 2006b). The former refers to those which purport to explain only a single case, are concerned with particularisation, and hence are typically (although not exclusively) associated with more interpretivist approaches. The latter are those focused studies that reflect upon a larger population and are more concerned with generalisation, as is often so with more positivist approaches[2]. The importance of this distinction, and its relation to the advantages and limitations of single case study analysis, is returned to below.

Thirdly, in methodological terms, given that the case study has often been seen as more of an interpretivist and idiographic tool, it has also been associated with a distinctly qualitative approach (Bryman, 2009: 67-68). However, as Yin notes, case studies can – like all forms of social science research – be exploratory, descriptive, and/or explanatory in nature. It is “a common misconception”, he notes, “that the various research methods should be arrayed hierarchically… many social scientists still deeply believe that case studies are only appropriate for the exploratory phase of an investigation” (Yin, 2009: 6). If case studies can reliably perform any or all three of these roles – and given that their in-depth approach may also require multiple sources of data and the within-case triangulation of methods – then it becomes readily apparent that they should not be limited to only one research paradigm. Exploratory and descriptive studies usually tend toward the qualitative and inductive, whereas explanatory studies are more often quantitative and deductive (David and Sutton, 2011: 165-166). As such, the association of case study analysis with a qualitative approach is a “methodological affinity, not a definitional requirement” (Gerring, 2006a: 36). It is perhaps better to think of case studies as transparadigmatic; it is mistaken to assume single case study analysis to adhere exclusively to a qualitative methodology (or an interpretivist epistemology) even if it – or rather, practitioners of it – may be so inclined. By extension, this also implies that single case study analysis therefore remains an option for a multitude of IR theories and issue areas; it is how this can be put to researchers’ advantage that is the subject of the next section.

Having elucidated the defining principles of the single case study approach, the paper now turns to an overview of its main benefits. As noted above, a lack of consensus still exists within the wider social science literature on the principles and purposes – and by extension the advantages and limitations – of case study research. Given that this paper is directed towards the particular sub-field of International Relations, it suggests Bennett and Elman’s (2010) more discipline-specific understanding of contemporary case study methods as an analytical framework. It begins however, by discussing Harry Eckstein’s seminal (1975) contribution to the potential advantages of the case study approach within the wider social sciences.

Eckstein proposed a taxonomy which usefully identified what he considered to be the five most relevant types of case study. Firstly were so-called configurative-idiographic studies, distinctly interpretivist in orientation and predicated on the assumption that “one cannot attain prediction and control in the natural science sense, but only understanding ( verstehen )… subjective values and modes of cognition are crucial” (1975: 132). Eckstein’s own sceptical view was that any interpreter ‘simply’ considers a body of observations that are not self-explanatory and “without hard rules of interpretation, may discern in them any number of patterns that are more or less equally plausible” (1975: 134). Those of a more post-modernist bent, of course – sharing an “incredulity towards meta-narratives”, in Lyotard’s (1994: xxiv) evocative phrase – would instead suggest that this more free-form approach actually be advantageous in delving into the subtleties and particularities of individual cases.

Eckstein’s four other types of case study, meanwhile, promote a more nomothetic (and positivist) usage. As described, disciplined-configurative studies were essentially about the use of pre-existing general theories, with a case acting “passively, in the main, as a receptacle for putting theories to work” (Eckstein, 1975: 136). As opposed to the opportunity this presented primarily for theory application, Eckstein identified heuristic case studies as explicit theoretical stimulants – thus having instead the intended advantage of theory-building. So-called p lausibility probes entailed preliminary attempts to determine whether initial hypotheses should be considered sound enough to warrant more rigorous and extensive testing. Finally, and perhaps most notably, Eckstein then outlined the idea of crucial case studies , within which he also included the idea of ‘most-likely’ and ‘least-likely’ cases; the essential characteristic of crucial cases being their specific theory-testing function.

Whilst Eckstein’s was an early contribution to refining the case study approach, Yin’s (2009: 47-52) more recent delineation of possible single case designs similarly assigns them roles in the applying, testing, or building of theory, as well as in the study of unique cases[3]. As a subset of the latter, however, Jack Levy (2008) notes that the advantages of idiographic cases are actually twofold. Firstly, as inductive/descriptive cases – akin to Eckstein’s configurative-idiographic cases – whereby they are highly descriptive, lacking in an explicit theoretical framework and therefore taking the form of “total history”. Secondly, they can operate as theory-guided case studies, but ones that seek only to explain or interpret a single historical episode rather than generalise beyond the case. Not only does this therefore incorporate ‘single-outcome’ studies concerned with establishing causal inference (Gerring, 2006b), it also provides room for the more postmodern approaches within IR theory, such as discourse analysis, that may have developed a distinct methodology but do not seek traditional social scientific forms of explanation.

Applying specifically to the state of the field in contemporary IR, Bennett and Elman identify a ‘third generation’ of mainstream qualitative scholars – rooted in a pragmatic scientific realist epistemology and advocating a pluralistic approach to methodology – that have, over the last fifteen years, “revised or added to essentially every aspect of traditional case study research methods” (2010: 502). They identify ‘process tracing’ as having emerged from this as a central method of within-case analysis. As Bennett and Checkel observe, this carries the advantage of offering a methodologically rigorous “analysis of evidence on processes, sequences, and conjunctures of events within a case, for the purposes of either developing or testing hypotheses about causal mechanisms that might causally explain the case” (2012: 10).

Harnessing various methods, process tracing may entail the inductive use of evidence from within a case to develop explanatory hypotheses, and deductive examination of the observable implications of hypothesised causal mechanisms to test their explanatory capability[4]. It involves providing not only a coherent explanation of the key sequential steps in a hypothesised process, but also sensitivity to alternative explanations as well as potential biases in the available evidence (Bennett and Elman 2010: 503-504). John Owen (1994), for example, demonstrates the advantages of process tracing in analysing whether the causal factors underpinning democratic peace theory are – as liberalism suggests – not epiphenomenal, but variously normative, institutional, or some given combination of the two or other unexplained mechanism inherent to liberal states. Within-case process tracing has also been identified as advantageous in addressing the complexity of path-dependent explanations and critical junctures – as for example with the development of political regime types – and their constituent elements of causal possibility, contingency, closure, and constraint (Bennett and Elman, 2006b).

Bennett and Elman (2010: 505-506) also identify the advantages of single case studies that are implicitly comparative: deviant, most-likely, least-likely, and crucial cases. Of these, so-called deviant cases are those whose outcome does not fit with prior theoretical expectations or wider empirical patterns – again, the use of inductive process tracing has the advantage of potentially generating new hypotheses from these, either particular to that individual case or potentially generalisable to a broader population. A classic example here is that of post-independence India as an outlier to the standard modernisation theory of democratisation, which holds that higher levels of socio-economic development are typically required for the transition to, and consolidation of, democratic rule (Lipset, 1959; Diamond, 1992). Absent these factors, MacMillan’s single case study analysis (2008) suggests the particularistic importance of the British colonial heritage, the ideology and leadership of the Indian National Congress, and the size and heterogeneity of the federal state.

Most-likely cases, as per Eckstein above, are those in which a theory is to be considered likely to provide a good explanation if it is to have any application at all, whereas least-likely cases are ‘tough test’ ones in which the posited theory is unlikely to provide good explanation (Bennett and Elman, 2010: 505). Levy (2008) neatly refers to the inferential logic of the least-likely case as the ‘Sinatra inference’ – if a theory can make it here, it can make it anywhere. Conversely, if a theory cannot pass a most-likely case, it is seriously impugned. Single case analysis can therefore be valuable for the testing of theoretical propositions, provided that predictions are relatively precise and measurement error is low (Levy, 2008: 12-13). As Gerring rightly observes of this potential for falsification:

“a positivist orientation toward the work of social science militates toward a greater appreciation of the case study format, not a denigration of that format, as is usually supposed” (Gerring, 2007: 247, emphasis added).

In summary, the various forms of single case study analysis can – through the application of multiple qualitative and/or quantitative research methods – provide a nuanced, empirically-rich, holistic account of specific phenomena. This may be particularly appropriate for those phenomena that are simply less amenable to more superficial measures and tests (or indeed any substantive form of quantification) as well as those for which our reasons for understanding and/or explaining them are irreducibly subjective – as, for example, with many of the normative and ethical issues associated with the practice of international relations. From various epistemological and analytical standpoints, single case study analysis can incorporate both idiographic sui generis cases and, where the potential for generalisation may exist, nomothetic case studies suitable for the testing and building of causal hypotheses. Finally, it should not be ignored that a signal advantage of the case study – with particular relevance to international relations – also exists at a more practical rather than theoretical level. This is, as Eckstein noted, “that it is economical for all resources: money, manpower, time, effort… especially important, of course, if studies are inherently costly, as they are if units are complex collective individuals ” (1975: 149-150, emphasis added).

Limitations

Single case study analysis has, however, been subject to a number of criticisms, the most common of which concern the inter-related issues of methodological rigour, researcher subjectivity, and external validity. With regard to the first point, the prototypical view here is that of Zeev Maoz (2002: 164-165), who suggests that “the use of the case study absolves the author from any kind of methodological considerations. Case studies have become in many cases a synonym for freeform research where anything goes”. The absence of systematic procedures for case study research is something that Yin (2009: 14-15) sees as traditionally the greatest concern due to a relative absence of methodological guidelines. As the previous section suggests, this critique seems somewhat unfair; many contemporary case study practitioners – and representing various strands of IR theory – have increasingly sought to clarify and develop their methodological techniques and epistemological grounding (Bennett and Elman, 2010: 499-500).

A second issue, again also incorporating issues of construct validity, concerns that of the reliability and replicability of various forms of single case study analysis. This is usually tied to a broader critique of qualitative research methods as a whole. However, whereas the latter obviously tend toward an explicitly-acknowledged interpretive basis for meanings, reasons, and understandings:

“quantitative measures appear objective, but only so long as we don’t ask questions about where and how the data were produced… pure objectivity is not a meaningful concept if the goal is to measure intangibles [as] these concepts only exist because we can interpret them” (Berg and Lune, 2010: 340).

The question of researcher subjectivity is a valid one, and it may be intended only as a methodological critique of what are obviously less formalised and researcher-independent methods (Verschuren, 2003). Owen (1994) and Layne’s (1994) contradictory process tracing results of interdemocratic war-avoidance during the Anglo-American crisis of 1861 to 1863 – from liberal and realist standpoints respectively – are a useful example. However, it does also rest on certain assumptions that can raise deeper and potentially irreconcilable ontological and epistemological issues. There are, regardless, plenty such as Bent Flyvbjerg (2006: 237) who suggest that the case study contains no greater bias toward verification than other methods of inquiry, and that “on the contrary, experience indicates that the case study contains a greater bias toward falsification of preconceived notions than toward verification”.

