action research study design

Qualitative study design: Action research

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Action research / Participatory Action Research

These methods focus on the emancipation, collaboration and empowerment of the participants. This methodology is appropriate for collaborative research with groups, especially marginalised groups, where there is more flexibility in how the research is conducted and considers feedback from the participants. 

Has three primary characteristics:  

Action oriented, participants are actively involved in the research.

involvement by participants in the research, collaborative process between participant and researcher - empowerment of participants. The participants have more of a say in what is being researched and how they want the research to be conducted.

cycle is iterative so that it is flexible and responsive to a changing situation.  

• Questionnaires
• Oral recordings
• Focus groups,
• Photovoice (use of images or video to capture the local environment / community and to share with others)
• Informal conversations 

Produces knowledge from marginalised people's point of view and can lead to more personalised interventions.  

Provides a voice for people to speak about their issues and the ability to improve their own lives. People take an active role in implementing any actions arising from the research. 

Transforms social reality by linking theory and practice.  

Limitations

Open ended questions are mainly used, and these can be misinterpreted by researcher – data needs to be cross-checked with other sources.

Data ownership between researcher and research participants needs to be negotiated and clearly stated from the beginning of the project.

Ethical considerations with privacy and confidentiality.

This method is not considered scientific as it is more fluid in its gathering of information and is considered an unconventional research method – thus it may not attract much funding.

Example questions

• What is the cultural significance of yarning amongst Aboriginal people? 

Macro Question:

• “What would it take to improve the stability of young people’s living situations?” 

Micro Questions: 

• “What can we do to better engage with accommodation service providers?” 
• “What can we do to improve the service knowledge of young people?” 
• “What can we do to measure stability outcomes for our clients?” 

(Department of Social Services) 

Example studies

• Miller, A., Massey, P. D., Judd, J., Kelly, J., Durrheim, D. N., Clough, A. R., . . . Saggers, S. (2015). Using a participatory action research framework to listen to Aboriginal and Torres Strait Islander people in Australia about pandemic influenza.  Rural and Remote Health , 15(3), 2923-2923.  
• Spinney, A. (2013). Safe from the Start? An Action Research Project on Early Intervention Materials for Children Affected by Domestic and Family Violence. Children & Society, 27(5), 397-405. doi:10.1111/j.1099-0860.2012.00454.x 
• Department of Social Services. (2019).  On PAR  - Using participatory action research to improve early intervention. 
• Liamputtong, P. (2013). Qualitative research methods (4th ed.). South Melbourne: Oxford  University Press. 
• Mills, J., & Birks, M. (2014). Qualitative Methodology: A Practical Guide. Retrieved from https://methods.sagepub.com/book/qualitative-methodology-a-practical-guide doi:10.4135/9781473920163   
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Action research

A type of applied research designed to find the most effective way to bring about a desired social change or to solve a practical problem, usually in collaboration with those being researched.

SAGE Research Methods Videos

How do you define action research.

Professor David Coghlan explains action research as an approach that crosses many academic disciplines yet has a shared focus on taking action to address a problem. He describes the difference between this approach and empirical scientific approaches, particularly highlighting the challenge of getting action research to be taken seriously by academic journals

Dr. Nataliya Ivankova defines action research as using systematic research principles to address an issue in everyday life. She delineates the six steps of action research, and illustrates the concept using an anti-diabetes project in an urban area.

This is just one segment in a whole series about action research. You can find the rest of the series in our SAGE database, Research Methods:

Videos covering research methods and statistics

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Introduction

Before beginning your paper, you need to decide how you plan to design the study .

The research design refers to the overall strategy and analytical approach that you have chosen in order to integrate, in a coherent and logical way, the different components of the study, thus ensuring that the research problem will be thoroughly investigated. It constitutes the blueprint for the collection, measurement, and interpretation of information and data. Note that the research problem determines the type of design you choose, not the other way around!

De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Trochim, William M.K. Research Methods Knowledge Base. 2006.

General Structure and Writing Style

The function of a research design is to ensure that the evidence obtained enables you to effectively address the research problem logically and as unambiguously as possible . In social sciences research, obtaining information relevant to the research problem generally entails specifying the type of evidence needed to test the underlying assumptions of a theory, to evaluate a program, or to accurately describe and assess meaning related to an observable phenomenon.

With this in mind, a common mistake made by researchers is that they begin their investigations before they have thought critically about what information is required to address the research problem. Without attending to these design issues beforehand, the overall research problem will not be adequately addressed and any conclusions drawn will run the risk of being weak and unconvincing. As a consequence, the overall validity of the study will be undermined.

The length and complexity of describing the research design in your paper can vary considerably, but any well-developed description will achieve the following :

• Identify the research problem clearly and justify its selection, particularly in relation to any valid alternative designs that could have been used,
• Review and synthesize previously published literature associated with the research problem,
• Clearly and explicitly specify hypotheses [i.e., research questions] central to the problem,
• Effectively describe the information and/or data which will be necessary for an adequate testing of the hypotheses and explain how such information and/or data will be obtained, and
• Describe the methods of analysis to be applied to the data in determining whether or not the hypotheses are true or false.

The research design is usually incorporated into the introduction of your paper . You can obtain an overall sense of what to do by reviewing studies that have utilized the same research design [e.g., using a case study approach]. This can help you develop an outline to follow for your own paper.

NOTE: Use the SAGE Research Methods Online and Cases and the SAGE Research Methods Videos databases to search for scholarly resources on how to apply specific research designs and methods . The Research Methods Online database contains links to more than 175,000 pages of SAGE publisher's book, journal, and reference content on quantitative, qualitative, and mixed research methodologies. Also included is a collection of case studies of social research projects that can be used to help you better understand abstract or complex methodological concepts. The Research Methods Videos database contains hours of tutorials, interviews, video case studies, and mini-documentaries covering the entire research process.

Creswell, John W. and J. David Creswell. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 5th edition. Thousand Oaks, CA: Sage, 2018; De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Leedy, Paul D. and Jeanne Ellis Ormrod. Practical Research: Planning and Design . Tenth edition. Boston, MA: Pearson, 2013; Vogt, W. Paul, Dianna C. Gardner, and Lynne M. Haeffele. When to Use What Research Design . New York: Guilford, 2012.

Action Research Design

Definition and Purpose

The essentials of action research design follow a characteristic cycle whereby initially an exploratory stance is adopted, where an understanding of a problem is developed and plans are made for some form of interventionary strategy. Then the intervention is carried out [the "action" in action research] during which time, pertinent observations are collected in various forms. The new interventional strategies are carried out, and this cyclic process repeats, continuing until a sufficient understanding of [or a valid implementation solution for] the problem is achieved. The protocol is iterative or cyclical in nature and is intended to foster deeper understanding of a given situation, starting with conceptualizing and particularizing the problem and moving through several interventions and evaluations.

What do these studies tell you ?

• This is a collaborative and adaptive research design that lends itself to use in work or community situations.
• Design focuses on pragmatic and solution-driven research outcomes rather than testing theories.
• When practitioners use action research, it has the potential to increase the amount they learn consciously from their experience; the action research cycle can be regarded as a learning cycle.
• Action research studies often have direct and obvious relevance to improving practice and advocating for change.
• There are no hidden controls or preemption of direction by the researcher.

