case study for protocol

Designing and Conducting Case Studies

This guide examines case studies, a form of qualitative descriptive research that is used to look at individuals, a small group of participants, or a group as a whole. Researchers collect data about participants using participant and direct observations, interviews, protocols, tests, examinations of records, and collections of writing samples. Starting with a definition of the case study, the guide moves to a brief history of this research method. Using several well documented case studies, the guide then looks at applications and methods including data collection and analysis. A discussion of ways to handle validity, reliability, and generalizability follows, with special attention to case studies as they are applied to composition studies. Finally, this guide examines the strengths and weaknesses of case studies.

Definition and Overview

Case study refers to the collection and presentation of detailed information about a particular participant or small group, frequently including the accounts of subjects themselves. A form of qualitative descriptive research, the case study looks intensely at an individual or small participant pool, drawing conclusions only about that participant or group and only in that specific context. Researchers do not focus on the discovery of a universal, generalizable truth, nor do they typically look for cause-effect relationships; instead, emphasis is placed on exploration and description.

Case studies typically examine the interplay of all variables in order to provide as complete an understanding of an event or situation as possible. This type of comprehensive understanding is arrived at through a process known as thick description, which involves an in-depth description of the entity being evaluated, the circumstances under which it is used, the characteristics of the people involved in it, and the nature of the community in which it is located. Thick description also involves interpreting the meaning of demographic and descriptive data such as cultural norms and mores, community values, ingrained attitudes, and motives.

Unlike quantitative methods of research, like the survey, which focus on the questions of who, what, where, how much, and how many, and archival analysis, which often situates the participant in some form of historical context, case studies are the preferred strategy when how or why questions are asked. Likewise, they are the preferred method when the researcher has little control over the events, and when there is a contemporary focus within a real life context. In addition, unlike more specifically directed experiments, case studies require a problem that seeks a holistic understanding of the event or situation in question using inductive logic--reasoning from specific to more general terms.

In scholarly circles, case studies are frequently discussed within the context of qualitative research and naturalistic inquiry. Case studies are often referred to interchangeably with ethnography, field study, and participant observation. The underlying philosophical assumptions in the case are similar to these types of qualitative research because each takes place in a natural setting (such as a classroom, neighborhood, or private home), and strives for a more holistic interpretation of the event or situation under study.

Unlike more statistically-based studies which search for quantifiable data, the goal of a case study is to offer new variables and questions for further research. F.H. Giddings, a sociologist in the early part of the century, compares statistical methods to the case study on the basis that the former are concerned with the distribution of a particular trait, or a small number of traits, in a population, whereas the case study is concerned with the whole variety of traits to be found in a particular instance" (Hammersley 95).

Case studies are not a new form of research; naturalistic inquiry was the primary research tool until the development of the scientific method. The fields of sociology and anthropology are credited with the primary shaping of the concept as we know it today. However, case study research has drawn from a number of other areas as well: the clinical methods of doctors; the casework technique being developed by social workers; the methods of historians and anthropologists, plus the qualitative descriptions provided by quantitative researchers like LePlay; and, in the case of Robert Park, the techniques of newspaper reporters and novelists.

Park was an ex-newspaper reporter and editor who became very influential in developing sociological case studies at the University of Chicago in the 1920s. As a newspaper professional he coined the term "scientific" or "depth" reporting: the description of local events in a way that pointed to major social trends. Park viewed the sociologist as "merely a more accurate, responsible, and scientific reporter." Park stressed the variety and value of human experience. He believed that sociology sought to arrive at natural, but fluid, laws and generalizations in regard to human nature and society. These laws weren't static laws of the kind sought by many positivists and natural law theorists, but rather, they were laws of becoming--with a constant possibility of change. Park encouraged students to get out of the library, to quit looking at papers and books, and to view the constant experiment of human experience. He writes, "Go and sit in the lounges of the luxury hotels and on the doorsteps of the flophouses; sit on the Gold Coast settees and on the slum shakedowns; sit in the Orchestra Hall and in the Star and Garter Burlesque. In short, gentlemen [sic], go get the seats of your pants dirty in real research."

But over the years, case studies have drawn their share of criticism. In fact, the method had its detractors from the start. In the 1920s, the debate between pro-qualitative and pro-quantitative became quite heated. Case studies, when compared to statistics, were considered by many to be unscientific. From the 1930's on, the rise of positivism had a growing influence on quantitative methods in sociology. People wanted static, generalizable laws in science. The sociological positivists were looking for stable laws of social phenomena. They criticized case study research because it failed to provide evidence of inter subjective agreement. Also, they condemned it because of the few number of cases studied and that the under-standardized character of their descriptions made generalization impossible. By the 1950s, quantitative methods, in the form of survey research, had become the dominant sociological approach and case study had become a minority practice.

Educational Applications

The 1950's marked the dawning of a new era in case study research, namely that of the utilization of the case study as a teaching method. "Instituted at Harvard Business School in the 1950s as a primary method of teaching, cases have since been used in classrooms and lecture halls alike, either as part of a course of study or as the main focus of the course to which other teaching material is added" (Armisted 1984). The basic purpose of instituting the case method as a teaching strategy was "to transfer much of the responsibility for learning from the teacher on to the student, whose role, as a result, shifts away from passive absorption toward active construction" (Boehrer 1990). Through careful examination and discussion of various cases, "students learn to identify actual problems, to recognize key players and their agendas, and to become aware of those aspects of the situation that contribute to the problem" (Merseth 1991). In addition, students are encouraged to "generate their own analysis of the problems under consideration, to develop their own solutions, and to practically apply their own knowledge of theory to these problems" (Boyce 1993). Along the way, students also develop "the power to analyze and to master a tangled circumstance by identifying and delineating important factors; the ability to utilize ideas, to test them against facts, and to throw them into fresh combinations" (Merseth 1991).

In addition to the practical application and testing of scholarly knowledge, case discussions can also help students prepare for real-world problems, situations and crises by providing an approximation of various professional environments (i.e. classroom, board room, courtroom, or hospital). Thus, through the examination of specific cases, students are given the opportunity to work out their own professional issues through the trials, tribulations, experiences, and research findings of others. An obvious advantage to this mode of instruction is that it allows students the exposure to settings and contexts that they might not otherwise experience. For example, a student interested in studying the effects of poverty on minority secondary student's grade point averages and S.A.T. scores could access and analyze information from schools as geographically diverse as Los Angeles, New York City, Miami, and New Mexico without ever having to leave the classroom.

The case study method also incorporates the idea that students can learn from one another "by engaging with each other and with each other's ideas, by asserting something and then having it questioned, challenged and thrown back at them so that they can reflect on what they hear, and then refine what they say" (Boehrer 1990). In summary, students can direct their own learning by formulating questions and taking responsibility for the study.

Types and Design Concerns

Researchers use multiple methods and approaches to conduct case studies.

Types of Case Studies

Under the more generalized category of case study exist several subdivisions, each of which is custom selected for use depending upon the goals and/or objectives of the investigator. These types of case study include the following:

Illustrative Case Studies These are primarily descriptive studies. They typically utilize one or two instances of an event to show what a situation is like. Illustrative case studies serve primarily to make the unfamiliar familiar and to give readers a common language about the topic in question.

Exploratory (or pilot) Case Studies These are condensed case studies performed before implementing a large scale investigation. Their basic function is to help identify questions and select types of measurement prior to the main investigation. The primary pitfall of this type of study is that initial findings may seem convincing enough to be released prematurely as conclusions.

Cumulative Case Studies These serve to aggregate information from several sites collected at different times. The idea behind these studies is the collection of past studies will allow for greater generalization without additional cost or time being expended on new, possibly repetitive studies.

Critical Instance Case Studies These examine one or more sites for either the purpose of examining a situation of unique interest with little to no interest in generalizability, or to call into question or challenge a highly generalized or universal assertion. This method is useful for answering cause and effect questions.

Identifying a Theoretical Perspective

Much of the case study's design is inherently determined for researchers, depending on the field from which they are working. In composition studies, researchers are typically working from a qualitative, descriptive standpoint. In contrast, physicists will approach their research from a more quantitative perspective. Still, in designing the study, researchers need to make explicit the questions to be explored and the theoretical perspective from which they will approach the case. The three most commonly adopted theories are listed below:

Individual Theories These focus primarily on the individual development, cognitive behavior, personality, learning and disability, and interpersonal interactions of a particular subject.

Organizational Theories These focus on bureaucracies, institutions, organizational structure and functions, or excellence in organizational performance.

Social Theories These focus on urban development, group behavior, cultural institutions, or marketplace functions.

Two examples of case studies are used consistently throughout this chapter. The first, a study produced by Berkenkotter, Huckin, and Ackerman (1988), looks at a first year graduate student's initiation into an academic writing program. The study uses participant-observer and linguistic data collecting techniques to assess the student's knowledge of appropriate discourse conventions. Using the pseudonym Nate to refer to the subject, the study sought to illuminate the particular experience rather than to generalize about the experience of fledgling academic writers collectively.

For example, in Berkenkotter, Huckin, and Ackerman's (1988) study we are told that the researchers are interested in disciplinary communities. In the first paragraph, they ask what constitutes membership in a disciplinary community and how achieving membership might affect a writer's understanding and production of texts. In the third paragraph they state that researchers must negotiate their claims "within the context of his sub specialty's accepted knowledge and methodology." In the next paragraph they ask, "How is literacy acquired? What is the process through which novices gain community membership? And what factors either aid or hinder students learning the requisite linguistic behaviors?" This introductory section ends with a paragraph in which the study's authors claim that during the course of the study, the subject, Nate, successfully makes the transition from "skilled novice" to become an initiated member of the academic discourse community and that his texts exhibit linguistic changes which indicate this transition. In the next section the authors make explicit the sociolinguistic theoretical and methodological assumptions on which the study is based (1988). Thus the reader has a good understanding of the authors' theoretical background and purpose in conducting the study even before it is explicitly stated on the fourth page of the study. "Our purpose was to examine the effects of the educational context on one graduate student's production of texts as he wrote in different courses and for different faculty members over the academic year 1984-85." The goal of the study then, was to explore the idea that writers must be initiated into a writing community, and that this initiation will change the way one writes.

The second example is Janet Emig's (1971) study of the composing process of a group of twelfth graders. In this study, Emig seeks to answer the question of what happens to the self as a result educational stimuli in terms of academic writing. The case study used methods such as protocol analysis, tape-recorded interviews, and discourse analysis.

In the case of Janet Emig's (1971) study of the composing process of eight twelfth graders, four specific hypotheses were made:

• Twelfth grade writers engage in two modes of composing: reflexive and extensive.
• These differences can be ascertained and characterized through having the writers compose aloud their composition process.
• A set of implied stylistic principles governs the writing process.
• For twelfth grade writers, extensive writing occurs chiefly as a school-sponsored activity, or reflexive, as a self-sponsored activity.

In this study, the chief distinction is between the two dominant modes of composing among older, secondary school students. The distinctions are:

• The reflexive mode, which focuses on the writer's thoughts and feelings.
• The extensive mode, which focuses on conveying a message.

Emig also outlines the specific questions which guided the research in the opening pages of her Review of Literature , preceding the report.

Designing a Case Study

After considering the different sub categories of case study and identifying a theoretical perspective, researchers can begin to design their study. Research design is the string of logic that ultimately links the data to be collected and the conclusions to be drawn to the initial questions of the study. Typically, research designs deal with at least four problems:

• What questions to study
• What data are relevant
• What data to collect
• How to analyze that data

In other words, a research design is basically a blueprint for getting from the beginning to the end of a study. The beginning is an initial set of questions to be answered, and the end is some set of conclusions about those questions.

Because case studies are conducted on topics as diverse as Anglo-Saxon Literature (Thrane 1986) and AIDS prevention (Van Vugt 1994), it is virtually impossible to outline any strict or universal method or design for conducting the case study. However, Robert K. Yin (1993) does offer five basic components of a research design:

• A study's questions.
• A study's propositions (if any).
• A study's units of analysis.
• The logic that links the data to the propositions.
• The criteria for interpreting the findings.

In addition to these five basic components, Yin also stresses the importance of clearly articulating one's theoretical perspective, determining the goals of the study, selecting one's subject(s), selecting the appropriate method(s) of collecting data, and providing some considerations to the composition of the final report.

Conducting Case Studies

To obtain as complete a picture of the participant as possible, case study researchers can employ a variety of approaches and methods. These approaches, methods, and related issues are discussed in depth in this section.

Method: Single or Multi-modal?

To obtain as complete a picture of the participant as possible, case study researchers can employ a variety of methods. Some common methods include interviews , protocol analyses, field studies, and participant-observations. Emig (1971) chose to use several methods of data collection. Her sources included conversations with the students, protocol analysis, discrete observations of actual composition, writing samples from each student, and school records (Lauer and Asher 1988).

Berkenkotter, Huckin, and Ackerman (1988) collected data by observing classrooms, conducting faculty and student interviews, collecting self reports from the subject, and by looking at the subject's written work.

A study that was criticized for using a single method model was done by Flower and Hayes (1984). In this study that explores the ways in which writers use different forms of knowing to create space, the authors used only protocol analysis to gather data. The study came under heavy fire because of their decision to use only one method.

Participant Selection

Case studies can use one participant, or a small group of participants. However, it is important that the participant pool remain relatively small. The participants can represent a diverse cross section of society, but this isn't necessary.

For example, the Berkenkotter, Huckin, and Ackerman (1988) study looked at just one participant, Nate. By contrast, in Janet Emig's (1971) study of the composition process of twelfth graders, eight participants were selected representing a diverse cross section of the community, with volunteers from an all-white upper-middle-class suburban school, an all-black inner-city school, a racially mixed lower-middle-class school, an economically and racially mixed school, and a university school.

Often, a brief "case history" is done on the participants of the study in order to provide researchers with a clearer understanding of their participants, as well as some insight as to how their own personal histories might affect the outcome of the study. For instance, in Emig's study, the investigator had access to the school records of five of the participants, and to standardized test scores for the remaining three. Also made available to the researcher was the information that three of the eight students were selected as NCTE Achievement Award winners. These personal histories can be useful in later stages of the study when data are being analyzed and conclusions drawn.

Data Collection

There are six types of data collected in case studies:

• Archival records.
• Interviews.
• Direct observation.
• Participant observation.

In the field of composition research, these six sources might be:

• A writer's drafts.
• School records of student writers.
• Transcripts of interviews with a writer.
• Transcripts of conversations between writers (and protocols).
• Videotapes and notes from direct field observations.
• Hard copies of a writer's work on computer.

Depending on whether researchers have chosen to use a single or multi-modal approach for the case study, they may choose to collect data from one or any combination of these sources.

Protocols, that is, transcriptions of participants talking aloud about what they are doing as they do it, have been particularly common in composition case studies. For example, in Emig's (1971) study, the students were asked, in four different sessions, to give oral autobiographies of their writing experiences and to compose aloud three themes in the presence of a tape recorder and the investigator.

In some studies, only one method of data collection is conducted. For example, the Flower and Hayes (1981) report on the cognitive process theory of writing depends on protocol analysis alone. However, using multiple sources of evidence to increase the reliability and validity of the data can be advantageous.

Case studies are likely to be much more convincing and accurate if they are based on several different sources of information, following a corroborating mode. This conclusion is echoed among many composition researchers. For example, in her study of predrafting processes of high and low-apprehensive writers, Cynthia Selfe (1985) argues that because "methods of indirect observation provide only an incomplete reflection of the complex set of processes involved in composing, a combination of several such methods should be used to gather data in any one study." Thus, in this study, Selfe collected her data from protocols, observations of students role playing their writing processes, audio taped interviews with the students, and videotaped observations of the students in the process of composing.

It can be said then, that cross checking data from multiple sources can help provide a multidimensional profile of composing activities in a particular setting. Sharan Merriam (1985) suggests "checking, verifying, testing, probing, and confirming collected data as you go, arguing that this process will follow in a funnel-like design resulting in less data gathering in later phases of the study along with a congruent increase in analysis checking, verifying, and confirming."

It is important to note that in case studies, as in any qualitative descriptive research, while researchers begin their studies with one or several questions driving the inquiry (which influence the key factors the researcher will be looking for during data collection), a researcher may find new key factors emerging during data collection. These might be unexpected patterns or linguistic features which become evident only during the course of the research. While not bearing directly on the researcher's guiding questions, these variables may become the basis for new questions asked at the end of the report, thus linking to the possibility of further research.

Data Analysis

As the information is collected, researchers strive to make sense of their data. Generally, researchers interpret their data in one of two ways: holistically or through coding. Holistic analysis does not attempt to break the evidence into parts, but rather to draw conclusions based on the text as a whole. Flower and Hayes (1981), for example, make inferences from entire sections of their students' protocols, rather than searching through the transcripts to look for isolatable characteristics.

However, composition researchers commonly interpret their data by coding, that is by systematically searching data to identify and/or categorize specific observable actions or characteristics. These observable actions then become the key variables in the study. Sharan Merriam (1988) suggests seven analytic frameworks for the organization and presentation of data:

• The role of participants.
• The network analysis of formal and informal exchanges among groups.
• Historical.
• Thematical.
• Ritual and symbolism.
• Critical incidents that challenge or reinforce fundamental beliefs, practices, and values.

There are two purposes of these frameworks: to look for patterns among the data and to look for patterns that give meaning to the case study.

As stated above, while most researchers begin their case studies expecting to look for particular observable characteristics, it is not unusual for key variables to emerge during data collection. Typical variables coded in case studies of writers include pauses writers make in the production of a text, the use of specific linguistic units (such as nouns or verbs), and writing processes (planning, drafting, revising, and editing). In the Berkenkotter, Huckin, and Ackerman (1988) study, for example, researchers coded the participant's texts for use of connectives, discourse demonstratives, average sentence length, off-register words, use of the first person pronoun, and the ratio of definite articles to indefinite articles.

Since coding is inherently subjective, more than one coder is usually employed. In the Berkenkotter, Huckin, and Ackerman (1988) study, for example, three rhetoricians were employed to code the participant's texts for off-register phrases. The researchers established the agreement among the coders before concluding that the participant used fewer off-register words as the graduate program progressed.

Composing the Case Study Report

In the many forms it can take, "a case study is generically a story; it presents the concrete narrative detail of actual, or at least realistic events, it has a plot, exposition, characters, and sometimes even dialogue" (Boehrer 1990). Generally, case study reports are extensively descriptive, with "the most problematic issue often referred to as being the determination of the right combination of description and analysis" (1990). Typically, authors address each step of the research process, and attempt to give the reader as much context as possible for the decisions made in the research design and for the conclusions drawn.

This contextualization usually includes a detailed explanation of the researchers' theoretical positions, of how those theories drove the inquiry or led to the guiding research questions, of the participants' backgrounds, of the processes of data collection, of the training and limitations of the coders, along with a strong attempt to make connections between the data and the conclusions evident.

Although the Berkenkotter, Huckin, and Ackerman (1988) study does not, case study reports often include the reactions of the participants to the study or to the researchers' conclusions. Because case studies tend to be exploratory, most end with implications for further study. Here researchers may identify significant variables that emerged during the research and suggest studies related to these, or the authors may suggest further general questions that their case study generated.

For example, Emig's (1971) study concludes with a section dedicated solely to the topic of implications for further research, in which she suggests several means by which this particular study could have been improved, as well as questions and ideas raised by this study which other researchers might like to address, such as: is there a correlation between a certain personality and a certain composing process profile (e.g. is there a positive correlation between ego strength and persistence in revising)?

Also included in Emig's study is a section dedicated to implications for teaching, which outlines the pedagogical ramifications of the study's findings for teachers currently involved in high school writing programs.

Sharan Merriam (1985) also offers several suggestions for alternative presentations of data:

• Prepare specialized condensations for appropriate groups.
• Replace narrative sections with a series of answers to open-ended questions.
• Present "skimmer's" summaries at beginning of each section.
• Incorporate headlines that encapsulate information from text.
• Prepare analytic summaries with supporting data appendixes.
• Present data in colorful and/or unique graphic representations.

Issues of Validity and Reliability

Once key variables have been identified, they can be analyzed. Reliability becomes a key concern at this stage, and many case study researchers go to great lengths to ensure that their interpretations of the data will be both reliable and valid. Because issues of validity and reliability are an important part of any study in the social sciences, it is important to identify some ways of dealing with results.

Multi-modal case study researchers often balance the results of their coding with data from interviews or writer's reflections upon their own work. Consequently, the researchers' conclusions become highly contextualized. For example, in a case study which looked at the time spent in different stages of the writing process, Berkenkotter concluded that her participant, Donald Murray, spent more time planning his essays than in other writing stages. The report of this case study is followed by Murray's reply, wherein he agrees with some of Berkenkotter's conclusions and disagrees with others.

As is the case with other research methodologies, issues of external validity, construct validity, and reliability need to be carefully considered.

Commentary on Case Studies

Researchers often debate the relative merits of particular methods, among them case study. In this section, we comment on two key issues. To read the commentaries, choose any of the items below:

Strengths and Weaknesses of Case Studies

Most case study advocates point out that case studies produce much more detailed information than what is available through a statistical analysis. Advocates will also hold that while statistical methods might be able to deal with situations where behavior is homogeneous and routine, case studies are needed to deal with creativity, innovation, and context. Detractors argue that case studies are difficult to generalize because of inherent subjectivity and because they are based on qualitative subjective data, generalizable only to a particular context.

Flexibility

The case study approach is a comparatively flexible method of scientific research. Because its project designs seem to emphasize exploration rather than prescription or prediction, researchers are comparatively freer to discover and address issues as they arise in their experiments. In addition, the looser format of case studies allows researchers to begin with broad questions and narrow their focus as their experiment progresses rather than attempt to predict every possible outcome before the experiment is conducted.

Emphasis on Context

By seeking to understand as much as possible about a single subject or small group of subjects, case studies specialize in "deep data," or "thick description"--information based on particular contexts that can give research results a more human face. This emphasis can help bridge the gap between abstract research and concrete practice by allowing researchers to compare their firsthand observations with the quantitative results obtained through other methods of research.

Inherent Subjectivity

"The case study has long been stereotyped as the weak sibling among social science methods," and is often criticized as being too subjective and even pseudo-scientific. Likewise, "investigators who do case studies are often regarded as having deviated from their academic disciplines, and their investigations as having insufficient precision (that is, quantification), objectivity and rigor" (Yin 1989). Opponents cite opportunities for subjectivity in the implementation, presentation, and evaluation of case study research. The approach relies on personal interpretation of data and inferences. Results may not be generalizable, are difficult to test for validity, and rarely offer a problem-solving prescription. Simply put, relying on one or a few subjects as a basis for cognitive extrapolations runs the risk of inferring too much from what might be circumstance.

High Investment

Case studies can involve learning more about the subjects being tested than most researchers would care to know--their educational background, emotional background, perceptions of themselves and their surroundings, their likes, dislikes, and so on. Because of its emphasis on "deep data," the case study is out of reach for many large-scale research projects which look at a subject pool in the tens of thousands. A budget request of $10,000 to examine 200 subjects sounds more efficient than a similar request to examine four subjects.

Ethical Considerations

Researchers conducting case studies should consider certain ethical issues. For example, many educational case studies are often financed by people who have, either directly or indirectly, power over both those being studied and those conducting the investigation (1985). This conflict of interests can hinder the credibility of the study.

The personal integrity, sensitivity, and possible prejudices and/or biases of the investigators need to be taken into consideration as well. Personal biases can creep into how the research is conducted, alternative research methods used, and the preparation of surveys and questionnaires.

A common complaint in case study research is that investigators change direction during the course of the study unaware that their original research design was inadequate for the revised investigation. Thus, the researchers leave unknown gaps and biases in the study. To avoid this, researchers should report preliminary findings so that the likelihood of bias will be reduced.

Concerns about Reliability, Validity, and Generalizability

Merriam (1985) offers several suggestions for how case study researchers might actively combat the popular attacks on the validity, reliability, and generalizability of case studies:

• Prolong the Processes of Data Gathering on Site: This will help to insure the accuracy of the findings by providing the researcher with more concrete information upon which to formulate interpretations.
• Employ the Process of "Triangulation": Use a variety of data sources as opposed to relying solely upon one avenue of observation. One example of such a data check would be what McClintock, Brannon, and Maynard (1985) refer to as a "case cluster method," that is, when a single unit within a larger case is randomly sampled, and that data treated quantitatively." For instance, in Emig's (1971) study, the case cluster method was employed, singling out the productivity of a single student named Lynn. This cluster profile included an advanced case history of the subject, specific examination and analysis of individual compositions and protocols, and extensive interview sessions. The seven remaining students were then compared with the case of Lynn, to ascertain if there are any shared, or unique dimensions to the composing process engaged in by these eight students.
• Conduct Member Checks: Initiate and maintain an active corroboration on the interpretation of data between the researcher and those who provided the data. In other words, talk to your subjects.
• Collect Referential Materials: Complement the file of materials from the actual site with additional document support. For example, Emig (1971) supports her initial propositions with historical accounts by writers such as T.S. Eliot, James Joyce, and D.H. Lawrence. Emig also cites examples of theoretical research done with regards to the creative process, as well as examples of empirical research dealing with the writing of adolescents. Specific attention is then given to the four stages description of the composing process delineated by Helmoltz, Wallas, and Cowley, as it serves as the focal point in this study.
• Engage in Peer Consultation: Prior to composing the final draft of the report, researchers should consult with colleagues in order to establish validity through pooled judgment.

Although little can be done to combat challenges concerning the generalizability of case studies, "most writers suggest that qualitative research should be judged as credible and confirmable as opposed to valid and reliable" (Merriam 1985). Likewise, it has been argued that "rather than transplanting statistical, quantitative notions of generalizability and thus finding qualitative research inadequate, it makes more sense to develop an understanding of generalization that is congruent with the basic characteristics of qualitative inquiry" (1985). After all, criticizing the case study method for being ungeneralizable is comparable to criticizing a washing machine for not being able to tell the correct time. In other words, it is unjust to criticize a method for not being able to do something which it was never originally designed to do in the first place.

Annotated Bibliography

Armisted, C. (1984). How Useful are Case Studies. Training and Development Journal, 38 (2), 75-77.

This article looks at eight types of case studies, offers pros and cons of using case studies in the classroom, and gives suggestions for successfully writing and using case studies.

Bardovi-Harlig, K. (1997). Beyond Methods: Components of Second Language Teacher Education . New York: McGraw-Hill.

A compilation of various research essays which address issues of language teacher education. Essays included are: "Non-native reading research and theory" by Lee, "The case for Psycholinguistics" by VanPatten, and "Assessment and Second Language Teaching" by Gradman and Reed.

Bartlett, L. (1989). A Question of Good Judgment; Interpretation Theory and Qualitative Enquiry Address. 70th Annual Meeting of the American Educational Research Association. San Francisco.

Bartlett selected "quasi-historical" methodology, which focuses on the "truth" found in case records, as one that will provide "good judgments" in educational inquiry. He argues that although the method is not comprehensive, it can try to connect theory with practice.

Baydere, S. et. al. (1993). Multimedia conferencing as a tool for collaborative writing: a case study in Computer Supported Collaborative Writing. New York: Springer-Verlag.

The case study by Baydere et. al. is just one of the many essays in this book found in the series "Computer Supported Cooperative Work." Denley, Witefield and May explore similar issues in their essay, "A case study in task analysis for the design of a collaborative document production system."

Berkenkotter, C., Huckin, T., N., & Ackerman J. (1988). Conventions, Conversations, and the Writer: Case Study of a Student in a Rhetoric Ph.D. Program. Research in the Teaching of English, 22, 9-44.

The authors focused on how the writing of their subject, Nate or Ackerman, changed as he became more acquainted or familiar with his field's discourse community.

Berninger, V., W., and Gans, B., M. (1986). Language Profiles in Nonspeaking Individuals of Normal Intelligence with Severe Cerebral Palsy. Augmentative and Alternative Communication, 2, 45-50.

Argues that generalizations about language abilities in patients with severe cerebral palsy (CP) should be avoided. Standardized tests of different levels of processing oral language, of processing written language, and of producing written language were administered to 3 male participants (aged 9, 16, and 40 yrs).

Bockman, J., R., and Couture, B. (1984). The Case Method in Technical Communication: Theory and Models. Texas: Association of Teachers of Technical Writing.

Examines the study and teaching of technical writing, communication of technical information, and the case method in terms of those applications.

Boehrer, J. (1990). Teaching With Cases: Learning to Question. New Directions for Teaching and Learning, 42 41-57.

This article discusses the origins of the case method, looks at the question of what is a case, gives ideas about learning in case teaching, the purposes it can serve in the classroom, the ground rules for the case discussion, including the role of the question, and new directions for case teaching.

Bowman, W. R. (1993). Evaluating JTPA Programs for Economically Disadvantaged Adults: A Case Study of Utah and General Findings . Washington: National Commission for Employment Policy.

"To encourage state-level evaluations of JTPA, the Commission and the State of Utah co-sponsored this report on the effectiveness of JTPA Title II programs for adults in Utah. The technique used is non-experimental and the comparison group was selected from registrants with Utah's Employment Security. In a step-by-step approach, the report documents how non-experimental techniques can be applied and several specific technical issues can be addressed."

Boyce, A. (1993) The Case Study Approach for Pedagogists. Annual Meeting of the American Alliance for Health, Physical Education, Recreation and Dance. (Address). Washington DC.

This paper addresses how case studies 1) bridge the gap between teaching theory and application, 2) enable students to analyze problems and develop solutions for situations that will be encountered in the real world of teaching, and 3) helps students to evaluate the feasibility of alternatives and to understand the ramifications of a particular course of action.

Carson, J. (1993) The Case Study: Ideal Home of WAC Quantitative and Qualitative Data. Annual Meeting of the Conference on College Composition and Communication. (Address). San Diego.