The third and arguably most prominent critique of single case study analysis is the issue of external validity or generalisability. How is it that one case can reliably offer anything beyond the particular? “We always do better (or, in the extreme, no worse) with more observation as the basis of our generalization”, as King et al write; “in all social science research and all prediction, it is important that we be as explicit as possible about the degree of uncertainty that accompanies out prediction” (1994: 212). This is an unavoidably valid criticism. It may be that theories which pass a single crucial case study test, for example, require rare antecedent conditions and therefore actually have little explanatory range. These conditions may emerge more clearly, as Van Evera (1997: 51-54) notes, from large-N studies in which cases that lack them present themselves as outliers exhibiting a theory’s cause but without its predicted outcome. As with the case of Indian democratisation above, it would logically be preferable to conduct large-N analysis beforehand to identify that state’s non-representative nature in relation to the broader population.

There are, however, three important qualifiers to the argument about generalisation that deserve particular mention here. The first is that with regard to an idiographic single-outcome case study, as Eckstein notes, the criticism is “mitigated by the fact that its capability to do so [is] never claimed by its exponents; in fact it is often explicitly repudiated” (1975: 134). Criticism of generalisability is of little relevance when the intention is one of particularisation. A second qualifier relates to the difference between statistical and analytical generalisation; single case studies are clearly less appropriate for the former but arguably retain significant utility for the latter – the difference also between explanatory and exploratory, or theory-testing and theory-building, as discussed above. As Gerring puts it, “theory confirmation/disconfirmation is not the case study’s strong suit” (2004: 350). A third qualification relates to the issue of case selection. As Seawright and Gerring (2008) note, the generalisability of case studies can be increased by the strategic selection of cases. Representative or random samples may not be the most appropriate, given that they may not provide the richest insight (or indeed, that a random and unknown deviant case may appear). Instead, and properly used , atypical or extreme cases “often reveal more information because they activate more actors… and more basic mechanisms in the situation studied” (Flyvbjerg, 2006). Of course, this also points to the very serious limitation, as hinted at with the case of India above, that poor case selection may alternatively lead to overgeneralisation and/or grievous misunderstandings of the relationship between variables or processes (Bennett and Elman, 2006a: 460-463).

As Tim May (2011: 226) notes, “the goal for many proponents of case studies […] is to overcome dichotomies between generalizing and particularizing, quantitative and qualitative, deductive and inductive techniques”. Research aims should drive methodological choices, rather than narrow and dogmatic preconceived approaches. As demonstrated above, there are various advantages to both idiographic and nomothetic single case study analyses – notably the empirically-rich, context-specific, holistic accounts that they have to offer, and their contribution to theory-building and, to a lesser extent, that of theory-testing. Furthermore, while they do possess clear limitations, any research method involves necessary trade-offs; the inherent weaknesses of any one method, however, can potentially be offset by situating them within a broader, pluralistic mixed-method research strategy. Whether or not single case studies are used in this fashion, they clearly have a great deal to offer.

References 

Bennett, A. and Checkel, J. T. (2012) ‘Process Tracing: From Philosophical Roots to Best Practice’, Simons Papers in Security and Development, No. 21/2012, School for International Studies, Simon Fraser University: Vancouver.

Bennett, A. and Elman, C. (2006a) ‘Qualitative Research: Recent Developments in Case Study Methods’, Annual Review of Political Science , 9, 455-476.

Bennett, A. and Elman, C. (2006b) ‘Complex Causal Relations and Case Study Methods: The Example of Path Dependence’, Political Analysis , 14, 3, 250-267.

Bennett, A. and Elman, C. (2007) ‘Case Study Methods in the International Relations Subfield’, Comparative Political Studies , 40, 2, 170-195.

Bennett, A. and Elman, C. (2010) Case Study Methods. In C. Reus-Smit and D. Snidal (eds) The Oxford Handbook of International Relations . Oxford University Press: Oxford. Ch. 29.

Berg, B. and Lune, H. (2012) Qualitative Research Methods for the Social Sciences . Pearson: London.

Bryman, A. (2012) Social Research Methods . Oxford University Press: Oxford.

David, M. and Sutton, C. D. (2011) Social Research: An Introduction . SAGE Publications Ltd: London.

Diamond, J. (1992) ‘Economic development and democracy reconsidered’, American Behavioral Scientist , 35, 4/5, 450-499.

Eckstein, H. (1975) Case Study and Theory in Political Science. In R. Gomm, M. Hammersley, and P. Foster (eds) Case Study Method . SAGE Publications Ltd: London.

Flyvbjerg, B. (2006) ‘Five Misunderstandings About Case-Study Research’, Qualitative Inquiry , 12, 2, 219-245.

Geertz, C. (1973) The Interpretation of Cultures: Selected Essays by Clifford Geertz . Basic Books Inc: New York.

Gerring, J. (2004) ‘What is a Case Study and What Is It Good for?’, American Political Science Review , 98, 2, 341-354.

Gerring, J. (2006a) Case Study Research: Principles and Practices . Cambridge University Press: Cambridge.

Gerring, J. (2006b) ‘Single-Outcome Studies: A Methodological Primer’, International Sociology , 21, 5, 707-734.

Gerring, J. (2007) ‘Is There a (Viable) Crucial-Case Method?’, Comparative Political Studies , 40, 3, 231-253.

King, G., Keohane, R. O. and Verba, S. (1994) Designing Social Inquiry: Scientific Inference in Qualitative Research . Princeton University Press: Chichester.

Layne, C. (1994) ‘Kant or Cant: The Myth of the Democratic Peace’, International Security , 19, 2, 5-49.

Levy, J. S. (2008) ‘Case Studies: Types, Designs, and Logics of Inference’, Conflict Management and Peace Science , 25, 1-18.

Lipset, S. M. (1959) ‘Some Social Requisites of Democracy: Economic Development and Political Legitimacy’, The American Political Science Review , 53, 1, 69-105.

Lyotard, J-F. (1984) The Postmodern Condition: A Report on Knowledge . University of Minnesota Press: Minneapolis.

MacMillan, A. (2008) ‘Deviant Democratization in India’, Democratization , 15, 4, 733-749.

Maoz, Z. (2002) Case study methodology in international studies: from storytelling to hypothesis testing. In F. P. Harvey and M. Brecher (eds) Evaluating Methodology in International Studies . University of Michigan Press: Ann Arbor.

May, T. (2011) Social Research: Issues, Methods and Process . Open University Press: Maidenhead.

Owen, J. M. (1994) ‘How Liberalism Produces Democratic Peace’, International Security , 19, 2, 87-125.

Seawright, J. and Gerring, J. (2008) ‘Case Selection Techniques in Case Study Research: A Menu of Qualitative and Quantitative Options’, Political Research Quarterly , 61, 2, 294-308.

Stake, R. E. (2008) Qualitative Case Studies. In N. K. Denzin and Y. S. Lincoln (eds) Strategies of Qualitative Inquiry . Sage Publications: Los Angeles. Ch. 17.

Van Evera, S. (1997) Guide to Methods for Students of Political Science . Cornell University Press: Ithaca.

Verschuren, P. J. M. (2003) ‘Case study as a research strategy: some ambiguities and opportunities’, International Journal of Social Research Methodology , 6, 2, 121-139.

Yin, R. K. (2009) Case Study Research: Design and Methods . SAGE Publications Ltd: London.

[1] The paper follows convention by differentiating between ‘International Relations’ as the academic discipline and ‘international relations’ as the subject of study.

[2] There is some similarity here with Stake’s (2008: 445-447) notion of intrinsic cases, those undertaken for a better understanding of the particular case, and instrumental ones that provide insight for the purposes of a wider external interest.

[3] These may be unique in the idiographic sense, or in nomothetic terms as an exception to the generalising suppositions of either probabilistic or deterministic theories (as per deviant cases, below).

[4] Although there are “philosophical hurdles to mount”, according to Bennett and Checkel, there exists no a priori reason as to why process tracing (as typically grounded in scientific realism) is fundamentally incompatible with various strands of positivism or interpretivism (2012: 18-19). By extension, it can therefore be incorporated by a range of contemporary mainstream IR theories.

— Written by: Ben Willis Written at: University of Plymouth Written for: David Brockington Date written: January 2013

Further Reading on E-International Relations

• Identity in International Conflicts: A Case Study of the Cuban Missile Crisis
• Imperialism’s Legacy in the Study of Contemporary Politics: The Case of Hegemonic Stability Theory
• Recreating a Nation’s Identity Through Symbolism: A Chinese Case Study
• Ontological Insecurity: A Case Study on Israeli-Palestinian Conflict in Jerusalem
• Terrorists or Freedom Fighters: A Case Study of ETA
• A Critical Assessment of Eco-Marxism: A Ghanaian Case Study

Please Consider Donating

Before you download your free e-book, please consider donating to support open access publishing.

E-IR is an independent non-profit publisher run by an all volunteer team. Your donations allow us to invest in new open access titles and pay our bandwidth bills to ensure we keep our existing titles free to view. Any amount, in any currency, is appreciated. Many thanks!

Donations are voluntary and not required to download the e-book - your link to download is below.

Not logged in

Single case study, page actions.

• View source

A single case study is a research method used in management to investigate a particular phenomenon in depth by focusing on a single example, often a person, organization , event, or action . It involves in-depth analysis of a single case to explore the underlying concepts and causes of the phenomenon being studied. It enables researchers to explore the unique context of a particular situation and to collect detailed, in-depth data on the topic of interest . By understanding the context of a single case, researchers can develop a more comprehensive understanding of the phenomenon being studied.

• 1 Example of single case study
• 2 When to use single case study
• 3 Types of single case study
• 4 Steps of single case study
• 5 Advantages of single case study
• 6 Limitations of single case study
• 7 Other approaches related to single case study
• 8 References

Example of single case study

• A single case study of a particular patient could examine their physical, mental, and emotional health over the course of their treatment. This could involve tracking the patient's progress through various stages of treatment, such as initial diagnosis, treatment plan , and follow-up care. This type of study could provide a better understanding of the individual's experience with their condition and the effectiveness of the treatment plan.
• A single case study of a particular organization could focus on the organization's management practices and culture. This type of study could look at the organization's structure, decision-making processes, and communication strategies to understand how it operates. It could also explore the organization's internal and external environment and the ways in which it interacts with different stakeholders .
• A single case study of a particular event could examine the circumstances surrounding the event and the strategies used to respond to it. This type of study could provide an in-depth analysis of the event and the factors that contributed to its success or failure. It could also examine the impact of the event on different groups of people and the lessons learned from it.