What these studies don't tell you ?

• It is harder to do than conducting conventional research because the researcher takes on responsibilities of advocating for change as well as for researching the topic.
• Action research is much harder to write up because it is less likely that you can use a standard format to report your findings effectively [i.e., data is often in the form of stories or observation].
• Personal over-involvement of the researcher may bias research results.
• The cyclic nature of action research to achieve its twin outcomes of action [e.g. change] and research [e.g. understanding] is time-consuming and complex to conduct.
• Advocating for change usually requires buy-in from study participants.

Coghlan, David and Mary Brydon-Miller. The Sage Encyclopedia of Action Research . Thousand Oaks, CA:  Sage, 2014; Efron, Sara Efrat and Ruth Ravid. Action Research in Education: A Practical Guide . New York: Guilford, 2013; Gall, Meredith. Educational Research: An Introduction . Chapter 18, Action Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Kemmis, Stephen and Robin McTaggart. “Participatory Action Research.” In Handbook of Qualitative Research . Norman Denzin and Yvonna S. Lincoln, eds. 2nd ed. (Thousand Oaks, CA: SAGE, 2000), pp. 567-605; McNiff, Jean. Writing and Doing Action Research . London: Sage, 2014; Reason, Peter and Hilary Bradbury. Handbook of Action Research: Participative Inquiry and Practice . Thousand Oaks, CA: SAGE, 2001.

Case Study Design

A case study is an in-depth study of a particular research problem rather than a sweeping statistical survey or comprehensive comparative inquiry. It is often used to narrow down a very broad field of research into one or a few easily researchable examples. The case study research design is also useful for testing whether a specific theory and model actually applies to phenomena in the real world. It is a useful design when not much is known about an issue or phenomenon.

• Approach excels at bringing us to an understanding of a complex issue through detailed contextual analysis of a limited number of events or conditions and their relationships.
• A researcher using a case study design can apply a variety of methodologies and rely on a variety of sources to investigate a research problem.
• Design can extend experience or add strength to what is already known through previous research.
• Social scientists, in particular, make wide use of this research design to examine contemporary real-life situations and provide the basis for the application of concepts and theories and the extension of methodologies.
• The design can provide detailed descriptions of specific and rare cases.
• A single or small number of cases offers little basis for establishing reliability or to generalize the findings to a wider population of people, places, or things.
• Intense exposure to the study of a case may bias a researcher's interpretation of the findings.
• Design does not facilitate assessment of cause and effect relationships.
• Vital information may be missing, making the case hard to interpret.
• The case may not be representative or typical of the larger problem being investigated.
• If the criteria for selecting a case is because it represents a very unusual or unique phenomenon or problem for study, then your interpretation of the findings can only apply to that particular case.

Case Studies. Writing@CSU. Colorado State University; Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 4, Flexible Methods: Case Study Design. 2nd ed. New York: Columbia University Press, 1999; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Greenhalgh, Trisha, editor. Case Study Evaluation: Past, Present and Future Challenges . Bingley, UK: Emerald Group Publishing, 2015; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Stake, Robert E. The Art of Case Study Research . Thousand Oaks, CA: SAGE, 1995; Yin, Robert K. Case Study Research: Design and Theory . Applied Social Research Methods Series, no. 5. 3rd ed. Thousand Oaks, CA: SAGE, 2003.

Causal Design

Causality studies may be thought of as understanding a phenomenon in terms of conditional statements in the form, “If X, then Y.” This type of research is used to measure what impact a specific change will have on existing norms and assumptions. Most social scientists seek causal explanations that reflect tests of hypotheses. Causal effect (nomothetic perspective) occurs when variation in one phenomenon, an independent variable, leads to or results, on average, in variation in another phenomenon, the dependent variable.

Conditions necessary for determining causality:

• Empirical association -- a valid conclusion is based on finding an association between the independent variable and the dependent variable.
• Appropriate time order -- to conclude that causation was involved, one must see that cases were exposed to variation in the independent variable before variation in the dependent variable.
• Nonspuriousness -- a relationship between two variables that is not due to variation in a third variable.
• Causality research designs assist researchers in understanding why the world works the way it does through the process of proving a causal link between variables and by the process of eliminating other possibilities.
• Replication is possible.
• There is greater confidence the study has internal validity due to the systematic subject selection and equity of groups being compared.
• Not all relationships are causal! The possibility always exists that, by sheer coincidence, two unrelated events appear to be related [e.g., Punxatawney Phil could accurately predict the duration of Winter for five consecutive years but, the fact remains, he's just a big, furry rodent].
• Conclusions about causal relationships are difficult to determine due to a variety of extraneous and confounding variables that exist in a social environment. This means causality can only be inferred, never proven.
• If two variables are correlated, the cause must come before the effect. However, even though two variables might be causally related, it can sometimes be difficult to determine which variable comes first and, therefore, to establish which variable is the actual cause and which is the  actual effect.

Beach, Derek and Rasmus Brun Pedersen. Causal Case Study Methods: Foundations and Guidelines for Comparing, Matching, and Tracing . Ann Arbor, MI: University of Michigan Press, 2016; Bachman, Ronet. The Practice of Research in Criminology and Criminal Justice . Chapter 5, Causation and Research Designs. 3rd ed. Thousand Oaks, CA: Pine Forge Press, 2007; Brewer, Ernest W. and Jennifer Kubn. “Causal-Comparative Design.” In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 125-132; Causal Research Design: Experimentation. Anonymous SlideShare Presentation; Gall, Meredith. Educational Research: An Introduction . Chapter 11, Nonexperimental Research: Correlational Designs. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Trochim, William M.K. Research Methods Knowledge Base. 2006.

Cohort Design

Often used in the medical sciences, but also found in the applied social sciences, a cohort study generally refers to a study conducted over a period of time involving members of a population which the subject or representative member comes from, and who are united by some commonality or similarity. Using a quantitative framework, a cohort study makes note of statistical occurrence within a specialized subgroup, united by same or similar characteristics that are relevant to the research problem being investigated, rather than studying statistical occurrence within the general population. Using a qualitative framework, cohort studies generally gather data using methods of observation. Cohorts can be either "open" or "closed."

• Open Cohort Studies [dynamic populations, such as the population of Los Angeles] involve a population that is defined just by the state of being a part of the study in question (and being monitored for the outcome). Date of entry and exit from the study is individually defined, therefore, the size of the study population is not constant. In open cohort studies, researchers can only calculate rate based data, such as, incidence rates and variants thereof.
• Closed Cohort Studies [static populations, such as patients entered into a clinical trial] involve participants who enter into the study at one defining point in time and where it is presumed that no new participants can enter the cohort. Given this, the number of study participants remains constant (or can only decrease).
• The use of cohorts is often mandatory because a randomized control study may be unethical. For example, you cannot deliberately expose people to asbestos, you can only study its effects on those who have already been exposed. Research that measures risk factors often relies upon cohort designs.
• Because cohort studies measure potential causes before the outcome has occurred, they can demonstrate that these “causes” preceded the outcome, thereby avoiding the debate as to which is the cause and which is the effect.
• Cohort analysis is highly flexible and can provide insight into effects over time and related to a variety of different types of changes [e.g., social, cultural, political, economic, etc.].
• Either original data or secondary data can be used in this design.
• In cases where a comparative analysis of two cohorts is made [e.g., studying the effects of one group exposed to asbestos and one that has not], a researcher cannot control for all other factors that might differ between the two groups. These factors are known as confounding variables.
• Cohort studies can end up taking a long time to complete if the researcher must wait for the conditions of interest to develop within the group. This also increases the chance that key variables change during the course of the study, potentially impacting the validity of the findings.
• Due to the lack of randominization in the cohort design, its external validity is lower than that of study designs where the researcher randomly assigns participants.