"Increasingly, one of the most pressing questions for WAC advocates is how to keep [WAC] programs going in the face of numerous difficulties. Case histories offer the best chance for fashioning rhetorical arguments to keep WAC programs going because they offer the opportunity to provide a coherent narrative that contextualizes all documents and data, including what is generally considered scientific data. A case study of the WAC program, . . . at Robert Morris College in Pittsburgh demonstrates the advantages of this research method. Such studies are ideal homes for both naturalistic and positivistic data as well as both quantitative and qualitative information."

---. (1991). A Cognitive Process Theory of Writing. College Composition and Communication. 32. 365-87.

No abstract available.

Cromer, R. (1994) A Case Study of Dissociations Between Language and Cognition. Constraints on Language Acquisition: Studies of Atypical Children . Hillsdale: Lawrence Erlbaum Associates, 141-153.

Crossley, M. (1983) Case Study in Comparative and International Education: An Approach to Bridging the Theory-Practice Gap. Proceedings of the 11th Annual Conference of the Australian Comparative and International Education Society. Hamilton, NZ.

Case study research, as presented here, helps bridge the theory-practice gap in comparative and international research studies of education because it focuses on the practical, day-to-day context rather than on the national arena. The paper asserts that the case study method can be valuable at all levels of research, formation, and verification of theories in education.

Daillak, R., H., and Alkin, M., C. (1982). Qualitative Studies in Context: Reflections on the CSE Studies of Evaluation Use . California: EDRS

The report shows how the Center of the Study of Evaluation (CSE) applied qualitative techniques to a study of evaluation information use in local, Los Angeles schools. It critiques the effectiveness and the limitations of using case study, evaluation, field study, and user interview survey methodologies.

Davey, L. (1991). The Application of Case Study Evaluations. ERIC/TM Digest.

This article examines six types of case studies, the type of evaluation questions that can be answered, the functions served, some design features, and some pitfalls of the method.

Deutch, C. E. (1996). A course in research ethics for graduate students. College Teaching, 44, 2, 56-60.

This article describes a one-credit discussion course in research ethics for graduate students in biology. Case studies are focused on within the four parts of the course: 1) major issues, 2 )practical issues in scholarly work, 3) ownership of research results, and 4) training and personal decisions.

DeVoss, G. (1981). Ethics in Fieldwork Research. RIE 27p. (ERIC)

This article examines four of the ethical problems that can happen when conducting case study research: acquiring permission to do research, knowing when to stop digging, the pitfalls of doing collaborative research, and preserving the integrity of the participants.

Driscoll, A. (1985). Case Study of a Research Intervention: the University of Utah’s Collaborative Approach . San Francisco: Far West Library for Educational Research Development.

Paper presented at the annual meeting of the American Association of Colleges of Teacher Education, Denver, CO, March 1985. Offers information of in-service training, specifically case studies application.

Ellram, L. M. (1996). The Use of the Case Study Method in Logistics Research. Journal of Business Logistics, 17, 2, 93.

This article discusses the increased use of case study in business research, and the lack of understanding of when and how to use case study methodology in business.

Emig, J. (1971) The Composing Processes of Twelfth Graders . Urbana: NTCE.

This case study uses observation, tape recordings, writing samples, and school records to show that writing in reflexive and extensive situations caused different lengths of discourse and different clusterings of the components of the writing process.

Feagin, J. R. (1991). A Case For the Case Study . Chapel Hill: The University of North Carolina Press.

This book discusses the nature, characteristics, and basic methodological issues of the case study as a research method.

Feldman, H., Holland, A., & Keefe, K. (1989) Language Abilities after Left Hemisphere Brain Injury: A Case Study of Twins. Topics in Early Childhood Special Education, 9, 32-47.

"Describes the language abilities of 2 twin pairs in which 1 twin (the experimental) suffered brain injury to the left cerebral hemisphere around the time of birth and1 twin (the control) did not. One pair of twins was initially assessed at age 23 mo. and the other at about 30 mo.; they were subsequently evaluated in their homes 3 times at about 6-mo intervals."

Fidel, R. (1984). The Case Study Method: A Case Study. Library and Information Science Research, 6.

The article describes the use of case study methodology to systematically develop a model of online searching behavior in which study design is flexible, subject manner determines data gathering and analyses, and procedures adapt to the study's progressive change.

Flower, L., & Hayes, J. R. (1984). Images, Plans and Prose: The Representation of Meaning in Writing. Written Communication, 1, 120-160.

Explores the ways in which writers actually use different forms of knowing to create prose.

Frey, L. R. (1992). Interpreting Communication Research: A Case Study Approach Englewood Cliffs, N.J.: Prentice Hall.

The book discusses research methodologies in the Communication field. It focuses on how case studies bridge the gap between communication research, theory, and practice.

Gilbert, V. K. (1981). The Case Study as a Research Methodology: Difficulties and Advantages of Integrating the Positivistic, Phenomenological and Grounded Theory Approaches . The Annual Meeting of the Canadian Association for the Study of Educational Administration. (Address) Halifax, NS, Can.

This study on an innovative secondary school in England shows how a "low-profile" participant-observer case study was crucial to the initial observation, the testing of hypotheses, the interpretive approach, and the grounded theory.

Gilgun, J. F. (1994). A Case for Case Studies in Social Work Research. Social Work, 39, 4, 371-381.

This article defines case study research, presents guidelines for evaluation of case studies, and shows the relevance of case studies to social work research. It also looks at issues such as evaluation and interpretations of case studies.

Glennan, S. L., Sharp-Bittner, M. A. & Tullos, D. C. (1991). Augmentative and Alternative Communication Training with a Nonspeaking Adult: Lessons from MH. Augmentative and Alternative Communication, 7, 240-7.

"A response-guided case study documented changes in a nonspeaking 36-yr-old man's ability to communicate using 3 trained augmentative communication modes. . . . Data were collected in videotaped interaction sessions between the nonspeaking adult and a series of adult speaking."

Graves, D. (1981). An Examination of the Writing Processes of Seven Year Old Children. Research in the Teaching of English, 15, 113-134.

Hamel, J. (1993). Case Study Methods . Newbury Park: Sage. .

"In a most economical fashion, Hamel provides a practical guide for producing theoretically sharp and empirically sound sociological case studies. A central idea put forth by Hamel is that case studies must "locate the global in the local" thus making the careful selection of the research site the most critical decision in the analytic process."

Karthigesu, R. (1986, July). Television as a Tool for Nation-Building in the Third World: A Post-Colonial Pattern, Using Malaysia as a Case-Study. International Television Studies Conference. (Address). London, 10-12.

"The extent to which Television Malaysia, as a national mass media organization, has been able to play a role in nation building in the post-colonial period is . . . studied in two parts: how the choice of a model of nation building determines the character of the organization; and how the character of the organization influences the output of the organization."

Kenny, R. (1984). Making the Case for the Case Study. Journal of Curriculum Studies, 16, (1), 37-51.

The article looks at how and why the case study is justified as a viable and valuable approach to educational research and program evaluation.

Knirk, F. (1991). Case Materials: Research and Practice. Performance Improvement Quarterly, 4 (1 ), 73-81.

The article addresses the effectiveness of case studies, subject areas where case studies are commonly used, recent examples of their use, and case study design considerations.

Klos, D. (1976). Students as Case Writers. Teaching of Psychology, 3.2, 63-66.

This article reviews a course in which students gather data for an original case study of another person. The task requires the students to design the study, collect the data, write the narrative, and interpret the findings.

Leftwich, A. (1981). The Politics of Case Study: Problems of Innovation in University Education. Higher Education Review, 13.2, 38-64.

The article discusses the use of case studies as a teaching method. Emphasis is on the instructional materials, interdisciplinarity, and the complex relationships within the university that help or hinder the method.

Mabrito, M. (1991, Oct.). Electronic Mail as a Vehicle for Peer Response: Conversations of High and Low Apprehensive Writers. Written Communication, 509-32.

McCarthy, S., J. (1955). The Influence of Classroom Discourse on Student Texts: The Case of Ella . East Lansing: Institute for Research on Teaching.

A look at how students of color become marginalized within traditional classroom discourse. The essay follows the struggles of one black student: Ella.

Matsuhashi, A., ed. (1987). Writing in Real Time: Modeling Production Processes Norwood, NJ: Ablex Publishing Corporation.

Investigates how writers plan to produce discourse for different purposes to report, to generalize, and to persuade, as well as how writers plan for sentence level units of language. To learn about planning, an observational measure of pause time was used" (ERIC).

Merriam, S. B. (1985). The Case Study in Educational Research: A Review of Selected Literature. Journal of Educational Thought, 19.3, 204-17.

The article examines the characteristics of, philosophical assumptions underlying the case study, the mechanics of conducting a case study, and the concerns about the reliability, validity, and generalizability of the method.

---. (1988). Case Study Research in Education: A Qualitative Approach San Francisco: Jossey Bass.

Merry, S. E., & Milner, N. eds. (1993). The Possibility of Popular Justice: A Case Study of Community Mediation in the United States . Ann Arbor: U of Michigan.

". . . this volume presents a case study of one experiment in popular justice, the San Francisco Community Boards. This program has made an explicit claim to create an alternative justice, or new justice, in the midst of a society ordered by state law. The contributors to this volume explore the history and experience of the program and compare it to other versions of popular justice in the United States, Europe, and the Third World."

Merseth, K. K. (1991). The Case for Cases in Teacher Education. RIE. 42p. (ERIC).

This monograph argues that the case method of instruction offers unique potential for revitalizing the field of teacher education.

Michaels, S. (1987). Text and Context: A New Approach to the Study of Classroom Writing. Discourse Processes, 10, 321-346.

"This paper argues for and illustrates an approach to the study of writing that integrates ethnographic analysis of classroom interaction with linguistic analysis of written texts and teacher/student conversational exchanges. The approach is illustrated through a case study of writing in a single sixth grade classroom during a single writing assignment."

Milburn, G. (1995). Deciphering a Code or Unraveling a Riddle: A Case Study in the Application of a Humanistic Metaphor to the Reporting of Social Studies Teaching. Theory and Research in Education, 13.

This citation serves as an example of how case studies document learning procedures in a senior-level economics course.

Milley, J. E. (1979). An Investigation of Case Study as an Approach to Program Evaluation. 19th Annual Forum of the Association for Institutional Research. (Address). San Diego.

The case study method merged a narrative report focusing on the evaluator as participant-observer with document review, interview, content analysis, attitude questionnaire survey, and sociogram analysis. Milley argues that case study program evaluation has great potential for widespread use.

Minnis, J. R. (1985, Sept.). Ethnography, Case Study, Grounded Theory, and Distance Education Research. Distance Education, 6.2.

This article describes and defines the strengths and weaknesses of ethnography, case study, and grounded theory.

Nunan, D. (1992). Collaborative language learning and teaching . New York: Cambridge University Press.

Included in this series of essays is Peter Sturman’s "Team Teaching: a case study from Japan" and David Nunan’s own "Toward a collaborative approach to curriculum development: a case study."

Nystrand, M., ed. (1982). What Writers Know: The Language, Process, and Structure of Written Discourse . New York: Academic Press.

Owenby, P. H. (1992). Making Case Studies Come Alive. Training, 29, (1), 43-46. (ERIC)

This article provides tips for writing more effective case studies.

---. (1981). Pausing and Planning: The Tempo of Writer Discourse Production. Research in the Teaching of English, 15 (2),113-34.

Perl, S. (1979). The Composing Processes of Unskilled College Writers. Research in the Teaching of English, 13, 317-336.

"Summarizes a study of five unskilled college writers, focusing especially on one of the five, and discusses the findings in light of current pedagogical practice and research design."

Pilcher J. and A. Coffey. eds. (1996). Gender and Qualitative Research . Brookfield: Aldershot, Hants, England.

This book provides a series of essays which look at gender identity research, qualitative research and applications of case study to questions of gendered pedagogy.

Pirie, B. S. (1993). The Case of Morty: A Four Year Study. Gifted Education International, 9 (2), 105-109.

This case study describes a boy from kindergarten through third grade with above average intelligence but difficulty in learning to read, write, and spell.

Popkewitz, T. (1993). Changing Patterns of Power: Social Regulation and Teacher Education Reform. Albany: SUNY Press.

Popkewitz edits this series of essays that address case studies on educational change and the training of teachers. The essays vary in terms of discipline and scope. Also, several authors include case studies of educational practices in countries other than the United States.

---. (1984). The Predrafting Processes of Four High- and Four Low Apprehensive Writers. Research in the Teaching of English, 18, (1), 45-64.

Rasmussen, P. (1985, March) A Case Study on the Evaluation of Research at the Technical University of Denmark. International Journal of Institutional Management in Higher Education, 9 (1).

This is an example of a case study methodology used to evaluate the chemistry and chemical engineering departments at the University of Denmark.

Roth, K. J. (1986). Curriculum Materials, Teacher Talk, and Student Learning: Case Studies in Fifth-Grade Science Teaching . East Lansing: Institute for Research on Teaching.

Roth offers case studies on elementary teachers, elementary school teaching, science studies and teaching, and verbal learning.

Selfe, C. L. (1985). An Apprehensive Writer Composes. When a Writer Can't Write: Studies in Writer's Block and Other Composing-Process Problems . (pp. 83-95). Ed. Mike Rose. NMY: Guilford.

Smith-Lewis, M., R. and Ford, A. (1987). A User's Perspective on Augmentative Communication. Augmentative and Alternative Communication, 3, 12-7.

"During a series of in-depth interviews, a 25-yr-old woman with cerebral palsy who utilized augmentative communication reflected on the effectiveness of the devices designed for her during her school career."

St. Pierre, R., G. (1980, April). Follow Through: A Case Study in Metaevaluation Research . 64th Annual Meeting of the American Educational Research Association. (Address).

The three approaches to metaevaluation are evaluation of primary evaluations, integrative meta-analysis with combined primary evaluation results, and re-analysis of the raw data from a primary evaluation.

Stahler, T., M. (1996, Feb.) Early Field Experiences: A Model That Worked. ERIC.

"This case study of a field and theory class examines a model designed to provide meaningful field experiences for preservice teachers while remaining consistent with the instructor's beliefs about the role of teacher education in preparing teachers for the classroom."

Stake, R. E. (1995). The Art of Case Study Research. Thousand Oaks: Sage Publications.

This book examines case study research in education and case study methodology.

Stiegelbauer, S. (1984) Community, Context, and Co-curriculum: Situational Factors Influencing School Improvements in a Study of High Schools. Presented at the annual meeting of the American Educational Research Association, New Orleans, LA.

Discussion of several case studies: one looking at high school environments, another examining educational innovations.

Stolovitch, H. (1990). Case Study Method. Performance And Instruction, 29, (9), 35-37.

This article describes the case study method as a form of simulation and presents guidelines for their use in professional training situations.

Thaller, E. (1994). Bibliography for the Case Method: Using Case Studies in Teacher Education. RIE. 37 p.

This bibliography presents approximately 450 citations on the use of case studies in teacher education from 1921-1993.

Thrane, T. (1986). On Delimiting the Senses of Near-Synonyms in Historical Semantics: A Case Study of Adjectives of 'Moral Sufficiency' in the Old English Andreas. Linguistics Across Historical and Geographical Boundaries: In Honor of Jacek Fisiak on the Occasion of his Fiftieth Birthday . Berlin: Mouton de Gruyter.

United Nations. (1975). Food and Agriculture Organization. Report on the FAO/UNFPA Seminar on Methodology, Research and Country: Case Studies on Population, Employment and Productivity . Rome: United Nations.

This example case study shows how the methodology can be used in a demographic and psychographic evaluation. At the same time, it discusses the formation and instigation of the case study methodology itself.

Van Vugt, J. P., ed. (1994). Aids Prevention and Services: Community Based Research . Westport: Bergin and Garvey.

"This volume has been five years in the making. In the process, some of the policy applications called for have met with limited success, such as free needle exchange programs in a limited number of American cities, providing condoms to prison inmates, and advertisements that depict same-sex couples. Rather than dating our chapters that deal with such subjects, such policy applications are verifications of the type of research demonstrated here. Furthermore, they indicate the critical need to continue community based research in the various communities threatened by acquired immuno-deficiency syndrome (AIDS) . . . "

Welch, W., ed. (1981, May). Case Study Methodology in Educational Evaluation. Proceedings of the Minnesota Evaluation Conference. Minnesota. (Address).

The four papers in these proceedings provide a comprehensive picture of the rationale, methodology, strengths, and limitations of case studies.

Williams, G. (1987). The Case Method: An Approach to Teaching and Learning in Educational Administration. RIE, 31p.

This paper examines the viability of the case method as a teaching and learning strategy in instructional systems geared toward the training of personnel of the administration of various aspects of educational systems.

Yin, R. K. (1993). Advancing Rigorous Methodologies: A Review of 'Towards Rigor in Reviews of Multivocal Literatures.' Review of Educational Research, 61, (3).

"R. T. Ogawa and B. Malen's article does not meet its own recommended standards for rigorous testing and presentation of its own conclusions. Use of the exploratory case study to analyze multivocal literatures is not supported, and the claim of grounded theory to analyze multivocal literatures may be stronger."

---. (1989). Case Study Research: Design and Methods. London: Sage Publications Inc.

This book discusses in great detail, the entire design process of the case study, including entire chapters on collecting evidence, analyzing evidence, composing the case study report, and designing single and multiple case studies.

Related Links

Consider the following list of related Web sites for more information on the topic of case study research. Note: although many of the links cover the general category of qualitative research, all have sections that address issues of case studies.

• Sage Publications on Qualitative Methodology: Search here for a comprehensive list of new books being published about "Qualitative Methodology" http://www.sagepub.co.uk/
• The International Journal of Qualitative Studies in Education: An on-line journal "to enhance the theory and practice of qualitative research in education." On-line submissions are welcome. http://www.tandf.co.uk/journals/tf/09518398.html
• Qualitative Research Resources on the Internet: From syllabi to home pages to bibliographies. All links relate somehow to qualitative research. http://www.nova.edu/ssss/QR/qualres.html

Becker, Bronwyn, Patrick Dawson, Karen Devine, Carla Hannum, Steve Hill, Jon Leydens, Debbie Matuskevich, Carol Traver, & Mike Palmquist. (2005). Case Studies. Writing@CSU . Colorado State University. https://writing.colostate.edu/guides/guide.cfm?guideid=60

Write an Error-free Research Protocol As Recommended by WHO: 21 Elements You Shouldn’t Miss!

Principal Investigator: Did you draft the research protocol?

Student: Not yet. I have too many questions about it. Why is it important to write a research protocol? Is it similar to research proposal? What should I include in it? How should I structure it? Is there a specific format?

Researchers at an early stage fall short in understanding the purpose and importance of some supplementary documents, let alone how to write them. Let’s better your understanding of writing an acceptance-worthy research protocol.

Table of Contents

What Is Research Protocol?

The research protocol is a document that describes the background, rationale, objective(s), design, methodology, statistical considerations and organization of a clinical trial. It is a document that outlines the clinical research study plan. Furthermore, the research protocol should be designed to provide a satisfactory answer to the research question. The protocol in effect is the cookbook for conducting your study

Why Is Research Protocol Important?

In clinical research, the research protocol is of paramount importance. It forms the basis of a clinical investigation. It ensures the safety of the clinical trial subjects and integrity of the data collected. Serving as a binding document, the research protocol states what you are—and you are not—allowed to study as part of the trial. Furthermore, it is also considered to be the most important document in your application with your Institution’s Review Board (IRB).

It is written with the contributions and inputs from a medical expert, a statistician, pharmacokinetics expert, the clinical research coordinator, and the project manager to ensure all aspects of the study are covered in the final document.

Is Research Protocol Same As Research Proposal?

Often misinterpreted, research protocol is not similar to research proposal. Here are some significant points of difference between a research protocol and a research proposal:

A is written to persuade the grant committee, university department, instructors, etc.	A research protocol is written to detail a clinical study’s plan to meet specified ethical norms for participating subjects.
It is a plan to obtain funding or conduct research.	It is meant to clearly provide an overview of a proposed study to satisfy an organization’s guidelines for protecting the safety of subjects.
Research proposals are submitted to funding bodies	Research protocols are submitted to Institutional Review Boards (IRBs) within universities and research centers.

What Are the Elements/Sections of a Research Protocol?

According to Good Clinical Practice guidelines laid by WHO, a research protocol should include the following:

1. General Information

• Protocol title, protocol identifying number (if any), and date.
• Name and address of the funder.
• Name(s) and contact details of the investigator(s) responsible for conducting the research, the research site(s).
• Responsibilities of each investigator.
• Name(s) and address(es) of the clinical laboratory(ies), other medical and/or technical department(s) and/or institutions involved in the research.

2. Rationale & Background Information

• The rationale and background information provides specific reasons for conducting the research in light of pertinent knowledge about the research topic.
• It is a statement that includes the problem that is the basis of the project, the cause of the research problem, and its possible solutions.
• It should be supported with a brief description of the most relevant literatures published on the research topic.

3. Study Objectives

• The study objectives mentioned in the research proposal states what the investigators hope to accomplish. The research is planned based on this section.
• The research proposal objectives should be simple, clear, specific, and stated prior to conducting the research.
• It could be divided into primary and secondary objectives based on their relativity to the research problem and its solution.

4. Study Design

• The study design justifies the scientific integrity and credibility of the research study.
• The study design should include information on the type of study, the research population or the sampling frame, participation criteria (inclusion, exclusion, and withdrawal), and the expected duration of the study.

5. Methodology

• The methodology section is the most critical section of the research protocol.
• It should include detailed information on the interventions to be made, procedures to be used, measurements to be taken, observations to be made, laboratory investigations to be done, etc.
• The methodology should be standardized and clearly defined if multiple sites are engaged in a specified protocol.

6. Safety Considerations

• The safety of participants is a top-tier priority while conducting clinical research .
• Safety aspects of the research should be scrutinized and provided in the research protocol.

7. Follow-up

• The research protocol clearly indicate of what follow up will be provided to the participating subjects.
• It must also include the duration of the follow-up.

8. Data Management and Statistical Analysis

• The research protocol should include information on how the data will be managed, including data handling and coding for computer analysis, monitoring and verification.
• It should clearly outline the statistical methods proposed to be used for the analysis of data.
• For qualitative approaches, specify in detail how the data will be analysed.

9. Quality Assurance

• The research protocol should clearly describe the quality control and quality assurance system.
• These include GCP, follow up by clinical monitors, DSMB, data management, etc.

10. Expected Outcomes of the Study

• This section indicates how the study will contribute to the advancement of current knowledge, how the results will be utilized beyond publications.
• It must mention how the study will affect health care, health systems, or health policies.

11. Dissemination of Results and Publication Policy

• The research protocol should specify not only how the results will be disseminated in the scientific media, but also to the community and/or the participants, the policy makers, etc.
• The publication policy should be clearly discussed as to who will be mentioned as contributors, who will be acknowledged, etc.

12. Duration of the Project

• The protocol should clearly mention the time likely to be taken for completion of each phase of the project.
• Furthermore a detailed timeline for each activity to be undertaken should also be provided.

13. Anticipated Problems

• The investigators may face some difficulties while conducting the clinical research. This section must include all anticipated problems in successfully completing their projects.
• Furthermore, it should also provide possible solutions to deal with these difficulties.

14. Project Management

• This section includes detailed specifications of the role and responsibility of each investigator of the team.
• Everyone involved in the research project must be mentioned here along with the specific duties they have performed in completing the research.
• The research protocol should also describe the ethical considerations relating to the study.
• It should not only be limited to providing ethics approval, but also the issues that are likely to raise ethical concerns.
• Additionally, the ethics section must also describe how the investigator(s) plan to obtain informed consent from the research participants.
• This section should include a detailed commodity-wise and service-wise breakdown of the requested funds.
• It should also include justification of utilization of each listed item.

17. Supplementary Support for the Project

• This section should include information about the received funding and other anticipated funding for the specific project.

18. Collaboration With Other Researchers or Institutions

• Every researcher or institute that has been a part of the research project must be mentioned in detail in this section of the research protocol.

19. Curriculum Vitae of All Investigators

• The CVs of the principal investigator along with all the co-investigators should be attached with the research protocol.
• Ideally, each CV should be limited to one page only, unless a full-length CV is requested.

20. Other Research Activities of Investigators

• A list of all current research projects being conducted by all investigators must be listed here.

21. References

• All relevant references should be mentioned and cited accurately in this section to avoid plagiarism.

How Do You Write a Research Protocol? (Research Protocol Example)

Main Investigator    

Number of Involved Centers (for multi-centric studies)

Indicate the reference center

Title of the Study

Protocol ID (acronym)

Keywords (up to 7 specific keywords)

Study Design

Mono-centric/multi-centric

Perspective/retrospective

Controlled/uncontrolled

Open-label/single-blinded or double-blinded

Randomized/non-randomized

n parallel branches/n overlapped branches

Experimental/observational

Endpoints (main primary and secondary endpoints to be listed)

Expected Results                                                

Analyzed Criteria

Main variables/endpoints of the primary analysis

Main variables/endpoints of the secondary analysis

Safety variables

Health Economy (if applicable)

Visits and Examinations

Therapeutic plan and goals

Visits/controls schedule (also with graphics)

Comparison to treatment products (if applicable)

Dose and dosage for the study duration (if applicable)

Formulation and power of the studied drugs (if applicable)

Method of administration of the studied drugs (if applicable)

Informed Consent

Study Population

Short description of the main inclusion, exclusion, and withdrawal criteria

Sample Size

Estimated Duration of the Study

Safety Advisory

Classification Needed

Requested Funds

Additional Features (based on study objectives)

Click Here to Download the Research Protocol Example/Template

Be prepared to conduct your clinical research by writing a detailed research protocol. It is as easy as mentioned in this article. Follow the aforementioned path and write an impactful research protocol. All the best!

Clear as template! Please, I need your help to shape me an authentic PROTOCOL RESEARCH on this theme: Using the competency-based approach to foster EFL post beginner learners’ writing ability: the case of Benin context. I’m about to start studies for a master degree. Please help! Thanks for your collaboration. God bless.

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Study protocol

Publishing study protocols in BMC Public Health is part of our commitment to improving research standards by promoting transparency, reducing publication bias, and enhancing the reproducibility of study design and analysis. We consider study protocols for proposed or ongoing prospective clinical research that provide a detailed account of the hypothesis, rationale and methodology of the study, and the associated ethical requirements. By publishing your protocol with us, it becomes a fully citable open-access article.

We evaluate study protocol submissions on a case-by-case basis and consider only those for proposed or ongoing studies that have not completed participant recruitment at the time of submission. We encourage authors to submit their study protocols well in advance of participant recruitment completion and confirm the study status within the cover letter.

Study protocols for pilot or feasibility studies are not considered, and authors are encouraged to submit the pilot results as a research article and the study protocol for the definitive study. Additionally, we may not consider study protocols where authors have other articles published or under consideration relating to the same protocol. Please note that study protocols for systematic reviews are not considered by the BMC Series journals.

If a proposed study protocol has obtained formal ethical approval and undergone independent peer-review from a major funding body, it will usually be considered for publication without further peer-review. Please ensure the Declarations section in your manuscript outlines the funding information, including whether it was peer reviewed and information about ethical approval. In some cases, the Editor may request to see the peer-review reports from the funder and/or may send the protocol for additional peer review.

Please note that study protocols without major external funding or ethics approval may not be considered for publication.

Protocols of randomized controlled trials should follow the  SPIRIT  guidelines and must have a trial registration number included in the last line of the abstract, as described in our editorial policies. Please provide a completed SPIRIT checklist as a supplementary file when submitting your protocol.

When conducting peer-review of study protocols, the intention is not to change the study design. Instead, we ask our reviewers to evaluate and report on the study's adequacy in testing the hypothesis, whether there is sufficient detail for replication or comparison, the appropriateness of the planned statistical analysis, and the acceptability of the writing.

The final decision on whether to consider a study protocol for publication will rest with the Editor, and appeals will not be considered. 

To ensure a smooth submission process, please take note of the following before submitting:

• Confirm the status of your study within the cover letter.
• Ensure that the Declarations section is complete and contains ethical approval and funding information.
• For protocols describing clinical trials, provide a completed copy of the SPIRIT checklist as a supplementary file.

Professionally produced Visual Abstracts

BMC Public Health   will consider visual abstracts. As an author submitting to the journal, you may wish to make use of services provided at Springer Nature for high quality and affordable visual abstracts where you are entitled to a 20% discount. Click here to find out more about the service, and your discount will be automatically be applied when using this link.

What we are looking for

The journal considers protocols for ongoing or proposed large-scale, prospective studies related to public health and public health management activities and submissions should provide a detailed account of the hypothesis, rationale and methodology of the study. We are particularly interested in protocols for public health interventions aimed at improving health outcomes of populations.

Protocols for clinical research will not be considered and should be submitted to the relevant BMC Series medical journal.

Preparing your manuscript

The information below details the section headings that you should include in your manuscript and what information should be within each section.

Please note that your manuscript must include a 'Declarations' section including all of the subheadings (please see below for more information).

The title page should:

• "A versus B in the treatment of C: a randomized controlled trial", "X is a risk factor for Y: a case control study", "What is the impact of factor X on subject Y: A systematic review"
• or for non-clinical or non-research studies: a description of what the article reports
• if a collaboration group should be listed as an author, please list the Group name as an author. If you would like the names of the individual members of the Group to be searchable through their individual PubMed records, please include this information in the “Acknowledgements” section in accordance with the instructions below
• Large Language Models (LLMs), such as ChatGPT , do not currently satisfy our authorship criteria . Notably an attribution of authorship carries with it accountability for the work, which cannot be effectively applied to LLMs. Use of an LLM should be properly documented in the Methods section (and if a Methods section is not available, in a suitable alternative part) of the manuscript
• indicate the corresponding author

The Abstract should not exceed 350 words. Please minimize the use of abbreviations and do not cite references in the abstract. The abstract must include the following separate sections:

• Background: the context and purpose of the study
• Methods: how the study will be performed
• Discussion: a brief summary and potential implications
• Trial registration:  If your article reports the results of a health care intervention on human participants, it must be registered in an appropriate registry and the registration number and date of registration should be in stated in this section. If it was not registered prospectively (before enrollment of the first participant), you should include the words 'retrospectively registered'. See our editorial policies for more information on trial registration

Three to ten keywords representing the main content of the article.