When to use single case study

Single case studies are useful when researchers are interested in exploring a phenomenon in depth, particularly when the context of the phenomenon is unique or complex. They can be used to:

• Examine the causal relationship between variables in a single case and explore the underlying concepts and causes of the phenomenon;
• Investigate a particular problem or issue in detail, such as a new technology , a new way of working, or a new policy;
• Understand the impact of an event, organization, or action on individuals, groups, or organizations;
• Study rare or unusual phenomena;
• Develop an in-depth understanding of a particular context or situation;
• Test the generalizability of existing theories and models.

Types of single case study

A single case study can take many forms depending on the research objectives. Below are some of the types of single case study:

• Exploratory case study : This type of case study is used to explore a particular topic or phenomenon. It is used as an initial step to gain an understanding of the topic and to identify possible further research.
• Descriptive case study : This type of case study focuses on describing the phenomenon being studied. It uses detailed data on the case to provide a comprehensive description of the phenomenon.
• Explanatory case study : This type of case study is used to explain a particular phenomenon or behavior . It seeks to identify the factors that are influencing the phenomenon and to explain why it is occurring.
• Intensive case study : This type of case study focuses on a single case or individual. It seeks to understand the context of the case or individual in order to gain a deeper understanding of the phenomenon being studied.
• Comparative case study : This type of case study compares two or more cases to understand similarities and differences between them. It seeks to identify the factors that are influencing the similarities and differences between the cases.

Steps of single case study

A single case study is a powerful research method used to investigate a particular phenomenon in depth by focusing on a single example. The following steps are required to effectively conduct a single case study:

• Define the research question : The first step in a single case study is to define the research question that is to be studied. This should be done in a way that is relevant to the context of the case study and should be clear and concise.
• Select the case : The second step is to select a single case that is suitable for the research question. This should be done carefully, taking into account the particular context of the case and the research question.
• Collect data : After selecting the case, data must be collected in order to answer the research question. This can include surveys, interviews, documents, and observation.
• Analyze the data : Once the data has been collected, it must be analyzed in order to draw conclusions about the research question. This may involve using qualitative or quantitative methods to analyze the data.
• Report the findings : The final step is to report the findings of the case study. This should include a thorough discussion of the results and a clear explanation of the implications of the findings.

Advantages of single case study

Single case studies have a number of advantages for research. They allow for an in-depth examination of a phenomenon that is not possible with other types of research. Specifically, single case studies can provide:

• Rich and detailed data, as the researcher can gather in-depth information from the single case.
• The opportunity to explore issues and phenomena in a unique context, as the researcher can gain insights into the particular situation and its context.
• The ability to identify patterns and relationships that may be missed in other types of research.
• The ability to gain a more holistic understanding of a phenomenon by taking into account a range of factors, such as culture, history, and context.
• The ability to identify cause-and-effect relationships, as the researcher can observe changes in the case over time.
• The ability to uncover unexpected findings, as the researcher can explore the complexities of the case.

Limitations of single case study

One of the major limitations of single case study is its limited generalizability. Since the study focuses on a single case, the results cannot be applied to other contexts or settings. Additionally, it can be difficult to identify the cause-and-effect relationships between variables, as the case study may only provide a snapshot of the current situation rather than an in-depth analysis of the underlying factors. Furthermore, the case study may be biased due to the researcher’s pre-existing expectations or biases. Finally, the case study requires a great deal of time and resources to conduct in-depth research, which can be costly and may limit its applicability to complex research questions.

Other approaches related to single case study

A single case study is a research method used in management to investigate a particular phenomenon in depth by focusing on a single example, often a person, organization, event, or action. Other approaches related to single case study include:

• Comparative case studies, which involve comparing multiple cases to identify patterns, similarities, and differences.
• Qualitative case studies, which involve collecting and analyzing qualitative data from participants to understand the subjective experience of the phenomenon being studied.
• Ethnography, which involves observing and recording the behavior of participants in their natural environment .
• Action research, which involves engaging participants in the research process to identify opportunities for improvement.

Overall, single case studies provide an in-depth look at a particular phenomenon, while other approaches such as comparative case studies, qualitative case studies, ethnography, and action research provide different perspectives that help to shed light on the phenomenon in question.

• Gustafsson, J. (2017). Single case studies vs . multiple case studies: A comparative study.
• Mariotto, F. L., Zanni, P. P., & Moraes, G. H. S. (2014). What is the use of a single-case study in management research? . Revista de Administração de Empresas, 54, 358-369.
• Methods and techniques
• Recent changes
• Random page
• Page information

Table of Contents

• Special pages

User page tools

• What links here
• Related changes
• Printable version
• Permanent link

• This page was last edited on 18 November 2023, at 04:35.
• Content is available under CC BY-SA Attribution-ShareAlike 4.0 International unless otherwise noted.
• Privacy policy
• About CEOpedia | Management online
• Disclaimers

EMT en Español Para Autismo : A Collaborative Communication Intervention Approach and Single Case Design Pilot Study

• Original Article
• Open access
• Published: 13 April 2024

Cite this article

You have full access to this open access article

• Natalie S. Pak   ORCID: orcid.org/0000-0003-1032-5813 1   nAff2 ,
• Tatiana Nogueira Peredo   ORCID: orcid.org/0000-0002-2558-6736 1 ,
• Ana Paula Madero Ucero 1 &
• Ann P. Kaiser   ORCID: orcid.org/0000-0001-9406-685X 1  

30 Accesses

Explore all metrics

The primary purpose of the current pilot study was to test the effects of an adapted and collaborative intervention model with a systematic teaching approach on Latina Spanish-speaking caregivers’ use of EMT en Español Para Autismo strategies with their young children on the autism spectrum. A multiple baseline across behaviors single case design was replicated across two dyads. A series of family interviews and a direct therapist-child intervention phase supported individualization of the intervention. Families were provided speech generating devices as part of their children’s intervention protocol. Caregivers were taught to use EMT en Español Para Autismo strategies with aided language input. Strategies included contingent target-level and proximal target-level language modeling, linguistic expansions, and communication elicitations. Secondary variables measured included generalization of strategy use to unsupported interactions and at a 2-month follow-up, child communication outcomes, and social validity. There was a strong functional relation for one dyad between the adapted and collaborative intervention and caregiver use of EMT strategies. The functional relation was weakened by behavioral covariation for the other dyad. Children increased the quantity and diversity of their communication during the study. Caregivers generalized their use of most EMT strategies and reported most aspects of the approach to be socially valid. The current study provides an initial demonstration of an effective model for adaptation and individualization of naturalistic developmental behavioral interventions for Latino Spanish-speaking families with children on the autism spectrum.

Avoid common mistakes on your manuscript.

Early diagnoses of autism are increasingly prevalent in the United States, affecting an estimated 1 in 46 preschool-aged children across all races and ethnicities and 1 in 34 Hispanic children (Shaw et al., 2023 ). Latino Spanish-speaking (LSS) families face multiple systemic barriers to accessing early intervention for their young children on the autism spectrum and are more likely than non-Latino White children to receive no or inadequate services (Stahmer et al., 2019 ; Zuckerman et al., 2017 ). Caregiver-mediated (or implemented) interventions have been shown to positively influence children’s language outcomes for monolingual English-speaking children (Heidlage et al., 2020 ; Roberts et al., 2019 ). In this article, caregiver refers to children’s primary caregivers in the home (e.g., parent, other family member). Importantly, LSS caregivers report a desire to be partners in the delivery of intervention for their children on the autism spectrum, and they report children’s communication skills to be a high priority for intervention (DuBay et al., 2018 ). In a scoping review of the literature, DuBay ( 2022 ) identified 19 studies investigating culturally adapted caregiver-mediated interventions for Latino families and children on the autism spectrum. Only two involved interventions specifically targeting children’s early communication skills (Gevarter et al., 2022 ; Meadan et al., 2020 ). To reduce the disparities in early intervention services, more culturally and linguistically adapted caregiver-implemented language interventions for children on the autism spectrum are necessary (Martinez-Torres et al., 2021 ).

EMT en Español

EMT en Español is a Spanish language, caregiver-mediated adaptation of Enhanced Milieu Teaching (EMT) that has been tested with LSS families and their preschool children with language delays (Peredo et al., 2018 , 2022 ). EMT en Español and EMT are naturalistic developmental behavioral interventions (NDBIs) which involve use of behavioral principles to teach developmentally appropriate communication skills in naturalistic settings (Schreibman et al., 2015 ). Among NDBIs, EMT is uniquely focused on improving child language and communication development and has been demonstrated to be effective for children with a variety of etiologies of language impairments (Kaiser & Hampton, 2017 ; Kaiser et al., 2021 ; Roberts & Kaiser, 2015 ; Wright et al., 2013 ).

Cultural and linguistic adaptations to interventions such as EMT may be linked to dimensions of the ecological validity model (EVM), a framework designed specifically for adapting interventions to be more culturally sensitive for Spanish-speaking families (Bernal et al., 1995 ). According to this model, there are eight dimensions that can influence the cultural consistency of an intervention for a given client or community. These dimensions are language, persons, metaphors, content, concepts, goals, methods, and context. Adaptations to EMT en Español have addressed several dimensions of the EVM (see Peredo et al., 2018 , and Peredo et al., 2022 , for more details). For example, rather than simply following the child’s lead, caregivers are coached to first comment on the child’s focus of interest within adult-directed activities. This addresses the dimensions of content and concepts. Additional adaptations have been implemented in the procedures and delivery of intervention (method). For example, interventionists speak Spanish with families (language, persons) and deliver intervention in homes during familiar and/or valued routines (context, goals) (Peredo et al., 2018 , 2022 ).

These adaptations have been tested in two studies. Using a single-case experimental design, Peredo et al. ( 2018 ) demonstrated that three Spanish-speaking mothers from Mexico applied EMT en Español strategies with their preschool children with developmental language disorders when the mothers were taught using a systematic training approach (Teach-Model-Coach-Review or TMCR; Roberts & Kaiser, 2015 ). The mothers generalized use of most EMT en Español strategies to a novel context at home and reported using the strategies additional times throughout the week. Results for LSS caregivers receiving systematic instruction to use EMT en Español were also positive in a small randomized trial (Peredo et al., 2022 ). Twenty LSS caregivers and their children with language delays (age range 29–43 months) were randomized to a 24-session intervention at home ( n  = 10) or waitlist control group ( n  = 10). There were statistically significant intervention effects for caregivers’ use of matched turns, expansions, and linguistic targets ( d  = 1.24–1.90).