Healy P, Devane D. “Methodological Considerations in Cohort Study Designs.” Nurse Researcher 18 (2011): 32-36; Glenn, Norval D, editor. Cohort Analysis . 2nd edition. Thousand Oaks, CA: Sage, 2005; Levin, Kate Ann. Study Design IV: Cohort Studies. Evidence-Based Dentistry 7 (2003): 51–52; Payne, Geoff. “Cohort Study.” In The SAGE Dictionary of Social Research Methods . Victor Jupp, editor. (Thousand Oaks, CA: Sage, 2006), pp. 31-33; Study Design 101. Himmelfarb Health Sciences Library. George Washington University, November 2011; Cohort Study. Wikipedia.

Cross-Sectional Design

Cross-sectional research designs have three distinctive features: no time dimension; a reliance on existing differences rather than change following intervention; and, groups are selected based on existing differences rather than random allocation. The cross-sectional design can only measure differences between or from among a variety of people, subjects, or phenomena rather than a process of change. As such, researchers using this design can only employ a relatively passive approach to making causal inferences based on findings.

• Cross-sectional studies provide a clear 'snapshot' of the outcome and the characteristics associated with it, at a specific point in time.
• Unlike an experimental design, where there is an active intervention by the researcher to produce and measure change or to create differences, cross-sectional designs focus on studying and drawing inferences from existing differences between people, subjects, or phenomena.
• Entails collecting data at and concerning one point in time. While longitudinal studies involve taking multiple measures over an extended period of time, cross-sectional research is focused on finding relationships between variables at one moment in time.
• Groups identified for study are purposely selected based upon existing differences in the sample rather than seeking random sampling.
• Cross-section studies are capable of using data from a large number of subjects and, unlike observational studies, is not geographically bound.
• Can estimate prevalence of an outcome of interest because the sample is usually taken from the whole population.
• Because cross-sectional designs generally use survey techniques to gather data, they are relatively inexpensive and take up little time to conduct.
• Finding people, subjects, or phenomena to study that are very similar except in one specific variable can be difficult.
• Results are static and time bound and, therefore, give no indication of a sequence of events or reveal historical or temporal contexts.
• Studies cannot be utilized to establish cause and effect relationships.
• This design only provides a snapshot of analysis so there is always the possibility that a study could have differing results if another time-frame had been chosen.
• There is no follow up to the findings.

Bethlehem, Jelke. "7: Cross-sectional Research." In Research Methodology in the Social, Behavioural and Life Sciences . Herman J Adèr and Gideon J Mellenbergh, editors. (London, England: Sage, 1999), pp. 110-43; Bourque, Linda B. “Cross-Sectional Design.” In  The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman, and Tim Futing Liao. (Thousand Oaks, CA: 2004), pp. 230-231; Hall, John. “Cross-Sectional Survey Design.” In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 173-174; Helen Barratt, Maria Kirwan. Cross-Sectional Studies: Design Application, Strengths and Weaknesses of Cross-Sectional Studies. Healthknowledge, 2009. Cross-Sectional Study. Wikipedia.

Descriptive Design

Descriptive research designs help provide answers to the questions of who, what, when, where, and how associated with a particular research problem; a descriptive study cannot conclusively ascertain answers to why. Descriptive research is used to obtain information concerning the current status of the phenomena and to describe "what exists" with respect to variables or conditions in a situation.

• The subject is being observed in a completely natural and unchanged natural environment. True experiments, whilst giving analyzable data, often adversely influence the normal behavior of the subject [a.k.a., the Heisenberg effect whereby measurements of certain systems cannot be made without affecting the systems].
• Descriptive research is often used as a pre-cursor to more quantitative research designs with the general overview giving some valuable pointers as to what variables are worth testing quantitatively.
• If the limitations are understood, they can be a useful tool in developing a more focused study.
• Descriptive studies can yield rich data that lead to important recommendations in practice.
• Appoach collects a large amount of data for detailed analysis.
• The results from a descriptive research cannot be used to discover a definitive answer or to disprove a hypothesis.
• Because descriptive designs often utilize observational methods [as opposed to quantitative methods], the results cannot be replicated.
• The descriptive function of research is heavily dependent on instrumentation for measurement and observation.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 5, Flexible Methods: Descriptive Research. 2nd ed. New York: Columbia University Press, 1999; Given, Lisa M. "Descriptive Research." In Encyclopedia of Measurement and Statistics . Neil J. Salkind and Kristin Rasmussen, editors. (Thousand Oaks, CA: Sage, 2007), pp. 251-254; McNabb, Connie. Descriptive Research Methodologies. Powerpoint Presentation; Shuttleworth, Martyn. Descriptive Research Design, September 26, 2008; Erickson, G. Scott. "Descriptive Research Design." In New Methods of Market Research and Analysis . (Northampton, MA: Edward Elgar Publishing, 2017), pp. 51-77; Sahin, Sagufta, and Jayanta Mete. "A Brief Study on Descriptive Research: Its Nature and Application in Social Science." International Journal of Research and Analysis in Humanities 1 (2021): 11; K. Swatzell and P. Jennings. “Descriptive Research: The Nuts and Bolts.” Journal of the American Academy of Physician Assistants 20 (2007), pp. 55-56; Kane, E. Doing Your Own Research: Basic Descriptive Research in the Social Sciences and Humanities . London: Marion Boyars, 1985.

Experimental Design

A blueprint of the procedure that enables the researcher to maintain control over all factors that may affect the result of an experiment. In doing this, the researcher attempts to determine or predict what may occur. Experimental research is often used where there is time priority in a causal relationship (cause precedes effect), there is consistency in a causal relationship (a cause will always lead to the same effect), and the magnitude of the correlation is great. The classic experimental design specifies an experimental group and a control group. The independent variable is administered to the experimental group and not to the control group, and both groups are measured on the same dependent variable. Subsequent experimental designs have used more groups and more measurements over longer periods. True experiments must have control, randomization, and manipulation.