The Background section should explain the background to the study, its aims, a summary of the existing literature and why this study is necessary or its contribution to the field.

Methods/Design

The methods section should include:

• the aim, design and setting of the study
• the characteristics of participants or description of materials
• a clear description of all processes, interventions and comparisons. Generic drug names should generally be used. When proprietary brands are used in research, include the brand names in parentheses
• the type of statistical analysis used, including a power calculation if appropriate.

This should include a discussion of any practical or operational issues involved in performing the study and any issues not covered in other sections.

List of abbreviations

If abbreviations are used in the text they should be defined in the text at first use, and a list of abbreviations should be provided.

Declarations

All manuscripts must contain the following sections under the heading 'Declarations':

Ethics approval and consent to participate

Consent for publication, availability of data and materials, competing interests, authors' contributions, acknowledgements.

• Authors' information (optional)

Please see below for details on the information to be included in these sections.

If any of the sections are not relevant to your manuscript, please include the heading and write 'Not applicable' for that section. 

Manuscripts reporting studies involving human participants, human data or human tissue must:

• include a statement on ethics approval and consent (even where the need for approval was waived)
• include the name of the ethics committee that approved the study and the committee’s reference number if appropriate

Studies involving animals must include a statement on ethics approval and for experimental studies involving client-owned animals, authors must also include a statement on informed consent from the client or owner.

See our editorial policies for more information.

If your manuscript does not report on or involve the use of any animal or human data or tissue, please state “Not applicable” in this section.

If your manuscript contains any individual person’s data in any form (including any individual details, images or videos), consent for publication must be obtained from that person, or in the case of children, their parent or legal guardian. All presentations of case reports must have consent for publication.

You can use your institutional consent form or our consent form if you prefer. You should not send the form to us on submission, but we may request to see a copy at any stage (including after publication).

See our editorial policies for more information on consent for publication.

If your manuscript does not contain data from any individual person, please state “Not applicable” in this section.

All manuscripts must include an ‘Availability of data and materials’ statement. Data availability statements should include information on where data supporting the results reported in the article can be found including, where applicable, hyperlinks to publicly archived datasets analysed or generated during the study. By data we mean the minimal dataset that would be necessary to interpret, replicate and build upon the findings reported in the article. We recognise it is not always possible to share research data publicly, for instance when individual privacy could be compromised, and in such instances data availability should still be stated in the manuscript along with any conditions for access.

Authors are also encouraged to preserve search strings on searchRxiv https://searchrxiv.org/ , an archive to support researchers to report, store and share their searches consistently and to enable them to review and re-use existing searches. searchRxiv enables researchers to obtain a digital object identifier (DOI) for their search, allowing it to be cited. 

Data availability statements can take one of the following forms (or a combination of more than one if required for multiple datasets):

• The datasets generated and/or analysed during the current study are available in the [NAME] repository, [PERSISTENT WEB LINK TO DATASETS]
• The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
• All data generated or analysed during this study are included in this published article [and its supplementary information files].
• The datasets generated and/or analysed during the current study are not publicly available due [REASON WHY DATA ARE NOT PUBLIC] but are available from the corresponding author on reasonable request.
• Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.
• The data that support the findings of this study are available from [third party name] but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of [third party name].
• Not applicable. If your manuscript does not contain any data, please state 'Not applicable' in this section.

More examples of template data availability statements, which include examples of openly available and restricted access datasets, are available here .

BioMed Central strongly encourages the citation of any publicly available data on which the conclusions of the paper rely in the manuscript. Data citations should include a persistent identifier (such as a DOI) and should ideally be included in the reference list. Citations of datasets, when they appear in the reference list, should include the minimum information recommended by DataCite and follow journal style. Dataset identifiers including DOIs should be expressed as full URLs. For example:

Hao Z, AghaKouchak A, Nakhjiri N, Farahmand A. Global integrated drought monitoring and prediction system (GIDMaPS) data sets. figshare. 2014. http://dx.doi.org/10.6084/m9.figshare.853801

With the corresponding text in the Availability of data and materials statement:

The datasets generated during and/or analysed during the current study are available in the [NAME] repository, [PERSISTENT WEB LINK TO DATASETS]. [Reference number]  

If you wish to co-submit a data note describing your data to be published in BMC Research Notes , you can do so by visiting our submission portal . Data notes support open data and help authors to comply with funder policies on data sharing. Co-published data notes will be linked to the research article the data support ( example ).

All financial and non-financial competing interests must be declared in this section.

See our editorial policies for a full explanation of competing interests. If you are unsure whether you or any of your co-authors have a competing interest please contact the editorial office.

Please use the authors initials to refer to each authors' competing interests in this section.

If you do not have any competing interests, please state "The authors declare that they have no competing interests" in this section.

All sources of funding for the research reported should be declared. If the funder has a specific role in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript, this should be declared.

The individual contributions of authors to the manuscript should be specified in this section. Guidance and criteria for authorship can be found in our editorial policies .

Please use initials to refer to each author's contribution in this section, for example: "FC analyzed and interpreted the patient data regarding the hematological disease and the transplant. RH performed the histological examination of the kidney, and was a major contributor in writing the manuscript. All authors read and approved the final manuscript."

Please acknowledge anyone who contributed towards the article who does not meet the criteria for authorship including anyone who provided professional writing services or materials.

Authors should obtain permission to acknowledge from all those mentioned in the Acknowledgements section.

See our editorial policies for a full explanation of acknowledgements and authorship criteria.

If you do not have anyone to acknowledge, please write "Not applicable" in this section.

Group authorship (for manuscripts involving a collaboration group): if you would like the names of the individual members of a collaboration Group to be searchable through their individual PubMed records, please ensure that the title of the collaboration Group is included on the title page and in the submission system and also include collaborating author names as the last paragraph of the “Acknowledgements” section. Please add authors in the format First Name, Middle initial(s) (optional), Last Name. You can add institution or country information for each author if you wish, but this should be consistent across all authors.

Please note that individual names may not be present in the PubMed record at the time a published article is initially included in PubMed as it takes PubMed additional time to code this information.

Authors' information

This section is optional.

You may choose to use this section to include any relevant information about the author(s) that may aid the reader's interpretation of the article, and understand the standpoint of the author(s). This may include details about the authors' qualifications, current positions they hold at institutions or societies, or any other relevant background information. Please refer to authors using their initials. Note this section should not be used to describe any competing interests.

Footnotes can be used to give additional information, which may include the citation of a reference included in the reference list. They should not consist solely of a reference citation, and they should never include the bibliographic details of a reference. They should also not contain any figures or tables.

Footnotes to the text are numbered consecutively; those to tables should be indicated by superscript lower-case letters (or asterisks for significance values and other statistical data). Footnotes to the title or the authors of the article are not given reference symbols.

Always use footnotes instead of endnotes.

Examples of the Vancouver reference style are shown below.

See our editorial policies for author guidance on good citation practice

Web links and URLs: All web links and URLs, including links to the authors' own websites, should be given a reference number and included in the reference list rather than within the text of the manuscript. They should be provided in full, including both the title of the site and the URL, as well as the date the site was accessed, in the following format: The Mouse Tumor Biology Database. http://tumor.informatics.jax.org/mtbwi/index.do . Accessed 20 May 2013. If an author or group of authors can clearly be associated with a web link, such as for weblogs, then they should be included in the reference.

Example reference style:

Article within a journal

Smith JJ. The world of science. Am J Sci. 1999;36:234-5.

Article within a journal (no page numbers)

Rohrmann S, Overvad K, Bueno-de-Mesquita HB, Jakobsen MU, Egeberg R, Tjønneland A, et al. Meat consumption and mortality - results from the European Prospective Investigation into Cancer and Nutrition. BMC Medicine. 2013;11:63.

Article within a journal by DOI

Slifka MK, Whitton JL. Clinical implications of dysregulated cytokine production. Dig J Mol Med. 2000; doi:10.1007/s801090000086.

Article within a journal supplement

Frumin AM, Nussbaum J, Esposito M. Functional asplenia: demonstration of splenic activity by bone marrow scan. Blood 1979;59 Suppl 1:26-32.

Book chapter, or an article within a book

Wyllie AH, Kerr JFR, Currie AR. Cell death: the significance of apoptosis. In: Bourne GH, Danielli JF, Jeon KW, editors. International review of cytology. London: Academic; 1980. p. 251-306.

OnlineFirst chapter in a series (without a volume designation but with a DOI)

Saito Y, Hyuga H. Rate equation approaches to amplification of enantiomeric excess and chiral symmetry breaking. Top Curr Chem. 2007. doi:10.1007/128_2006_108.

Complete book, authored

Blenkinsopp A, Paxton P. Symptoms in the pharmacy: a guide to the management of common illness. 3rd ed. Oxford: Blackwell Science; 1998.

Online document

Doe J. Title of subordinate document. In: The dictionary of substances and their effects. Royal Society of Chemistry. 1999. http://www.rsc.org/dose/title of subordinate document. Accessed 15 Jan 1999.

Online database

Healthwise Knowledgebase. US Pharmacopeia, Rockville. 1998. http://www.healthwise.org. Accessed 21 Sept 1998.

Supplementary material/private homepage

Doe J. Title of supplementary material. 2000. http://www.privatehomepage.com. Accessed 22 Feb 2000.

University site

Doe, J: Title of preprint. http://www.uni-heidelberg.de/mydata.html (1999). Accessed 25 Dec 1999.

Doe, J: Trivial HTTP, RFC2169. ftp://ftp.isi.edu/in-notes/rfc2169.txt (1999). Accessed 12 Nov 1999.

Organization site

ISSN International Centre: The ISSN register. http://www.issn.org (2006). Accessed 20 Feb 2007.

Dataset with persistent identifier

Zheng L-Y, Guo X-S, He B, Sun L-J, Peng Y, Dong S-S, et al. Genome data from sweet and grain sorghum (Sorghum bicolor). GigaScience Database. 2011. http://dx.doi.org/10.5524/100012 .

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Published peer-reviewed protocols 

A research protocol is a detailed study design or set of instructions for carrying out a specific experimental process or procedure.

Benefits of Published Protocols

Peer-review of protocols supports rigorous, high-quality research, while publication increases discoverability, supports reproducibility, and recognizes the importance of the scientific work. Articles published under an Open Access license are freely available for anyone, anywhere in the world to discover, read, distribute or reuse at no cost. For that reason, Open Access articles are more widely read than subscription research.

Improve  your approach Expert peer review feedback can help to refine and shape your protocol, promoting usability and efficiency.

Earn readers’ trust  It’s difficult to reproduce results—or even confirm the question a study is designed to answer—based on a research article alone. Protocols show that you did what you set out to do, and how you went about it.

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When it comes to methods sharing, Lab Protocols at PLOS ONE offer researchers the best of both worlds: a platform specifically designed for step-by-step protocols, and a peer-reviewed publication in a well-regarded journal.

Our ongoing partnership with protocols.io led to a new and exciting PLOS ONE article type, Lab Protocols, which offers a new avenue to share research in-line with the principles of Open Science.

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• Corpus ID: 39692556

Designing a Case Study Protocol for Application in IS Research

• Hilangwa Maimbo , G. Pervan
• Published in Pacific Asia Conference on… 2005
• Computer Science

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Guthrie S, Bienkowska-Gibbs T, Manville C, et al. The impact of the National Institute for Health Research Health Technology Assessment programme, 2003–13: a multimethod evaluation. Southampton (UK): NIHR Journals Library; 2015 Aug. (Health Technology Assessment, No. 19.67.)

The impact of the National Institute for Health Research Health Technology Assessment programme, 2003–13: a multimethod evaluation.

Appendix 3 case study interview protocol.

• A. Introduction

RAND Europe has been commissioned by the HTA programme to assess its impact over the last 10 years.

RAND Europe is a non-profit policy research organisation, with an interest in research policy.

As part of this project, we are building a series of case studies around research funded by the HTA programme to identify the nature and range of impacts the programme has had, and how they came about. In a separate stream of work we are also looking across the programme as a whole for the impacts it has had using interviews, bibliometrics and a survey.

Our previous work in this area includes: payback studies of research impact on Mental Health research, Cardiovascular research, Arthritis research and Social science research. We have also carried out two studies for government and charitable research funders estimating the economic benefit of investing in medical research.

Drawing on a range of sources, we identified a long list of potential case studies and selected a stratified sample which included your study into XXXX published in the HTA journal article XXXX. We’d like to talk to you about how that research came about how it fitted into the other research you were doing at the time and how it developed.

For this project, we are looking at both how the findings of the research were developed and translated; and also, how the research undertaken developed the careers of the researchers involved.

We would like to record this interview. You will be given the opportunity to review the draft case study before it is published and request that any direct quotations used are removed or anonymised.

You should also emphasize that not all the questions will be relevant to their research project, and indeed we wouldn’t expect them all to be.

You shouldn’t stick to the protocol as written – it just provides guidance of the areas you should aim to cover. During your desk research you will have identified additional questions that you will want to ask and it’s probably best to add these to the protocol.

• B. Introductory questions

To begin, talk briefly about their current work and how it relates to what they were doing at the time.

Can you tell us a bit about what you were doing at the time?

Where you were in your career?

Can you give us some background to this project?

Why do you think this project was seen as important?

• C. Stage 0: Opportunity identification/research needs assessment

Was this project commissioned or was it a response mode grant?

• If commissioned, what was the source of the idea for the research?
• If response mode, what was the original impetus for the work? (Solely scientific curiosity? The desire to fill certain gaps in knowledge? Targeting of a particular disease state? Your own clinical experience?)

Was there a clear intended impact on policy or practice from the outset?

What other ideas were you pursuing at the time, how did they relate to this work?

Who influenced your decision to work in this area?

Was it a continuation of previous work?

How far was your identification of the research topic influenced by:

• Research you had done before? Funded by whom?
• The research of others? If so how did you hear about this research?
• For primary research, an existing systematic review?

How much interaction was involved in determining your choice of research topic?

• With representatives of patient or practitioner groups?
• With funders?
• With peers internationally in a specific research community?

Did institutional conditions such as lab space, equipment, or availability of researchers affect the research proposal?

• D. Stage 1: Inputs to research and project specification and selection

How much funding did you receive from the HTA?

Were there other sources of funding which supported this work?

• What were the different forms of support and why was each important?
• Was there soft or core funding (e.g. funding the needs to be applied for vs. guaranteed funding)?

Did you make any unsuccessful applications for funding? Did you make any resubmissions?

Did any of the peer review or applications processes affect the design or direction of the work?

Did you have to compete for funding?

Did you consult with patients, the public or practitioners in developing the research design? What role did their input play?

What was the institutional setting (hospital, university, research institute) for the research?

Who were the main researchers involved in the project?

What was their level of research experience and seniority at that time?

Had they previously worked in this research area?

For primary research: did any existing systematic review play a role in your research design (e.g. in determining necessary sample sizes)?

Which of the following inputs were important?

• Knowledge/expertise
• Samples/study recruits
• Consumables
• Collaborators
• Reputation.
• E. Stage 2: Processes

Did the methods proposed prove to be appropriate? Which avenues of research were successful and which weren’t?

Was there any interaction with potential users of the research during the research processes?

How much freedom did you or the research group have to pursue different lines of enquiry/deviate from the original proposal? How important was this flexibility in achieving the final results?

Did you publish the research protocol at the start of the study?

Did the research require new techniques/new expertise/new approaches to the subject?

How would you describe your role in the research process?

What was the role of collaborators in the research process (both academic and industrial)?

Who else was working in the area?

What interaction did you have with HTA programme staff during the research process? How useful was this interaction?

• F. Stage 3: Primary outputs

Which publications do you think were most important from this research and why?

Did this work have any impact on the agenda for your subsequent research?

Did this research make any impact on the career of any of the research team? For example: contribute to research training in terms of research degrees or the gaining of additional skills

• enable them to establish themselves in the field?
• help the lead researcher to build a team of researchers?

Are you aware of any other researchers who have built on this work or used the methods you developed? What is the role of collaborators in this?

Did the research spawn a new area of investigation or make a major impact on the approach used in subsequent research?

If the research was clinical, were any basic researchers also involved? If so did this influence their attitude to clinical research?

Were any health practitioners involved in assisting with the research, and if so did it have any impact on their attitude towards implementing research findings in general?

For primary research: has the research been included in any subsequent systematic reviews or meta-analyses?

For evidence synthesis: has any primary research been conducted based on the findings of your work?

Have you had any impact outside the field of research you are working in?

Were any findings of the research not published (e.g. dead ends, negative findings)?

• G. Interface B: Dissemination

Apart from publications, what attempt did you make to disseminate the findings

• to academic audiences?
• to wider audiences? Did you work with funders or stakeholders to do this?

Did you use specially designed dissemination approaches to particular audiences, for example policy briefs for policy-makers? What were the most effective mechanisms for this?

What was the role of your networks in dissemination?

Did you receive support from funders/employers for dissemination? What form did this take?

• H. Stage 4: Secondary outputs

Has the research been cited directly in any clinical guideline, audit criteria or similar document from a professional body or public policy-making body at national or local level?

Do you know how far the research directly influenced the formulation of any policy, or the realisation that a policy was needed?

Has any subsequent research by you or others that built on this project been cited in any clinical guideline, audit criteria or similar document from a professional body or public policy-making body at national or local level? Do you think this might happen in future?

Did the research from your project lead to any patents/licences? Was it taken up by industry? Has it contributed to any commercial products?

If the research has made some impact, what are the key reasons for this? If it has failed to have an impact what are the reasons for this?

What barriers were there to the research having an impact/being translated?

What factors facilitated the research having an impact/being translated?

Has your research had an impact on teaching for clinicians?

Has any advisory role to government, hospitals, industry led to an impact from your research? How did this come about?

• I. Stage 5: Applications

Have the findings from the research influenced practitioners directly through them reading the articles or hearing a presentation about the research?

What were the impacts on practice through clinical guidelines or policies based either specifically on the research or on other research that built on your research?

Can you comment on the extent of implementation? How widely have those policies or guidelines been taken up?

Have the findings been disseminated through other routes such as networks or existing relationships with practitioners?

Has any impact been local, regional, national or international?

If the research has been taken up by industry, do you know what level of sales has been achieved by any product to which it contributed?

Do you expect any greater take-up of the findings in the future? Where and how?

Has there been an impact on practice through your own clinical work (if you have any)? What has been the knock-on effect of that on other clinicians?

• J. Stage 6: Public engagement

Depending on answers to previous questions about involvement of the public in shaping the research agenda, ask how far there has been any interaction with patients, patient groups or the wider public about the findings and their implication. Has this led to any improvement in the way patients manage their own care or interact with therapy? Or had any impact on public attitudes to medical research? Please describe these.

Did engagement with the public/patient groups lead to changes in the researchers’ perceptions of these groups? Please describe.

• K. Stage 7: Final outcomes

If the research has made impact on policy or practice, or on the behaviour of the public, is there any way of assessing the benefits in terms of: patient health gain? Qualitative improvements in the way the service is delivered that increase patient and/or practitioner satisfaction? Cost savings?

If it is possible to assess the potential benefit for one patient, approximately how many patients might be able to benefit from the improved therapy or organisation of the service?

If the improved therapy based on the research has resulted in a health gain, will this also result in fewer days lost from work/decreased benefits payments/decreased visits to secondary health care?

If the research has resulted in commercial development is anything known about the amount of employment generated, the level of import substitution, or the revenue generated for the company by the product?

• L. Other general questions

Who else should we speak to about your research?

Are there other questions we should have asked or things that you want to talk about?

Are you happy for us to contact you to follow up on details arising from the case study research?

Included under terms of UK Non-commercial Government License .

• Cite this Page Guthrie S, Bienkowska-Gibbs T, Manville C, et al. The impact of the National Institute for Health Research Health Technology Assessment programme, 2003–13: a multimethod evaluation. Southampton (UK): NIHR Journals Library; 2015 Aug. (Health Technology Assessment, No. 19.67.) Appendix 3, Case study interview protocol.
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The Case Study Protocol

A case study protocol has only one thing in common with a survey question­naire: Both are directed at a single data point—either a single case (even if the case is part of a larger, multiple-case study) or a single respondent.

Beyond this similarity are major differences. The protocol is more than a questionnaire or instrument. First, the protocol contains the instrument but also contains the procedures and general rales to be followed in using the pro­tocol. Second, the protocol is directed at an entirely different party than that of a survey questionnaire, explained below. Third, having a case study protocol is desirable under all circumstances, but it is essential if you are doing a mul­tiple-case study.

The protocol is a major way of increasing the reliability of case study research and is intended to guide the investigator in carrying out the data col­lection from a single case (again, even if the single case is one of several in a multiple-case study). Figure 3.2 gives a table of contents from an illustrative protocol, which was used in a study of innovative law enforcement practices supported by federal funds. The practices had been defined earlier through a careful screening process (see later discussion in this chapter for more detail on “screening case study nominations”). Furthermore, because data were to be collected from 18 such cases as part of a multiple-case study, the information about any given case could not be collected in great depth, and thus the number of the case study questions was minimal.

As a general matter, a case study protocol should have the following sections:

• an overview of the case study project (project objectives and auspices, case study issues, and relevant readings about the topic being investigated),
• field procedures (presentation of credentials, access to the case study “sites,” language pertaining to the protection of human subjects, sources of data, and procedural reminders),
• case study questions (the specific questions that the case study investigator must keep in mind in collecting data, “table shells” for specific arrays of data, and the potential sources of information for answering each question—see Figure 3.3 for an example), and
• a guide for the case study report (outline, format for the data, use and presenta­tion of other documentation, and bibliographical information).

A quick glance at these topics will indicate why the protocol is so important. First, it keeps you targeted on the topic of the case study. Second, preparing the protocol forces you to anticipate several problems, including the way that the case study reports are to be completed. This means, for instance, that you will have to identify the audience for your case study report even before you have conducted your case study. Such forethought will help to avoid mismatches in the long run.

The table of contents of the illustrative protocol in Figure 3.2 reveals another important feature of the case study report: In this instance, the desired report starts by calling for a description of the innovative practice being studied (see item Cl in Figure 3.2)—and only later covers the agency context and history pertaining to the practice (see item C4). This choice reflects the fact that most investigators write too extensively on history and background conditions. While these are important, the description of the subject of the study—the innovative practice—needs more attention.

Each section of the protocol is discussed next.

1. Overview of the Case Study Project

The overview should cover the background information about the project, the substantive issues being investigated, and the relevant readings about the issues.

As for background information, every project has its own context and perspective. Some projects, for instance, are funded by government agencies having a general mission and clientele that need to be remembered in con­ducting the research. Other projects have broader theoretical concerns or are offshoots, of earlier research studies. Whatever the situation, this type of back­ground information, in summary form, belongs in the overview section.

A procedural element of this background section is a statement about the project which you can present to anyone who may want to know about the pro­ject, its purpose, and the people involved in conducting and sponsoring the project. This statement can even be accompanied by a letter of introduction, to be sent to all major interviewees and organizations that may be the subject of study. (See Figure 3.4 for an illustrative letter.) The bulk of the overview, how­ever, should be devoted to the substantive issues being investigated. This may include the rationale for selecting the case(s), the propositions or hypotheses being examined, and the broader theoretical or policy relevance of the inquiry. For all of these topics, relevant readings should be cited, and the essential read­ing materials should be made available to everyone on the case study team.

A good overview will communicate to the informed reader (that is, some­one familiar with the general topic of inquiry) the case study’s purpose and set­ting. Some of the materials (such as a summary describing the project) may be needed for other purposes anyway, so that writing the overview should be seen as a doubly worthwhile activity. In the same vein, a well-conceived overview even may later form the basis for the background and introduction to the final case study report.

2. Field Procedures

Chapter 1 has previously defined case studies as studies of events within their real-life context. This has important implications for defining and design­ing the case study, which have been discussed in Chapters 1 and 2.

For data collection, however, this characteristic of case studies also raises an important issue, for which properly designed field procedures are essential. You will be collecting data from people and institutions in their everyday situations, not within the controlled confines of a laboratory, the sanctity of a library, or the structured limitations of a survey questionnaire. In a case study, you must there­fore learn to integrate real-world events with the needs of the data collection plan. In this sense, you do not have the control over the data collection environment as others might have in using the other research methods discussed in Chapter 1.

Note that in a laboratory experiment, human “subjects” are solicited to enter into the laboratory—an environment controlled nearly entirely by the research investigator. The subject, within ethical and physical constraints, must follow the investigator’s instructions, which carefully prescribe the desired behavior. Similarly, the human “respondent” to a survey questionnaire cannot deviate from the agenda set by the questions. Therefore, the respondent’s behavior also is con­strained by the ground rules of the investigator. Naturally, the subject or respon­dent who does not wish to follow the prescribed behaviors may freely drop out of the experiment or survey. Finally, in the historical archive, pertinent documents may not always be available, but the investigator can inspect what exists at his or her own pace and at a time convenient to her or his schedule. In all three situa­tions, the research investigator closely controls the formal data collection activity.

Doing case studies involves an entirely different situation. For interviewing key persons, you must cater to the interviewee’s schedule and availability, not your own. The nature of the interview is much more open-ended, and an interviewee may not necessarily cooperate fully in sticking to your line of questions. Similarly, in making observations of real-life activities, you are intruding into the world of the subject being studied rather than the reverse; under these conditions, you are the one who may have to make special arrangements, to be able to act as an observer (or even as a participant- observer). As a result, your behavior—and not that of the subject or respon­dent—is the one likely to be constrained.

This contrasting process of doing data collection leads to the need to have explicit and well-planned field procedures encompassing guidelines for “cop­ing” behaviors. Imagine, for instance, sending a youngster to camp; because you do not know what to expect, the best preparation is to have the resources to be prepared. Case study field procedures should be the same way.

With the preceding orientation in mind, the field procedures of the protocol need to emphasize the major tasks in collecting data, including

• gaining access to key organizations or interviewees;
• having sufficient resources while in the field—including a personal computer, writing instruments, paper, paper clips, and a preestablished, quiet place to write notes privately;
• developing a procedure for calling for assistance and guidance, if needed, from other case study investigators or colleagues;
• making a clear schedule of the data collection activities that are expected to be completed within specified periods of time; and
• providing for unanticipated events, including changes in the availability of interview­ees as well as changes in the mood and motivation of the case study investigator.

These are the types of topics that can be included in the field procedures sec­tion of the protocol. Depending upon the type of study being done, the specific procedures will vary.

The more operational these procedures are, the better. To take but one minor issue as an example, case study data collection frequently results in the accu­mulation of numerous documents at the field site. The burden of carrying such bulky documents can be reduced by two procedures. First, the case study team may have had the foresight to bring large, prelabeled envelopes, to mail the documents back to the office rather than carry them. Second, field time may have been set aside for perusing the documents and then going to a local copier facility and copying only the few relevant pages of each document—and then returning the original documents to the informants at the field site. These and other operational details can enhance the overall quality and efficiency of case study data collection.

A final part of this portion of the protocol should carefully describe the procedures for protecting human subjects. First, the protocol should repeat the rationale for the IRB-approved field procedures. Then, the protocol should include the “scripted” words or instructions for the team to use in obtaining informed consent or otherwise informing case study interviewees and other participants of the risks and conditions associated with the research.

3. Case Study Questions

The heart of the protocol is a set of substantive questions reflecting your actual line of inquiry. Some people may consider this part of the protocol to be the case study “instrument.” However, two characteristics distinguish case study questions from those in a survey instrument. (Refer back to Figure 3.3 for an illustrative question from a study of a school program; the complete protocol included dozens of such questions.)

General orientation of questions. First, the questions are posed to you, the investigator, not to an interviewee. In this sense, the protocol is directed at an entirely different party than a survey instrument. The protocol’s questions, in essence, are your reminders regarding the information that needs to be col­lected, and why. In some instances, the specific questions also may serve as prompts in asking questions during a case study interview. However, the main purpose of the protocol’s questions is to keep the investigator on track as data collection proceeds.

Each question should be accompanied by a list of likely sources of evidence. Such sources may include the names of individual interviewees, documents, or observations. This crosswalk between the questions of interest and the likely sources of evidence is extremely helpful in collecting case study data. Before arriving on the case study scene, for instance, a case study investigator can quickly review the major questions that the data collection should cover.

(Again, these questions form the structure of the inquiry and are not intended as the literal questions to be asked of any given interviewee.)

Levels of questions. Second, the questions in the case study protocol should distinguish clearly among different types or levels of questions. The poten­tially relevant questions can, remarkably, occur at any of five levels:

Level 1: questions asked of specific interviewees;

Level 2: questions asked of the individual case (these are the questions in the case study protocol to be answered by the investigator during a single case, even when the single case is part of a larger, multiple-case study);

Level 3: questions asked of the pattern of findings across multiple cases;

Level 4: questions asked of an entire study—for example, calling on information beyond the case study evidence and including other literature or published data that may have been reviewed; and

Level 5: normative questions about policy recommendations and conclusions, going beyond the narrow scope of the study.

Of these five levels, you should concentrate heavily on Level 2 for the case study protocol.

The difference between Level 1 and Level 2 questions is highly significant. The two types of questions are most commonly confused because investigators think that their questions of inquiry (Level 2) are synonymous with the spe­cific questions they will ask in the field (Level 1). To disentangle these two levels in your own mind, think again about a detective, especially a wily one. The detective has in mind what the course of events in a crime might have been (Level 2), but the actual questions posed to any witness or suspect (Level 1) do not necessarily betray the detective’s thinking. The verbal line of inquiry is different from the mental line of inquiry, and this is the difference between Level 1 and Level 2 questions. For the case study protocol, explicitly articu­lating the Level 2 questions is therefore of much greater importance than any attempt to identify the Level 1 questions.