EMT en Español Para Autismo

The current study was a pilot investigation of EMT en Español Para Autismo , an adaptation of EMT en Español aiming to address the specific needs of LSS families of children on the autism spectrum. Prior to the study, four LSS primary caregivers of children on the autism spectrum provided feedback on EMT en Español materials in a focus group format. The focus group caregivers were positive about the materials, reported the materials were relevant to them, and noted areas in which they would benefit from more information. This feedback was combined with clinical expertise and experience from previous EMT studies with children on the autism spectrum (e.g., Hampton et al., 2021 ) to make adaptations for the current study.

The first adaptation was to include information to expand caregivers’ knowledge about autism. Focus group findings were consistent with reports that LSS parents of children on the autism spectrum often begin evaluation and treatment services with limited knowledge about autism, which can lead to self-blame for their children’s challenges (Chlebowski et al., 2018 ; Zuckerman et al., 2017 ). The second adaptation was to teach caregivers individualized strategies for promoting child engagement in interactions and activities, which was a need reported by focus group caregivers. Strategies to support children’s engagement have been reported in previous EMT and EMT en Español studies. These include: (a) arranging the setting to support children’s contact with activities and to minimize distractions, (b) choosing high interest toys, (c) sitting at the child’s level, (d) scaffolding play and engagement, (e) shifting activities when children lose interest, and (f) specific behavior supports such as use of timers and first-then charts (Hampton et al., 2019 , 2021 ; Peredo et al., 2018 , 2022 ). In the current pilot study, many of the same strategies were employed; however, the selected strategies were individualized based on family concerns and preferences expressed throughout the study and based on an initial phase of therapist-delivered child intervention. The third adaptation was to provide access to high-tech augmentative and alternative communication (AAC) for children who began the study with little to no expressive spoken language. AAC, which includes various modes of communication used instead of or in addition to speech, may be important for young children at high risk of delayed development of spoken language (Beukelman & Light, 2020 ). Specifically, children received speech-generating devices (SGDs) in the form of iPad minis with the Proloquo2Go communication app (AssistiveWare, 2023 ). Spanish and English were both available on the Proloquo2Go app; Spanish vocabulary was primarily used during the study for language modeling, with vocabulary selections made collaboratively with each family. Families were coached to model language with both the SGD and speech while delivering EMT en Español Para Autismo with their children (i.e., aided AAC modeling; Beukelman & Light, 2020 ).

The primary purpose of this pilot study was to assess the effects using a systematic teaching approach to teach LSS caregivers of children on the autism spectrum to implement EMT en Español Para Autismo . We posed the following research questions: (a) Do LSS caregivers of children on the autism spectrum use EMT en Español Para Autismo strategies during coached caregiver-child interactions when taught using the TMCR approach? (b) Do LSS caregivers use EMT en Español Para Autismo strategies during caregiver-child interactions without coaching during and after the intervention period when taught using the TMCR approach? (c) Do LSS children on the autism spectrum increase the frequency and diversity of their communication when their caregivers are taught EMT en Español Para Autismo strategies? (d) How do caregivers perceive the intervention approach?

Experimental Design

The experimental design was a single-case multiple baseline design across behaviors replicated across caregiver-child dyads (Baer et al., 1968 ). In multiple baseline designs across behaviors, participants are taught functionally similar but independent behavior sets with a time-lagged introduction of intervention for each behavior set (Gast et al., 2018 ). In the current study, the behavior sets (i.e., tiers of the intervention) were sets of EMT en Español Para Autismo strategies: (a) contingent target-level language modeling, (b) contingent higher-level language modeling including proximal targets and expansions, and (c) communication elicitation strategies (see Table  1 for definitions). Environmental arrangement strategies to support child engagement and communication (e.g., eliminating distractions, using timers if needed to increase duration of child play, reducing questions and instructions) were taught in Tier 1 along with target level language models. The sequence of study phases and activities is shown in Fig.  1 .

Flowchart of study activities. The order of phases is pre-intervention, Tier 1 intervention, Tier 2 intervention, Tier 3 intervention, and post-intervention. Within each intervention tier, there is an interview activity, workshop, TMCR intervention, and a generalization session. Boxes with square corners indicate activities that were part of the experimental design

The study phases were (a) pre-intervention, (b) teaching caregivers three sets of EMT strategies using the TMCR approach across tiers of the intervention design, and (c) post-intervention assessment. The pre-intervention phase included three initial baseline sessions with the caregiver, eight sessions of direct therapist delivery of the intervention to the child, and a second set of three baseline sessions. Measuring caregiver baseline performance prior to and after therapist-child intervention was included to detect any change in caregiver use of strategies from watching the therapist use the strategies before the TMCR intervention. The experimental design was implemented in the second set of baseline sessions and the planning, teaching, and coaching components of the intervention during the TMCR phase (boxes with square corners in Fig.  1 ). The post-intervention phase included a caregiver exit interview immediately after intervention and a follow-up observation 2 months later.

Recruitment

Caregiver-child dyads who met the following criteria and wished to participate in the study were recruited: (a) Spanish was the primary language spoken in the home; (b) the child had an autism diagnosis or flagged on an autism screening measure; (c) the child was 30–42 months old at the beginning of intervention; (d) the child had a Total Language Score at least 1.5 SD below the mean standardized score on the Preschool Language Scales, 5th edition Spanish (PLS-5 Spanish; Zimmerman et al., 2012 ); and (e) at least one primary caregiver was willing and able to participate in the intensive intervention for several months. Participants were recruited from a list of children who were assessed for eligibility for an ongoing randomized controlled trial (Kaiser & Peredo, 2019 –2024) but were excluded because the children already had an autism diagnosis or exhibited characteristics of autism based on the Screening Tool for Autism in Toddlers and Young Children (STAT; Stone & Ousley, 2008 ). A bilingual member of the research team called participants who had consented to being contacted for future studies for a phone screening. Subsequent in-person eligibility assessments were conducted in families’ homes. Interested families whose children demonstrated characteristics of autism based on the STAT but did not yet have a diagnosis were provided with a full evaluation including administration of the TELE-ASD-PEDS (Corona et al., 2020 ) and a diagnostic interview by qualified providers. Prior to any study activities, consent was obtained from caregivers indicating that they wished to participate and that they gave consent for their children to participate. Written consent forms and verbal explanations of the consent forms were in Spanish. All study procedures and materials were approved by a university Institutional Review Board (IRB). Participating families received toys and books (shape sorter, blocks, bubbles, and two bilingual picture books) at the beginning of the study valued at approximately $50. Additional incentives included intervention materials that were collaboratively selected with the family during the individualization process described in the following section.

Intervention Planning and Individualization

Individualizing the intervention at the beginning of the study occurred during the therapist-child intervention phase and the series of interviews (see Fig.  1 ). The primary purposes of the therapist-child intervention phase were to (a) give the child experience in the intervention context as a foundation for the caregiver-implemented intervention and (b) provide the research team with specific information about how to best individualize intervention based on their interactions with the child. Family members in addition to the participating caregiver were invited to the initial interview and planning session, which occurred after all baseline sessions were completed and prior to any caregiver instruction (see Fig.  1 ). The Family Values and Activities Interview (FVAI) was administered in Spanish by the interventionist using the FVAI protocol (Peredo, 2016 ). The first part of this semi-structured protocol was a series of open-ended questions about the family values, goals, and beliefs about communication. The second part included questions about the activities that occurred frequently, were important to the family, or both.

During the planning portion of the session, the family and interventionist first selected specific routines or activities that were typical for each family and could be used in the intervention sessions to practice the EMT en Español Para Autismo intervention strategies with coaching. Second, the interviewer, interventionist, and family collaborated to select additional play materials (within a $50 budget per family) that would be engaging for the child and facilitate communicative interactions. Third, families and therapists determined whether to introduce the SGD if the child used fewer than five spoken words at the beginning of intervention and during therapist-child intervention sessions. When applicable, families were provided iPad minis loaded with Proloquo2Go. Activity grid displays with Spanish vocabulary were primarily used for this pilot study. The families kept the SGDs between sessions during the study and after the study ended. Prior to beginning the caregiver-implemented intervention phase, children’s abilities to visually scan symbols on the iPad were tested using a “chase the ball” task to determine the grid size (see Hampton et al., 2020 , for a description). Core vocabulary words (e.g., sí/yes, no, poner/to put) were added to each page, and activity pages were individualized to the participant. Symbols were added on an ongoing basis based on caregiver preferences and therapist suggestions, ensuring that an adequate number of verbs, nouns, and adjectives were available, and that vocabulary matched the family’s dialect and vocabulary preferences (Bernal et al., 1995 ; Binger et al., 2023 ).

Each family also participated in two shorter mid-intervention interviews (“mini-interviews”; see Fig.  1 and Online Resource) with the interventionist. The mini-interviews occurred immediately before the introduction of Tier 2 and Tier 3 strategies. During mini-interviews, the interventionist asked the families how they felt about the intervention, their child’s progress, and any changes in family activities relevant to intervention.

Participants

Five dyads completed in-person screening for the study. One dyad did not enroll in the study due to limited ability to participate in study sessions multiple times per week. Two dyads enrolled in the study but dropped out before starting intervention or before completing Tier 1 of intervention. In both cases, the caregivers did not wish to continue with the study sessions because their children became eligible to start receiving services at school or from other providers. Table 2 shows characteristics of the two dyads who enrolled and completed the study.

Dyad 1 included a 33-month-old boy and his maternal grandmother, referred to as Daniel and Dayana. Daniel received an autism diagnosis from an evaluation team in Mexico during the study prior to the FVAI and planning session. Daniel was not receiving any additional services at the beginning of the study, but he began attending full-day monolingual English-speaking preschool during Tier 2 of the study intervention. Dayana and Daniel’s mother participated in the initial FVAI and planning session. Per the family’s report and observation during therapist-child sessions, Daniel enjoyed playing with a variety of toys, movement (e.g., jumping on a trampoline), and looking at books. He communicated primarily by vocalizing, leading others by the hand, and giving objects. The therapist and family decided to introduce the SGD, which was available during all subsequent TMCR and generalization sessions except for one session when the battery had died. Although Daniel preferred reading books independently and would turn away when others joined him, shared book-reading was valued by the family and was incorporated into TMCR sessions. The additional materials collaboratively selected for intervention included toys representing various foods and cooking tools, board books, and a pop-up toy. Snack and mealtime routines were preferred activities for Daniel and were selected as contexts for caregiver practice and coaching. Daniel’s mother, father, and grandmother all participated in the first mini-interview (prior to Tier 2) and the exit interview. Only Dayana participated in the second mini-interview (prior to Tier 3). During mini-interviews, the family discussed child progress that they noticed, such as that he was making eye contact more often and sleeping better. After the first mini-interview, drawing with markers was added as an intervention session activity and handouts were provided to help with ongoing potty training outside of sessions. Although shared book-reading continued to be a struggle, the family continued to state its importance and it remained an intervention session activity.