• Experimental research allows the researcher to control the situation. In so doing, it allows researchers to answer the question, “What causes something to occur?”
• Permits the researcher to identify cause and effect relationships between variables and to distinguish placebo effects from treatment effects.
• Experimental research designs support the ability to limit alternative explanations and to infer direct causal relationships in the study.
• Approach provides the highest level of evidence for single studies.
• The design is artificial, and results may not generalize well to the real world.
• The artificial settings of experiments may alter the behaviors or responses of participants.
• Experimental designs can be costly if special equipment or facilities are needed.
• Some research problems cannot be studied using an experiment because of ethical or technical reasons.
• Difficult to apply ethnographic and other qualitative methods to experimentally designed studies.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 7, Flexible Methods: Experimental Research. 2nd ed. New York: Columbia University Press, 1999; Chapter 2: Research Design, Experimental Designs. School of Psychology, University of New England, 2000; Chow, Siu L. "Experimental Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 448-453; "Experimental Design." In Social Research Methods . Nicholas Walliman, editor. (London, England: Sage, 2006), pp, 101-110; Experimental Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Kirk, Roger E. Experimental Design: Procedures for the Behavioral Sciences . 4th edition. Thousand Oaks, CA: Sage, 2013; Trochim, William M.K. Experimental Design. Research Methods Knowledge Base. 2006; Rasool, Shafqat. Experimental Research. Slideshare presentation.

Exploratory Design

An exploratory design is conducted about a research problem when there are few or no earlier studies to refer to or rely upon to predict an outcome . The focus is on gaining insights and familiarity for later investigation or undertaken when research problems are in a preliminary stage of investigation. Exploratory designs are often used to establish an understanding of how best to proceed in studying an issue or what methodology would effectively apply to gathering information about the issue.

The goals of exploratory research are intended to produce the following possible insights:

• Familiarity with basic details, settings, and concerns.
• Well grounded picture of the situation being developed.
• Generation of new ideas and assumptions.
• Development of tentative theories or hypotheses.
• Determination about whether a study is feasible in the future.
• Issues get refined for more systematic investigation and formulation of new research questions.
• Direction for future research and techniques get developed.
• Design is a useful approach for gaining background information on a particular topic.
• Exploratory research is flexible and can address research questions of all types (what, why, how).
• Provides an opportunity to define new terms and clarify existing concepts.
• Exploratory research is often used to generate formal hypotheses and develop more precise research problems.
• In the policy arena or applied to practice, exploratory studies help establish research priorities and where resources should be allocated.
• Exploratory research generally utilizes small sample sizes and, thus, findings are typically not generalizable to the population at large.
• The exploratory nature of the research inhibits an ability to make definitive conclusions about the findings. They provide insight but not definitive conclusions.
• The research process underpinning exploratory studies is flexible but often unstructured, leading to only tentative results that have limited value to decision-makers.
• Design lacks rigorous standards applied to methods of data gathering and analysis because one of the areas for exploration could be to determine what method or methodologies could best fit the research problem.

Cuthill, Michael. “Exploratory Research: Citizen Participation, Local Government, and Sustainable Development in Australia.” Sustainable Development 10 (2002): 79-89; Streb, Christoph K. "Exploratory Case Study." In Encyclopedia of Case Study Research . Albert J. Mills, Gabrielle Durepos and Eiden Wiebe, editors. (Thousand Oaks, CA: Sage, 2010), pp. 372-374; Taylor, P. J., G. Catalano, and D.R.F. Walker. “Exploratory Analysis of the World City Network.” Urban Studies 39 (December 2002): 2377-2394; Exploratory Research. Wikipedia.

Field Research Design

Sometimes referred to as ethnography or participant observation, designs around field research encompass a variety of interpretative procedures [e.g., observation and interviews] rooted in qualitative approaches to studying people individually or in groups while inhabiting their natural environment as opposed to using survey instruments or other forms of impersonal methods of data gathering. Information acquired from observational research takes the form of “ field notes ” that involves documenting what the researcher actually sees and hears while in the field. Findings do not consist of conclusive statements derived from numbers and statistics because field research involves analysis of words and observations of behavior. Conclusions, therefore, are developed from an interpretation of findings that reveal overriding themes, concepts, and ideas. More information can be found HERE .

• Field research is often necessary to fill gaps in understanding the research problem applied to local conditions or to specific groups of people that cannot be ascertained from existing data.
• The research helps contextualize already known information about a research problem, thereby facilitating ways to assess the origins, scope, and scale of a problem and to gage the causes, consequences, and means to resolve an issue based on deliberate interaction with people in their natural inhabited spaces.
• Enables the researcher to corroborate or confirm data by gathering additional information that supports or refutes findings reported in prior studies of the topic.
• Because the researcher in embedded in the field, they are better able to make observations or ask questions that reflect the specific cultural context of the setting being investigated.
• Observing the local reality offers the opportunity to gain new perspectives or obtain unique data that challenges existing theoretical propositions or long-standing assumptions found in the literature.

What these studies don't tell you

• A field research study requires extensive time and resources to carry out the multiple steps involved with preparing for the gathering of information, including for example, examining background information about the study site, obtaining permission to access the study site, and building trust and rapport with subjects.
• Requires a commitment to staying engaged in the field to ensure that you can adequately document events and behaviors as they unfold.
• The unpredictable nature of fieldwork means that researchers can never fully control the process of data gathering. They must maintain a flexible approach to studying the setting because events and circumstances can change quickly or unexpectedly.
• Findings can be difficult to interpret and verify without access to documents and other source materials that help to enhance the credibility of information obtained from the field  [i.e., the act of triangulating the data].
• Linking the research problem to the selection of study participants inhabiting their natural environment is critical. However, this specificity limits the ability to generalize findings to different situations or in other contexts or to infer courses of action applied to other settings or groups of people.
• The reporting of findings must take into account how the researcher themselves may have inadvertently affected respondents and their behaviors.

Historical Design

The purpose of a historical research design is to collect, verify, and synthesize evidence from the past to establish facts that defend or refute a hypothesis. It uses secondary sources and a variety of primary documentary evidence, such as, diaries, official records, reports, archives, and non-textual information [maps, pictures, audio and visual recordings]. The limitation is that the sources must be both authentic and valid.

• The historical research design is unobtrusive; the act of research does not affect the results of the study.
• The historical approach is well suited for trend analysis.
• Historical records can add important contextual background required to more fully understand and interpret a research problem.
• There is often no possibility of researcher-subject interaction that could affect the findings.
• Historical sources can be used over and over to study different research problems or to replicate a previous study.
• The ability to fulfill the aims of your research are directly related to the amount and quality of documentation available to understand the research problem.
• Since historical research relies on data from the past, there is no way to manipulate it to control for contemporary contexts.
• Interpreting historical sources can be very time consuming.
• The sources of historical materials must be archived consistently to ensure access. This may especially challenging for digital or online-only sources.
• Original authors bring their own perspectives and biases to the interpretation of past events and these biases are more difficult to ascertain in historical resources.
• Due to the lack of control over external variables, historical research is very weak with regard to the demands of internal validity.
• It is rare that the entirety of historical documentation needed to fully address a research problem is available for interpretation, therefore, gaps need to be acknowledged.

Howell, Martha C. and Walter Prevenier. From Reliable Sources: An Introduction to Historical Methods . Ithaca, NY: Cornell University Press, 2001; Lundy, Karen Saucier. "Historical Research." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor. (Thousand Oaks, CA: Sage, 2008), pp. 396-400; Marius, Richard. and Melvin E. Page. A Short Guide to Writing about History . 9th edition. Boston, MA: Pearson, 2015; Savitt, Ronald. “Historical Research in Marketing.” Journal of Marketing 44 (Autumn, 1980): 52-58;  Gall, Meredith. Educational Research: An Introduction . Chapter 16, Historical Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007.