In the field, keeping in mind the Level 2 questions while simultaneously articulating Level 1 questions in conversing with an interviewee is not easy. In a like manner, you can lose sight of your Level 2 questions when examin­ing a detailed document that will become part of the case study evidence (the common revelation occurs when you ask yourself, “Why am I reading this document?”). To overcome these problems, successful participation in the earlier seminar training helps. Remember that being a “senior” investigator means maintaining a working knowledge of the entire case study inquiry. The (Level 2) questions in the case study protocol embody this inquiry.

The other levels also should be understood clearly. A cross-case question, for instance (Level 3), may be whether the larger school districts among your cases are more responsive than smaller school districts or whether complex bureaucratic structures make the larger districts more cumbersome and less responsive. However, this Level 3 question should not be part of the protocol for collecting data from the single case, because the single case only can address the responsiveness of a single school district. The Level 3 question cannot be addressed until the data from all the single cases (in a multiple-case study) are examined. Thus, only the multiple-case analysis can cover Level 3 questions. Similarly, the questions at Levels 4 and 5 also go well beyond any individual case study, and you should note this limitation if you include such questions in the case study protocol. Remember: The protocol is for the data collection from a single case (even when part of a multiple-case study) and is not intended to serve the entire project.

Undesired confusion between unit of data collection and unit of analysis. Related to the distinction between Level 1 and Level 2 questions, a more sub­tle and serious problem can arise in articulating the questions in the case study protocol. The questions should cater to the unit of analysis of the case study, which may be at a different level from the unit of data collection of the case study. Confusion will occur if, under these circumstances, the data collection process leads to an (undesirable) distortion of the unit of analysis.

The common confusion begins because the data collection sources may be individual people (e.g., interviews with individuals), whereas the unit of analy­sis of your case study may be a collective (e.g., the organization to which the individual belongs)—a frequent design when the case study is about an orga­nization, community, or social group. Even though your data collection may have to rely heavily on information from individual interviewees, your con­clusions cannot be based entirely on interviews as a source of information (you would then have collected information about individuals’ reports about the organization, not necessarily about organizational events as they actually had occurred). In this example, the protocol questions therefore need to be about the organization, not the individual.

However, the reverse situation also can be true. Your case study may be about an individual, but the sources of information can include archival records (e.g., personnel files or student records) from an organization. In this situation, you also would want to avoid basing your conclusions about the individual from the organizational sources of information only. In this example, the protocol ques­tions therefore need to be about the individual, not the organization.

Figure 3.5 illustrates these two situations, where the unit of analysis for the case study is different from the unit of data collection.

Other data collection devices. The protocol questions also can include empty “table shells” (for more detail, see Miles & Huberman, 1994). These are the outlines of a table, defining precisely the “rows” and “columns” of a data array—but in the absence of having the actual data. In this sense, the table shell indicates the data to be collected, and your job is to collect the data called forth by the table. Such table shells help in several ways. First, the table shells force you to identify exactly what data are being sought. Second, they ensure that parallel information will be collected at different sites, where a multiple- case design is being used. Finally, the table shells aid in understanding what will be done with the data once they have been collected.

4. Guide for the Case Study Report

This element is generally missing in most case study plans. Investigators neglect to think about the outline, format, or audience for the case study report until after the data have been collected. Yet, some planning at this preparatory stage—admittedly out of sequence in the typical conduct of most research— means that a tentative outline can (and should) appear in the case study protocol. (Such planning accounts for the arrow between “prepare” and “share” in the figure at the outset of this chapter.)

Again, one reason for the traditional, linear sequence is related to practices with other research methods. One does not worry about the report from an exper­iment until after the experiment has been completed, because the format of the report and its likely audience already have been dictated by the conventional for­mats of academic journals. Most reports of experiments follow a similar outline: the posing of the research questions and hypotheses; a description of the research design, apparatus, and data collection procedures; the presentation of the data collected; the analysis of the data; and a discussion of findings and conclusions.

Unfortunately, case study reports do not have such a uniformly acceptable outline. Nor, in many instances, do case study reports end up in journals (Feagin et al., 1991, pp. 269-273). For this reason, each investigator must be concerned, throughout the conduct of a case study, with the design of the final case study report. The problem is not easy to deal with.

In addition, the protocol also can indicate the extent of documentation for the case study report. Properly done, the data collection is likely to lead to large amounts of documentary evidence, in the form of published reports, publica­tions, memoranda, and other documents collected about the case. What is to be done with this documentation, for later presentation? In most studies, the docu­ments are filed away and seldom retrieved. Yet, this documentation is an impor­tant part of the “database” for a case study (see Chapter 4) and should not be ignored until after the case study has been completed. One possibility is to have the case study report include an annotated bibliography in which each of the available documents is itemized. The annotations would help a reader (or the investigator, at some later date) to know which documents might be relevant for further inquiry.

In summary, to the extent possible, the basic outline of the case study report should be part of the protocol. This will facilitate the collection of relevant data, in the appropriate format, and will reduce the possibility that a return visit to the case study site will be necessary. At the same time, the existence of such an outline should not imply rigid adherence to a predesigned protocol. In fact, case study plans can change as a result of the initial data collection, and you are encouraged to consider these flexibilities—if used properly and with­out bias—to be an advantage of the case study method.

EXERCISE 3.4 Developing a Case Study Protocol

Select some phenomenon in need of explanation from the everyday life of your university or school (past or present). Illustrative topics might be, for example, why the university or school changed some policy or how it makes decisions about its curriculum requirements. For these illustrative topics (or some topics of your own choosing), design a case study protocol to collect the information needed to make an adequate explanation. What would be your main research questions or propositions? What specific sources of data would you seek (e.g., persons to be interviewed, documents to be sought, and field observations to be made)? Would your protocol be sufficient in guiding you through the entire process of doing your case study?

Source: Yin K Robert (2008), Case Study Research Designs and Methods , SAGE Publications, Inc; 4th edition.

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Guidelines for conducting and reporting case study research in software engineering

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• Published: 19 December 2008
• Volume 14 , pages 131–164, ( 2009 )

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• Per Runeson 1 &
• Martin Höst 1  

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Case study is a suitable research methodology for software engineering research since it studies contemporary phenomena in its natural context. However, the understanding of what constitutes a case study varies, and hence the quality of the resulting studies. This paper aims at providing an introduction to case study methodology and guidelines for researchers conducting case studies and readers studying reports of such studies. The content is based on the authors’ own experience from conducting and reading case studies. The terminology and guidelines are compiled from different methodology handbooks in other research domains, in particular social science and information systems, and adapted to the needs in software engineering. We present recommended practices for software engineering case studies as well as empirically derived and evaluated checklists for researchers and readers of case study research.

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Guidelines for Case Survey Research in Software Engineering

The design science paradigm as a frame for empirical software engineering, data science and empirical software engineering.

Avoid common mistakes on your manuscript.

1 Introduction

The acceptance of empirical studies in software engineering and their contributions to increasing knowledge is continuously growing. The analytical research paradigm is not sufficient for investigating complex real life issues, involving humans and their interactions with technology. However, the overall share of empirical studies is negligibly small in computer science research; Sjøberg et al. ( 2005 ), found 103 experiments in 5,453 articles Ramesh et al. ( 2004 ) and identified less than 2% experiments with human subjects, and only 0.16% field studies among 628 articles. Further, existing work on empirical research methodology in software engineering has a strong focus on experimental research; the earliest by Moher and Schneider ( 1981 ), Basili et al. ( 1986 ), the first methodology handbook by Wohlin et al. ( 2000 ), and promoted by Tichy ( 1998 ). All have a tendency towards quantitative approaches, although also qualitative approaches are discussed during the later years, e.g. by Seaman ( 1999 ). There exist guidelines for experiments’ conduct (Kitchenham et al. 2002 ; Wohlin et al. 2000 ) and reporting (Jedlitschka and Pfahl 2005 ), measurements (Basili and Weiss 1984 ; Fenton and Pfleeger 1996 ; van Solingen and Berghout 1999 ), and systematic reviews (Kitchenham 2007 ), while only little is written on case studies in software engineering (Höst and Runeson 2007 ; Kitchenham et al. 1995 ; Wohlin et al. 2003 ) and qualitative methods (Dittrich 2007 ; Seaman 1999 ; Sim et al. 2001 ). Recently, a comprehensive view of empirical research issues for software engineering has been presented, edited by Shull et al. ( 2008 ).

The term “case study” appears every now and then in the title of software engineering research papers. However, the presented studies range from very ambitious and well organized studies in the field, to small toy examples that claim to be case studies. Additionally, there are different taxonomies used to classify research. The term case study is used in parallel with terms like field study and observational study, each focusing on a particular aspect of the research methodology. For example, Lethbridge et al. use field studies as the most general term (Lethbridge et al. 2005 ), while Easterbrook et al. ( 2008 ) call case studies one of five “classes of research methods”. Zelkowitz and Wallace propose a terminology that is somewhat different from what is used in other fields, and categorize project monitoring, case study and field study as observational methods (Zelkowitz and Wallace 1998 ). This plethora of terms causes confusion and problems when trying to aggregate multiple empirical studies.

The case study methodology is well suited for many kinds of software engineering research, as the objects of study are contemporary phenomena, which are hard to study in isolation. Case studies do not generate the same results on e.g. causal relationships as controlled experiments do, but they provide deeper understanding of the phenomena under study. As they are different from analytical and controlled empirical studies, case studies have been criticized for being of less value, impossible to generalize from, being biased by researchers etc. This critique can be met by applying proper research methodology practices as well as reconsidering that knowledge is more than statistical significance (Flyvbjerg 2007 ; Lee 1989 ). However, the research community has to learn more about the case study methodology in order to review and judge it properly.

Case study methodology handbooks are superfluously available in e.g. social sciences (Robson 2002 ; Stake 1995 ; Yin 2003 ) which literature also has been used in software engineering. In the field of information systems (IS) research, the case study methodology is also much more mature than in software engineering. For example, Benbasat et al. provide a brief overview of case study research in information systems (Benbasat et al. 1987 ), Lee analyzes case studies from a positivistic perspective (Lee 1989 ) and Klein and Myers do the same from an interpretive perspective (Klein and Myers 1999 ).

It is relevant to raise the question: what is specific for software engineering that motivates specialized research methodology? In addition to the specifics of the examples, the characteristics of software engineering objects of study are different from social science and also to some extent from information systems. The study objects are 1) private corporations or units of public agencies developing software rather than public agencies or private corporations using software systems; 2) project oriented rather than line or function oriented; and 3) the studied work is advanced engineering work conducted by highly educated people rather than routine work. Additionally, the software engineering research community has a pragmatic and result-oriented view on research methodology, rather than a philosophical stand, as noticed by Seaman ( 1999 ).

The purpose of this paper is to provide guidance for the researcher conducting case studies, for reviewers of case study manuscripts and for readers of case study papers. It is synthesized from general methodology handbooks, mainly from the social science field, as well as literature from the information systems field, and adapted to software engineering needs. Existing literature on software engineering case studies is of course included as well. The underlying analysis is done by structuring the information according to a general case study research process (presented in Section 2.4 ). Where different recommendations or terms appear, the ones considered most suited for the software engineering domain are selected, based on the authors’ experience on conducting case studies and reading case study reports. Links to data sources are given by regular references. Specifically, checklists for researchers and readers are derived through a systematic analysis of existing checklists (Höst and Runeson 2007 ), and later evaluated by PhD students as well as by members of the International Software Engineering Research Network and updated accordingly.

This paper does not provide absolute statements for what is considered a “good” case study in software engineering. Rather it focuses on a set of issues that all contribute to the quality of the research. The minimum requirement for each issue must be judged in its context, and will most probably evolve over time. This is similar to the principles by Klein and Myers for IS case studies (Klein and Myers 1999 ), “it is incumbent upon authors, reviewers, and exercise their judgment and discretion in deciding whether, how and which of the principles should be applied”. We do neither assess the current status of case study research in software engineering. This is worth a study on its own, similar to the systematic review on experiments by Sjøberg et al. ( 2005 ). Further, examples are used both to illustrate good practices and lack thereof.

This paper is outlined as follows. We first define a set of terms in the field of empirical research, which we use throughout the paper (Section 2.1 ), set case study research into the context of other research methodologies (Section 2.2 ) and discuss the motivations for software engineering case studies (Section 2.3 ). We define a case study research process (Section 2.4 ) and terminology (Section 2.5 ), which are used for the rest of the paper. Section 3 discusses the design of a case study and planning for data collection. Section 4 describes the process of data collection. In Section 5 issues on data analysis are treated, and reporting is discussed in Section 6 . Section 7 discusses reading and reviewing case study report, and Section 8 summarizes the paper. Checklists for conducting and reading case study research are linked to each step in the case study process, and summarized in the Appendix .

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2 Background and Definition of Concepts

2.1 research methodology.

In order to set the scope for the type of empirical studies we address in this paper, we put case studies into the context of other research methodologies and refer to general definitions of the term case study according to Robson ( 2002 ), Yin ( 2003 ) and Benbasat et al. ( 1987 ) respectively.

The three definitions agree on that case study is an empirical method aimed at investigating contemporary phenomena in their context . Robson calls it a research strategy and stresses the use of multiple sources of evidence , Yin denotes it an inquiry and remarks that the boundary between the phenomenon and its context may be unclear , while Benbasat et al. make the definitions somewhat more specific, mentioning information gathering from few entities (people, groups, organizations), and the lack of experimental control .

There are three other major research methodologies which are related to case studies:

Survey, which is the “collection of standardized information from a specific population, or some sample from one, usually, but not necessarily by means of a questionnaire or interview” (Robson 2002 ).

Experiment, or controlled experiment, which is characterized by “measuring the effects of manipulating one variable on another variable” (Robson 2002 ) and that “subjects are assigned to treatments by random.”(Wohlin et al. 2000 ). Quasi-experiments are similar to controlled experiments, except that subjects are not randomly assigned to treatments. Quasi-experiments conducted in an industry setting may have many characteristics in common with case studies.

Action research, with its purpose to “influence or change some aspect of whatever is the focus of the research” (Robson 2002 ), is closely related to case study. More strictly, a case study is purely observational while action research is focused on and involved in the change process. In software process improvement (Dittrich et al. 2008 ; Iversen et al. 2004 ) and technology transfer studies (Gorschek et al. 2006 ), the research method should be characterized as action research. However, when studying the effects of a change, e.g. in pre- and post-event studies, we classify the methodology as case study. In IS, where action research is widely used, there is a discussion on finding the balance between action and research, see e.g. (Avison et al. 2001 ; Baskerville and Wood-Harper 1996 ). For the research part of action research, these guidelines apply as well.

Easterbrook et al. ( 2008 ) also count ethnographic studies among the major research methodologies. We prefer to consider ethnographic studies as a specialized type of case studies with focus on cultural practices (Easterbrook et al. 2008 ) or long duration studies with large amounts of participant-observer data (Klein and Myers 1999 ). Zelkowitz and Wallace define four different “observational methods” in software engineering (Zelkowitz and Wallace 1998 ); project monitoring, case study, assertion and field study . Our guidelines apply to all these, except assertion which is not considered a proper research method. In general, the borderline between the types of study is not always distinct. We prefer to see project monitoring as a part of a case study and field studies as multiple case studies. Robson summarizes his view, which seems functional in software engineering as well: “Many flexible design studies, although not explicitly labeled as such, can be usefully viewed as case studies.” (Robson 2002 ) p 185.

Finally, a case study may contain elements of other research methods, e.g. a survey may be conducted within a case study, literature search often precede a case study and archival analyses may be a part of its data collection. Ethnographic methods, like interviews and observations are mostly used for data collection in case studies.

2.2 Characteristics of Research Methodologies

Different research methodologies serve different purposes; one type of research methodology does not fit all purposes. We distinguish between four types of purposes for research based on Robson’s ( 2002 ) classification:

Exploratory—finding out what is happening, seeking new insights and generating ideas and hypotheses for new research.

Descriptive—portraying a situation or phenomenon.

Explanatory—seeking an explanation of a situation or a problem, mostly but not necessary in the form of a causal relationship. Footnote 1

Improving—trying to improve a certain aspect of the studied phenomenon. Footnote 2

Case study methodology was originally used primarily for exploratory purposes, and some researchers still limit case studies for this purpose, as discussed by Flyvbjerg ( 2007 ). However, it is also used for descriptive purposes, if the generality of the situation or phenomenon is of secondary importance. Case studies may be used for explanatory purposes, e.g. in interrupted time series design (pre- and post-event studies) although the isolation of factors may be a problem. This involves testing of existing theories in confirmatory studies. Finally, as indicated above, case studies in the software engineering discipline often take an improvement approach, similar to action research; see e.g. the QA study (Andersson and Runeson 2007b ).

Klein and Myers define three types of case study depending on the research perspective, positivist, critical and interpretive (Klein and Myers 1999 ). A positivist case study searches evidence for formal propositions, measures variables, tests hypotheses and draws inferences from a sample to a stated population, i.e. is close to the natural science research model (Lee 1989 ) and related to Robson’s explanatory category. A critical case study aims at social critique and at being emancipatory, i.e. identifying different forms of social, cultural and political domination that may hinder human ability. Improving case studies may have a character of being critical. An interpretive case study attempts to understand phenomena through the participants’ interpretation of their context, which is similar to Robson’s exploratory and descriptive types. Software engineering case studies tend to lean towards a positivist perspective, especially for explanatory type studies.

Conducting research on real world issues implies a trade-off between level of control and degree of realism. The realistic situation is often complex and non-deterministic, which hinders the understanding of what is happening, especially for studies with explanatory purposes. On the other hand, increasing the control reduces the degree of realism, sometimes leading to the real influential factors being set outside the scope of the study. Case studies are by definition conducted in real world settings, and thus have a high degree of realism, mostly at the expense of the level of control.

The data collected in an empirical study may be quantitative or qualitative. Quantitative data involves numbers and classes, while qualitative data involves words, descriptions, pictures, diagrams etc. Quantitative data is analyzed using statistics, while qualitative data is analyzed using categorization and sorting. Case studies tend mostly to be based on qualitative data, as these provide a richer and deeper description. However, a combination of qualitative and quantitative data often provides better understanding of the studied phenomenon (Seaman 1999 ), i.e. what is sometimes called “mixed methods” (Robson 2002 ).

The research process may be characterized as fixed or flexible according to Anastas and MacDonald ( 1994 ) and Robson ( 2002 ). In a fixed design process, all parameters are defined at the launch of the study, while in a flexible design process key parameters of the study may be changed during the course of the study. Case studies are typically flexible design studies, while experiments and surveys are fixed design studies. Other literature use the terms quantitative and qualitative design studies, for fixed and flexible design studies respectively. We prefer to adhere to the fixed/flexible terminology since it reduces the risk for confusion that a study with qualitative design may collect both qualitative and quantitative data. Otherwise it may be unclear whether the term qualitative refers to the data or the design of the study,

Triangulation is important to increase the precision of empirical research. Triangulation means taking different angles towards the studied object and thus providing a broader picture. The need for triangulation is obvious when relying primarily on qualitative data, which is broader and richer, but less precise than quantitative data. However, it is relevant also for quantitative data, e.g. to compensate for measurement or modeling errors. Four different types of triangulation may be applied (Stake 1995 ):

Data (source) triangulation—using more than one data source or collecting the same data at different occasions.

Observer triangulation—using more than one observer in the study.

Methodological triangulation—combining different types of data collection methods, e.g. qualitative and quantitative methods.

Theory triangulation—using alternative theories or viewpoints.

Table  1 shows an overview of the primary characteristics of the above discussed research methodologies

Yin adds specifically to the characteristics of a case study that it (Yin 2003 ):

“copes with the technically distinctive situation in which there will be many more variables than data points, and as one result

relies on multiple sources of evidence, with data needing to converge in a triangulating fashion, and as another result

benefits from the prior development of theoretical propositions to guide data collection and analysis.”

Hence, a case study will never provide conclusions with statistical significance. On the contrary, many different kinds of evidence, figures, statements, documents, are linked together to support a strong and relevant conclusion.

Perry et al. define similar criteria for a case study (Perry et al. 2005 ). It is expected that a case study:

“Has research questions set out from the beginning of the study

Data is collected in a planned and consistent manner

Inferences are made from the data to answer the research question

Explores a phenomenon, or produces an explanation, description, or causal analysis of it

Threats to validity are addressed in a systematic way.”

In summary, the key characteristics of a case study are that 1) it is of flexible type, coping with the complex and dynamic characteristics of real world phenomena, like software engineering, 2) its conclusions are based on a clear chain of evidence, whether qualitative or quantitative, collected from multiple sources in a planned and consistent manner, and 3) it adds to existing knowledge by being based on previously established theory, if such exist, or by building theory.

2.3 Why Case Studies in Software Engineering?

Case studies are commonly used in areas like psychology, sociology, political science, social work, business, and community planning (e.g. Yin 2003 ). In these areas case studies are conducted with objectives to increase knowledge about individuals, groups, and organizations, and about social, political, and related phenomena. It is therefore reasonable to compare the area of software engineering to those areas where case study research is common, and to compare the research objectives in software engineering to the objectives of case study research in other areas.

The area of software engineering involves development, operation, and maintenance of software and related artifacts, e.g. (Jedlitschka and Pfahl 2005 ). Research on software engineering is to a large extent aimed at investigating how this development, operation, and maintenance are conducted by software engineers and other stakeholders under different conditions. Software development is carried out by individuals, groups and organizations, and social and political questions are of importance for this development. That is, software engineering is a multidisciplinary area involving areas where case studies normally are conducted. This means that many research questions in software engineering are suitable for case study research.

The definition of case study in Section 2.1 focuses on studying phenomena in their context, especially when the boundary between the phenomenon and its context is unclear. This is particularly true in software engineering. Experimentation in software engineering has clearly shown, e.g. when trying to replicate studies, that there are many factors impacting on the outcome of a software engineering activity (Shull et al. 2002 ). Case studies offer an approach which does not need a strict boundary between the studied object and its environment; perhaps the key to understanding is in the interaction between the two?

2.4 Case Study Research Process

When conducting a case study, there are five major process steps to be walked through:

Case study design: objectives are defined and the case study is planned.

Preparation for data collection: procedures and protocols for data collection are defined.

Collecting evidence: execution with data collection on the studied case.

Analysis of collected data

This process is almost the same for any kind of empirical study; compare e.g. to the processes proposed by Wohlin et al. ( 2000 ) and Kitchenham et al. ( 2002 ). However, as case study methodology is a flexible design strategy, there is a significant amount of iteration over the steps (Andersson and Runeson 2007b ). The data collection and analysis may be conducted incrementally. If insufficient data is collected for the analysis, more data collection may be planned etc. However, there is a limit to the flexibility; the case study should have specific objectives set out from the beginning. If the objectives change, it is a new case study rather than a change to the existing one, though this is a matter of judgment as all other classifications. Eisenhardt adds two steps between 4 and 5 above in her process for building theories from case study research (Eisenhardt 1989 ) a) shaping hypotheses and b) enfolding literature, while the rest except for terminological variations are the same as above.

2.5 Definitions

In this paper, we use the following terminology. The overall objective is a statement of what is expected to be achieved in the case study. Others may use goals, aims or purposes as synonyms or hyponyms for objective. The objective is refined into a set of research questions , which are to be answered through the case study analysis. A case may be based on a software engineering theory . It is beyond the scope of this article to discuss in detail what is meant by a theory. However, Sjøberg et al., describe a framework for theories including constructs of interest, relations between constructs, explanations to the relations, and scope of the theory (Sjøberg et al. 2008 ). With this way of describing theories, software engineering theories include at least one construct from software engineering. A research question may be related to a hypothesis (sometimes called a proposition (Yin 2003 )), i.e. a supposed explanation for an aspect of the phenomenon under study. Hypotheses may alternatively be generated from the case study for further research. The case is referred to as the object of the study (e.g. a project), and it contains one or more units of analysis (e.g. subprojects). Data is collected from the subjects of the study, i.e. those providing the information. Data may be quantitative (numbers, measurements) or qualitative (words, descriptions). A case study protocol defines the detailed procedures for collection and analysis of the raw data, sometimes called field procedures .

The guidelines for conducting case studies presented below are organized according to this process. Section 3 is about setting up goals for the case study and preparing for data collection, Section 4 discusses collection of data, Section 5 discusses data analysis and Section 6 provides some guidelines for reporting.

3 Case Study Design and Planning

3.1 defining a case.

Case study research is of flexible type, as mentioned before. This does not mean planning is unnecessary. On the contrary, good planning for a case study is crucial for its success. There are several issues that need to be planned, such as what methods to use for data collection, what departments of an organization to visit, what documents to read, which persons to interview, how often interviews should be conducted, etc. These plans can be formulated in a case study protocol, see Section 3.2 .

A plan for a case study should at least contain the following elements (Robson 2002 ):

Objective—what to achieve?

The case—what is studied?

Theory—frame of reference

Research questions—what to know?

Methods—how to collect data?

Selection strategy—where to seek data?

The objective of the study may be, for example, exploratory, descriptive, explanatory, or improving. The objective is naturally more generally formulated and less precise than in fixed research designs. The objective is initially more like a focus point which evolves during the study. The research questions state what is needed to know in order to fulfill the objective of the study. Similar to the objective, the research questions evolve during the study and are narrowed to specific research questions during the study iterations (Andersson and Runeson 2007b ).

The case may in general be virtually anything which is a “contemporary phenomenon in its real-life context” (Yin 2003 ). In software engineering, the case may be a software development project, which is the most straightforward choice. It may alternatively be an individual, a group of people, a process, a product, a policy, a role in the organization, an event, a technology, etc. The project, individual, group etc. may also constitute a unit of analysis within a case. In the information systems field, the case may be “individuals, groups…or an entire organization. Alternatively, the unit of analysis may be a specific project or decision”(Benbasat et al. 1987 ). Studies on “toy programs” or similarly are of course excluded due to its lack of real-life context. Yin ( 2003 ) distinguishes between holistic case studies , where the case is studied as a whole, and embedded case studies where multiple units of analysis are studied within a case, see Fig.  1 . Whether to define a study consisting of two cases as holistic or embedded depends on what we define as the context and research goals. In our XP example, two projects are studied in two different companies in two different application domains, both using agile practices (Karlström and Runeson 2006 ). The projects may be considered two units of analysis in an embedded case study if the context is software companies in general and the research goal is to study agile practices. On the contrary, if the context is considered being the specific company or application domain, they have to be seen as two separate holistic cases. Benbasat et al. comment on a specific case study, “Even though this study appeared to be a single-case, embedded unit analysis, it could be considered a multiple-case design, due to the centralized nature of the sites.” (Benbasat et al. 1987 ).

Holistic case study ( left ) and embedded case study ( right )

Using theories to develop the research direction is not well established in the software engineering field, as concluded in a systematic review on the topic (Hannay et al. 2007 ; Shull and Feldman 2008 ). However, defining the frame of reference of the study makes the context of the case study research clear, and helps both those conducting the research and those reviewing the results of it. As theories are underdeveloped in software engineering, the frame of reference may alternatively be expressed in terms of the viewpoint taken in the research and the background of the researchers. Grounded theory case studies naturally have no specified theory (Corbin and Strauss 2008 ).

The principal decisions on methods for data collection are defined at design time for the case study, although detailed decisions on data collection procedures are taken later. Lethbridge et al. ( 2005 ) define three categories of methods: direct (e.g. interviews), indirect (e.g. tool instrumentation) and independent (e.g. documentation analysis). These are further elaborated in Section 4 .

In case studies, the case and the units of analysis should be selected intentionally. This is in contrast to surveys and experiments, where subjects are sampled from a population to which the results are intended to be generalized. The purpose of the selection may be to study a case that is expected to be “typical”, “critical”, “revelatory” or “unique” in some respect (Benbasat et al. 1987 ), and the case is selected accordingly. Flyvbjerg defines four variants of information-oriented case study selections: “extreme/deviant”, “maximum variation”, “critical” and “paradigmatic” (Flyvbjerg 2007 ). In a comparative case study, the units of analysis must be selected to have the variation in properties that the study intends to compare. However, in practice, many cases are selected based on availability (Benbasat et al. 1987 ) as is the case for many experiments (Sjøberg et al. 2005 ).

Case selection is particularly important when replicating case studies. A case study may be literally replicated , i.e. the case is selected to predict similar results, or it is theoretically replicated , i.e. the case is selected to predict contrasting results for predictable reasons (Yin 2003 ).

3.2 Case Study Protocol

The case study protocol is a container for the design decisions on the case study as well as field procedures for its carrying through. The protocol is a continuously changed document that is updated when the plans for the case study are changed.

There are several reasons for keeping an updated version of a case study protocol. Firstly, it serves as a guide when conducting the data collection, and in that way prevents the researcher from missing to collect data that were planned to be collected. Secondly, the processes of formulating the protocol makes the research concrete in the planning phase, which may help the researcher to decide what data sources to use and what questions to ask. Thirdly, other researchers and relevant people may review it in order to give feedback on the plans. Feedback on the protocol from other researchers can, for example, lower the risk of missing relevant data sources, interview questions or roles to include in the research and to assure the relation between research questions and interview questions. Finally, it can serve as a log or diary where all conducted data collection and analysis is recorded together with change decisions based on the flexible nature of the research. This can be an important source of information when the case study later on is reported. In order to keep track of changes during the research project, the protocol should be kept under some form of version control.

Pervan and Maimbo propose an outline of a case study protocol, which is summarized in Table  2 . As the proposal shows, the protocol is quite detailed to support a well structured research approach.