Dyad 2 included a 31-month-old boy and his mother, referred to as Luis and María. Luis demonstrated signs of autism during screening and was subsequently diagnosed during a professional evaluation arranged by the research team. Luis attended a bilingual English- and Spanish-speaking childcare for approximately 4–7 h each weekday at the beginning of the study, but his enrollment was inconsistent during the study. Each week, he received occupational therapy 30 min and speech-language therapy 60 min in English. His mother had monthly telepractice consultations in Spanish regarding strategies to support Luis at home. María participated in the FVAI and planning session. Per caregiver report and observation during therapist-child sessions, Luis enjoyed taking walks, watching television, shared book reading, blocks, tickles, and sensory play (e.g., Play-Doh). He communicated by vocalizing, using gestures such as reaching and giving, and a few spoken words (e.g., mamá, no). María was hesitant about the SGD, as she wanted to limit her children’s screen time; however, she agreed to try using it for a few sessions before deciding. In the fifth TMCR session with the SGD, María mentioned that she liked that he was trying to use the device more frequently to communicate. The SGD was available in all subsequent TMCR and generalization sessions. The additional materials selected for intervention included puppets, books, and a Play-Doh set. Preparing and eating food, getting dressed, and combing hair were preferred routines for Luis; these were incorporated into TMCR sessions as routines for practice and coaching with EMT en Español Para Autismo strategies. María and Luis’s grandmother participated in mini-interviews. They reported noticing changes in the child’s communication and behavior, including more vocalizations and pointing, more interest in play, and more awareness of his surroundings. They also shared that they still hoped he would talk more. Brushing teeth and washing dishes were routines added to TMCR sessions based on feedback during mini-interviews. Playing with Play-Doh became a favorite activity for Luis.

Sessions occurred up to three times per week (approximately 120–180 min/week) in families’ homes and were video recorded. One interview with Dayana occurred via a Zoom (version 5.13.7) videoconference due to family illness. There were two primary interventionists, one for each of the two participating families. The first interventionist (female, 31 years old, Korean/White) was a doctoral candidate in Special Education and a speech-language pathologist with 4 years of training and experience delivering EMT and EMT en Español to young children with language delays in research settings. She was a proficient Spanish speaker, a native English speaker, and a lifelong resident of the United States. The second interventionist (female, 42 years old, Latina) had over 20 years of clinical experience in language and behavioral interventions with young children. She had a master’s degree in psychology and over 5 years of experience with EMT en Español and TMCR in research settings. She was a native Spanish speaker, a fluent English speaker, and had been a resident of the United States (9 years) and Mexico.

Pre-Intervention Phase

Pre-intervention activities are shown in Fig.  1 . During caregiver baseline sessions (approximately 25 min per visit), the therapist video recorded the caregiver and child interacting in typical play or book-reading contexts for 15 min. Families were provided with the standard toys and books at the first session. During therapist-delivered intervention sessions (approximately 35 min per visit), the intervention lasted 25 min, including 20 min of play with toys and 5 min of book reading. The caregiver was invited but not required to observe the session. No caregiver instruction occurred in this phase.

Teach-Model-Coach-Review Phase

TMCR sessions lasted approximately 1 h and contained four segments corresponding to teach, model, coach, and review. The duration and activities of each are shown in Table  3 .

The Teach portion included a workshop (20–30 min) when a new strategy was introduced (i.e., at the beginning of the phase change for each tier), and the remaining sessions included a shorter review of the target strategies (5–10 min). During the Model portion (10 min), the therapist modeled all EMT en Español Para Autismo strategies with the child, including those that had not yet been taught to the caregiver. To avoid behavioral covariation across tiers (Gast et al., 2018 ), the therapist narrated and discussed her use of only the strategies that had been introduced to the caregiver. In the Coach segment (15 min), the caregiver used strategies during play, book-reading, and routines that had been collaboratively selected during the planning meeting. The interventionist coached the caregiver and provided brief positive feedback to support her use of the targeted strategies. The interventionist modeled and coached the caregiver to model spoken language targets while simultaneously activating corresponding symbols with the SGD (Biggs et al., 2018 ; Sevcik et al., 1995 ). In some cases, 10 min of play was divided into shorter segments with visual timers for the child. Finally, in the Review segment (5–10 min), the caregiver and therapist reviewed and reflected on the session. Overall, the child received intervention from the caregiver for 15 min during the Coach component and from the interventionist for 10 min during the Model component. Only 10 min of caregiver-child interaction were coded, as described below.

Generalization sessions lasted 15 min and occurred four times for each family during the TMCR phase—once before each of the three workshops, and once before the exit interview. Like baseline sessions, the therapist did not provide any coaching or instruction before, during, or after the caregiver-child interaction. Like TMCR sessions, the therapist asked the family to engage in the three activity contexts: play (10 min), book-reading (2–3 min), and routine (2–3 min) (Table  3 ).

Post-Intervention Phase

Daniel’s mother, father, and grandmother participated in the exit interview (English version available in Online Resource). María and Luis’s grandmother participated in the exit interview. The exit interviews were conducted in Spanish by the interventionist who did not coach the family. Questions were related to the utility of EMT en Español Para Autismo strategies, approximately how often the caregivers practiced the strategies each week during different types of activities, and how the intervention could be improved for families who would participate in the future. The interviewer also asked families to rate the effectiveness and appropriateness of each of the EMT en Español Para Autismo strategies on a 5-point Likert-type scale (1 = ineffective or inappropriate, 5 = very effective and appropriate). Follow-up generalization session procedures were identical to TMCR phase generalization session procedures.

Data Collection

Sessions were transcribed and coded from video following each session using Systematic Analysis of Language Transcripts (SALT) software, Version 20 (Miller & Iglesias, 2020 ). Transcription and coding were performed by native Spanish speakers who were unaware of condition changes to mitigate potential bias (Ledford et al., 2018 ). These transcribers and coders were undergraduate students or bachelor’s or master’s level research staff who had been trained to transcribe and code similar interactions using videos from EMT en Español projects. Coded segments were 10 min in length and included 8 min of play, 1 min of routines, and 1 min of book reading from caregiver-child interactions (i.e., in TMCR sessions, the Coach segment).

Dependent variable definitions are in Table  1 . Caregiver variables were the caregivers’ use of EMT en Español Para Autismo strategies. Target level language for the current study was based on a three-level framework for Spanish language targets developed and used in an ongoing study with LSS children with developmental language disorders (Kaiser & Peredo, 2019 –2024). Children in the current study were in the first level; target level and proximal target level language models are described in Table  1 . Child dependent variables were the number of total words (NTW), the number of different words (NDW), and the number of times the child communicated with a vocalization, gesture, or word in any mode. All words used by the children were in Spanish during these sessions; however, any words used in English would also have been counted in NTW and NDW.

Fidelity and Reliability

Procedural fidelity refers to the extent to which each experimental condition was executed as planned (Barton et al., 2018b ). For each type of session (baseline, therapist-child intervention, TMCR, or generalization), 33% of sessions were randomly selected (using the RAND() function in Excel) for procedural fidelity measurement by a trained research team member who did not participate in carrying out sessions. Fidelity checklists specific to each session type were completed from video by a trained observer (other than the interventionist) in a REDCap database (Harris et al., 2009 ). The interventionists were unaware of which sessions were randomly selected for procedural fidelity measurement. Procedural fidelity averaged 90.2% (75.0–100.0%) across 39 sessions.

Point-by-point interobserver reliability was measured for a randomly selected sample of 33% of sessions for caregiver-child interaction data. The first author performed the random selection of sessions using Excel. Coders were unaware of which sessions were randomly selected for interobserver reliability until after primary transcription and coding of the session were complete. Interobserver reliability for 29 caregiver-child interactions averaged 89.1% (77.5–95.5%) for caregiver data and 87.2% (73.1–95.1%) for child data.

There were concerns regarding low interobserver reliability for some sessions, especially at the beginning of the study. Many disagreements were related to determining whether child vocalizations had communicative intent and whether the adult gave the child enough time to respond. Coding error patterns were reviewed, discussed, and consensus coded at weekly meetings throughout the study (Yoder et al., 2018 ). Consensus codes were revised in the primary data. Midway through the study, to ensure consistency of coding over the course of the study, a trained coder reviewed and verified coding of sessions that had been transcribed and coded up to that point. Sixty-four caregiver-child interactions (out of 82 coded sessions, 78%) were verified.

Data Analysis

Caregiver data were graphed and visually analyzed to inform decision-making and to determine the presence or absence of a functional relation for each dyad (Barton et al., 2018a ; Gast et al., 2018 ). Graphs were produced using GraphPad Prism 10 for Windows version 10.1.0 (GraphPad Software, LLC , 2023). The first, second, and fourth authors reviewed primary data weekly throughout the study; decisions were made by consensus. Secondary dependent variables (i.e., generalization and maintenance of caregiver strategy use, child communication) were also graphed and visually analyzed at the end of the study but were not considered in decisions related to phase changes. In addition to visual analysis, we measured the magnitude of change for each demonstration of effect by calculating the log response ratio (LRR) effect sizes. LRRs are advantageous because of the relative insensitivity to procedural variables and the interpretation as percentage of change over baseline (Pustejovsky, 2018 , 2019 ). LRRs were calculated using RStudio version 4.0.2 (R Core Team, 2020 ) and the batch_calc_es() function in the SingleCaseES package (Pustejovsky et al., 2021 ). To analyze the social validity of the intervention, responses and notes relevant to the fourth research question (pertaining to how caregivers perceived the intervention approach) from mini-interviews and exit interviews were synthesized by the first author and reviewed by the second and fourth authors. Responses to Likert-type questions were averaged, and family comments were summarized.

Caregiver Strategy Use

Dayana’s data are in Fig.  2 . Her use of target level language (Tier 1), expansions (a Tier 2 dependent variable), and communication elicitations (Tier 3) were low and stable during baseline. Contingent target language and communication elicitations immediately increased (within 3 sessions) and her expansions began on a clear increasing trend after the strategies were introduced. In baseline, contingent proximal target language (a Tier 2 dependent variable) increased from near zero to approximately 20 ( M  = 15.5, range 3–23) when Tier 1 strategies were introduced. Proximal targets increased again slightly and became more variable ( M  = 26.0, range 13–41) in Tier 2. Dayana generalized her use of all strategies to sessions without coaching during the study and at follow-up, although communication elicitations decreased at the 2-month follow-up. Overall, Dayana increased use of contingent targets by 883% over baseline ( LRRi  = 2.30) and her use of proximal targets by 211% over baseline ( LRRi  = 1.13) with the TMCR intervention. Effect sizes for expansions and communication elicitations were not interpretable because caregiver use of these strategies was near 0 in baseline.