Longitudinal Design

A longitudinal study follows the same sample over time and makes repeated observations. For example, with longitudinal surveys, the same group of people is interviewed at regular intervals, enabling researchers to track changes over time and to relate them to variables that might explain why the changes occur. Longitudinal research designs describe patterns of change and help establish the direction and magnitude of causal relationships. Measurements are taken on each variable over two or more distinct time periods. This allows the researcher to measure change in variables over time. It is a type of observational study sometimes referred to as a panel study.

• Longitudinal data facilitate the analysis of the duration of a particular phenomenon.
• Enables survey researchers to get close to the kinds of causal explanations usually attainable only with experiments.
• The design permits the measurement of differences or change in a variable from one period to another [i.e., the description of patterns of change over time].
• Longitudinal studies facilitate the prediction of future outcomes based upon earlier factors.
• The data collection method may change over time.
• Maintaining the integrity of the original sample can be difficult over an extended period of time.
• It can be difficult to show more than one variable at a time.
• This design often needs qualitative research data to explain fluctuations in the results.
• A longitudinal research design assumes present trends will continue unchanged.
• It can take a long period of time to gather results.
• There is a need to have a large sample size and accurate sampling to reach representativness.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 6, Flexible Methods: Relational and Longitudinal Research. 2nd ed. New York: Columbia University Press, 1999; Forgues, Bernard, and Isabelle Vandangeon-Derumez. "Longitudinal Analyses." In Doing Management Research . Raymond-Alain Thiétart and Samantha Wauchope, editors. (London, England: Sage, 2001), pp. 332-351; Kalaian, Sema A. and Rafa M. Kasim. "Longitudinal Studies." In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 440-441; Menard, Scott, editor. Longitudinal Research . Thousand Oaks, CA: Sage, 2002; Ployhart, Robert E. and Robert J. Vandenberg. "Longitudinal Research: The Theory, Design, and Analysis of Change.” Journal of Management 36 (January 2010): 94-120; Longitudinal Study. Wikipedia.

Meta-Analysis Design

Meta-analysis is an analytical methodology designed to systematically evaluate and summarize the results from a number of individual studies, thereby, increasing the overall sample size and the ability of the researcher to study effects of interest. The purpose is to not simply summarize existing knowledge, but to develop a new understanding of a research problem using synoptic reasoning. The main objectives of meta-analysis include analyzing differences in the results among studies and increasing the precision by which effects are estimated. A well-designed meta-analysis depends upon strict adherence to the criteria used for selecting studies and the availability of information in each study to properly analyze their findings. Lack of information can severely limit the type of analyzes and conclusions that can be reached. In addition, the more dissimilarity there is in the results among individual studies [heterogeneity], the more difficult it is to justify interpretations that govern a valid synopsis of results. A meta-analysis needs to fulfill the following requirements to ensure the validity of your findings:

• Clearly defined description of objectives, including precise definitions of the variables and outcomes that are being evaluated;
• A well-reasoned and well-documented justification for identification and selection of the studies;
• Assessment and explicit acknowledgment of any researcher bias in the identification and selection of those studies;
• Description and evaluation of the degree of heterogeneity among the sample size of studies reviewed; and,
• Justification of the techniques used to evaluate the studies.
• Can be an effective strategy for determining gaps in the literature.
• Provides a means of reviewing research published about a particular topic over an extended period of time and from a variety of sources.
• Is useful in clarifying what policy or programmatic actions can be justified on the basis of analyzing research results from multiple studies.
• Provides a method for overcoming small sample sizes in individual studies that previously may have had little relationship to each other.
• Can be used to generate new hypotheses or highlight research problems for future studies.
• Small violations in defining the criteria used for content analysis can lead to difficult to interpret and/or meaningless findings.
• A large sample size can yield reliable, but not necessarily valid, results.
• A lack of uniformity regarding, for example, the type of literature reviewed, how methods are applied, and how findings are measured within the sample of studies you are analyzing, can make the process of synthesis difficult to perform.
• Depending on the sample size, the process of reviewing and synthesizing multiple studies can be very time consuming.

Beck, Lewis W. "The Synoptic Method." The Journal of Philosophy 36 (1939): 337-345; Cooper, Harris, Larry V. Hedges, and Jeffrey C. Valentine, eds. The Handbook of Research Synthesis and Meta-Analysis . 2nd edition. New York: Russell Sage Foundation, 2009; Guzzo, Richard A., Susan E. Jackson and Raymond A. Katzell. “Meta-Analysis Analysis.” In Research in Organizational Behavior , Volume 9. (Greenwich, CT: JAI Press, 1987), pp 407-442; Lipsey, Mark W. and David B. Wilson. Practical Meta-Analysis . Thousand Oaks, CA: Sage Publications, 2001; Study Design 101. Meta-Analysis. The Himmelfarb Health Sciences Library, George Washington University; Timulak, Ladislav. “Qualitative Meta-Analysis.” In The SAGE Handbook of Qualitative Data Analysis . Uwe Flick, editor. (Los Angeles, CA: Sage, 2013), pp. 481-495; Walker, Esteban, Adrian V. Hernandez, and Micheal W. Kattan. "Meta-Analysis: It's Strengths and Limitations." Cleveland Clinic Journal of Medicine 75 (June 2008): 431-439.

Mixed-Method Design

• Narrative and non-textual information can add meaning to numeric data, while numeric data can add precision to narrative and non-textual information.
• Can utilize existing data while at the same time generating and testing a grounded theory approach to describe and explain the phenomenon under study.
• A broader, more complex research problem can be investigated because the researcher is not constrained by using only one method.
• The strengths of one method can be used to overcome the inherent weaknesses of another method.
• Can provide stronger, more robust evidence to support a conclusion or set of recommendations.
• May generate new knowledge new insights or uncover hidden insights, patterns, or relationships that a single methodological approach might not reveal.
• Produces more complete knowledge and understanding of the research problem that can be used to increase the generalizability of findings applied to theory or practice.
• A researcher must be proficient in understanding how to apply multiple methods to investigating a research problem as well as be proficient in optimizing how to design a study that coherently melds them together.
• Can increase the likelihood of conflicting results or ambiguous findings that inhibit drawing a valid conclusion or setting forth a recommended course of action [e.g., sample interview responses do not support existing statistical data].
• Because the research design can be very complex, reporting the findings requires a well-organized narrative, clear writing style, and precise word choice.
• Design invites collaboration among experts. However, merging different investigative approaches and writing styles requires more attention to the overall research process than studies conducted using only one methodological paradigm.
• Concurrent merging of quantitative and qualitative research requires greater attention to having adequate sample sizes, using comparable samples, and applying a consistent unit of analysis. For sequential designs where one phase of qualitative research builds on the quantitative phase or vice versa, decisions about what results from the first phase to use in the next phase, the choice of samples and estimating reasonable sample sizes for both phases, and the interpretation of results from both phases can be difficult.
• Due to multiple forms of data being collected and analyzed, this design requires extensive time and resources to carry out the multiple steps involved in data gathering and interpretation.