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3.3 Ethical Considerations

At design time of a case study, ethical considerations must be made (Singer and Vinson 2002 ). Even though a research study first and foremost is built on trust between the researcher and the case (Amschler Andrews and Pradhan 2001 ), explicit measures must be taken to prevent problems. In software engineering, case studies often include dealing with confidential information in an organization. If it is not clear from the beginning how this kind of information is handled and who is responsible for accepting what information to publish, there may be problems later on. Key ethical factors include:

Informed consent

Review board approval

Confidentiality

Handling of sensitive results

Inducements

Subjects and organizations must explicitly agree to participate in the case study, i.e. give informed consent. In some countries, this is even legally required. It may be tempting for the researcher to collect data e.g. through indirect or independent data collection methods, without asking for consent. However, the ethical standards must be maintained for the long term trust in software engineering research.

Legislation of research ethics differs between countries and continents. In many countries it is mandatory to have the study proposal reviewed and accepted with respect to ethical issues (Seaman 1999 ) by a review board or a similar function at a university. In other countries, there are no such rules. Even if there are no such rules, it is recommended that the case study protocol is reviewed by colleagues to help avoiding pitfalls.

Consent agreements are preferably handled through a form or contract between the researchers and the individual participant, see e.g. Robson ( 2002 ) for an example. In an empirical study conduced by the authors of this paper, the following information were included in this kind of form:

Names of researchers and contact information.

Purpose of empirical study.

Procedures used in the empirical study, i.e. a short description of what the participant should do during the study and what steps the researcher will carry out during these activities.

A text clearly stating that the participation is voluntary, and that collected data will be anonymous.

A list of known risks.

A list of benefits for the participants, in this case for example experience from using a new technique and feedback effectiveness.

A description of how confidentiality will be assured. This includes a description of how collected material will be coded and identified in the study.

Information about approvals from review board.

Date and signatures from participant and researchers.

If the researchers intend to use the data for other, not yet defined purposes, this should be signed separately to allow participants to choose if their contribution is for the current study only, or for possible future studies.

Issues on confidentiality and publication should also be regulated in a contract between the researcher and the studied organization. However, not only can information be sensitive when leaking outside a company. Data collected from and opinions stated by individual employees may be sensitive if presented e.g. to their managers (Singer and Vinson 2002 ). The researchers must have the right to keep their integrity and adhere to agreed procedures in this kind of cases. Companies may not know academic practices for publication and dissemination, and must hence be explicitly informed about those. From a publication point of view, the relevant data to publish is rarely sensitive to the company since data may be made anonymous. However, it is important to remember that it is not always sufficient to remove names of companies or individuals. They may be identified by their characteristics if they are selected from a small set of people or companies.

Results may be sensitive to a company, e.g. by revealing deficiencies in their software engineering practices, or if their product comes out last in a comparison (Amschler Andrews and Pradhan 2001 ). The chance that this may occur must be discussed upfront and made clear to the participants of the case study. In case violations of the law are identified during the case study, these must be reported, even though “whistle-blowers” rarely are rewarded.

The inducements for individuals and organizations to participate in a case study vary, but there are always some kinds of incentives, tangible or intangible. It is preferable to make the inducements explicit, i.e. specify what the incentives are for the participants. Thereby the inducement’s role in threatening the validity of the study may also be analyzed.

Giving feedback to the participants of a study is critical for the long term trust and for the validity of the research. Firstly, transcript of interviews and observations should be sent back to the participants to enable correction of raw data. Secondly, analyses should be presented to them in order to maintain their trust in the research. Participants must not necessarily agree in the outcome of the analysis, but feeding back the analysis results increases the validity of the study.

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3.4 Checklist

The checklist items for case study design are shown in Table  3 .

4 Collecting Data

4.1 different data sources.

There are several different sources of information that can be used in a case study. It is important to use several data sources in a case study in order to limit the effects of one interpretation of one single data source. If the same conclusion can be drawn from several sources of information, i.e. triangulation (Section 2.2 ), this conclusion is stronger than a conclusion based a single source. In a case study it is also important to take into account viewpoints of different roles, and to investigate differences, for example, between different projects and products. Commonly, conclusions are drawn by analyzing differences between data sources.

According to Lethbridge et al. ( 2005 ) data collection techniques can be divided into three levels:

First degree: Direct methods means that the researcher is in direct contact with the subjects and collect data in real time. This is the case with, for example interviews, focus groups, Delphi surveys (Dalkey and Helmer 1963 ), and observations with “think aloud protocols”.

Second degree: Indirect methods where the researcher directly collects raw data without actually interacting with the subjects during the data collection. This approach is, for example taken in Software Project Telemetry (Johnson et al. 2005 ) where the usage of software engineering tools is automatically monitored, and observed through video recording.

Third degree: Independent analysis of work artifacts where already available and sometimes compiled data is used. This is for example the case when documents such as requirements specifications and failure reports from an organization are analyzed or when data from organizational databases such as time accounting is analyzed.

First degree methods are mostly more expensive to apply than second or third degree methods, since they require significant effort both from the researcher and the subjects. An advantage of first and second degree methods is that the researcher can to a large extent exactly control what data is collected, how it is collected, in what form the data is collected, which the context is etc. Third degree methods are mostly less expensive, but they do not offer the same control to the researcher; hence the quality of the data is not under control either, neither regarding the original data quality nor its use for the case study purpose. In many cases the researcher must, to some extent, base the details of the data collection on what data is available. For third degree methods it should also be noticed that the data has been collected and recorded for another purpose than that of the research study, contrary to general metrics guidelines (van Solingen and Berghout 1999 ). It is not certain that requirements on data validity and completeness were the same when the data was collected as they are in the research study.

In Sections 4.2 – 4.5 we discuss specific data collection methods, where we have found interviews, observations, archival data and metrics being applicable to software engineering case studies (Benbasat et al. 1987 ; Yin 2003 ).

4.2 Interviews

Data collection through interviews is important in case studies. In interview-based data collection, the researcher asks a series of questions to a set of subjects about the areas of interest in the case study. In most cases one interview is conducted with every single subject, but it is possible to conduct group-interviews. The dialogue between the researcher and the subject(s) is guided by a set of interview questions.

The interview questions are based on the topic of interest in the case study. That is, the interview questions are based on the formulated research questions (but they are of course not formulated in the same way). Questions can be open , i.e. allowing and inviting a broad range of answers and issues from the interviewed subject, or closed offering a limited set of alternative answers.

Interviews can, for example, be divided into unstructured , semi-structured and fully structured interviews (Robson 2002 ). In an unstructured interview, the interview questions are formulated as general concerns and interests from the researcher. In this case the interview conversation will develop based on the interest of the subject and the researcher. In a fully structured interview all questions are planned in advance and all questions are asked in the same order as in the plan. In many ways, a fully structured interview is similar to a questionnaire-based survey. In a semi-structured interview, questions are planned, but they are not necessarily asked in the same order as they are listed. The development of the conversation in the interview can decide which order the different questions are handled, and the researcher can use the list of questions to be certain that all questions are handled. Additionally, semi-structured interviews allow for improvisation and exploration of the studied objects. Semi-structured interviews are common in case studies. The different types of interviews are summarized in Table  4 .

An interview session may be divided into a number of phases. First the researcher presents the objectives of the interview and the case study, and explains how the data from the interview will be used. Then a set of introductory questions are asked about the background etc. of the subject, which are relatively simple to answer. After the introduction comes the main interview questions, which take up the largest part of the interview. If the interview contains personal and maybe sensitive questions, e.g. concerning economy, opinions about colleagues, why things went wrong, or questions related to the interviewees own competence (Hove and Anda 2005 ), special care must be taken. In this situation it is important that the interviewee is ensured confidentiality and that the interviewee trusts the interviewer. It is not recommended to start the interview with these questions or to introduce them before a climate of trust has been obtained. It is recommended that the major findings are summarized by the researcher towards the end of the interview, in order to get feedback and avoid misunderstandings.

Interview sessions can be structured according to three general principles, as outlined in Fig.  2 (Caroline Seaman, personal communication). The funnel model begins with open questions and moves towards more specific ones. The pyramid model begins with specific ones, and opens the questions during the course of the interview. The time-glass model begins with open questions, straightens the structure in the middle and opens up again towards the end of the interview.

General principles for interview sessions. a funnel, b pyramid, and c time-glass

During the interview sessions it is recommended to record the discussion in a suitable audio or video format. Even if notes are taken, it is in many cases hard to record all details, and it is impossible to know what is important to record during the interview. Possibly a dedicated and trained scribe may capture sufficient detail in real-time, but the recording should at least be done as a backup (Hove and Anda 2005 ). When the interview has been recorded it needs to be transcribed into text before it is analyzed. This is a time consuming task, but in many cases new insights are made during the transcription, and it is therefore not recommended that this task is conducted by anyone else than the researcher. In some cases it may be advantageous to have the transcripts reviewed by the interview subject. In this way questions about what was actually said can be sorted out, and the interview subject has the chance to point out if she does not agree with the interpretation of what was said or if she simply has changed her mind and wants to rephrase any part of the answers.

During the planning phase of an interview study it is decided whom to interview. Due to the qualitative nature of the case study it is recommended to select subjects based on differences instead of trying to replicate similarities, as discussed in Section 3.1 . This means that it is good to try to involve different roles, personalities, etc in the interview. The number of interviewees has to be decided during the study. One criterion for when sufficient interviews are conducted is “saturation”, i.e. when no new information or viewpoint is gained from new subjects (Corbin and Strauss 2008 ).

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4.3 Observations

Observations can be conducted in order to investigate how a certain task is conducted by software engineers. This is a first or second degree method according to the classification in Section 4.1 . There are many different approaches for observation. One approach is to monitor a group of software engineers with a video recorder and later on analyze the recording, for example through protocol analysis (Owen et al. 2006 ; von Mayrhauser and Vans 1996 ). Another alternative is to apply a “think aloud” protocol, where the researcher are repeatedly asking questions like “What is your strategy?” and “What are you thinking?” to remind the subjects to think aloud. This can be combined with recording of audio and keystrokes as proposed e.g. by Wallace et al. ( 2002 ). Observations in meetings is another type, where meeting attendants interact with each other, and thus generate information about the studied object. An alternative approach is presented by Karahasanović et al. ( 2005 ) where a tool for sampling is used to obtain data and feedback from the participants.

Approaches for observations can be divided into high or low interaction of the researcher and high or low awareness of the subjects of being observed, see Table  5 .

Observations according to case 1 or case 2 are typically conducted in action research or classical ethnographic studies where the researcher is part of the team, and not only seen as a researcher by the other team members. The difference between case 1 and case 2 is that in case 1 the researcher is seen as an “observing participant” by the other subjects, while she is more seen as a “normal participant” in case 2. In case 3 the researcher is seen only as a researcher. The approaches for observation typically include observations with first degree data collection techniques, such as a “think aloud” protocol as described above. In case 4 the subjects are typically observed with a second degree technique such as video recording (sometimes called video ethnography).

An advantage of observations is that they may provide a deep understanding of the phenomenon that is studied. Further, it is particularly relevant to use observations, where it is suspected that there is a deviation between an “official” view of matters and the “real” case (Robinson et al. 2007 ). It should however be noted that it produces a substantial amount of data which makes the analysis time consuming.

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4.4 Archival Data

Archival data refers to, for example, meeting minutes, documents from different development phases, organizational charts, financial records, and previously collected measurements in an organization. Benbasat et al. ( 1987 ) and Yin ( 2003 ) distinguish between documentation and archival records, while we treat them together and see the borderline rather between qualitative data (minutes, documents, charts) and quantitative data (records, metrics), the latter discussed in Section 4.5 .

Archival data is a third degree type of data that can be collected in a case study. For this type of data a configuration management tool is an important source, since it enables the collection of a number of different documents and different versions of documents. As for other third degree data sources it is important to keep in mind that the documents were not originally developed with the intention to provide data to research in a case study. A document may, for example, include parts that are mandatory according to an organizational template but of lower interest for the project, which may affect the quality of that part. It should also be noted that it is possible that some information that is needed by the researcher may be missing, which means that archival data analysis must be combined with other data collection techniques, e.g. surveys, in order to obtain missing historical factual data (Flynn et al. 1990 ). It is of course hard for the researcher to assess the quality of the data, although some information can be obtained by investigating the purpose of the original data collection, and by interviewing relevant people in the organization.

4.5 Metrics

The above mentioned data collection techniques are mostly focused on qualitative data. However, quantitative data is also important in a case study. Software measurement is the process of representing software entities, like processes, products, and resources, in quantitative numbers (Fenton and Pfleeger 1996 ).

Collected data can either be defined and collected for the purpose of the case study, or already available data can be used in a case study. The first case gives, of course, most flexibility and the data that is most suitable for the research questions under investigation.

The definition of what data to collect should be based on a goal-oriented measurement technique, such as the Goal Question Metric method (GQM) (Basili and Weiss 1984 ; van Solingen and Berghout 1999 ). In GQM, goals are first formulated, and the questions are refined based on these goals, and after that metrics are derived based on the questions. This means that metrics are derived based on goals that are formulated for the measurement activity, and thus that relevant metrics are collected. It also implies that the researcher can control the quality of the collected data and that no unnecessary data is collected.

Examples of already available data are effort data from older projects, sales figures of products, metrics of product quality in terms of failures etc. This kind of data may, for example, be available in a metrics database in an organization. When this kind of data is used it should be noticed that all the problems are apparent that otherwise are solved with a goal oriented measurement approach. The researcher can neither control nor assess the quality of the data, since it was collected for another purpose, and as for other forms of archival analysis there is a risk of missing important data.

4.6 Checklists

The checklist items for preparation and conduct of data collection are shown in Tables  6 and 7 , respectively.

5 Data Analysis

5.1 quantitative data analysis.

Data analysis is conducted differently for quantitative and qualitative data. For quantitative data, the analysis typically includes analysis of descriptive statistics, correlation analysis, development of predictive models, and hypothesis testing. All of these activities are relevant in case study research.

Descriptive statistics, such as mean values, standard deviations, histograms and scatter plots, are used to get an understanding of the data that has been collected. Correlation analysis and development of predictive models are conducted in order to describe how a measurement from a later process activity is related to an earlier process measurement. Hypothesis testing is conducted in order to determine if there is a significant effect of one or several variables (independent variables) on one or several other variables (dependent variables).

It should be noticed that methods for quantitative analysis assume a fixed research design. For example, if a question with a quantitative answer is changed halfway in a series of interviews, this makes it impossible to interpret the mean value of the answers. Further, quantitative data sets from single cases tend to be very small, due to the number of respondents or measurement points, which causes special concerns in the analysis.

Quantitative analysis is not covered any further in this paper, since it is extensively covered in other texts. The rest of this chapter covers qualitative analysis. For more information about quantitative analysis, refer for example to (Wohlin et al. 2000 ; Wohlin and Höst 2001 ; Kitchenham et al. 2002 ).

5.2 Qualitative Data Analysis

Since case study research is a flexible research method, qualitative data analysis methods (Seaman 1999 ) are commonly used. The basic objective of the analysis is to derive conclusions from the data, keeping a clear chain of evidence. The chain of evidence means that a reader should be able to follow the derivation of results and conclusions from the collected data (Yin 2003 ). This means that sufficient information from each step of the study and every decision taken by the researcher must be presented.

In addition to the need to keep a clear chain of evidence in mind, analysis of qualitative research is characterized by having analysis carried out in parallel with the data collection and the need for systematic analysis techniques. Analysis must be carried out in parallel with the data collection since the approach is flexible and that new insights are found during the analysis. In order to investigate these insights, new data must often be collected, and instrumentation such as interview questionnaires must be updated. The need to be systematic is a direct result of that the data collection techniques can be constantly updated, while the same time being required to maintain a chain of evidence.

In order to reduce bias by individual researchers, the analysis benefits from being conducted by multiple researchers. The preliminary results from each individual researcher is merged into a common analysis result in a second step. Keeping track and reporting the cooperation scheme helps increasing the validity of the study.

5.2.1 General Techniques for Analysis

There are two different parts of data analysis of qualitative data, hypothesis generating techniques and hypothesis confirmation techniques (Seaman 1999 ), which can be used for exploratory and explanatory case studies, respectively.

Hypothesis generation is intended to find hypotheses from the data. When using these kinds of techniques, there should not be too many hypotheses defined before the analysis is conducted. Instead the researcher should try to be unbiased and open for whatever hypotheses are to be found in the data. The results of these techniques are the hypotheses as such. Examples of hypotheses generating techniques are “constant comparisons” and “cross-case analysis” (Seaman 1999 ). Hypothesis confirmation techniques denote techniques that can be used to confirm that a hypothesis is really true, e.g. through analysis of more data. Triangulation and replication are examples of approaches for hypothesis confirmation (Seaman 1999 ). Negative case analysis tries to find alternative explanations that reject the hypotheses. These basic types of techniques are used iteratively and in combination. First hypotheses are generated and then they are confirmed. Hypothesis generation may take place within one cycle of a case study, or with data from one unit of analysis, and hypothesis confirmation may be done with data from another cycle or unit of analysis (Andersson and Runeson 2007b ).

This means that analysis of qualitative data is conducted in a series of steps (based on (Robson 2002 ), p. 459). First the data is coded, which means that parts of the text can be given a code representing a certain theme, area, construct, etc. One code is usually assigned to many pieces of text, and one piece of text can be assigned more than one code. Codes can form a hierarchy of codes and sub-codes. The coded material can be combined with comments and reflections by the researcher (i.e. “memos”). When this has been done, the researcher can go through the material to identify a first set of hypotheses. This can, for example, be phrases that are similar in different parts of the material, patterns in the data, differences between sub-groups of subjects, etc. The identified hypotheses can then be used when further data collection is conducted in the field, i.e. resulting in an iterative approach where data collection and analysis is conducted in parallel as described above. During the iterative process a small set of generalizations can be formulated, eventually resulting in a formalized body of knowledge, which is the final result of the research attempt. This is, of course, not a simple sequence of steps. Instead, they are executed iteratively and they affect each other.

The activity where hypotheses are identified requires some more information. This is in no way a simple step that can be carried out by following a detailed, mechanical, approach. Instead it requires ability to generalize, innovative thinking, etc. from the researcher. This can be compared to quantitative analysis, where the majority of the innovative and analytical work of the researcher is in the planning phase (i.e. deciding design, statistical tests, etc). There is, of course, also a need for innovative work in the analysis of quantitative data, but it is not as clear as in the planning phase. In qualitative analysis there are major needs for innovative and analytical work in both phases.

One example of a useful technique for analysis is tabulation, where the coded data is arranged in tables, which makes it possible to get an overview of the data. The data can, for example be organized in a table where the rows represent codes of interest and the columns represent interview subjects. However, how to do this must be decided for every case study.

There are specialized software tools available to support qualitative data analysis, e.g. NVivo and Atlas. However, in some cases standard tools such as word processors and spreadsheet tools are useful when managing the textual data.

)

5.2.2 Level of Formalism

A structured approach is, as described above, important in qualitative analysis. This means, for example, in all cases that a pre-planned approach for analysis must be applied, all decisions taken by the researcher must be recorded, all versions of instrumentation must be kept, links between data, codes, and memos must be explicitly recorded in documentation, etc. However, the analysis can be conducted at different levels of formalism. In (Robson 2002 ) the following approaches are mentioned:

Immersion approaches: These are the least structured approaches, with very low level of structure, more reliant on intuition and interpretive skills of the researcher. These approaches may be hard to combine with requirements on keeping and communicating a chain of evidence.

Editing approaches: These approaches include few a priori codes, i.e. codes are defined based on findings of the researcher during the analysis.

Template approaches: These approaches are more formal and include more a priori based on research questions.

Quasi-statistical approaches: These approaches are much formalized and include, for example, calculation of frequencies of words and phrases.

To our experience editing approaches and template approaches are most suitable in software engineering case studies. It is hard to present and obtain a clear chain of evidence in informal immersion approaches. It is also hard to interpret the result of, for example, frequencies of words in documents and interviews.

Section

5.2.3 Validity

The validity of a study denotes the trustworthiness of the results, to what extent the results are true and not biased by the researchers’ subjective point of view. It is, of course, too late to consider the validity during the analysis. The validity must be addressed during all previous phases of the case study. However, the validity is discussed in this section, since it cannot be finally evaluated until the analysis phase.

There are different ways to classify aspects of validity and threats to validity in the literature. Here we chose a classification scheme which is also used by Yin ( 2003 ) and similar to what is usually used in controlled experiments in software engineering (Wohlin et al. 2000 ). Some researchers have argued for having a different classification scheme for flexible design studies (credibility, transferability, dependability, confirmability), while we prefer to operationalize this scheme for flexible design studies, instead of changing the terms (Robson 2002 ). This scheme distinguishes between four aspects of the validity, which can be summarized as follows:

Construct validity: This aspect of validity reflect to what extent the operational measures that are studied really represent what the researcher have in mind and what is investigated according to the research questions. If, for example, the constructs discussed in the interview questions are not interpreted in the same way by the researcher and the interviewed persons, there is a threat to the construct validity.

Internal validity: This aspect of validity is of concern when causal relations are examined. When the researcher is investigating whether one factor affects an investigated factor there is a risk that the investigated factor is also affected by a third factor. If the researcher is not aware of the third factor and/or does not know to what extent it affects the investigated factor, there is a threat to the internal validity.

External validity: This aspect of validity is concerned with to what extent it is possible to generalize the findings, and to what extent the findings are of interest to other people outside the investigated case. During analysis of external validity, the researcher tries to analyze to what extent the findings are of relevance for other cases. There is no population from which a statistically representative sample has been drawn. However, for case studies, the intention is to enable analytical generalization where the results are extended to cases which have common characteristics and hence for which the findings are relevant, i.e. defining a theory.

Reliability: This aspect is concerned with to what extent the data and the analysis are dependent on the specific researchers. Hypothetically, if another researcher later on conducted the same study, the result should be the same. Threats to this aspect of validity is, for example, if it is not clear how to code collected data or if questionnaires or interview questions are unclear.

It is, as described above, important to consider the validity of the case study from the beginning. Examples of ways to improve validity are triangulation, developing and maintaining a detailed case study protocol, having designs, protocols, etc. reviewed by peer researchers, having collected data and obtained results reviewed by case subjects, spending sufficient time with the case, and giving sufficient concern to analysis of “negative cases”, i.e. looking for theories that contradict your findings.

( ).

5.3 Checklist

The checklist items for analysis of collected data are shown in Table  8 .

6 Reporting

An empirical study cannot be distinguished from its reporting. The report communicates the findings of the study, but is also the main source of information for judging the quality of the study. Reports may have different audiences, such as peer researchers, policy makers, research sponsors, and industry practitioners (Yin 2003 ). This may lead to the need of writing different reports for difference audiences. Here, we focus on reports with peer researchers as main audience, i.e. journal or conference articles and possibly accompanying technical reports. Benbasat et al. propose that due to the extensive amount of data generated in case studies, “books or monographs might be better vehicles to publish case study research” (Benbasat et al. 1987 ).

Guidelines for reporting experiments have been proposed by Jedlitschka and Pfahl ( 2005 ) and evaluated by Kitchenham et al. ( 2008 ). Their work aims at defining a standardized reporting of experiments that enables cross-study comparisons through e.g. systematic reviews. For case studies, the same high-level structure may be used, but since they are more flexible and mostly based on qualitative data, the low-level detail is less standardized and more depending on the individual case. Below, we first discuss the characteristics of a case study report and then a proposed structure.

6.1 Characteristics

Robson defines a set of characteristics which a case study report should have (Robson 2002 ), which in summary implies that it should:

tell what the study was about

communicate a clear sense of the studied case

provide a “history of the inquiry” so the reader can see what was done, by whom and how.

provide basic data in focused form, so the reader can make sure that the conclusions are reasonable

articulate the researcher’s conclusions and set them into a context they affect.

In addition, this must take place under the balance between researcher’s duty and goal to publish their results, and the companies’ and individuals’ integrity (Amschler Andrews and Pradhan 2001 ).

Reporting the case study objectives and research questions is quite straightforward. If they are changed substantially over the course of the study, this should be reported to help understanding the case.

Describing the case might be more sensitive, since this might enable identification of the case or its subjects. For example, “a large telecommunications company in Sweden” is most probably a branch of the Ericsson Corporation. However, the case may be better characterized by other means than application domain and country. Internal characteristics, like size of the studied unit, average age of the personnel, etc may be more interesting than external characteristics like domain and turnover. Either the case constitutes a small subunit of a large corporation, and then it can hardly be identified among the many subunits, or it is a small company and hence it is hard to identify it among many candidates. Still, care must be taken to find this balance.

Providing a “history of the inquiry” requires a level of substantially more detail than pure reporting of used methodologies, e.g. “we launched a case study using semi-structured interviews”. Since the validity of the study is highly related to what is done, by whom and how, it must be reported about the sequence of actions and roles acting in the study process. On the other hand, there is no room for every single detail of the case study conduct, and hence a balance must be found.

Data is collected in abundance in a qualitative study, and the analysis has as its main focus to reduce and organize data to provide a chain of evidence for the conclusions. However, to establish trust in the study, the reader needs relevant snapshots from the data that support the conclusions. These snapshots may be in the form of e.g. citations (typical or special statements), pictures, or narratives with anonymized subjects. Further, categories used in the data classification, leading to certain conclusions may help the reader follow the chain of evidence.

Finally, the conclusions must be reported and set into a context of implications, e.g. by forming theories. A case study can not be generalized in the meaning of being representative of a population, but this is not the only way of achieving and transferring knowledge. Conclusions can be drawn without statistics, and they may be interpreted and related to other cases. Communicating research results in terms of theories is an underdeveloped practice in software engineering (Hannay et al. 2007 ).

6.2 Structure

Yin proposes several alternative structures for reporting case studies in general (Yin 2003 ).

Linear-analytic—the standard research report structure (problem, related work, methods, analysis, conclusions)

Comparative—the same case is repeated twice or more to compare alternative descriptions, explanations or points of view.

Chronological—a structure most suitable for longitudinal studies.

Theory-building—presents the case according to some theory-building logic in order to constitute a chain of evidence for a theory.

Suspense—reverts the linear-analytic structure and reports conclusions first and then backs them up with evidence.

Unsequenced—with none of the above, e.g. when reporting general characteristics of a set of cases.

For the academic reporting of case studies which we focus on, the linear-analytic structure is the most accepted structure. The high level structure for reporting experiments in software engineering proposed by Jedlitschka and Pfahl ( 2005 ) therefore also fits the purpose of case study reporting. However, some changes are needed, based on specific characteristics of case studies and other issues based on an evaluation conducted by Kitchenham et al. ( 2008 ). The resulting structure is presented in Table  9 . The differences and our considerations are presented below.

In a case study, the theory may constitute a framework for the analysis; hence, there are two kinds of related work: a) earlier studies on the topic and b) theories on which the current study is based.

The design section corresponds to the case study protocol, i.e. it reports the planning of the case study including the measures taken to ensure the validity of the study.

Since the case study is of flexible design, and data collection and analysis are more intertwined, these sections may be combined into one. Consequently, the contents at the lower level must be adjusted, as proposed in Table  9 . Specifically for the combined data section, the coding scheme often constitutes a natural subsection structure. Alternatively, for a comparative case study, the data section may be structured according to the compared cases, and for a longitudinal study, the time scale may constitute the structure of the data section. This combined results section also includes an evaluation of the validity of the final results.

) ) ).

6.3 Checklist

The checklist items for reporting are shown in Table  10 .

7 Reading and Reviewing Case Study Research

7.1 reader’s perspective.

The reader of a case study report—independently of whether the intention is to use the findings or to review it for inclusion in a journal—must judge the quality of the study based on the written material. Case study reports tend to be large, firstly since case studies often are based on qualitative data, and hence the data cannot be presented in condensed form, like quantitative data may be in tables, diagrams and statistics. Secondly, the conclusions in qualitative analyses are not based on statistical significance which can be interpreted in terms of a probability for erroneous conclusion, but on reasoning and linking of observations to conclusions.

Reviewing empirical research in general must be done with certain care (Tichy 2000 ). Reading case study reports requires judging the quality of the report, without having the power of strict criteria which govern experimental studies to a larger extent, e.g. statistical confidence levels. This does however not say that any report can do as a case study report. The reader must have a decent chance of finding the information of relevance, both to judge the quality of the case study and to get the findings from the study and set them into practice or build further research on.

The criteria and guidance presented above for performing and reporting case studies are relevant for the reader as well. However, in our work with derivation of checklists for case study research (Höst and Runeson 2007 ), evaluation feedback identified a need for a more condensed checklist for readers and reviewers. This is presented in Table  11 with numbers referring to the items of the other checklists for more in depth criteria.

Case study research is conducted in order to investigate contemporary phenomena in their natural context. That is, no laboratory environment is set up by the researcher, where factors can be controlled. Instead the phenomena are studied in their normal context, allowing the researcher to understand how the phenomena interact with the context. Selection of subjects and objects is not based on statistically representative samples. Instead, research findings are obtained through the analysis in depth of typical or special cases.

Cases study research is conducted by iteration over a set of phases. In the design phase objectives are decided and the case is defined. Data collection is first planned with respect to data collection techniques and data sources, and then conducted in practice. Methods for data collection include, for example, interviews, observation, and usage of archival data. During the analysis phase, insights are both generated and analyzed, e.g. through coding of data and looking for patterns. During the analysis it is important to maintain a chain of evidence from the findings to the original data. The report should include sufficient data and examples to allow the reader to understand the chain of evidence.

This paper aims to provide a frame of reference for researchers when conducting case study research in software engineering, which is based on an analysis of existing case study literature and the author’s own experiences of conducting case studies. As with other guidelines, there is a need to evaluate them through practical usage.

Easterbrook et al. distinguish between exploratory and confirmatory case studies. We interpret Robson’s explanatory category being closely related to Easterbrook’s confirmatory category.

Robson denotes this category “emancipatory” in the social science context, while improvement is our adaptation to an engineering context.