Graphs with four tiers depicting Dayana’s use of strategies. Strategy use increased intervention was introduced for target language and communication elicitations. Proximal targets increased when Tier 1 intervention began. Expansions increased gradually when Tier 2 intervention began. The vertical lines indicate when intervention began for each strategy. Gray boxes indicate when therapist-child intervention occurred. Line graphs show the number of times the caregiver used the targets or proximal targets in coached interactions (black circles) and uncoached interactions (white circles). White bars indicate opportunities to expand or communication elicitation attempts. Black bars indicate expansions or high-quality communication elicitations

María’s data are in Fig.  3 . Her use of Tier 2 strategies (proximal target language modeling and expansions) were low and stable during baseline. Contingent target language (Tier 1) and communication elicitations (Tier 3) were somewhat variable during baseline. Data for all strategies demonstrated clear increases in level in the first or second session after the strategies were introduced. There were slight decreasing trends for target language (Tier 1), expansions (a Tier 2 dependent variable), and communication elicitations (Tier 3). Contingent target language remained variable during the intervention phase ( M  = 26.3, range 6–46) but was higher than baseline ( M  = 7.2, range 2–16), on average. Caregiver 2’s generalization to sessions without coaching was variable across strategies. She used targets and communication elicitations but not proximal targets at the follow-up session (there were no opportunities for expansions). Overall, María increased her use of targets by 250% over baseline ( LRRi  = 1.25) and her use of proximal targets by 168% over baseline ( LRRi  = 0.99) with the TMCR intervention. The effect sizes for expansions and communication elicitations were not interpretable because caregiver use of these strategies was near 0 in baseline.

Graphs with four tiers depicting María’s use of strategies. Strategy use increased for each set when intervention was introduced, but contingent targets remained variable. The vertical lines indicate when intervention began for each strategy. Gray boxes indicate when therapist-child intervention occurred. Line graphs show the number of times the caregiver used the targets or proximal targets in coached interactions (black circles) and uncoached interactions (white circles). White bars indicate opportunities to expand or communication elicitation attempts. Black bars indicate expansions or high-quality communication elicitations

Child Communication

Child communication outcomes are displayed in Figs.  4 and 5 .

Line graphs showing Daniel’s NTW, NDW, and social communication per caregiver-child interaction in TMCR (black circles) and generalization (white circles) sessions. Vertical lines indicate when new intervention strategies were introduced. NTW and NDW were low in baseline and Tier 1. They increased and became variable in Tiers 2 and 3. Social communication was highly variable and increasing in Tiers 2 and 3. Gray boxes indicate when therapist-child intervention occurred

Line graphs showing Luis’s NTW, NDW, and social communication per caregiver-child interaction in TMCR (black circles) and generalization (white circles) sessions. Vertical lines indicate when new intervention strategies were introduced. NTW and NDW were low in baseline. They increased and were variable in all three tiers of intervention. Social communication was highly variable and had an increasing trend across all phases. Gray boxes indicate when therapist-child intervention occurred

Nearly all words children used were communicated via the SGD. Daniel’s communication with words remained near zero until Tier 2 of intervention, then NTW and NDW increased and became more variable. In Tier 3, Daniel averaged 20.7 total words (range 0–45) and 10.8 different words (range 0–23) per session. For social communication (i.e., utterances with vocalizations, gestures, or words), there was a decreasing trend in baseline ( M  = 16.2, range 4–30), and data were variable through the middle of Tier 2. In Tier 3, Daniel was communicating more frequently on average ( M  = 34.7, range 15–54) than in baseline with a large amount of overlap. Luis communicated using fewer than five words per session until the end of Tier 1 when he used 14 words in one session. NTW and NDW were variable but higher than baseline throughout Tiers 2 and 3 (NTW, M  = 11.3, range 3–25; NDW, M  = 8.2, range 3–17). The number of social communication acts was variable throughout the study with an increasing trend. Luis’s social communication in Tier 3 ( M  = 32.8, range 19–51) was higher than in baseline ( M  = 12.7, range 5–29) with some overlap. Notably, Luis’s NTW and NDW decreased to 0 at the follow-up session. Upon arrival, it was discovered that his SGD had been malfunctioning for some time. It was repaired prior to the follow-up generalization session.

Social Validity

At the exit interview, caregivers reported that the most helpful component of TMCR was watching the interventionist model the intervention with the child (Dayana) or practicing implementing the strategies with coach feedback (María). Both reported using EMT en Español Para Autismo strategies every day, including during play, pre-academic activities (e.g., coloring, book-sharing), and caregiving routines (e.g., bath time, mealtime). They rarely used intervention strategies during housekeeping routines (e.g., laundry, cleaning). Both participating caregivers taught the strategies to other family members. When asked how the intervention could be improved, one family suggested adding music to some of the activities to help the child concentrate. The other family suggested a longer intervention period. Dayana rated all strategies on which she was trained with a 5 (very effective and appropriate). María rated all strategies with a 4 or 5 except for the Tier 1 strategies of reducing instructions and questions, which she rated a 1 (ineffective and inappropriate). Both families reported difficulty with managing the SGD. María did not agree with allowing children to frequently use tablets and phones, but she could see her child was happy when he was understood by others. Daniel’s family became frustrated when he became so focused on his device that he did not participate in the activity at hand (e.g., eating his food at mealtime).

The primary purpose of the current pilot study was to test the effects of the collaborative TMCR approach to teach EMT en Español Para Autismo strategies to two Latina Spanish-speaking caregivers with their toddlers on the autism spectrum. Social validity analyses indicated both families felt the intervention was effective with some concerns related to use of the SGDs. This study extends the small research base on culturally and linguistically adapted early communication interventions for LSS families and their children on the autism spectrum.

The study’s development and design had unique strengths. First, the intervention was initially adapted for LSS families of young children with language delays (Peredo et al., 2018 , 2022 ) and adapted again for children on the autism spectrum. Second, the intervention was individualized for each participating dyad based on repeated family interviews throughout the study and a direct therapist-delivery phase of intervention prior to caregiver coaching. The essential components of EMT that support children’s language development (e.g., environmental arrangement, contingent language modeling) were maintained; however, these components allowed the therapist to build and maintain rapport with the family during baseline and while teaching the intervention strategies. They also supported collaboration and family preference related to intervention materials, activities, engagement supports, and introduction and programming of the SGD.

TMCR and EMT en Español Para Autismo Strategies

There was a clear functional relation between systematic implementation of the TMCR approach and use of EMT en Español Para Autismo strategies for one of the caregivers (María). In other words, she increased her use of specific EMT en Español Para Autismo strategies when and only when she was taught each strategy using the TMCR approach (Gast et al., 2018 ). For Dayana, there were three demonstrations of the effect of TMCR on use of target level language, expansions, and communication elicitations (Gast et al., 2018 ). However, the confidence in the functional relation was weakened by the covariation between contingent target and proximal target level language. The increase in proximal target level language (a Tier 2 strategy) corresponded with the introduction of Tier 1 strategies. This covariation indicates that use of proximal and target level phrases were not fully independent behaviors for Dayana; rather, she began using simpler phrases at a higher rate when target level language was introduced and did not discriminate targets from proximal targets. Although unexpected, this response generalization is not surprising given the precise linguistic distinctions between target-level and proximal target-level language targets as shown in Table  1 . For example, the label for popsicle would be a target if it were in singular form (la paleta) and a proximal target if it were in plural form (las paletas). Many caregivers would likely benefit from being taught target level and proximal target level language simultaneously rather than teaching proximal targets at the same time as expansions.

The caregivers reported the TMCR approach to be effective and helpful for them in learning the strategies. They reported that most of the EMT en Español Para Autismo strategies were effective and appropriate with one exception. María indicated that reducing instructions and questions to balance matched turns was ineffective and inappropriate for her in interactions with her child. This finding is somewhat consistent with other EMT en Español studies in which caregivers reported a cultural tension with reducing questions and directions but found it to be an effective strategy for their child (Peredo et al., 2018 , 2020 ). Further research on the perceived effectiveness of reducing test questions and behavioral directions from LSS caregivers of children on the autism spectrum will help determine if further adaptation of this strategy is needed.

The findings should be interpreted in light of the fact that caregiver opportunities to practice and demonstrate skills such as use of targets and expansions were contingent on the opportunities presented by child communication and engagement. Simply put, for caregivers to immediately increase their behavior, there had to be child-presented opportunities to respond. Measuring contingent behavior in this way closely reflects the posited active ingredient of the intervention (Dillehay, 2023 ), and it may explain differences between results in the current and previous studies. Unlike in the Peredo et al. ( 2018 ) study, in the current pilot study, Dayana’s use of expansions increased gradually. Daniel often activated the same word many times in a row, and it was difficult to determine his communicative intent. This could have influenced Dayana’s ability to respond contingently using expansions and coders’ interobserver agreement.

Independent Use of Strategies

Use of strategies generalized or partially generalized to sessions without coaching support, including at follow-up. The overall number of generalization sessions was small, and the context only differed from the intervention context by one variable (the absence of coaching support); however, the current data are encouraging when interpreted alongside the caregiver reports that they used EMT en Español Para Autismo strategies throughout the week during play, book reading, and routines. The individualization of the intervention (i.e., collaborative selection of toys, interviews) may also have supported generalization by ensuring intervention activities aligned with family activities outside the study and that multiple family members were involved (DuBay et al., 2018 ). María’s use of Tier 2 strategies did not generalize or maintain at the 2-month follow-up. At that session, she did not have opportunities to expand because Luis did not use any verbal utterances. Luis’s decrease in verbal communication may have been related to lack of access to his SGD prior to the follow-up session. Families would likely benefit from booster sessions and check-ins for technical support for long-term generalization and maintenance of strategy use (Kent-Walsh & McNaughton, 2005 ).

Child Outcomes

While the design of this pilot study did not control for possible effects of maturation on child communication, both children in the study demonstrated significant growth during the 6–7 months they were in the study. Neither child was receiving any other targeted language intervention in Spanish at the time that might have accounted for the growth. Both children began using SGDs provided during the study (and were not using them during baseline), which was likely critical for supporting their increased communication, in addition to implementation of the EMT en Español Para Autismo strategies with aided modeling by their caregivers and the therapists. Also important to note regarding child outcome data was that, to increase coding reliability, a decision was made to score child vocalizations or activation of SGD symbols as communicative if the caregiver responded contingently. Therefore, it is possible that a greater proportion of child vocalizations and SGD activations were coded as communicative in later sessions than in earlier sessions, reflecting both increases in caregiver responsiveness and differences in child communication.