Burch, Patricia and Carolyn J. Heinrich. Mixed Methods for Policy Research and Program Evaluation . Thousand Oaks, CA: Sage, 2016; Creswell, John w. et al. Best Practices for Mixed Methods Research in the Health Sciences . Bethesda, MD: Office of Behavioral and Social Sciences Research, National Institutes of Health, 2010Creswell, John W. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 4th edition. Thousand Oaks, CA: Sage Publications, 2014; Domínguez, Silvia, editor. Mixed Methods Social Networks Research . Cambridge, UK: Cambridge University Press, 2014; Hesse-Biber, Sharlene Nagy. Mixed Methods Research: Merging Theory with Practice . New York: Guilford Press, 2010; Niglas, Katrin. “How the Novice Researcher Can Make Sense of Mixed Methods Designs.” International Journal of Multiple Research Approaches 3 (2009): 34-46; Onwuegbuzie, Anthony J. and Nancy L. Leech. “Linking Research Questions to Mixed Methods Data Analysis Procedures.” The Qualitative Report 11 (September 2006): 474-498; Tashakorri, Abbas and John W. Creswell. “The New Era of Mixed Methods.” Journal of Mixed Methods Research 1 (January 2007): 3-7; Zhanga, Wanqing. “Mixed Methods Application in Health Intervention Research: A Multiple Case Study.” International Journal of Multiple Research Approaches 8 (2014): 24-35 .

Observational Design

This type of research design draws a conclusion by comparing subjects against a control group, in cases where the researcher has no control over the experiment. There are two general types of observational designs. In direct observations, people know that you are watching them. Unobtrusive measures involve any method for studying behavior where individuals do not know they are being observed. An observational study allows a useful insight into a phenomenon and avoids the ethical and practical difficulties of setting up a large and cumbersome research project.

• Observational studies are usually flexible and do not necessarily need to be structured around a hypothesis about what you expect to observe [data is emergent rather than pre-existing].
• The researcher is able to collect in-depth information about a particular behavior.
• Can reveal interrelationships among multifaceted dimensions of group interactions.
• You can generalize your results to real life situations.
• Observational research is useful for discovering what variables may be important before applying other methods like experiments.
• Observation research designs account for the complexity of group behaviors.
• Reliability of data is low because seeing behaviors occur over and over again may be a time consuming task and are difficult to replicate.
• In observational research, findings may only reflect a unique sample population and, thus, cannot be generalized to other groups.
• There can be problems with bias as the researcher may only "see what they want to see."
• There is no possibility to determine "cause and effect" relationships since nothing is manipulated.
• Sources or subjects may not all be equally credible.
• Any group that is knowingly studied is altered to some degree by the presence of the researcher, therefore, potentially skewing any data collected.

Atkinson, Paul and Martyn Hammersley. “Ethnography and Participant Observation.” In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 248-261; Observational Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Patton Michael Quinn. Qualitiative Research and Evaluation Methods . Chapter 6, Fieldwork Strategies and Observational Methods. 3rd ed. Thousand Oaks, CA: Sage, 2002; Payne, Geoff and Judy Payne. "Observation." In Key Concepts in Social Research . The SAGE Key Concepts series. (London, England: Sage, 2004), pp. 158-162; Rosenbaum, Paul R. Design of Observational Studies . New York: Springer, 2010;Williams, J. Patrick. "Nonparticipant Observation." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor.(Thousand Oaks, CA: Sage, 2008), pp. 562-563.

Philosophical Design

Understood more as an broad approach to examining a research problem than a methodological design, philosophical analysis and argumentation is intended to challenge deeply embedded, often intractable, assumptions underpinning an area of study. This approach uses the tools of argumentation derived from philosophical traditions, concepts, models, and theories to critically explore and challenge, for example, the relevance of logic and evidence in academic debates, to analyze arguments about fundamental issues, or to discuss the root of existing discourse about a research problem. These overarching tools of analysis can be framed in three ways:

• Ontology -- the study that describes the nature of reality; for example, what is real and what is not, what is fundamental and what is derivative?
• Epistemology -- the study that explores the nature of knowledge; for example, by what means does knowledge and understanding depend upon and how can we be certain of what we know?
• Axiology -- the study of values; for example, what values does an individual or group hold and why? How are values related to interest, desire, will, experience, and means-to-end? And, what is the difference between a matter of fact and a matter of value?
• Can provide a basis for applying ethical decision-making to practice.
• Functions as a means of gaining greater self-understanding and self-knowledge about the purposes of research.
• Brings clarity to general guiding practices and principles of an individual or group.
• Philosophy informs methodology.
• Refine concepts and theories that are invoked in relatively unreflective modes of thought and discourse.
• Beyond methodology, philosophy also informs critical thinking about epistemology and the structure of reality (metaphysics).
• Offers clarity and definition to the practical and theoretical uses of terms, concepts, and ideas.
• Limited application to specific research problems [answering the "So What?" question in social science research].
• Analysis can be abstract, argumentative, and limited in its practical application to real-life issues.
• While a philosophical analysis may render problematic that which was once simple or taken-for-granted, the writing can be dense and subject to unnecessary jargon, overstatement, and/or excessive quotation and documentation.
• There are limitations in the use of metaphor as a vehicle of philosophical analysis.
• There can be analytical difficulties in moving from philosophy to advocacy and between abstract thought and application to the phenomenal world.

Burton, Dawn. "Part I, Philosophy of the Social Sciences." In Research Training for Social Scientists . (London, England: Sage, 2000), pp. 1-5; Chapter 4, Research Methodology and Design. Unisa Institutional Repository (UnisaIR), University of South Africa; Jarvie, Ian C., and Jesús Zamora-Bonilla, editors. The SAGE Handbook of the Philosophy of Social Sciences . London: Sage, 2011; Labaree, Robert V. and Ross Scimeca. “The Philosophical Problem of Truth in Librarianship.” The Library Quarterly 78 (January 2008): 43-70; Maykut, Pamela S. Beginning Qualitative Research: A Philosophic and Practical Guide . Washington, DC: Falmer Press, 1994; McLaughlin, Hugh. "The Philosophy of Social Research." In Understanding Social Work Research . 2nd edition. (London: SAGE Publications Ltd., 2012), pp. 24-47; Stanford Encyclopedia of Philosophy . Metaphysics Research Lab, CSLI, Stanford University, 2013.

Sequential Design

• The researcher has a limitless option when it comes to sample size and the sampling schedule.
• Due to the repetitive nature of this research design, minor changes and adjustments can be done during the initial parts of the study to correct and hone the research method.
• This is a useful design for exploratory studies.
• There is very little effort on the part of the researcher when performing this technique. It is generally not expensive, time consuming, or workforce intensive.
• Because the study is conducted serially, the results of one sample are known before the next sample is taken and analyzed. This provides opportunities for continuous improvement of sampling and methods of analysis.
• The sampling method is not representative of the entire population. The only possibility of approaching representativeness is when the researcher chooses to use a very large sample size significant enough to represent a significant portion of the entire population. In this case, moving on to study a second or more specific sample can be difficult.
• The design cannot be used to create conclusions and interpretations that pertain to an entire population because the sampling technique is not randomized. Generalizability from findings is, therefore, limited.
• Difficult to account for and interpret variation from one sample to another over time, particularly when using qualitative methods of data collection.