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Acknowledgement

The authors are grateful to the feedback to the checklists from the ISERN members and IASESE attendants in September 2007. A special thank to Professor Claes Wohlin, Mr. Kim Weyns and Mr. Andreas Jedlitschka for their review of an earlier draft of the paper. Thanks also to the anonymous reviewers for proposals on substantial improvements. The work is partly funded by the Swedish Research Council under grant 622-2004-552 for a senior researcher position in software engineering.

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Runeson, P., Höst, M. Guidelines for conducting and reporting case study research in software engineering. Empir Software Eng 14 , 131–164 (2009). https://doi.org/10.1007/s10664-008-9102-8

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• Effectiveness of self-management programmes for heart failure with reduced ejection fraction: a systematic review protocol
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• http://orcid.org/0000-0003-3169-3762 Pupalan Iyngkaran 1 , 2 ,
• Monika Buhler 3 ,
• http://orcid.org/0000-0001-9997-9359 Maximilian de Courten 4 ,
• http://orcid.org/0000-0002-0494-9585 Fahad Hanna 2
• 1 NT Medical School , The University of Notre Dame Australia Melbourne Clinical School , Werribee , Victoria , Australia
• 2 Health and Education , Torrens University Australia , Melbourne , Victoria , Australia
• 3 Cardiology , Heart West , Melbourne , Victoria , Australia
• 4 Mitchell Institute , Victoria University , Melbourne , Victoria , Australia
• Correspondence to Professor Fahad Hanna; fahad.hanna{at}torrens.edu.au

Introduction Chronic disease self-management (CDSM) is a vital component of congestive heart failure (CHF) programmes. Recent CHF guidelines have downgraded CDSM programmes citing a lack of gold-standard evidence. This protocol describes the aims and methods of a systematic review to collate and synthesise the published research evidence to determine the effectiveness of CDSM programmes and interventions for patients treated for CHF.

Methods Medline, PubMed, Embase, CENTRAL, CINAHL, Cochrane Central Register of Controlled Trials, PsycINFO, SCOPUS, Web of Science, the Science Citation Index and registers of clinical trials will be searched from 1966 to 2024. In addition, the reference lists of shortlisted articles will be reviewed. Randomised controlled trials, with case management interventions of CDSM and CHF with reported major adverse cardiovascular events (MACEs), will be extracted and analysed. There is no restriction on language. Study protocol template developed from Cochrane Collaboration and Reporting adheres to Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol guidelines for systematic review and meta-analyses 2020. Two independent authors will apply inclusions and exclusion criteria to limit article search and assess bias and certainty of evidence rating. Data extraction and study description of included studies will include quality appraisal of studies and quantitative synthesis of data will then be undertaken to ascertain evidence for the study aims. Subgroup analyses will be conducted for different CDSM programmes. The primary outcome will be a significant change in MACE parameters between intervention and control arms. Meta-analysis will be conducted using statistical software, if feasible.

Ethics and dissemination Ethics approval is not sought as the study is not collecting primary patient data. The results of this study will be disseminated through peer-reviewed scientific journals and also presented to audiences through meetings and scientific conferences.

PROSPERO registration number CRD42023431539.

• clinical trials
• systematic review
• heart failure
• self-management

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjopen-2023-079830

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STRENGTHS AND LIMITATIONS OF THIS STUDY

Extracts data on the effectiveness of major cardiovascular events from studies across several decades.

Only data from high-quality randomised controlled trials are extracted.

Impactful qualitative and observational studies are not included in the synthesis of evidence.

Publication bias, studies with positive or statistically significant results are more likely to be published than those with negative or non-significant findings.

Chronic disease self-management (CDSM) programmes are initiated with multiple goals. Among these are achieving four goals (performance mastery, modelling, interpretation of symptoms and social persuasion), three tasks (medical management, role management and emotional management) and five skills (problem-solving, decision-making, resource utilisation, forming a patient/healthcare provider partnership and taking action). When patients achieve higher grades of these skills (described as self-efficacy or self-tailoring) they can better use medical resources to stabilise their medical conditions, prevent hospital readmissions or new admissions, and reduce the burden on health system from higher level health seeking. 1 CDSM programmes are established for many chronic diseases, however, when the lens is turned toward congestive heart failure (CHF), the early momentum of evidence supporting improved self-efficacy, 2–4 and reducing readmissions 5 is not sustained particularly when accounting for major adverse cardiovascular events (MACEs). 6 Thus, th momentum this decade, began with a downgrade for CDSM from a key disease-specific performance measure to a quality measure in CHF, from this lacking of MACE evidence. 6–9

The importance of this, with perspective, to the disease burden and cost for CHF management that are escalating, is noteworthy. Globally the prevalence exceeds 30 million persons. There remains a gradient for delivering guideline care domain from developed to developing nations and within all nations. Hospitalisations and preventable readmissions remain a leading health economic burden with 20%–50% of patients seeking readmission at 1, 3 and 6 months. 10 These figures relate to HF with reduced ejection fraction (HFrEF). The focus of this paper does not include HF with preserved ejection fraction (HFpEF), that accounts for the other 50% of CHF patients, due to different pathophysiology and treatment strategies. 10 11

Chronic disease and CHF management programmes, share similar care domains, an aspect being CDSM. It is imperative that CDSM provides a valued contribution to CHF programmes. From a health services perspective the aims of CDSM programmes would primarily be to contain economic resource utilisation and healthcare costs. 12–18 Patient health-seeking interactions, wholistically, are binary and are contained to community health networks or via acute services (ambulance, emergency, hospital admission). When these cases transition back to ambulatory care new information and healthcare team members require integration into existing care plans. These and other chronic and subacute patients that spill over to acute pathways are potentially preventable using CDSM programmes to achieve self-efficacy in patients. It is imperative that CDSM provides a valued contribution to CHF programmes. On these facts, this systematic review (SR) on CDSM in CHF identifies two important gaps:

What is the effectiveness of CDSM in CHF in reducing MACE, primarily, as measured by established performance measures?

What is the magnitude of the effectiveness of CDSM in CHF, secondarily, in improving MACE?

The study goal, for this SR, to address the above gaps, will be to pool the published evidence for studies that used CDSM tools and programmes, in the management of participants with CHF which reported quantitative MACE evidence. In this context, the studies will provide assessments of the efficacy of CDSM for improving MACE in CHF. Second report trends for the positive and negative determinants for attaining self-efficacy and objective improvements in CHF outcome will be recorded. This study aims, primarily, to determine the current status among CHF patients of the efficacy of CDSM programmes compared with routine care in improving MACE (and quality-adjusted life-years (QALY)). Secondarily, to quantify the size of the effect wherever possible among CHF patients prescribed CDSM programmes.

This study has been registered under the International Prospective Register of Systematic Reviews (PROSPERO) under the registration number: CRD42023431539. This systemic review protocol was performed based on the standards derived from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement. 19 The process undertaken for the protocol will involve defining (1) eligibility criteria, (2) search strategy, (3) data extraction, (4) risk of bias assessment and (5) data analysis.

Review question: What is the current grade of evidence 20 for self-management in CHF and its impact on improving MACE?

Eligibility criteria

Types of studies.

The study will include randomised controlled trials (RCTs) that have studied and reported MACE outcomes on CDSM programmes in patients with HFrEF. To reduce the effect of bias in interpreting reported outcomes, we will limit observational trials. 21 Studies found in the search databases will be accepted without restrictions on language and publication date. Study protocols will be limited to search, description of programmes and description of data analysis with respect to relevant outcomes.

Types of participants

We will include adult participants (18 years and above), diagnosed with systolic HF or HFrEF, with ejection fraction <45% (grade 2 or higher), who have been enrolled in a study exploring CDSM programmes in those patients with documented HFrEF during one or more visits within a 12-month period of diagnosis or referred during an admission with acute decompensated HF. CHF classification, decompensation and terminology are referenced in section 2 American Heart Association and American College of Cardiology (ACC/AHA) HF guidelines. 10 We will enrol all aetiologies of CHF including, ischaemic, viral, idiopathic, drugs and alcohol, metabolic and others. Decompensation is defined as worsening symptoms and signs of CHF. 10 11 Population excluded—HFpEF and HFrEF diagnosed with left ventricular ejection fraction >50% (or grade 1) are excluded. Also excluded are trials that do not provide detailed description of the CDSM programme used in the CHF patients. No other groups or demographics, for for example, age, gender or ethnicity, will be excluded.

Types of interventions

Studies that use a CDSM programme, delivered through standardised disease management pathway, 22 that primarily aim to improve outcomes including MACE will be included. Terminology of interventions include disease management—an established pathway to organise and deliver care 23 ; gold standard—accepted as published within consensus guidelines and often with class 1a evidence 10 11 ; health provider—person delivering CDSM intervention are either medical staff (primary care or specialists) or allied health pharmacists, nurse, physiotherapist, occupational therapists; case manager—primary person involved in communicating with client and other relevant health services staff, who may or may not be primary intervention provider; monitoring—ongoing periodic assessment after initial intervention for at least 8–12 weeks. Within each trial, during the period of care, management changes may occur. These changes may be routine or usual care, and when documented will be recorded as a comparison to the study intervention. If there is ambiguity our team will contact the trial authors to clarify areas of ambiguity, however, it is acknowledged the length of time from these studies may make this difficult.

Experimental interventions

The gold-standard comparators for CDSM and CHF are standardised quality measures for CHF 6 and European Heart Association and ACC/AHA HF guidelines. 10 11 We acknowledge use of the Flinders Programme of Chronic Condition Self-management (CFPI) 12 18 and validated tools (SCHFI V.6.2, SCHFI V.7.2 and EHFScBS V.9). 9 19 The core principles of the CFPI are disease management, self-management, care coordination and coaching. Self-management domains include self-monitoring, self-maintenance and self-tailoring. Within each programme, additional disease-specific domains, for for example, CHF (which is largely guideline standardised), 10 11 comorbidities such as diabetes mellitus (DM), chronic renal impairment, hypertension and others may be included. Patients will be enrolled into these programmes and trials are randomised to the placebo arm or equivalent, which will be described. Trial programmes disease management will be standardised against domains described in Krumholtz et al 24 ; these will be of varying: ‘intensity’—the frequency of interval visits; ‘duration’—the time between the first and last session; ‘delivery’—the method of communication and personnel used; ‘location’—the site clients and staff are receiving and delivering the programmes; ‘cost’—the funding and cost of delivering the programmes; ‘transition, follow-up and discharge’—the support structure provided after programme ends for continued behavioural conditioning, readmission prevention and programme related supports and refreshers.

Comparator interventions

The study will compare baseline CDSM programme intervention in conjunction with CHF programs 10 11 vs only generic CHF programmes as routine baseline care. The intervention arm can be controlled or quasi- experimental (multiarm design) or non-controlled. No exclusion is made to disease management domains 23 in location (home versus (centre based, eg, primary health, cardiology clinic or hospital, method delivery (in person, technology, written, audio, etc), duration or intensity. These will, however, be graded and described.

Objectives, scientific hypotheses

CHF disease management programmes are comprehensive and revolve around published guidelines. 10 11 16 24 Process of care measures 23 (or key performance measures) used in an organised fashion factoring the relevant standardised disease management domains 23 24 have successfully translated CHF trial level outcomes, for hospitalised and hospital-based outpatient patients, to the general population attending these services. However, it is of interest that studies evaluating CDSM programmes 4 9 12 in CHF, have yet to provide gold-standard evidence. 6 Does this imply CDSM programmes do not work in CHF while they have been robust in other chronic disease such as asthma, DM and hypertension?. 1 12 Thus, based on the current ACC guidelines for CDSM in CHF 6 10 11 and other chronic diseases, we hypothesise:

Pooled data on the effectiveness as evidenced in MACE (and QALY) improvement will help inform the foundations for future studies.

Meta-analysis of quantitative data will point to strength of a CDSM intervention and this could help design definitive RCT’s in this area.

Types of outcome measures

Primary outcomes.

We anticipate this study to deliver several findings. First, the primary outcomes will conclude on the level and quality of quantitative evidence for CDSM in CHF in reducing MACE. Overall, any shortfalls extracted in deriving the conclusion will be sufficient information to inform a trial to test CDSM programmes in CHF, that could inform CHF guidelines.

Secondary outcomes

We anticipate this study will provide, data on health economics and quality of life. In addition, it may also provide an idea of trends in barriers and facilitators for CDSM in CHF. This may help steer a focused pooled study on this topic, in the future.

Search strategy

Study characteristics.

RCTs will be sought after in this systematic search. Nevertheless, we opted to exclude observational studies in order to mitigate bias and ensure the robustness of the evidence ( table 1 and Research Checklist PRISMA 2020 checklist).

• View inline

Screening protocol

Electronic search

Comprehensive search will be conducted, between July and August 2024, in Medline via EBSCOhost (1950–2024), the Cochrane Central Register of Controlled Trials (2024), Embase (1980–2024), CINAHL (1982–2024), PsycINFO (1887–2024), Science Citation Index (1987–2024) and Registers for clinical trials. Searches will be designed and conducted by PI and assisted by librarians. Experts in the area will also be contacted to provide feedback on gaps in the literature review. The following MeSH terms will be used to shortlist studies: “self-management”, or self management” or “self-care” or “self care” or “chronic disease self-management” or chronic disease self-management”; and “heart failure” or “cardiac failure” or “congestive heart failure” or congestive cardiac failure” or “chronic heart failure” or “chronic cardiac failure” or “cardiomyopathy” or heart failure with reduced ejection fraction (HFrEF) or systolic heart failure (SHF); AND [“effectiveness” or “efficacy” or “MACE” or “major adverse cardiovascular events” or “readmission” or “death”]. In addition, a ‘snowball’ search of relevant selected reviews, previously published reviews and reference lists of shortlisted studies on the to extract additional relevant studies. The search is not limited to language or publication date ( table 2 ).

Proposed search terms developed on MEDLINE

Searching other resources and information sources

It will be conducted as the study evolves and as required. All new changes will be documented as an amendment to the protocol.

Data collection and analysis

Study selection.

An initial assessment of title and abstract for eligibility will be performed independently by (PI and MB). Further evaluation in full text of potentially eligible studies will be selected unblinded according to a standardised procedure by (PI and MB) for definite eligibility. Disagreements during the full text-based study selection process will be discussed and resolved by consensus. A third reviewer (FH) will review all steps, details and resolve disagreement, discrepancies or uncertainties and act as arbiter. Study protocol authors will be contacted to provide further details on results or studies will be excluded from the main analysis. More information about the process of selection of studies is given in ( table 3 ).

Data extraction format

Data extraction and management (data collection)

Each study will undergo data extraction by two investigators independently. Phase 1 will involve a pilot and targeted extraction (approximately five studies) using a standardised protocol and case/study report form or instrument/tool ( table 3 ). 6 The areas of interest are study quality, trial characteristics, patient data and outcomes. PI and MB will extract data from each study independently. Phase 2 will involve the refinement of the instrument. Data will be extracted from reports of studies according to the following algorithm ‘((1) review of the study protocol, (2) review of the major publication ie, published in a ‘high-impact’ journal, report of major outcome, (3) review of all other publications with quantitative data and (4) contact to authors in the case of inconsistencies within reports). All data of a single study will be displayed comprehensively in the review even if reported in different publications’ ( table 2 ).

To tabulate findings from included articles, a data extraction template will be designed ( table 3 ), factoring CHF specific measures, 6 to include the following domains: (1) study source information (first author, year of publication and country); (2) characteristics of the study population (age, sex, race, comorbid conditions, CHF severity, stage, aetiology, etc), study enrolment criteria (sample size and mean age), details of interventions (content, number, length, frequency of session, format, delivery mode, setting, duration, follow-up and attrition rate), outcomes, measures and findings; (3) Nature of intervention (programme domains, case assessment, delivery, monitoring, reassessment and outcomes) and usual care and (4) types of primary and secondary quantitative outcomes chosen include MACE, clinical parameters, surrogate biomarkers, health resource utilisation, length of follow-up and QALY.

Assessment of risk of bias in included studies (quality assessment and certainty of evidence)

In order to assess the validity and quality of included studies, two reviewers will appraise each study and rate risk of bias according to predefined standards using the revised Cochrane Collaboration’s tool in RCT (RoB 2.0) for assessing risk of bias. 25 While this tool has been validated, a detailed checklist is needed to use it appropriately. 25 Using the risk of bias tool adopted by the EPOC Group, 26 we adapted a previously published checklist which we would like to publish a priori as recently suggested. 27 28 The certainty of the evidence for selected outcomes was rated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Five aspects (risk of bias, inconsistency, indirectness, imprecision and publication bias) of the GRADE will classify the evidence into four grades (very low, low, moderate and high). The GRADE profiler Guideline Development Tool (GRADEpro GDT) will be used to summarise findings.

Data analysis, assessment of heterogeneity and publication bias

Planned methods for studies analysis and statistical methodology.

The searching process and data extraction will be guided by Cochrane Handbook for Systematic Reviews of Interventions. 25 The initial step will be a summary of the included findings in a table and qualitative analysis. Table descriptors and subgroups will include intervention strategies, intensity and training standardisations used to deliver CDSM programmes, as well as usual care. Subgroup analyses will be performed on key domains likely various comorbid conditions, training of intervention arms, treatment intensity and other unanticipated factors to be described after all included articles are finalised. Study heterogeneity can be common in CDSM and other complex interventions, and heterogeneity tests will be performed on subgroups. 26–30 Quantitative synthesis will be conducted should relevant data be extracted; this includes meta-analysis using random effects model. Meta-analysis will be conducted using statistical software R, if feasible. To compare different outcome measures with single effect sizes (standardised mean differences) quantitative synthesis may be more appropriate.

Risk of bias in individual studies

The Cochrane Risk of Bias tool will be used to assess the risk of bias, and the Metafor package will be used to perform the data analysis. To assess the validity of studies that are included two reviewers, in pairs, will assess and rate risk of rate risk of bias from standards defined in the Cochrane Collaboration’s tool. 24–26 This validated tool requires a checklist that details how to appropriately assess risk of bias. 28 Using the risk of bias tool adapted by the EPOC Group and published by Freund. 26–30

Measures of treatment effect

The results will be presented using a risk ratio with a 95% CI to express estimates of effects for dichotomous variables and outcomes. For continuous variables and outcomes, the results will be expressed as the mean difference with 95% CI. For outcomes measured using a variety of methods, the size of the intervention effect will be presented as standardised mean difference with 95% CI.

Dealing with missing data

In cases where trials have missing data, attempts will be made to contact the authors of individual trials for clarification or to source any missing data. Should missing data be unavailable, the following strategy that evaluates any likely influence of missing data on the overall pooled analysis will be used 25 :

Worst-case scenario: all participants are counted as failures.

Extreme worst case: experimental group participants are counted as failures and control group participants are counted as successes.

Extreme best case: experimental group participants counted as successes and control group participants counted as failures.

Assessment of heterogeneity

For statistical heterogeneity, we will use a χ 2 test. In addition, heterogeneity will be quantified using the I 2 statistic value ranging from 0% to 100%; p<0.1 of χ 2 test or I 2 >50% indicates statistically significant heterogeneity. Subgroup analysis will subsequently be used to assess potential clinical heterogeneity. 25–30

Assessment of reporting biases

Should meta-analyses include 10 or more RCTs, asymmetry will be assessed visually using funnel plots. Asymmetry will also be tested using the Harbord modified test for dichotomous outcomes and the Egger test for continuous outcomes. 25–30

Data synthesis

If there are sufficient trials to examine the same intervention with comparable methods, in comparable populations, the trials will be combined and an estimated pooled intervention effect using meta-analysis be undertaken. Continuous data will be pooled using inverse variance method, and dichotomous data using the Mantel-Haenszel method. The fixed-effect model will be used to combine data when there is low statistical heterogeneity. However, when p<0.1 or I 2 >50%, the random-effect model will be used to provide a more conservative estimate of effect. All analyses will be performed using a specialised meta-analysis software. In the unlikely scenario of a meta-analysis not being possible, narrative summaries of individual trials will be detailed in a table format. 25–30

Subgroup analysis and investigation of heterogeneity

The subgroup analysis is required in order to understand the heterogeneity effects if there is sufficient data. A range of variables will be explored, these include age, sex, type of HF, aetiology of HF and nature of control group (placebo, self-management intervention). The intervention effects will then be analysed using χ 2 test, with p<0.05, demonstrating statistically significant differences between subgroups.

Summary of findings

The ‘summary of findings’ will be detailed in a table format. The GRADEpro GDT will be used to grade the quality of included trials against the outcomes outlined. Two coauthors will assess the included trials against the criteria within five grades, independently. These criteria include study limitations, imprecision, inconsistency, indirectness and publication bias. In addition, trials will be rated along four categories, which include (high, moderate, low and very low). Any differences or discrepancies in grade and rating will be resolved through consensus of the authors and/or if required a third author.

Any amendments will be documented in chronology, with changes and rationale described in detail and published for awareness of readers, in the methods section of the final output manuscript.

Patient and public involvement

No patient is involved.

Ethics and dissemination

Ethical approval is not required for the study, as no primary patient data are collected. This review will extract current and comprehensive research publications on CDSM and CHF. At this juncture it is vital to inform the literature on the efficacy of CDSM within the CHF context. It is important to plan studies to counter the downgrade of evidence and inform future guidelines. Our team will present the findings from this review at scientific conferences and also publish the findings in peer-reviewed scientific journals using the PRIMSA 2020 guidelines. 19 31

Ethics statements

Patient consent for publication.

Not applicable.

Acknowledgments

The authors acknowledge support from Victoria and Torrens University library staff. Professor Malcolm Battersby for advice on Flinders Programme of Chronic Condition Self-management and Professor Craig McLachlan, Torrens University Australia.

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X @maxdecourten

Contributors PI, FH and MdC provided substantial contributions towards the conceptual design of this protocol. PI, FH, MdC and MB contributed to conceptualisation for acquisition, analysis and interpretation aspects of the protocol. All authors contributed intellectual content to drafting, reviewing and final approval of the submitted version. All authors agreed to be accountable for all aspects of this protocol, this includes questions on accuracy, integrity and appropriate measures to investigate and resolve.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

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• Study protocol
• Open access
• Published: 18 June 2024

The effect of an online acceptance and commitment intervention on the meaning-making process in cancer patients following hematopoietic cell transplantation: study protocol for a randomized controlled trial enhanced with single-case experimental design

• Aleksandra Kroemeke   ORCID: orcid.org/0000-0001-8707-742X 1 ,
• Joanna Dudek 2 ,
• Marta Kijowska 1 ,
• Ray Owen 3 &
• Małgorzata Sobczyk-Kruszelnicka 4  

Trials volume  25 , Article number:  392 ( 2024 ) Cite this article

Metrics details

Hematopoietic cell transplantation (HCT) is a highly invasive and life-threatening treatment for hematological neoplasms and some types of cancer that can challenge the patient’s meaning structures. Restoring meaning (i.e., building more flexible and significant explanations of the disease and treatment burden) can be aided by strengthening psychological flexibility by means of an Acceptance and Commitment Therapy (ACT) intervention. Thus, this trial aims to examine the effect of the ACT intervention on the meaning-making process and the underlying mechanisms of change in patients following HCT compared to a minimally enhanced usual care (mEUC) control group. The trial will be enhanced with a single-case experimental design (SCED), where ACT interventions will be compared between individuals with various pre-intervention intervals.

In total, 192 patients who qualify for the first autologous or allogeneic HCT will be recruited for a two-armed parallel randomized controlled trial comparing an online self-help 14-day ACT training to education sessions (recommendations following HCT). In both conditions, participants will receive once a day a short survey and intervention proposal (about 5–10 min a day) in the outpatient period. Double-blinded assessment will be conducted at baseline, during the intervention, immediately, 1 month, and 3 months after the intervention. In addition, 6–9 participants will be invited to SCED and randomly assigned to pre-intervention measurement length (1–3 weeks) before completing ACT intervention, followed by 7-day observations at the 2nd and 3rd post-intervention measure. The primary outcome is meaning-related distress. Secondary outcomes include psychological flexibility, meaning-making coping, meanings made, and well-being as well as global and situational meaning.

This trial represents the first study that integrates the ACT and meaning-making frameworks to reduce meaning-related distress, stimulate the meaning-making process, and enhance the well-being of HCT recipients. Testing of an intervention to address existential concerns unique to patients undergoing HCT will be reinforced by a statistically rigorous idiographic approach to see what works for whom and when. Since access to interventions in the HCT population is limited, the web-based ACT self-help program could potentially fill this gap.

Trial registration

ClinicalTrials.gov ID: NCT06266182. Registered on February 20, 2024.

Peer Review reports

Administrative information

Note: the numbers in curly brackets in this protocol refer to SPIRIT checklist item numbers. The order of the items has been modified to group similar items (see http://www.equator-network.org/reporting-guidelines/spirit-2013-statement-defining-standard-protocol-items-for-clinical-trials/ ).

Title {1}	The Effect of an online Acceptance and Commitment Intervention on the Meaning-Making Process in Cancer Patients following Hematopoietic Cell Transplantation: Study Protocol for a Randomized Controlled Trial enhanced with Single-case Experimental Design
Trial registration {2a and 2b}.	ClinicalTrials.gov ID: NCT06266182
Protocol version {3}	Version 3.0 dated May 13, 2024.
Funding {4}	The work is supported by the National Science Centre, Poland [grant number 2020/39/B/HS6/01927 awarded to AK].
Author details {5a}	SWPS University, Institute of Psychology, Health & Coping Research Group, Poland; SWPS University, Faculty of Psychology in Warsaw, Poland; Private Practice, UK; Maria Sklodowska-Curie National Research Institute of Oncology Gliwice Branch, Department of Bone Marrow Transplantation and Oncohematology, Poland
Name and contact information for the trial sponsor {5b}	National Science Centre, Poland; [email protected]
Role of sponsor {5c}	The funders had no role in study design, data collection, analysis, and interpretation, decision to publish, or preparation of the manuscript

Introduction

Background and rationale {6a}.

Hematologic neoplasms (e.g., lymphomas or acute leukemias) due to unique and sometimes increased challenges are highly stressful conditions. Treatment-related challenges can impede the realization of life goals and violate general beliefs and a sense of meaning as defined by the integrative meaning-making model [ 1 ]. A significant point on the trajectory of coping, challenging the patient meaning structures, may be hematopoietic cell transplantation (HCT). HCT is a highly invasive and life-threatening treatment for hematological neoplasms and some types of cancer (e.g., testicular cancer). In the acute phase, HCT involves the destruction of the patient hematopoietic system through radio and/or chemotherapy and then its restoration via autologous or allogeneic cell transplantation [ 2 , 3 ]. During in- and outpatient conditions, patients usually experience burdensome adverse effects and have to follow strong medical regimens [ 2 , 4 ]. Evidence suggests that HCT affects a patient physical (e.g., fatigue), psychological (e.g., anxiety and depression symptoms), social (e.g., financial concerns, employment disruptions), and spiritual (e.g., existential concerns) well-being [ 5 ]. HCT recipients may confront fear of death, loss of control, feelings of uncertainty and social isolation, increased dependence, or disabling physical symptoms in the short and long term after transplantation [ 6 , 7 ]. Some models of adaptation and adjustment argue that restoring meaning is central to adapting to these conditions [ 8 ].

Meaning-making process following HCT

The most commonly mentioned factors of meaning reconstruction are meaning-making coping and meanings made [ 1 , 9 ]. Meaning-making is related to the process of searching for meaning and explanation for adversity (i.e., seeking understanding of disease), whereas meanings made is the product of the meaning-making process (i.e., giving meaning to the disease, acceptance, finding benefits, or change of identity due to disease). According to the integrative meaning-making model [ 1 , 10 ], distress related to the discrepancy between global meaning (i.e., basic goals and beliefs, and fundamental assumptions about life) and situational meaning (i.e., the personal significance of a particular situation) initiates meaning-making coping, which impacts the meanings made and then well-being. However, a prolonged unsuccessful search for meaning can be maladaptive. Indeed, the adaptability of meaning-making coping depends on whether the meaning has been found or restored [ 10 ].

A review of the narratives shows that HCT recipients who were able to find meaning in their experience were better able to cope with physical symptoms and were less likely to report unfavorable psychological outcomes after transplant than those who had difficulty finding meaning [ 6 ]. Meanings made was also an essential link connecting meaning-making and well-being in HCT recipients in a daily diary study lasting 28 days after hospital discharge [ 11 ]. The direct effect of average meaning-making coping was unfavorable but positive when mediated by meanings made. In another study among HCT recipients in the late outpatient period with a 4-month follow-up interval, only changes in meaning-making coping were associated with changes in well-being, and these correlates were positive and negative [ 12 ]. The role of meanings made in these relationships was, however, not tested. Indeed, few studies tested the assumptions of the integrative meaning-making model in the context of HCT. More often, the focus is on the global meaning which turns out to be a dynamic construct. In a longitudinal study, sense of meaning decreased 1 month post-HCT and returned to pre-transplant levels by 6 months post-HCT. Moreover, a greater pre-HCT sense of meaning predicted more favorable psychological and physical outcomes during the 12 months following HCT [ 13 ].

Hence, an intervention targeting the ability to successfully search for meaning and find it holds promise in terms of facilitating recovery following HCT and adjustment. To date, no trials tested such interventions among patients undergoing HCT. To the best of our knowledge, two studies are currently underway in HCT recipients that include modules directed at searching for meaning i.e., identifying benefits and meaning. The first one examines the effect of one-on-one, in-person intervention promoting resilience in stress management [ 14 ], whereas the second is a phone-delivered positive psychology intervention [ 15 ]. Both, however, will not evaluate the outcomes from the perspective of the meaning-making model. A systematic review shows that various psychosocial interventions can promote meaning and purpose in the cancer population [ 16 ]. Nevertheless, these targeting meaning enhancements demonstrate a higher effect size. One of the promising approaches potentially fostering meaning-making in disease is Acceptance and Commitment Therapy [ 17 ].