Limitations

The first major limitation to this pilot study was the number of participants. Four families enrolled in the study, and only two families completed the intervention. Both families that dropped out indicated that they did not want to tire their child by having them in too many therapies. This speaks to the time and effort that families must contribute to participating in an intensive early childhood intervention and particularly to the research requirements associated with added paperwork and scheduling of sessions. For researchers, it is important to consider shorter baselines, limited paperwork, and designs that require fewer sessions. Solutions in practice may include a greater degree of collaboration between the multiple providers (Part C developmental therapists, speech language pathologists, and others), more efficient use of therapy time, and continuously engaging with families to understand their priorities in choosing services and delivery models.

Another limitation was that introduction of new EMT en Español Para Autismo strategies roughly coincided with minor changes to routine contexts for intervention (described in the Participants section). After mini-interviews, routines began to include coloring for Daniel and brushing teeth and washing dishes for Luis. It is possible that the new contexts influenced the caregivers’ use of strategies at the time they were introduced; however, those changes would likely have affected caregivers’ data in all tiers. Routine contexts also comprised a small proportion of the data collection period in each session (1 min out of 10 min).

Other limitations pertained to interpretation of child outcomes. Given the study design, child communication outcomes could not be attributed specifically to caregiver use of EMT en Español Para Autismo strategies. The children received the full intervention from the therapist during the initial direct intervention phase and during the model portions of the TMCR sessions. The caregivers were not taught the full intervention until Tier 3 near the end of the study. Additionally, the contribution of the children’s access to the SGD could not be separated from the effects of the EMT en Español Para Autismo intervention delivered by the therapist and the caregiver. Future studies should investigate caregiver implementation of EMT en Español Para Autismo with SGDs using a study design that allows for detection of effects of caregiver training alone on child outcomes.

Future Directions for Research

Future research should build on the current findings by systematically replicating the current study with additional LSS families from diverse backgrounds. Children on the autism spectrum are heterogeneous as well, with different interests and abilities including social communication, receptive and expressive language skills, and engagement in play-based activities (McDuffie et al., 2012 ). Systematic assessment, the direct therapist intervention component, as well as the collaborative interview process and strategic individualization in this pilot study present one potential model for future studies to individualize EMT en Español Para Autismo for diverse LSS participants.

Future research should also expand the intervention to address all aspects of using AAC with this population of families. Although both children demonstrated increases in verbal communication using SGDs, one caregiver indicated that she was reluctant to use it at the beginning of the intervention and the other family reported difficulty managing the SGD during everyday routines. Researchers should continue to develop materials and methods for teaching LSS caregivers about AAC (De Leon et al., 2023 ), the evidence to support its use by children on the autism spectrum (e.g., Hampton et al., 2020 ), and instruction in how to model language using SGDs (Biggs et al., 2018 ; Sevcik et al., 1995 ). Low-tech forms of AAC may also be effective and preferred by some families. These materials should be culturally and linguistically adapted with the help of LSS families, as were the workshops for the current study. Future studies should also delineate systematic procedures for selection of Spanish and English vocabulary to include on the devices, incorporating principles of typical bilingual Spanish and English language development and individualized family communication needs (Binger et al., 2023 ; Soto & Cooper, 2021 ).

Implications for Practice

Practitioners could apply the collaborative interview process when working with LSS families and children on the autism spectrum using the protocols in the Online Resource and published by Peredo ( 2016 ). Conversations or interviews prior to implementing family-centered intervention have been recommended when working with culturally and linguistically diverse families (Cycyk & Iglesias, 2015 ; Peredo, 2016 ). In the current study, these interviews systematically occurred at regular intervals throughout intervention. Intervention should ideally be provided by practitioners that speak Spanish when that is the family’s home language. However, practitioners working with interpreters or with limited proficiency in the family’s home language could also use similar interview questions to structure conversations to better understand family values, frequent activities, and preferences.

Bilingual practitioners may also consider a direct intervention component when working with LSS families with toddlers on the autism spectrum. A direct therapist intervention phase prior to caregiver coaching could support planning and collaboration by giving the practitioner a better understanding of potentially needed supports (e.g., AAC, behavior supports). A continued direct intervention throughout the caregiver coaching phase, either via the Model component of TMCR or additional direct intervention sessions, could support overall dosage of intervention received by the child. This dual implementer approach could ease the pressure on caregivers to deliver the entire dosage of intervention necessary to see language skill gains while still engaging and empowering families to support their child’s growth.

Few intervention studies have focused specifically on the experiences, needs, and preferences of LSS families with children on the autism spectrum. This study demonstrated effective application of the TMCR approach to teach caregivers a culturally, linguistically, and individually adapted intervention. The caregivers in the current pilot study implemented EMT en Español Para Autismo strategies with their children on the autism spectrum, generalized use of most of the strategies to unsupported interactions, and gave positive feedback about their experience with the intervention. The children increased the frequency and diversity of communication with their caregivers over time. This study contributes to the literature on family-centered naturalistic developmental behavioral interventions for diverse families and children on the autism spectrum. More systematic inquiry is needed to understand the effects and social validity of the TMCR approach and EMT en Español Para Autismo strategies for diverse families.

AssistiveWare. (2023). Proloquo2Go AAC [Mobile app]. App Store. https://apps.apple.com/us/app/proloquo2go-aac/id308368164

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.

Article   PubMed   PubMed Central   Google Scholar  

Barton, E. E., Lloyd, B. P., Spriggs, A. D., & Gast, D. L. (2018a). Visual analysis of graphic data. In J. R. Ledford & D. L. Gast (Eds.), Single case research methodology: Applications in special education and behavioral sciences (3rd ed., pp. 179–214). Routledge.

Chapter   Google Scholar  

Barton, E. E., Meadan-Kaplansky, H., & Ledford, J. R. (2018b). Independent variables, fidelity, and social validity. In J. R. Ledford & D. L. Gast (Eds.), Single case research methodology: Applications in special education and behavioral sciences (3rd ed., pp. 133–156). Routledge.

Bernal, G., Bonilla, J., & Bellido, C. (1995). Ecological validity and cultural sensitivity for outcome research: Issues for the cultural adaptation and development of psychosocial treatments with Hispanics. Journal of Abnormal Child Psychology, 23 , 67–82.

Article   PubMed   Google Scholar  

Beukelman, D. R., & Light, J. K. (Eds.). (2020). Augmentative and alternative communication: Supporting children and adults with complex communication needs (5th ed.). Brookes.

Google Scholar  

Biggs, E. E., Carter, E. W., & Gilson, C. B. (2018). Systematic review of interventions involving aided AAC modeling for children with complex communication needs. American Journal on Intellectual and Developmental Disabilities , 123 (5), 443–473. https://doi.org/10.1352/1944-7558-123.5.443

Binger, C., Harrington, N., & Kent-Walsh, J. (2023). Applying a developmental model to preliterate aided language learning. American Journal of Speech-Language Pathology , 33 , 33–50. https://doi.org/10.1044/2023_AJSLP-23-00098

Chlebowski, C., Magaña, S., Wright, B., & Brookman-Frazee, L. (2018). Implementing an intervention to address challenging behaviors for autism spectrum disorder in publicly-funded mental health services: Therapist and parent perceptions of delivery with Latinx families. Cultural Diversity and Ethnic Minority Psychology, 24 (4), 552–563. https://doi.org/10.1037/cdp0000215

Corona, L., Hine, J., Nicholson, A., Stone, C., Swanson, A., Wade, J., Wagner, L., Weitlauf, A., & Warren, Z. (2020). TELE-ASD-PEDS: A telemedicine-based ASD evaluation tool for toddlers and young children . Vanderbilt University Medical Center.

Cycyk, L., & Iglesias, A. (2015). Parent programs for Latino families with young children: Social, cultural, and linguistic considerations. Seminars in Speech and Language, 36 (02), 143–153. https://doi.org/10.1055/s-0035-1549109

De Leon, M., Solomon-Rice, P., & Soto, G. (2023). Perspectives and experiences of eight Latina mothers of young children with augmentative and alternative communication needs. Perspectives of the ASHA Special Interest Groups , 8 (5), 1072–1085. https://doi.org/10.1044/2023_PERSP-23-00074

Article   Google Scholar  

Dillehay, K. M. (2023). Dosage, fidelity, and child outcomes in a small randomized controlled trial of EMT en Español . Dissertation, Vanderbilt University.

DuBay, M. (2022). Cultural adaptations to parent-mediated autism spectrum disorder interventions for Latin American families: A scoping review. American Journal of Speech-Language Pathology . https://doi.org/10.1044/2022_AJSLP-21-00239

DuBay, M., Watson, L. R., & Zhang, W. (2018). In search of culturally appropriate autism interventions: Perspectives of latino caregivers. Journal of Autism and Developmental Disorders, 48 (5), 1623–1639. https://doi.org/10.1007/s10803-017-3394-8

Gast, D. L., Lloyd, B. P., & Ledford, J. R. (2018). Multiple baseline and multiple probe designs. In J. R. Ledford & D. L. Gast (Eds.), Single case research methodology (3rd ed., pp. 239–281). Routledge/Taylor & Francis Group.

Gevarter, C., Najar, A. M., Flake, J., Tapia-Alvidrez, F., & Lucero, A. (2022). Naturalistic communication training for early intervention providers and Latinx parents of children with signs of autism. Journal of Developmental and Physical Disabilities, 34 (1), 147–169. https://doi.org/10.1007/s10882-021-09794-w

GraphPad Software, LLC. (2023). GraphPad Prism 10 for macOS (Version 10.0.0) [Computer Software]. https://www.graphpad.com/

Hampton, L. H., Harty, M., Fuller, E. A., & Kaiser, A. P. (2019). Enhanced milieu teaching for children with autism spectrum disorder in South Africa. International Journal of Speech-Language Pathology, 21 (6), 635–645. https://doi.org/10.1080/17549507.2018.1559357

Hampton, L. H., Kaiser, A. P., & Fuller, E. A. (2020). Multi-component communication intervention for children with autism: A randomized controlled trial. Autism, 24 (8), 2104–2116. https://doi.org/10.1177/1362361320934558

Hampton, L., Kaiser, A., Nietfeld, J., & Khachoyan, A. (2021). Generalized effects of naturalistic social communication intervention for minimally verbal children with autism. Journal of Autism and Developmental Disorders, 51 , 75–87. https://doi.org/10.1007/s10803-020-04521-4

Harris, P. A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., & Conde, J. G. (2009). Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics, 42 (2), 377–381. https://doi.org/10.1016/j.jbi.2008.08.010

Heidlage, J. K., Cunningham, J. E., Kaiser, A. P., Trivette, C. M., Barton, E. E., Frey, J. R., & Roberts, M. Y. (2020). The effects of parent-implemented language interventions on child linguistic outcomes: A meta-analysis. Early Childhood Research Quarterly , 50 , 6–23. https://doi.org/10.1016/j.ecresq.2018.12.006

Kaiser, A. P., Fuller, E. A., & Heidlage, J. K. (2021). Implementing enhanced milieu teaching with children who have autism spectrum disorder. In P. A. Prelock & R. J. McCauley (Eds.), Treatment of autism spectrum disorders: Evidence-based intervention strategies for communication and social interaction (2nd ed., pp. 255–286). Paul H. Brookes.