Betensky, Rebecca. Harvard University, Course Lecture Note slides; Bovaird, James A. and Kevin A. Kupzyk. "Sequential Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 1347-1352; Cresswell, John W. Et al. “Advanced Mixed-Methods Research Designs.” In Handbook of Mixed Methods in Social and Behavioral Research . Abbas Tashakkori and Charles Teddle, eds. (Thousand Oaks, CA: Sage, 2003), pp. 209-240; Henry, Gary T. "Sequential Sampling." In The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman and Tim Futing Liao, editors. (Thousand Oaks, CA: Sage, 2004), pp. 1027-1028; Nataliya V. Ivankova. “Using Mixed-Methods Sequential Explanatory Design: From Theory to Practice.” Field Methods 18 (February 2006): 3-20; Bovaird, James A. and Kevin A. Kupzyk. “Sequential Design.” In Encyclopedia of Research Design . Neil J. Salkind, ed. Thousand Oaks, CA: Sage, 2010; Sequential Analysis. Wikipedia.

Systematic Review

• A systematic review synthesizes the findings of multiple studies related to each other by incorporating strategies of analysis and interpretation intended to reduce biases and random errors.
• The application of critical exploration, evaluation, and synthesis methods separates insignificant, unsound, or redundant research from the most salient and relevant studies worthy of reflection.
• They can be use to identify, justify, and refine hypotheses, recognize and avoid hidden problems in prior studies, and explain data inconsistencies and conflicts in data.
• Systematic reviews can be used to help policy makers formulate evidence-based guidelines and regulations.
• The use of strict, explicit, and pre-determined methods of synthesis, when applied appropriately, provide reliable estimates about the effects of interventions, evaluations, and effects related to the overarching research problem investigated by each study under review.
• Systematic reviews illuminate where knowledge or thorough understanding of a research problem is lacking and, therefore, can then be used to guide future research.
• The accepted inclusion of unpublished studies [i.e., grey literature] ensures the broadest possible way to analyze and interpret research on a topic.
• Results of the synthesis can be generalized and the findings extrapolated into the general population with more validity than most other types of studies .
• Systematic reviews do not create new knowledge per se; they are a method for synthesizing existing studies about a research problem in order to gain new insights and determine gaps in the literature.
• The way researchers have carried out their investigations [e.g., the period of time covered, number of participants, sources of data analyzed, etc.] can make it difficult to effectively synthesize studies.
• The inclusion of unpublished studies can introduce bias into the review because they may not have undergone a rigorous peer-review process prior to publication. Examples may include conference presentations or proceedings, publications from government agencies, white papers, working papers, and internal documents from organizations, and doctoral dissertations and Master's theses.

Denyer, David and David Tranfield. "Producing a Systematic Review." In The Sage Handbook of Organizational Research Methods .  David A. Buchanan and Alan Bryman, editors. ( Thousand Oaks, CA: Sage Publications, 2009), pp. 671-689; Foster, Margaret J. and Sarah T. Jewell, editors. Assembling the Pieces of a Systematic Review: A Guide for Librarians . Lanham, MD: Rowman and Littlefield, 2017; Gough, David, Sandy Oliver, James Thomas, editors. Introduction to Systematic Reviews . 2nd edition. Los Angeles, CA: Sage Publications, 2017; Gopalakrishnan, S. and P. Ganeshkumar. “Systematic Reviews and Meta-analysis: Understanding the Best Evidence in Primary Healthcare.” Journal of Family Medicine and Primary Care 2 (2013): 9-14; Gough, David, James Thomas, and Sandy Oliver. "Clarifying Differences between Review Designs and Methods." Systematic Reviews 1 (2012): 1-9; Khan, Khalid S., Regina Kunz, Jos Kleijnen, and Gerd Antes. “Five Steps to Conducting a Systematic Review.” Journal of the Royal Society of Medicine 96 (2003): 118-121; Mulrow, C. D. “Systematic Reviews: Rationale for Systematic Reviews.” BMJ 309:597 (September 1994); O'Dwyer, Linda C., and Q. Eileen Wafford. "Addressing Challenges with Systematic Review Teams through Effective Communication: A Case Report." Journal of the Medical Library Association 109 (October 2021): 643-647; Okoli, Chitu, and Kira Schabram. "A Guide to Conducting a Systematic Literature Review of Information Systems Research."  Sprouts: Working Papers on Information Systems 10 (2010); Siddaway, Andy P., Alex M. Wood, and Larry V. Hedges. "How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-analyses, and Meta-syntheses." Annual Review of Psychology 70 (2019): 747-770; Torgerson, Carole J. “Publication Bias: The Achilles’ Heel of Systematic Reviews?” British Journal of Educational Studies 54 (March 2006): 89-102; Torgerson, Carole. Systematic Reviews . New York: Continuum, 2003.

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Chapter 7: Action Research

Darshini Ayton

Learning outcomes

Upon completion of this chapter, you should be able to:

• Explain the purpose of an action research approach.
• Explain the action research cycle.
• Describe action research characteristics.

What is action research?

The key concept in action research is change or action .

Action research (also known as ‘participatory action research’) aligns well with the practice of health and social care because researchers and practitioners in this discipline work with people and communities in holistic and relational ways to understand the history, culture and context of the setting. Action research aims to understand the setting and improve it through change or action. 1 This method has its roots in activism and advocacy and is focused on solutions. It is practical and deals with real-world problems and issues. Action research often undergoes phases in seeking to understand the problem, plan a solution, implement the solution and then reflect on or evaluate the solution, cyclically and iteratively. Action research is used in the practice of health and social care because it has two fundamental aims: to improve and to involve. This chapter outlines how this is evident, using examples from the research literature (see Table 7.1.).

Action research as involvement

Action research is a collaborative process between researchers and community members. This process is a core component of action research and represents a significant shift from typical research methods. Through action research, those who are being researched become the researchers, with close consideration given to power dynamics. The research participants become partners in the research and are involved in identifying and prioritising the research area, designing and undertaking data collection, conducting data analysis, and interpreting and disseminating the results. 1 The research partners may be provided with support and training to enable them to undertake these activities and to promote empowerment and capacity building (see examples following). Patient and public involvement in research and healthcare improvement (known in Australia as ‘consumer and community involvement’), has led to action research gaining popularity as a research design that captures the ‘living knowledge’ with, for and by people and communities throughout the research journey.