Acceptance and Commitment Therapy (ACT) intervention

Acceptance and Commitment Therapy (ACT) is a transdiagnostic therapeutic approach rooted in the contextual behavioral science that aims to improve the psychological functioning and well-being of individual by increasing psychological flexibility (i.e., the ability to engage in values-based actions even in the presence of unpleasant or difficult experiences) [ 17 ]. To achieve this goal ACT targets six core processes: ( 1 ) contact with the present moment—paying attention to different aspects of the internal and external environment; ( 2 ) self-as-context—the ability to look at one’s internal experiences from a broader perspective; ( 3 ) acceptance—making room for thoughts, feelings, and sensations, even those that are unpleasant; ( 4 ) defusion—noticing thoughts instead of being controlled by them; ( 5 ) values—knowing what really matters; and ( 6 ) committed action—taking values-congruent actions even in the presence of difficulties. During the therapy, the individual learns to assess the workability of strategies used to cope with difficult, unwanted private experiences and to use mindfulness and acceptance skills when necessary. Those skills allow the individual to recognize moments when they have an opportunity to engage in behaviors consistent with their values and fully immerse themselves in those activities, even in the presence of painful thoughts, feelings, or sensations. Individuals are not asked to accept painful private experiences (e.g., physical pain) if there is an effective way to get rid of the pain; acceptance means embracing painful private experiences only when there is no effective way of escaping painful experiences on a long-term basis or when the means of escape comes at too high a cost in terms of valued living. Techniques used in ACT to obtain the aforementioned changes include using metaphors, experiential exercises, and functional analysis [ 17 ].

Besides the typical use of ACT as an individual face-to-face therapy, ACT was also tested in a group format (e.g., for anxiety and depression [ 18 ] or chronic pain [ 19 ]), as a self-help form [ 20 ] as well as technology-supported intervention (using online materials, web or phone applications, telephone) with or without therapeutic guidance [ 21 ].

ACT has been proven to be an effective intervention for various conditions [ 22 ], with the growing number of randomized controlled trials [ 23 ] and mediational studies showing that psychological flexibility is a mediator of the intervention [ 24 ]. Several systematic reviews and metanalyses provide evidence for ACT effectiveness in improving the quality of life and decreasing psychological distress among cancer patients [ 25 , 26 , 27 , 28 , 29 ]. Other systematic reviews support ACT efficacy in improving quality of life and symptoms for long-term chronic conditions [ 30 , 31 ], also including the technology-supported delivery of ACT [ 21 ]. Finally, ACT is considered to be an effective treatment for chronic pain, being recognized by the American Psychological Association as an evidence-based treatment with “strong research support” [ 32 ].

The links between ACT and the meaning-making process

ACT and meaning-making frameworks share common philosophical roots, including constructivism and existentialism [ 9 ]. The ACT model promotes acceptance of what is difficult to change or is not subject to change (such as chronic disease or burden of toxic treatment), taking responsibility for one’s own experiences and actions and creating a meaningful life by engaging in activities that match one’s values [ 33 ]. While meaning-making is not an explicit goal of ACT, creating psychological flexibility should foster meaning-making in disease or following HCT by building more flexible and workable meaning-making explanations of disease [ 34 ]. ACT emphasizes increased awareness of what matters most to the individual and a stepping back from automatic patterns of thought and behavior. Both of these abilities should facilitate meaning-making, i.e., changing global meaning or a reappraisal of situational meaning to achieve congruence, thus alleviating the distress of the event such as HCT. Achieving congruence should end meaning-making coping and be associated with meanings made and improved well-being.

Objectives {7}

This trial aims to examine the effect of an online self-help ACT intervention on the meaning-making process and the underlying mechanisms of change in patients following HCT compared to a minimally enhanced usual care (mEUC) control group. The trial will be enhanced with a single-case experimental design (SCED), where ACT interventions will be compared between individuals with various pre-intervention intervals. As the change process is characterized by complexity, traditional examination of intervention efficacy will be enriched with a temporal perspective (i.e., examination of trajectories of change in primary and secondary outcomes over time) and a systems perspective (i.e., network analysis depicting the pattern of connections between components of the system). The latter assumes that an intervention transforms the connectivity of the networks of intervention goals, the outcome of the intervention, and the connections between the two networks [ 35 , 36 ].

It is hypothesized that the ACT intervention group would show increased psychological flexibility and decreased meaning-related distress compared with the control group (hypothesis 1). Additionally, an increase in meanings made and well-being is anticipated (hypothesis 2). In more exploratory terms, the moderating effect of individual resources (i.e., global and situational meaning, baseline well-being) and demographic and clinical factors on the effect of the intervention will also be examined. Moreover, it is hypothesized that psychological flexibility and meaning-making coping would mediate the ACT intervention effects on meaning-related distress, meanings made, and well-being in HCT recipients (hypothesis 3). Finally, following the network theory, it is hypothesized that the ACT intervention group will display more robust positive connections within the psychological flexibility and meaning-making coping network (hypothesis 4), weaker connections within the distress network (hypothesis 5), more negative connections of distress with psychological flexibility and meaning-making coping (hypothesis 6), and more positive connections between psychological flexibility, meaning-making coping, meanings made, and well-being as compared to control conditions (hypothesis 7).

Trial design {8}

A two-armed parallel randomized controlled trial (RCT) will be conducted to determine the effects of an online Acceptance and Commitment Therapy ACT intervention on the meaning-making process in patients following HCT. Participants will be randomly assigned in a double-blinded manner to ACT intervention and education conditions at a ratio of 1:1. RCT will be enhanced with a randomized multiple-baseline single-case experimental design (SCED). SCED will proceed according to the AB + post-intervention design, where A is the pre-intervention phase and B is the intervention phase, followed by the post-intervention phase. Participants will be randomly assigned to one of three pre-intervention measurement lengths (7 days, 14 days, 21 days) followed by 7-day observations at the 2nd and 3rd post-intervention measure.

Methods: participants, interventions and outcomes

Study setting {9}.

Recruitment will take place in the Department of Bone Marrow Transplantation and Oncohematology of the Maria Sklodowska-Curie National Research Institute of Oncology (MSCNRIO) Gliwice Branch. MSCNRIO branch in Gliwice is the leading facility in Poland that performs HCT. Approximately 150 primary transplants are performed there annually (approx. 200 HCT in total).

Eligibility criteria {10}

The participation criteria will include ( a ) qualification for the first autologous or allogeneic HCT due to hematologic malignancies or solid tumors, ( b ) age ≥ 18 years, ( c ) signed written informed consent, ( d ) ability to read and write in Polish, and ( e ) daily access to the Internet by computer and/or mobile device. The exclusion criteria will be as follows: ( a ) major psychiatric or cognitive disorder that would impede providing informed consent and study participation, ( b ) inability to cooperate and give informed consent, ( c ) hearing, seeing, or movement impairment that precludes participation, ( d ) current participation in any form of psychotherapy, ( e ) no access to the Internet and computer and/or mobile device, and ( f ) inability to use a computer and/or mobile device and the Internet.

Who will take informed consent? {26a}

Written informed consent to participate in the study will be obtained by the recruiter (member of the research team), in direct contact with the participant and after an extensive briefing.

Additional consent provisions for collection and use of participant data and biological specimens {26b}

N/A. Biological specimens will not be collected.

Interventions

Explanation for the choice of comparators {6b}.

In RCT, the ACT intervention will be compared with minimally enhanced usual care (mEUC). Standard psychological care following HCT does not include a standard psychological care protocol. Psychological care for HCT recipients is provided if needed according to the physician’s recommendation in the event of the patient’s functioning deteriorating. Thus, to maintain the same conditions in both trials, participants in the control condition will receive cognitively neutral tasks (education) from which no effects are expected for the meaning-making process. In SCED, comparisons between participants with different pre-intervention measurement lengths will be conducted.

Intervention description {11a}

ACT intervention “The Path to Health” will start on the second day after hospital discharge for individuals in RCT or after 7–21-day pre-intervention measurement in individuals in SCED. It will take 14 days (+ day 0 with organizational information). Each day, participants will receive a web-based intervention consisting of the theoretical introduction (including examples of patients’ experiences and metaphors) and practical ACT activity (e.g., reflective questions, experiential exercise, values card sorting test). Most of the activities are followed by a debrief that includes the patient’s reactions to this particular exercise and practical tips. On some days, participants will also receive additional exercise (optional).

Using the metaphor of life as a journey, participants will learn to recognize where they are headed (values), when there is a moment of choice between actions that lead towards values or away from them, and how to use attention flexibly to free themselves from the power of thoughts, to open up and accept emotions so that they can effectively take action in line with their values (Table  1 ). Each introduction and each activity will be available in written form and audio. The ACT intervention is built from standard ACT activities [ 37 , 38 , 39 , 40 ] and tailored to the context of the disease and treatment. Participants will be advised to do one activity a day, but they will be able to come back to the chosen activities or practice them a couple of times if necessary.

During the same period, participants allocated to the education in RCT will receive an online guide to post-HCT recommendations. Each day, participants will receive information about post-transplant prescriptions along with exercises. Participants will receive guidelines in several areas: diet, physical activity, hygiene, rest, social interactions, and sexual health. During the first 3 days, nutrition will be discussed, including the principles of healthy diet after HCT. On the fourth day, participants will learn the rules of personal hygiene. The fifth day is devoted to presenting the rules aimed at preventing infection. On the sixth day, the issue of body fatigue will be discussed. For the next 3 days, the main topic will be the resumption of activity, mostly physical activity. The tenth day is devoted to safe social contacts. On the eleventh day, participants will work on their sleep. On the twelfth day, sexual health will be discussed. Day 13 is devoted to discussing the issue of rest. And the last day will be a summary of all the guidelines. The exercises serve as an extension of the topic (e.g., watching a video presenting the principles of nutrition) or the emphasis is on practice to support the implementation (e.g., preparing a sequence of exercises and performing them several times a day). The content is prepared based on available guides for HCT recipients. It was also verified by a hemato-oncologist.

Criteria for discontinuing or modifying allocated interventions {11b}

Modification of assigned interventions is not provided for. Disease recurrence will be the criteria for discontinuation of the intervention. The participant can also discontinue the intervention at any time without any negative consequences.

Strategies to improve adherence to interventions {11c}

To improve adherence to the intervention, participants will receive daily reminders about the intervention. Also, direct technical support will be available 24/7. If participants drop out or stop using the intervention, they will be asked for the reason(s) why they decided to quit the intervention and/or study.

Relevant concomitant care permitted or prohibited during the trial {11d}

Individuals participating in any form of psychotherapy will not be eligible for the study. Participation in forms of psychological support will be monitored on an ongoing basis.

Provisions for post-trial care {30}

Upon completion of the study, all participants will have access to the self-help ACT intervention booklet with written and recorded exercises.

Outcomes {12}

The primary and secondary outcomes will be assessed at baseline (before HCT), during the intervention, immediately, 1 month, and 3 months after the intervention (Table  2 ). In SCED, 1 month and 3 months post-intervention assessments will be preceded by 7-day daily diaries. A summary of the outcome measures that will be used in this study is available in Table  3 .

Primary outcomes

The primary outcome will be the changes compared to the baseline in meaning-related distress as assessed by the Global Meaning Violation Scale (GMVS) [ 41 ].

Secondary outcomes

The secondary outcomes will be changes from baseline in global meaning, situational meaning, meanings made, and well-being. Global meaning will be measured by cognitive and emotional representations of illness and global presence of meaning using the Brief-Illness Perception Questionnaire (B-IBP) [ 42 ] and Meaning in Life Questionnaire (MLQ) [ 43 ], respectively. Coping self-efficacy, an indicator of situational meaning, will be assessed with the Perceived Coping Self-Efficacy (CSE) Scale [ 44 ]. Meanings made will be assessed using the “current standing” Post-Traumatic Growth Inventory-Short Form (C-PTGI-SF) [ 45 , 46 ] and 3-item scale based on the Meaning of Loss Codebook (MLC) [ 47 ]. Depressive and anxiety symptoms will be assessed with the Patient Health Questionnaire (PHQ-4) [ 48 ], while loneliness, as recommended by the British Office for National Statistics [ 49 ], will be evaluated with the enhanced R-UCLA 3-item Loneliness Scale [ 50 ] and direct question from the Community Life Survey [ 51 ].

Mediators and moderators

To assess putative mechanisms of change and change moderators, meaning-making coping and psychological flexibility will be measured longitudinally. In this scheme, deliberate and automatic meaning-making coping will be assessed with the Core Beliefs Inventory (CBI) [ 52 ] and the intrusive ruminations subscale from the Event-Related Rumination Inventory (ERRI) [ 53 ], respectively. Psychological flexibility will be measured using the Comprehensive Assessment of Acceptance and Commitment Therapy Processes (CompACT-9) [ 54 ]. In addition, fluctuations in meaning-making coping, meanings made, psychological flexibility, and well-being (i.e., subjective health and positive and negative affect) will be measured in an intensive longitudinal manner (i.e., daily) throughout the intervention in RCT and pre- to post-intervention in SCED. Daily meaning-making coping (deliberate and automatic) will be measured with an abbreviated and tailored to the daily measurement and context of the study 4-item version of the ERRI questionnaire. Daily meanings made will be evaluated using a contextualized 3-item scale based on the Meaning of Loss Codebook (MLC). Daily psychological flexibility will be measured using a shortened to 4-item version of the CompACT questionnaire. Daily subjective health will be assessed by a single-item statement “Generally, I can say my health today was…” on a 5-point scale ranging from 1 (bad) to 5 (excellent). Daily positive and negative affect will be assessed with two positive (happy, cheerful) and two negative adjectives (sad, gloomy) based on the Circumplex Model of Emotion [ 55 ].

Feasibility will be examined via attrition and adherence rates as well as questions about intervention engagement. Acceptability will be measured by intervention satisfaction and evaluation (attractiveness and easiness). Adherence to the intervention will be estimated based on the dropout rate (i.e., the percentage of participants who do not log in to the intervention on a given day) and self-reported questions about engagement in the intervention: ( 1 ) the number of days on which the proposed exercises were done seriously, ( 2 ) the number of minutes spent on average in training, and ( 3 ) the use of various training components. Satisfaction with the intervention will be measured using 4 questions (no. 3, 4, 7, and 8) from the Client Satisfaction Questionnaire (CSQ-8) [ 56 ] modified to the intervention context and online form. Evaluation of the intervention will be assessed using questions of the author’s own measuring the ease and attractiveness of the training.

The cost-effectiveness of the intervention will be examined by estimating health-related quality of life as measured by the Quality of Life Questionnaire of the European Organization for Research and Treatment of Cancer (EORTC QLQ-C30) [ 57 ].

Other measures

At the baseline, demographic data (e.g., age, sex, education, marital status, employment) will also be collected and partially measured using the Diversity Minimal Item Set (DiMIS) [ 58 ]. Clinical data (e.g., diagnosis, time since diagnosis, conditioning, concomitant diseases) will be obtained from the medical records.

Participant timeline {13}

Figure  1 describes the project timeline.

Timeline for RCT and SCED study

Sample size {14}

In RCT, the sample size was calculated based on an analysis of variance with two groups (ACT versus mEUC) and four repeated measures of variance (ANOVA) with within-between interaction (group x time) using the G*Power calculator [ 59 ] and simulation study of the time course with dichotomous between-person level predictor [ 60 ]. Given the large effects of ACT on psychological well-being, including hope (Hedge’s g  = 0.88–2.17) and medium effects on psychological flexibility among cancer patients (Hedge’s g  = 0.58) [ 29 ], the stronger effects in the population of women with breast cancer compared to patients with other types of cancer (large versus medium effect sizes) [ 31 ], and medium effect sizes of technology-supported ACT interventions (Hedges’ g  = 0.44–0.48) [ 21 ], moderate differences between conditions were expected. Assuming a medium effect size of f  = 0.25, a power of 0.80, and an alpha level of 0.05 in repeated measures of ANOVA, a total sample size of N  = 178 is required. In turn, on the basis of a simulation study, a total sample size of N  = 136 is required for multilevel modeling. Therefore, the minimum sample size was assumed of N  = 160 (80 per condition). Allowing for the potential attrition rate of 20%, this leads to a sample size of N  = 192 participants, including 96 in each arm. In SCED, 6–9 participants will be investigated, a minimum of 2 per condition. According to the simulation study [ 61 ], sufficient power (0.80) can be reached in SCED with six to eight participants, depending on the assumed effect size (large versus medium, respectively).

Recruitment {15}

Recruitment will take place at a single center, after elective admission to the bone marrow transplantation and oncohematology unit due to HCT before the start of conditioning treatment. Recruitment will take place on average on the 2nd day after admission. Every 2 days, the transplant coordinator, PI, and physician (members of the research team) will review the lists of patients enrolled for HCT. Those who meet the inclusion criteria will be initially informed of the purpose of the study and invited for an extensive briefing by a recruiter (member of the research team). Patients will also be allowed to ask any remaining questions about the aim of the study and the study procedures. After receiving an extensive briefing, all patients who give written informed consent will proceed with baseline. Recruitment will be carried out until the desired sample size is achieved. The flowchart of the study is depicted in Fig.  2 .

Participant flowchart in RCT and SCED study. ACT, Acceptance and Commitment Therapy; mEUC, minimally enhanced usual care

Assignment of interventions: allocation

Sequence generation {16a}.

The allocation sequence will be generated using the method of minimization. Minimization can be classified as dynamic allocation or covariate adaptive methods because the allocation depends on the characteristics of the patients and is performed continuously [ 62 ]. Randomization will be stratified by type of transplant (autologous versus allogeneic) to ensure a balanced representation between the study conditions because autologous and allogeneic HCT recipients experience different recovery trajectories and HCT impact on well-being [ 63 , 64 ].

Concealment mechanism {16b}

The mechanism of implementing the allocation sequence will be central randomization. It means generating an allocation sequence after the patient is enrolled [ 65 ]. This way, randomization will not affect the recruitment process.

Implementation {16c}

The trial coordinator (member of the research team) will enroll participants, generate the allocation sequence, and assign participants to interventions. Other members of the team will be blind to the allocation of the participants to the conditions.

Assignment of interventions: blinding

Who will be blinded {17a}.

In RCT, trial participants, care providers, outcome assessors, and data analysts will be blinded after assignment to interventions. Blinding will be performed using two separate databases: one containing participant allocation information (blinded) and the other containing the remaining information (unblinded). Only the trial coordinator will have access to the blinded database.

Procedure for unblinding if needed {17b}

Disclosure of the participant allocation will take place after the completion of the study and analysis of the first results examining the efficacy of the online ACT intervention.

Data collection and management

Plans for assessment and collection of outcomes {18a}.

Data will be collected via self-reported online questionnaires at the baseline (before HCT), post-intervention, and 1 and 3-month follow-ups (Table  2 ). In addition, to assess momentary changes and mechanisms of change, participants will complete daily diaries throughout the intervention. SCED participants will complete 7-day daily diaries repeatedly, i.e., before 1 and 3-month follow-ups. The detailed characteristics of the study instruments are presented in Table  3 .

We intend to collect clinical data (e.g., diagnosis, time from diagnosis, type of transplant and conditioning treatment, comorbidities) from the patient’s medical records. The participants will give their additional consent for the data to be collected from their medical history by a physician (team member). If the participant does not approve of access to the data from medical records, they will be requested to provide information themselves.

Plans to promote participant retention and complete follow-up {18b}

To improve participant retention and complete follow-up, participants will receive email and phone reminders about the survey and subsequent measurements. If participants fail to complete study assessments, motivational reminders will be sent repeatedly by email. In daily diary measurements, participants who give written consent will receive SMS reminders. Since the daily diaries will not be filled retrospectively, a single reminder with the mailing of the survey will be used.

During the study, direct technical support will be available 24/7, and a research team member will contact the participant by phone to resolve any issues and answer questions. If participants drop out of the study, they will be asked for the reason(s). Any other attritions (e.g., disqualification from HCT, death) along with the reasons will be recorded.

Data management {19}

Questionnaire data collection will be done electronically (using the SurveyMonkey platform, which encrypts and secures data during transit and the data stored; the accounts are password-protected with available complexity controls). Medical data will be collected electronically directly from the medical records registry by the physician (member of the research team). Only informed consents will be paper documents, collected and entered by recruiter (member of the research team). The PI will be responsible for the secure delivery of the documents to the trial office. The PI and trial coordinator will oversee the quality of the data. Data and metadata storage will take place in the university’s central resources according to the 3–2-1 rule. The detailed data management plan is available at OSF .

Confidentiality {27}

Personal data such as phone numbers and email addresses of the participants will be encrypted (using individual trial identification number) and stored only during the data collection period. Written informed consent and the data identifying the participants will be stored separately under lock and key and will be kept strictly confidential. The data will be accessed by the PI of the project and selected team members who will be contacting the participants (trained in the General Data Protection Regulation). Access to the data will be monitored and possible only after obtaining the access rights that the PI of the project will grant. Once data collection is completed, the data will be anonymized and in this form will be analyzed statistically.

Plans for collection, laboratory evaluation and storage of biological specimens for genetic or molecular analysis in this trial/future use {33}

N/a. Biological specimens will not be collected.

Statistical methods

Statistical methods for primary and secondary outcomes {20a}.

Analyses will be conducted using the latest Mplus statistical package [ 66 ], R [ 67 ], and IBM SPSS (IBM Corp.; Armonk, NY). We will use the standard α  = 0.05 or 95% confidence interval for the determination of value probability. All data analysis will be performed according to the intention-to-treat principle, where all randomized participants are included in the analysis assuming missing data at random. The collected data will be first analyzed in terms of sample characteristics and comparisons (frequency, descriptive statistics; ANOVA, t -test or their nonparametric counterparts; χ 2 ; Pearson’s or Kendall’s correlation), missing data (frequency, multilevel modeling), and sample attrition (logistic regression analysis). Multilevel confirmatory factor analysis (MCFA) will be performed to establish the respective measurement models and calculate the indicator reliabilities (omega coefficient) at the within- and between-person levels [ 60 , 68 ]. To examine hypotheses 1–3, latent curve growth modeling (LCGM) [ 69 ] and multilevel (MSEM) and dynamic structural equation modeling (DSEM) will be applied [ 60 , 70 ]. All methods allow for the examination of the time course. In addition, MSEM and DSEM allow for the calculation of simple between- and within-person associations and more advanced associations such as mediations and moderations. Hypotheses 4–7 will be verified using a multilevel vector autoregressive (mlVAR) model [ 71 ]. mlVAR allows for the examination of a temporal network (i.e., lagged predictive relations between each node in the network and each node in the network at the next measurement occasion), a contemporaneous network (i.e., partial correlations within the same measurement occasion), and a between-person network (i.e., associations between nodes that are averaged across measurement occasion).

Interim analyses {21b}

Due to a known minimal risk, i.e., testing interventions with known positive effects, an interim analysis plan was not created. The principal investigator (PI) will make the final decision to terminate the study once the optimal number of study participants has been obtained.

Methods for additional analyses (e.g., subgroup analyses) {20b}

All analyses will be supplemented by sensitivity analyses. In all models, possible confounders (i.e., demographics, clinical factors, and other confounders) will be considered after preliminary selection.

Methods in analysis to handle protocol non-adherence and any statistical methods to handle missing data {20c}

The statistical methods used (i.e., MSEM, DSEM) will allow the most recent flexible approach to the missing data (the full information maximum likelihood) [ 72 , 73 ]. In less sophisticated analyses, missing data will be multiple imputed in advance.

Plans to give access to the full protocol, participant-level data and statistical code {31c}

The full protocol, dataset, statistical codes, and outputs will be made available at the Open Science Framework (OSF). Participant-level datasets will be publicly available, however without demographics and clinical data due to privacy or ethical restrictions (the possibility of identification of participants).

Oversight and monitoring

Composition of the coordinating center and trial steering committee {5d}.

The study’s coordinating center is SWPS University. The study’s steering committee will consist of a health psychologist, a certified cognitive behavioral therapist (CBT) and ACT therapist, and a doctoral student (master’s degree in psychology). The committee’s responsibilities will be to develop the intervention and then implement it and monitor implementation. The committee will meet 2–4 times a month.

Composition of the data monitoring committee, its role and reporting structure {21a}

Due to known minimal risks, a formal committee of data monitoring is not needed.

Adverse event reporting and harms {22}

In this study, an adverse event will be defined as any deterioration in mood that requires specialized treatment, collected after the individual has received the intervention, and reported to the local institutional review board (IRB).

Frequency and plans for auditing trial conduct {23}

No audit procedures are planned. An independent audit may be conducted by the local IRB and the sponsor.

Plans for communicating important protocol amendments to relevant parties (e.g., trial participants, ethical committees) {25}

Communication of significant protocol modifications and study outcomes will be done to the funder, the ethics committee, and the public through ClinicalTrials.gov.

Dissemination plans {31a}

The results will be published in peer-reviewed journals and presented at thematic international scientific conferences. Also, during the debriefing, participants will be informed of the web address of the project website, where a lay summary of the study updated with the results (when available) will be posted.

Effective treatment of patients undergoing HCT likely requires a focus also on those mechanisms that support the reconstruction of meaning damaged by medical treatment and the disease itself. An intervention based on ACT, an empirically validated theoretical model [ 17 ], appears to be a promising psychological therapy to support the reconstruction of meanings [ 33 , 34 ]. This trial represents the first study that aims to integrate the ACT and meaning-making frameworks to reduce meaning-related distress, stimulate the meaning-making process, and enhance the well-being of HCT recipients. It builds on previous successful ACT interventions that strengthened cancer patient well-being albeit outside the context of meaning reconstruction [ 25 , 26 , 27 , 28 , 29 ]. Moreover, testing a specific theory-based intervention to address existential concerns unique to patients undergoing HCT will be reinforced by a statistically rigorous idiographic approach. SCED will allow us to go beyond aggregate group effects and see how a specific person responds to an ACT intervention, thereby providing clinical input into what works for whom and when . Beyond this, since access to interventions in the HCT population is limited, the web-based ACT self-help program we designed has the potential to fill that gap. Self-directed ACT interventions are considered cost-effective, flexible, and accessible for cancer patients [ 21 ]. They allow patients to self-determine what (content), when (time), where (location), and how (read or listen) to use ACT intervention booklets.

Despite these strengths, we expect several challenges and limitations. First, recruiting the HCT recipients will be challenging. Therefore, we allow for the possibility of recruiting at a second oncohematology center with identical credentials. Retaining participants in the study can be also a challenge, hence the contact maintenance and participation reminder activities we have planned. In addition, we plan to compensate participants for their participation at a rate of PLN 150 (approx. 34.5 Euros) in RCT and PLN 300 (approx. 69 Euros) in SCED. Another limitation is the targeting of the trial to all willing HCT recipients, regardless of the level of distress or the stage of the meaning reconstruction process. However, we are guided by pragmatic (restrictive inclusion/exclusion criteria would prolong the already long data collection time) and cognitive considerations (to our knowledge, this is the first study that will test the relationship of ACT interventions to meaning reconstruction processes) hoping that this will result in further research in this area.

Trial status

ClinicalTrials.gov, NCT06266182. Registered 20 February 2024, https://clinicaltrials.gov/study/NCT06266182 . Version 3.0 dated May 13, 2024. Patient recruitment began on March 6, 2024. Recruitment is expected to be completed in December 2025.

Availability of data and materials {29}

Data that will be collected during the current study (without demographics and clinical data due to the possibility of identification of participants), full protocol, statistical codes, and outputs will be made available at the Open Science Framework (OSF).

Abbreviations

• Acceptance and Commitment Therapy

Analysis of variance

Brief-Illness Perception Questionnaire

Core Beliefs Inventory

Cognitive behavioral therapy

Comprehensive Assessment of Acceptance and Commitment Therapy Processes

The “current standing” Post-Traumatic Growth Inventory-Short Form

Coping Self-Efficacy Scale

Client Satisfaction Questionnaire

Diversity Minimal Item Set

Dynamic structural equation modeling

Quality of Life Questionnaire of the European Organization for Research and Treatment of Cancer

Event-Related Rumination Inventory

Global Meaning Violation Scale

• Hematopoietic cell transplantation

Institutional review board

Latent curve growth modeling

Multilevel confirmatory factor analysis

Minimally enhanced usual care

Meaning of Loss Codebook

Meaning in Life Questionnaire

Multilevel vector autoregressive

Maria Sklodowska-Curie National Research Institute of Oncology

Multilevel structural equation modeling

Open Science Framework

Patient Health Questionnaire

Principal investigator

• Randomized controlled trial

Revised UCLA Loneliness Scale

• Single-case experimental design

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Acknowledgements

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The work is supported by the National Science Centre, Poland [grant number 2020/39/B/HS6/01927 awarded to AK]. The funders had no role in the study design, data collection, analysis, and interpretation, decision to publish, or preparation of the manuscript.

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Aleksandra Kroemeke & Marta Kijowska

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Joanna Dudek

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Department of Bone Marrow Transplantation and Oncohematology, Maria Sklodowska-Curie National Research Institute of Oncology Gliwice Branch, Gliwice, Poland

Małgorzata Sobczyk-Kruszelnicka

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AK is a principal investigator, who led the proposal and protocol development. JD developed the ACT intervention and contributed to the study design. MK developed cognitively neutral tasks (education) for the control group and assisted in the development of the ACT intervention. RO offered review and advice on ACT intervention component. MSK reviewed the manuscript. AK, MK, and MSK will be involved in the recruitment of participants and data collection. AK, JD, and MK drafted the manuscript. All authors have approved the manuscript.

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The study has been reviewed and approved by the Ethical Review Board at SWPS University, Faculty of Psychology in Warsaw (Decision No. 52/2023 of December 12, 2023), and adheres to the ethical guidelines of the Declaration of Helsinki. All participants will be requested to give written informed consent before participation (assessment and randomization).