Kaiser, A. P., & Hampton, L. H. (2017). Enhanced milieu teaching. In R. J. McCauley, M. E. Fey, & R. B. Gillam (Eds.), Treatment of language disorders in children (2nd ed., pp. 87–119). Paul H. Brookes.

Kaiser, A. P., & Peredo, T. N. (2019–2024). EMT en Español: Comprehensive early intervention to support school readiness skills for Spanish-speaking toddlers with language delays (Project No. R324A190177) [Grant]. National Center for Special Education Research. https://ies.ed.gov/funding/grantsearch/details.asp?ID=3293

Kent-Walsh, J., & McNaughton, D. (2005). Communication partner instruction in AAC: Present practices and future directions. Augmentative and Alternative Communication, 21 (3), 195–204. https://doi.org/10.1080/07434610400006646

Ledford, J. R., Lane, J. D., & Gast, D. L. (2018). Dependent variables, measurement, and reliability. In J. R. Ledford & D. L. Gast (Eds.), Single case research methodology (3rd ed., pp. 97–131). Routledge/Taylor & Francis Group.

Martinez-Torres, K., Boorom, O., Peredo, T., Camarata, S., & Lense, M. D. (2021). Using the ecological validity model to adapt parent-involved interventions for children with autism spectrum disorder in the latinx community: A conceptual review. Research in Developmental Disabilities, 116 , 1–12. https://doi.org/10.1016/j.ridd.2021.104012

McDuffie, A. S., Lieberman, R. G., & Yoder, P. J. (2012). Object interest in autism spectrum disorder: A treatment comparison. Autism, 16 (4), 398–405. https://doi.org/10.1177/1362361309360983

Meadan, H., Adams, N. B., Hacker, R. E., Ramos-Torres, S., & Fanta, A. (2020). Supporting Spanish-speaking families with children with disabilities: Evaluating a training and coaching program. Journal of Developmental and Physical Disabilities, 32 (3), 489–507. https://doi.org/10.1007/s10882-019-09704-1

Miller, J., & Iglesias, A. (2020). Systematic Analysis of Language Transcripts (SALT) (Version 20) [Computer Software]. SALT Software, LLC.

Peredo, T. N. (2016). Supporting culturally and linguistically diverse families in early intervention. Perspectives of the ASHA Special Interest Groups, 1 (1), 154–167. https://doi.org/10.1044/persp1.SIG1.154

Peredo, T. N., Dillehay, K. M., & Kaiser, A. P. (2020). Latino caregivers’ interactions with their children with language delays: A comparison study. Topics in Early Childhood Special Education . https://doi.org/10.1177/0271121419900269

Peredo, T. N., Mancilla-Martinez, J., Durkin, K., & Kaiser, A. P. (2022). Teaching Spanish-speaking caregivers to implement EMT en Español : A small randomized trial. Early Childhood Research Quarterly, 58 , 208–219. https://doi.org/10.1016/j.ecresq.2021.08.004

Peredo, T. N., Zelaya, M. I., & Kaiser, A. P. (2018). Teaching low-income Spanish-speaking caregivers to implement EMT en Español with their young children with language impairment: A pilot study. American Journal of Speech—Language Pathology, 27 (1), 136–153.

Pustejovsky, J. E. (2018). Using response ratios for meta-analyzing single-case designs with behavioral outcomes. Journal of School Psychology, 68 , 99–112. https://doi.org/10.1016/j.jsp.2018.02.003

Pustejovsky, J. E. (2019). Procedural sensitivities of effect sizes for single-case designs with directly observed behavioral outcome measures. Psychological Methods, 24 (2), 217–235. https://doi.org/10.1037/met0000179

Pustejovsky, J. E., Chen, M., & Swan, D. M. (2021). SingleCaseES: A Calculator for Single-Case Effect Sizes. R package (version 0.5.0). https://CRAN.R-project.org/package=SingleCaseES

R Core Team. (2020). R: A language and environment for statistical computing . R Foundation for Statistical Computing.

Roberts, M. Y., Curtis, P. R., Sone, B. J., & Hampton, L. H. (2019). Association of parent training with child language development: A systematic review and meta-analysis. JAMA Pediatrics , 173 (7), 671. https://doi.org/10.1001/jamapediatrics.2019.1197

Roberts, M. Y., & Kaiser, A. P. (2015). Early intervention for toddlers with language delays: A randomized controlled trial. Pediatrics, 135 (4), 686–693. https://doi.org/10.1542/peds.2014-2134

Schreibman, L., Dawson, G., Stahmer, A. C., Landa, R., Rogers, S. J., McGee, G. G., Kasari, C., Ingersoll, B., Kaiser, A. P., Bruinsma, Y., McNerney, E., Wetherby, A., & Halladay, A. (2015). Naturalistic developmental behavioral interventions: Empirically validated treatments for autism spectrum disorder. Journal of Autism and Developmental Disorders, 45 (8), 2411–2428. https://doi.org/10.1007/s10803-015-2407-8

Sevcik, R. A., Romski, M. A., Watkins, R. V., & Deffebach, K. P. (1995). Adult partner-augmented communication input to youth with mental retardation using the System for Augmenting Language (SAL). Journal of Speech, Language, and Hearing Research, 38 (4), 902–912. https://doi.org/10.1044/jshr.3804.902

Shaw, K. A., Bilder, D. A., McArthur, D., Williams, A. R., Amoakohene, E., Bakian, A. V., Durkin, M. S., Fitzgerald, R. T., Furnier, S. M., Hughes, M. M., Pas, E. T., Salinas, A., Warren, Z., Williams, S., Esler, A., Grzybowski, A., Ladd-Acosta, C. M., Patrick, M., Zahorodny, W., & Maenner, M. J. (2023). Early identification of autism spectrum disorder among children aged 4 years—Autism and developmental disabilities monitoring network, 11 Sites, United States, 2020. MMWR. Surveillance Summaries, 72 (1), 1–15. https://doi.org/10.15585/mmwr.ss7201a1

Article   PubMed Central   Google Scholar  

Soto, G., & Cooper, B. (2021). An early Spanish vocabulary for children who use AAC: Developmental and linguistic considerations. Augmentative and Alternative Communication , 37 (1), 64–74. https://doi.org/10.1080/07434618.2021.1881822

Stahmer, A. C., Vejnoska, S., Iadarola, S., Straiton, D., Segovia, F. R., Luelmo, P., Morgan, E. H., Lee, H. S., Javed, A., Bronstein, B., Hochheimer, S., Cho, E., Aranbarri, A., Mandell, D., Hassrick, E. M., Smith, T., & Kasari, C. (2019). Caregiver voices: Cross-cultural input on improving access to autism services. Journal of Racial and Ethnic Health Disparities, 6 (4), 752–773. https://doi.org/10.1007/s40615-019-00575-y

Stone, W. L., & Ousley, O. Y. (2008). Screening tool for autism in toddlers and young children . Vanderbilt University.

Wright, C., Kaiser, A., Reikowsky, D., & Roberts, M. (2013). Effects of a naturalistic sign intervention on expressive language of toddlers with Down syndrome. Journal of Speech, Language, and Hearing Research, 56 , 994–1008.

Yoder, P. J., Lloyd, B. P., & Symons, F. J. (2018). Observational measurement of behavior (2nd ed.). Brookes Publishing.

Zimmerman, I. L., Steiner, V. G., & Pond, R. E. (2012). Preschool language scales (5th Spanish) . Pearson.

Zuckerman, K. E., Lindly, O. J., Reyes, N. M., Chavez, A. E., Macias, K., Smith, K. N., & Reynolds, A. (2017). Disparities in diagnosis and treatment of autism in Latino and non-Latino white families. Pediatrics, 139 (5), e20163010.

Download references

Acknowledgments

This work was funded in part by an internal Scaling Success grant from Vanderbilt University, the United States Office of Special Education Programs Grants (H325D180095, PI: Ann P. Kaiser), and a Semmel Dissertation Enhancement Award from the Department of Special Education, Peabody College, Vanderbilt University. This study was registered on the Open Science Framework ( https://doi.org/10.17605/OSF.IO/HJ9MK ). We sincerely thank our coders Georgina Cisneros, Monica Alonso, Gabriela Conde, Vanessa Schor, and Kelsey Dillehay for their contributions to this project.

Author information

Natalie S. Pak

Present address: Department of Communication Sciences and Disorders, University of South Florida, Tampa, FL, USA

Authors and Affiliations

Department of Special Education, Peabody College, Vanderbilt University, Nashville, TN, USA

Natalie S. Pak, Tatiana Nogueira Peredo, Ana Paula Madero Ucero & Ann P. Kaiser

You can also search for this author in PubMed   Google Scholar

Contributions

NSP contributed to the study conceptualization, methodology, data collection, writing original draft, project administration, analysis. TNP contributed to the study conceptualization, methodology, funding acquisition, writing review & editing, supervision. APMU contributed to the study conceptualization, data collection, writing review & editing. APK contributed to the study conceptualization, methodology, writing review & editing, funding acquisition, supervision.

Corresponding author

Correspondence to Natalie S. Pak .

Ethics declarations

Conflict of interest.

The intervention evaluated in this study was developed and adapted by authors of this paper. The study was completed for the dissertation of the first author in partial fulfillment of degree requirements.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Pak, N.S., Peredo, T.N., Madero Ucero, A.P. et al. EMT en Español Para Autismo : A Collaborative Communication Intervention Approach and Single Case Design Pilot Study. J Autism Dev Disord (2024). https://doi.org/10.1007/s10803-024-06322-5

Download citation

Accepted : 12 March 2024

Published : 13 April 2024

DOI : https://doi.org/10.1007/s10803-024-06322-5

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Early language intervention
• Single case
• Find a journal
• Publish with us
• Track your research

• Study Guides
• Homework Questions

Week 7 Case of Edward-1

• Health Science