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Kroemeke, A., Dudek, J., Kijowska, M. et al. The effect of an online acceptance and commitment intervention on the meaning-making process in cancer patients following hematopoietic cell transplantation: study protocol for a randomized controlled trial enhanced with single-case experimental design. Trials 25 , 392 (2024). https://doi.org/10.1186/s13063-024-08235-1

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How To Fix the ERR_HTTP2_PROTOCOL_ERROR

Using the HTTP/2 Network Protocol , you can reach websites faster than ever before. However, you may stumble across an err_http2_protocol_error. This can prevent you from accessing certain web pages.

Fortunately, there are many solutions for the HTTP/2 protocol error. Whether you fix the problem within your browser or operating system, you can easily remove this troublesome message. Then, you can continue with your normal online browsing.

In this post, we’ll introduce you to the err_http2_protocol_error and its causes. Then, we’ll show you how to fix this problem on both a browser and a personal device. Let’s get started!

What Does the err_http2_protocol_error Mean?

When you perform a search, you may receive an “err_http2_protocol_error” message. This can prevent you from accessing a web page, stating that it is currently down or was permanently moved  to another address:

To understand the err_http2_protocol_error, let’s first discuss the Hypertext Transfer Protocol (HTTP). This is the application protocol that allows the retrieval of online resources.

A protocol is a set of rules that controls how data is transferred between clients. In this case, it can govern the HTTP requests  between users and web browsers.

Currently, most browsers , applications, and systems run on the HTTP/2 network protocol . This updated protocol comes with enhanced efficiency for virtual data communication.

Although this update has many benefits, you still may experience errors when accessing online content. Sometimes, the err_http2_protocol_error will display as an HTTP error message  and prevent you from accessing the online resource you’re looking for.

What Causes the err_http2_protocol_error?

In general, the err_http2_protocol_error can appear because of issues with the browser, network, or conflicts with third-party software. Usually, this happens when HTTP/2 is outdated or not supported at all.

For an HTTP/2 protocol error, something interrupts the communication between the HTTP application layer and a user’s device. Unfortunately, this can happen to a wide variety of applications or systems. However, it is most common in web browsers like Google Chrome .

If you’re seeing this error, here are some common causes:

• Outdated software . When your device’s operating system or web browser is outdated, it can be incompatible with a certain website. This will cause the err_http2_protocol_error if the site fails to parse your device’s data packets.
• Corrupted browser cache . If your browser’s cache, cookies, or history is corrupted, then the requested site may be unable to authenticate your device’s legitimacy. As a result, the web server  can refuse to make the connection and return this error.
• Conflicting browser extensions . In some cases, third-party browser extensions  can interrupt communication with the website’s server. This can prevent the site from rendering.
• Third-party antivirus or firewall software . If you’re using antivirus or firewall software to secure your connections , it can prevent you from accessing certain websites.

As you can see, there are multiple reasons why you might see the HTTP/2 protocol error. Luckily, there are also many methods you can use to fix this problem.

How To Fix the err_http2_protocol_error In a Browser

Once you receive the err_http2_protocol_error, you can start troubleshooting to find the source of the issue. Although we’ll fully discuss some methods you can use, there are some simpler fixes you can start with.

First, try refreshing the web page. Hitting F5 on your keyboard will send a request with an If-Modified-Since header. If the site was temporarily down , this may solve the problem.

Alternatively, you can visit the site using a different browser. You may also want to close some tabs if there are too many open. If the error persists, continue with the following methods.

1. Update Your Browser

If you’re making searches with an outdated browser, this can easily lead to an HTTP/2 protocol error. This is because your browser’s data packets are incompatible with the site you’re trying to load.

To fix this problem, you can update your browser. Using Google Chrome, you can simply click on the three-dot icon in the upper right-hand corner and select Update Google Chrome .

If you don’t see this button, your browser is likely already up-to-date. To check if this is the case, go to Help > About Google Chrome :

This will prompt Google Chrome to check for a new update. If there is one, it will automatically install it. To finish updating, you’ll need to relaunch the browser:

If you’re using the Google Chrome mobile app, you can simply open the App Store or Play Store, depending on your device type. Then, check for any app updates and install them!

2. Clear Your Browser Data

Whenever you experience issues during the rendering process, it’s a good idea to clear your browser data. By clearing your cache , cookies, and history, you can enable visited websites to authenticate your device and fulfill the request.

Depending on your browser, there are a few different ways to clear the cache . For Google Chrome, you can select More Tools > Clear Browsing Data :

Using the pop-up window, you can specify the information you want to clear. You’ll want to be sure to select Cached images and files , but you can also get rid of your browsing history, cookies , and other data:

If you’re using Safari , it will be a similar process. To do this, go to Safari > Clear History :

Then, you can choose to clear your cache, cookies, and site data from a specific time range. When you’re done, click on Clear History :

To clear your browser data on Mozilla Firefox , you’ll need to find the hamburger icon in the upper right-hand corner. Next, select History :

In the new tab, click on Clear recent history :

Like other browsers, you can choose only to clear certain data. However, it’s important to remember to select the Cache  option:

Now that you’ve cleared your browser cache try to visit the website where the error occurred. If you still see the err_http2_protocol_error message, you’ll need to try some alternative solutions.

3. Open a Private or Incognito Browser Window

Whenever you visit a new website, your browser will save information about that site in a cache. Once you visit the page again, your browser will pull the cached data  rather than requesting the server all over again. Often, this can make the site load faster  on repeat visits.

For this reason, you may want to avoid clearing your browser cache when trying to bypass the HTTP/2 protocol error. In this case, you can launch the browser in private or incognito mode .

This can be an effective one-time solution to avoid permanently deleting the cache or disabling third-party extensions. To do this in Google Chrome, extend the menu and click on New Incognito Window . This will open a private browser:

Using the incognito mode, try to visit the website again. It may enable you to do this without having to use more complicated solutions. However, keep in mind that this is primarily a short-term fix.

4. Disable or Uninstall Browser Extensions

As we mentioned earlier, third-party extensions could potentially interfere with how your browser and a web page interact. After you see the err_http2_protocol_error message, you can consider disabling these extensions to see if the error disappears.

To do this in Google Chrome, visit More Tools > Extensions :

This will take you to a web page that lists your Chrome extensions. First, use the switches on the bottom-right corner to turn off each extension:

Now that your extensions are disabled try to go to the web page that caused the error. If the page loads, you’ll know that one of your extensions caused the problem.

Now, you can go back to the Extensions  page and enable them one by one. After you turn on an extension, see if the error returns. When you find the problematic extension, consider removing it entirely .

5. Turn Off the Browser’s QUIC Protocol

Quick UDP Internet Connections (QUIC)  is an encrypted transport network protocol that was developed by Google. Essentially, its goal was to increase the speed, security, and efficiency of HTTP traffic.

Currently, only eight percent  of websites use QUIC. Therefore, when sites aren’t configured to process this kind of traffic, it can cause incompatibility between the client and server. As a result, this can display an HTTP/2 protocol error.

To solve this problem, you can turn off the QUIC protocol in your browser. In Chrome, you’ll simply need to enter the following URL into your search bar:

chrome://flags/#enable-quic

Now you’ll see a highlighted result labeled Experimental QUIC protocol . For this setting, change it to Disabled :

Once you make this change, you’ll need to relaunch your browser. This will disable QUIC, allowing you to view the incompatible website.

6. Restore the Browser’s Default Settings

As you use Google Chrome, you may not notice small glitches that can change its default settings. Over time, this can lead to more errors like the err_http2_protocol_error.

Fortunately, you can get your browser back to normal by reverting its settings to the default options. To get started, open the Google Chrome Settings  page:

On the left, find the Reset settings  tab. Then, select the Restore settings to their original defaults  option:

Finally, you’ll just need to confirm that you want to erase your current Chrome settings. If you do, click on Reset settings :

It’s important to keep in mind that this will erase your current search engine history, startup page, pinned tabs, extensions, bookmarks, and more. It will essentially revert your browser to a clean slate. However, it can remove any conflicting software or settings that are causing the HTTP/2 protocol error.

You can also consider resetting the experimental settings in your browser. These are not fully tested, functional features, so they could prevent your browser from communicating properly with a website.

To find your advanced experimental settings, search for the following address:

chrome://flags/

In the upper right-hand corner, select the Reset All  option. If certain features were accidentally enabled, this will revert them to the default settings:

Then, these changes will be applied whenever you relaunch Chrome!

7. Reinstall Google Chrome

After executing all these methods, you may still see the troublesome HTTP/2 protocol error. If so, there could be an error within the Google Chrome app. Even if you restored the default settings, you may want to consider reinstalling the entire browser.

First, you’ll need to delete the browser from your device. To do this with a macOS operating system, open the Applications  folder and move the Google Chrome app to the trash:

You’ll also want to delete any Chrome software updates. To find them, search for ‘ ~/Library/Google ’ on your device. In your results, delete the “GoogleSoftwareUpdate” folder:

If you’re a Windows user, you’ll use different steps to delete Chrome. To start, click on the Windows Start  button and search for the Control Panel . Open it, then find the Programs  option. Click on Uninstall a Program under Programs :

Now you’ll need to find Google Chrome and right-click on it. Lastly, hit Uninstall :

For both Mac and Windows users, you can reinstall Chrome in the same way. You’ll simply need to download the file included on the Google Chrome website :

Although this method could potentially solve the err_http2_protocol_error, it’s best only to use it as a last resort. Deleting Chrome will also remove all of its data, so be sure to try a few simpler solutions beforehand.

How To Fix the err_http2_protocol_error In a Device

So far, we’ve examined some methods to fix the err_http2_protocol_error using a web browser. However, in some cases, the browser may not be the source of the problem. To help you troubleshoot the issue, let’s discuss how to make your device compatible with the HTTP/2 protocol.

1. Reset Your Device’s Date and Time

Although it may not seem like a big deal, it’s important to have the correct date and time displayed on your device. If this information isn’t accurate, the incorrectly time-stamped data packets could be refused. This can lead to an err_http2_protocol_error.

With a Windows operating system, you can right-click on the clock in the bottom-right corner of your desktop. Then, select Adjust date and time :

If your computer isn’t automatically displaying the right time, you’ll need to disable the Set time automatically  setting. Beneath this, be sure to set the correct time zone:

Next, select the Change  button to Set the date and time manually . In the pop-up window, enter the correct date and time:

For Mac users, click on the Apple menu. Then, select System Preferences . Here, find the Date & Time  option:

In the bottom-left corner, click on the lock to make changes. Now you can deselect the Set date and time automatically  option and choose the correct values:

After you make these changes, try relaunching the web page!

2. Update Your Operating System

If you haven’t updated your device in a while, this can cause a multitude of performance issues . To ensure you can avoid any conflicts between your operating system and visited websites, you’ll need to check for recent upgrades.

Using a macOS device, you can start by performing a backup. Then, go to System Preferences > Software Update :

In this window, you’ll see any newly available updates. If you’re ready to install them, click on Update Now .

With a Windows computer, you can navigate to Start > Settings > Windows Update . If you haven’t already, install the latest update:

Once your device is up-to-date, it should be compatible with most websites that you want to visit. To see if this is the case, check whether the HTTP/2 protocol error is fixed. If not, continue with the following methods.

3. Flush the DNS

On the internet, the Domain Name System (DNS)  functions as an index for all available websites and their unique IP addresses. When you visit a website, your operating system or browser will save this information in a database. This can lead to faster loading times on revisited websites.

If you’re seeing the err_http2_protocol_error, you can try flushing your DNS cache . Put simply, this will erase the IP addresses  and other DNS data from your computer.

To flush a Mac DNS cache, open the command line interface called Terminal. In this window, enter the following command:

sudo killall -HUP mDNSResponder

This should successfully clear the DNS, removing the HTTP/2 protocol error. However, keep in mind that you’ll need to use slightly different processes for older versions of macOS.

If you have Windows 10, 8, 7, or XP, you can start by opening Command Prompt. In the command line, paste this command:

ipconfig /flushdns

You should see a confirmation message once the DNS has been flushed!

4. Check Antivirus Software

To keep your computer safe while you’re browsing, you likely have an antivirus program installed. Although this software offers many security benefits , it can occasionally flag certain applications as malicious. When this happens, it may unnecessarily limit your access to a website.

If none of the previous methods worked, you can check your antivirus software to see if it is functioning properly. First, open your notifications, which can display new security issues:

Most antivirus software will also have a quarantine list. This will contain all of the detected security threats on your computer:

In either of these areas, evaluate whether any unwanted applications are being flagged. If so, you may need to temporarily disable your antivirus software.

When the err_http2_protocol_error happens, it can be extremely frustrating. Instead of quickly viewing necessary online resources, you’ll only be able to see an error message. Luckily, you can take a few simple steps to solve this problem.

Even as a complete beginner, you can optimize your web browser to bypass HTTP/2 protocol errors. By simply clearing the cache, opening a private window, or turning off third-party extensions, you can successfully view the blocked content. If the problem lies in your operating system, you can consider performing software updates or flushing the DNS cache instead.

As a website owner, you’ll need to know that your web pages can be reached at any time. With Kinsta, you’re able to use our HTTP Status and Redirect Checker  to make sure your website is functioning correctly. Additionally, you can check your disk usage in the MyKinsta dashboard!

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CFR - Code of Federal Regulations Title 21

The information on this page is current as of Dec 22, 2023 .

For the most up-to-date version of CFR Title 21, go to the Electronic Code of Federal Regulations (eCFR).

|

[Code of Federal Regulations]

[Title 21, Volume 5]

[CITE: 21CFR312.32]

TITLE 21--FOOD AND DRUGS CHAPTER I--FOOD AND DRUG ADMINISTRATION SUBCHAPTER D - DRUGS FOR HUMAN USE Sec. 312.32 IND safety reporting. The following definitions of terms apply to this section: means any untoward medical occurrence associated with the use of a drug in humans, whether or not considered drug related. or An adverse event or suspected adverse reaction is considered "life-threatening" if, in the view of either the investigator or sponsor, its occurrence places the patient or subject at immediate risk of death. It does not include an adverse event or suspected adverse reaction that, had it occurred in a more severe form, might have caused death. or An adverse event or suspected adverse reaction is considered "serious" if, in the view of either the investigator or sponsor, it results in any of the following outcomes: Death, a life-threatening adverse event, inpatient hospitalization or prolongation of existing hospitalization, a persistent or significant incapacity or substantial disruption of the ability to conduct normal life functions, or a congenital anomaly/birth defect. Important medical events that may not result in death, be life-threatening, or require hospitalization may be considered serious when, based upon appropriate medical judgment, they may jeopardize the patient or subject and may require medical or surgical intervention to prevent one of the outcomes listed in this definition. Examples of such medical events include allergic bronchospasm requiring intensive treatment in an emergency room or at home, blood dyscrasias or convulsions that do not result in inpatient hospitalization, or the development of drug dependency or drug abuse. means any adverse event for which there is a reasonable possibility that the drug caused the adverse event. For the purposes of IND safety reporting, "reasonable possibility" means there is evidence to suggest a causal relationship between the drug and the adverse event. Suspected adverse reaction implies a lesser degree of certainty about causality than adverse reaction, which means any adverse event caused by a drug. or An adverse event or suspected adverse reaction is considered "unexpected" if it is not listed in the investigator brochure or is not listed at the specificity or severity that has been observed; or, if an investigator brochure is not required or available, is not consistent with the risk information described in the general investigational plan or elsewhere in the current application, as amended. For example, under this definition, hepatic necrosis would be unexpected (by virtue of greater severity) if the investigator brochure referred only to elevated hepatic enzymes or hepatitis. Similarly, cerebral thromboembolism and cerebral vasculitis would be unexpected (by virtue of greater specificity) if the investigator brochure listed only cerebral vascular accidents. "Unexpected," as used in this definition, also refers to adverse events or suspected adverse reactions that are mentioned in the investigator brochure as occurring with a class of drugs or as anticipated from the pharmacological properties of the drug, but are not specifically mentioned as occurring with the particular drug under investigation. The sponsor must promptly review all information relevant to the safety of the drug obtained or otherwise received by the sponsor from foreign or domestic sources, including information derived from any clinical or epidemiological investigations, animal or in vitro studies, reports in the scientific literature, and unpublished scientific papers, as well as reports from foreign regulatory authorities and reports of foreign commercial marketing experience for drugs that are not marketed in the United States. The sponsor must notify FDA and all participating investigators (i.e., all investigators to whom the sponsor is providing drug under its INDs or under any investigator's IND) in an IND safety report of potential serious risks, from clinical trials or any other source, as soon as possible, but in no case later than 15 calendar days after the sponsor determines that the information qualifies for reporting under paragraph (c)(1)(i), (c)(1)(ii), (c)(1)(iii), or (c)(1)(iv) of this section. In each IND safety report, the sponsor must identify all IND safety reports previously submitted to FDA concerning a similar suspected adverse reaction, and must analyze the significance of the suspected adverse reaction in light of previous, similar reports or any other relevant information. The sponsor must report any suspected adverse reaction that is both serious and unexpected. The sponsor must report an adverse event as a suspected adverse reaction only if there is evidence to suggest a causal relationship between the drug and the adverse event, such as: The sponsor must report any findings from epidemiological studies, pooled analysis of multiple studies, or clinical studies (other than those reported under paragraph (c)(1)(i) of this section), whether or not conducted under an IND, and whether or not conducted by the sponsor, that suggest a significant risk in humans exposed to the drug. Ordinarily, such a finding would result in a safety-related change in the protocol, informed consent, investigator brochure (excluding routine updates of these documents), or other aspects of the overall conduct of the clinical investigation. The sponsor must report any findings from animal or in vitro testing, whether or not conducted by the sponsor, that suggest a significant risk in humans exposed to the drug, such as reports of mutagenicity, teratogenicity, or carcinogenicity, or reports of significant organ toxicity at or near the expected human exposure. Ordinarily, any such findings would result in a safety-related change in the protocol, informed consent, investigator brochure (excluding routine updates of these documents), or other aspects of the overall conduct of the clinical investigation. The sponsor must report any clinically important increase in the rate of a serious suspected adverse reaction over that listed in the protocol or investigator brochure. The sponsor must submit each IND safety report in a narrative format or on FDA Form 3500A or in an electronic format that FDA can process, review, and archive. FDA will periodically issue guidance on how to provide the electronic submission (e.g., method of transmission, media, file formats, preparation and organization of files). The sponsor may submit foreign suspected adverse reactions on a Council for International Organizations of Medical Sciences (CIOMS) I Form instead of a FDA Form 3500A. Reports of overall findings or pooled analyses from published and unpublished in vitro, animal, epidemiological, or clinical studies must be submitted in a narrative format. Each notification to FDA must bear prominent identification of its contents, i.e., "IND Safety Report," and must be transmitted to the review division in the Center for Drug Evaluation and Research or in the Center for Biologics Evaluation and Research that has responsibility for review of the IND. Upon request from FDA, the sponsor must submit to FDA any additional data or information that the agency deems necessary, as soon as possible, but in no case later than 15 calendar days after receiving the request. The sponsor must also notify FDA of any unexpected fatal or life-threatening suspected adverse reaction as soon as possible but in no case later than 7 calendar days after the sponsor's initial receipt of the information. FDA may require a sponsor to submit IND safety reports in a format or at a frequency different than that required under this paragraph. The sponsor may also propose and adopt a different reporting format or frequency if the change is agreed to in advance by the director of the FDA review division that has responsibility for review of the IND. A sponsor of a clinical study of a drug marketed or approved in the United States that is conducted under an IND is required to submit IND safety reports for suspected adverse reactions that are observed in the clinical study, at domestic or foreign study sites. The sponsor must also submit safety information from the clinical study as prescribed by the postmarketing safety reporting requirements (e.g., §§ 310.305, 314.80, and 600.80 of this chapter). Study endpoints (e.g., mortality or major morbidity) must be reported to FDA by the sponsor as described in the protocol and ordinarily would not be reported under paragraph (c) of this section. However, if a serious and unexpected adverse event occurs for which there is evidence suggesting a causal relationship between the drug and the event (e.g., death from anaphylaxis), the event must be reported under § 312.32(c)(1)(i) as a serious and unexpected suspected adverse reaction even if it is a component of the study endpoint (e.g., all-cause mortality). (1) The sponsor must promptly investigate all safety information it receives. A safety report or other information submitted by a sponsor under this part (and any release by FDA of that report or information) does not necessarily reflect a conclusion by the sponsor or FDA that the report or information constitutes an admission that the drug caused or contributed to an adverse event. A sponsor need not admit, and may deny, that the report or information submitted by the sponsor constitutes an admission that the drug caused or contributed to an adverse event. [75 FR 59961, Sept. 29, 2010] This website has been translated to Spanish from English, and is updated often. It is possible that some links will connect you to content only available in English or some of the words on the page will appear in English until translation has been completed (usually within 24 hours). We appreciate your patience with the translation process. In the case of any discrepancy in meaning, the English version is considered official. Thank you for visiting esp.fda.gov/tabaco. 451 IMAGES [PDF] Designing a Case Study Protocol for Application in IS Research Figure 2 from Designing a Case Study Protocol for Application in IS Using a Protocol Template for Case Study The case study protocol case study protocol in research Case-study protocol VIDEO Study Protocol Assessment Video Presentation Group 7 Ms.P.Revathi,AP/AI&DS|Case Study of Telnet Protocol SNS Institutions Case Control Study JBS Case Study Analysis Phantom Protocol Group Lec 26: UML Case Study Cisco PPDIOO Model Explained: Understand Cisco PPDIOO Model with Practical Examples COMMENTS Case Study Method: A Step-by-Step Guide for Business Researchers Case study protocol is a formal document capturing the entire set of procedures involved in the collection of empirical material . It extends direction to researchers for gathering evidences, empirical material analysis, and case study reporting . This section includes a step-by-step guide that is used for the execution of the actual study. Case Study Methodology of Qualitative Research: Key Attributes and The reliability of a case study is best established by developing what he calls a 'case study protocol' (ibid., pp. 101-104). A case study protocol should have the following constituent elements: (a) an overview of the entire study including its objectives, (b) a detailed description of field procedures including the techniques of data ... PDF Designing a Case Study Protocol for Application in IS research A Case Study Protocol (CSP) is a set of guidelines that can be used to structure and govern a. case research project (Yin 1994). It therefore outlines the procedures and rules governing the. conduct of researcher(s) before, during and after a case research project. In addition, a case. Case Study Method: A Step-by-Step Guide for Business Researchers Case study protocol Field phase a. Contact b. Interact Reporting phase a. Case study reporting Foundation Phase This is the first and foremost step in conducting the case study. This phase is based on some considerations that research stu-dents should carefully look into. If there is ambiguity in under- How to Write a Research Protocol: Tips and Tricks Open in a separate window. First section: Description of the core center, contacts of the investigator/s, quantification of the involved centers. A research protocol must start from the definition of the coordinator of the whole study: all the details of the main investigator must be reported in the first paragraph. Guide: Designing and Conducting Case Studies Designing and Conducting Case Studies. This guide examines case studies, a form of qualitative descriptive research that is used to look at individuals, a small group of participants, or a group as a whole. Researchers collect data about participants using participant and direct observations, interviews, protocols, tests, examinations of ... How to write a research study protocol A study protocol is an essential part of a research project. It describes the study in detail to allow all members of the team to know and adhere to the steps of the methodology. Most funders, such as the NHS Health Research Authority in the United Kingdom, encourage researchers to publish their study protocols to create a record of the ... Developing a robust case study protocol Based on a systematic review of relevant literature, this paper catalogs the use of validity and reliability measures within academic publications between 2008 and 2018. The review analyzes case study research across 15 peer-reviewed journals (total of 1,372 articles) and highlights the application of validity and reliability measures. Protocol Writing in Clinical Research However, once the study is launched, the protocol should not be altered during the progression of the study or trials. If the changes during progress of study are minor, then that part of the study should be excluded from the analysis. ... Study design (cross-sectional, case-control, intervention study, RCT, etc.): Proper explanation should be ... Using a protocol template for case study planning The link between the purpose of the study and the data to be collected is explained in a case study protocol based on the templates suggested by Yin (2009) and Brereton et al. (2008), which is ... PDF Guidelines for completing a research protocol for observational studies The two most commonly used designs for observational studies are (A) case-control studies (including nested case-control studies) and (B) cohort studies. In the former, the study groups are chosen on the basis of their disease or outcome of interest. In a cohort study the comparison groups are identified according to an exposure of interest. 21 Elements of a Research Protocol with Example (WHO Guidelines) The research protocol is a document that describes the background, rationale, objective (s), design, methodology, statistical considerations and organization of a clinical trial. It is a document that outlines the clinical research study plan. Furthermore, the research protocol should be designed to provide a satisfactory answer to the research ... PDF Case Study Protocol Case Study Protocol NCPI Project 5.1 Introduction Project 5.1 of the National Center for Postsecondary Improvement is primarily responsible for researching the dynamics and effects of the assessment policies and practices of regional accrediting associations and state governments. More specifically, the project focuses on the Case Study Interview Protocol Case Study Interview Protocol 29 6.3 Case Study Questions The following outline shows the general format and flow of the D-B case study process. Where appropriate, the outline highlights how this layout differed between D-B and CM-GC projects. Again, to mitigate response bias from agency representatives, the questions and topics were inten ... THE CASE STUDY PROTOCOL The case study protocol defines the procedures and general rules to be followed using the protocol (Yin, 2009). Yin (2009) reminds the researcher that the protocol is a major way of increasing the reliability of case study research and is intended to guide the researcher in carrying out data collection from a single case. The case study ... Study protocol We evaluate study protocol submissions on a case-by-case basis and consider only those for proposed or ongoing studies that have not completed participant recruitment at the time of submission. We encourage authors to submit their study protocols well in advance of participant recruitment completion and confirm the study status within the cover ... Protocols Study protocols describe detailed plans and proposals for research projects that have not yet generated results. They consist of a single article in PLOS ONE that can be referenced in future papers.. Already common in the health sciences, sharing a study's design and analysis plan before the research is carried out improves transparency and coordinates effort. Designing a Case Study Protocol for Application in IS Research A set of guidelines that may be used by researchers in the development of Case Study Protocols are presented, which are an integral part of the case research design and contains the procedures for conducting the research, the research instrument itself, and the guidelines for data analysis. A review of the literature has shown that there is a growing call for the use of the case research ... Sage Research Methods Case study research has a long history within the natural sciences, social sciences, and humanities, dating back to the early 1920's. At first it was a useful way for researchers to make valid inferences from events outside the laboratory in ways consistent with the rigorous practices of investigation inside the lab. Case study interview protocol As part of this project, we are building a series of case studies around research funded by the HTA programme to identify the nature and range of impacts the programme has had, and how they came about. ... Case study interview protocol - The impact of the National Institute for Health Research Health Technology Assessment programme, 2003-13 ... The Case Study Protocol The protocol is a major way of increasing the reliability of case study research and is intended to guide the investigator in carrying out the data col­lection from a single case (again, even if the single case is one of several in a multiple-case study). Figure 3.2 gives a table of contents from an illustrative protocol, which was used in a ... Guidelines for conducting and reporting case study research in software 3.2 Case Study Protocol. The case study protocol is a container for the design decisions on the case study as well as field procedures for its carrying through. The protocol is a continuously changed document that is updated when the plans for the case study are changed. There are several reasons for keeping an updated version of a case study ... Effectiveness of self-management programmes for heart failure with Each study will undergo data extraction by two investigators independently. Phase 1 will involve a pilot and targeted extraction (approximately five studies) using a standardised protocol and case/study report form or instrument/tool .6 The areas of interest are study quality, trial characteristics, patient data and outcomes. PI and MB will ... Toward Developing a Framework for Conducting Case Study Research Later on, Tellis (1997) developed four stage of the methodology based on a modification of the methodology devised by Yin (1984): design the case study protocol (determine the required skills and develop and review the protocol), conduct the case study (prepare for data collection, distribute questionnaire, and conduct interviews), analyze case ... The effect of an online acceptance and commitment intervention on the Study protocol; Open access; Published: 18 June 2024 The effect of an online acceptance and commitment intervention on the meaning-making process in cancer patients following hematopoietic cell transplantation: study protocol for a randomized controlled trial enhanced with single-case experimental design Failure to Order Medical Imaging Leads to Permanent Vision Loss [Case The expert review of the case was critical of both ophthalmologists for failure to order a CT or X-ray to rule out a foreign body and that the delayed diagnosis of the foreign body likely caused the permanent vision loss. This case was settled for more than $1M. Analysis. The failure to order a test resulted in a delay in diagnosis and treatment. How To Fix the ERR_HTTP2_PROTOCOL_ERROR To understand the err_http2_protocol_error, let's first discuss the Hypertext Transfer Protocol (HTTP). This is the application protocol that allows the retrieval of online resources. A protocol is a set of rules that controls how data is transferred between clients. In this case, it can govern the HTTP requests between users and web browsers. Randomized Phase III Study of Amcenestrant Plus Palbociclib Versus Study Protocol. The following protocol information is provided solely to describe how the authors conducted the research underlying this article. The information provided may not reflect the complete protocol or any previous amendments or modifications. ... study protocol with any amendments, blank case report form, statistical analysis plan ... CFR For the most up-to-date version of CFR Title 21, go to the Electronic Code of Federal Regulations (eCFR). Sec. 312.32 IND safety reporting. (a) Definitions. The following definitions of terms apply to this section: Adverse event means any untoward medical occurrence associated with the use of a drug in humans, whether or not considered drug ... The short- and longer-term effects of brief behavioral parent training Background: The access to and uptake of evidence-based behavioral parent training for children with behavioral difficulties (i.e., oppositional, defiant, aggressive, hyperactive, impulsive, and inattentive behavior) are currently limited because of a scarcity of certified therapists and long waiting lists. These problems are in part due to the long and sometimes perceived as rigid nature of ... essay homework paper phd project resume review speech study thesis