As an example, in the project Relationships Matter for Youth ‘Aging Out’ of Care, 2 Doucet and colleagues aimed to examine relationships that matter to young people in care and how these relationships can be nurtured and supported over time. The project is a collaborative participatory action research study incorporating photovoice (see Chapter 17 for more information on photovoice). Eight young people, formerly in care and from diverse backgrounds, were recruited to the study. The lead researcher highlighted their own lived experience of the child welfare system and a consciousness of the power dynamics at play. The lead researcher created processes within the project to ensure the youth co-researchers were empowered to share their experiences and that the research team members were working with the youth co-researchers and not for them. These processes included three months of weekly facilitated group discussions, shared meals before project commencement and group outings and community engagement during the project to encourage connection, bonding and trust. The youth co-researchers were provided with photography training and digital cameras. Data collection included the youth co-researchers submitting 6–7 photographs with responses to the following questions for photo contextualisation:

• What does this photograph mean to you? Why is this photo, in particular, most significant to you?
• How do you see this photo as a reflection of the issue of supportive long-term relationships – and one that is relevant to you as a former youth in care in your community?
• What is the relationship between the content of the photo and how you perceive the community or the world around you? What recommendation for change in your community is associated with this photo? 2(para22)

The photographs were showcased at an exhibition that was open to the community; those in attendance included policymakers, advocates and community representatives. The change documented through this project was one of social transformation for the community and self-transformation and healing for the individuals.

Action research as improvement

Action research can be practitioner-led, whereby the study investigates problems identified by the practitioner with the goal of understanding and improving practice over time. Improvement can be both social improvement and healthcare improvement. Healthcare improvement, in particular quality (of healthcare) improvement, has been the focus of clinical practice, research, education and advocacy for more than 30 years. The two main frameworks guiding healthcare and quality improvement efforts are the Plan, Do, Study, Act (PDSA) cycle and Learning Health Systems. 3 Both of these frameworks lend themselves to action research. For example, the PDSA cycle is guided by three overarching questions:

• What are we trying to accomplish?
• How will we know that a change is an improvement?
• What change can we make that will result in improvement? 4(Figure1)

Learning Health Systems is another approach to quality improvement that has gained popularity over the past decade. Data collected by health services (e.g. patient data, health records, laboratory results) are used for knowledge creation in continuous and rapid cycles of study, feedback and practice change. 5 A Learning Health Systems framework incorporates systems science, data science, research methods for real-world contexts, implementation science, participatory research and quality improvement approaches.

Van Heerden and colleagues adopted an action research study to transform the practice and environment of neonatal care in the maternity section of a district hospital in South Africa. The study Strategies to sustain a quality improvement initiative in neonatal resuscitation 6 was conducted in three cycles. Cycle 1 was a situation analysis that explored and described the existing practices and factors influencing neonatal resuscitation and mortality in the hospital through administering questionnaires with nurses (n=69); a focus group with nine doctors; and an analysis of hospital records. A nominal group discussion (structured group discussion including prioritisation) was conducted with 10 managers and staff, followed by a reflective meeting with the project’s steering committee. Cycle 2 developed and implemented strategies to sustain a quality improvement initiative. The strategies addressed training, equipment and stock, staff attitudes, staff shortages, transport transfer for critically ill neonates, and protocols. Cycle 3 was an evaluation of change and sustainability after the implementation of strategies (Cycle 2) and involved the analysis of hospital record data, repeat questionnaire with nurses (n=40), focus group discussion with 10 doctors, steering committee and management members, followed by reflective meetings with the steering committee. Qualitative data was analysed through open coding, and quantitative data was analysed descriptively. The neonatal mortality rate declined (yet still needed to improve) and the implementation strategies facilitated change that led to improvement and practice transformation.

Action research as a methodology or an approach

There is debate as to whether action research is a methodology or an approach, since several different research methods and methodologies can be used. For example, multiple forms of data collection can be utilized, including quantitative data from surveys or medical records, to inform the identification and understanding of the problem and evaluation of the solution. Action research can also draw on descriptive qualitative research, quantitative cross-sectional studies, case studies (see Chapter 8 ), ethnography ( Chapter 9 ) and grounded theory ( Chapter 10 ). Action research can therefore take a purely qualitative approach, or can take a mixed-methods approach. See Table 7.1. for examples of action research studies.

Advantages and disadvantages of action research

Action research addresses practical problems, drawing on principles of empowerment, capacity-building and participation. The research problem to be addressed is typically identified by the community, and the solutions are for the community. The research participants are collaborators in the research process. The examples presented in this chapter demonstrate how the research collaborators and co-researchers received training and support to lead elements of the project. Another advantage of action research is that it is a continuous cycle of development. Hence, the approach is iterative and the full solution can take multiple cycles and iterations to develop and sustain. 7,8

Since action research is fundamentally about relationships and integrating research into the real world, studies can take years to result in a solution. It is important to be able to adapt and be flexible in response to community and stakeholder needs and contexts. The research can therefore be constrained by what is practical and also ethical within the setting. This may limit the scope and scale of the research and compromise its rigour. Action research can also create unanticipated work for community members and participants because they are not usually involved in research in this way, and thus training may be required, as well as remuneration for time and experience. 7,8

Action research is a research design in which researchers and community members work together to identify problems, design and implement solutions and evaluate the impact of these solutions. Change or action is a core component of this research design.

• Baum F, MacDougall C, Smith D. Participatory action research. J Epidemiol Community Health .  2006;60(10):854-857. doi:10.1136/jech.2004.028662
• Doucet M, Pratt H, Dzhenganin M, Read J. Nothing About Us Without Us: Using Participatory Action Research (PAR) and arts-based methods as empowerment and social justice tools in doing research with youth ‘aging out’ of care. Child Abuse Negl . 2022;130:105358. doi: 10.1016/j.chiabu.2021.105358
• Taylor J, Coates E, Wessels B, Mountain G, Hawley MS. Implementing solutions to improve and expand telehealth adoption: participatory action research in four community healthcare settings. BMC Health Serv Res . 2015;15:529. doi:10.1186/s12913-015-1195-3
• Taylor MJ, McNicholas C, Nicolay C, Darzi A, Bell D, Reed JE. Systematic review of the application of the plan-do-study-act method to improve quality in healthcare. BMJ Qual Saf .  2014;23(4):290-298. doi:10.1136/bmjqs-2013-001862
• Menear M, Blanchette MA, Demers-Payette O, Roy D. A framework for value-creating learning health systems. Health Res Policy Syst . 2019;17(1):79. doi:10.1186/s12961-019-0477-3
• Van Heerden C, Maree C, Janse Van Rensburg ES. Strategies to sustain a quality improvement initiative in neonatal resuscitation. Afr J Prim Health Care Fam Med . 2016;8(2):a958. doi:10.4102/phcfm.v8i2.958
• Liamputtong P. Qualitative Research Methods . 5th ed. Oxford University Press; 2020.
• Liamputtong P, Ezzy D. Qualitative Research Methods: A Health Focus . Oxford University Press; 1999.
• Middleton TRF, Schinke RJ, Lefebvre D, Habra B, Coholic D, Giffin C. Critically examining a community-based participatory action research project with forced migrant youth. Sport Soc . 2021;25(2):418-433. doi:10.1080/17430437.2022.2017619

Qualitative Research – a practical guide for health and social care researchers and practitioners Copyright © 2023 by Darshini Ayton is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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9 Research Design: Action Research

• Published: July 2023
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Action research is an exciting research design that leads to social and systems change. In this chapter, the authors describe action research, including how it differs from other approaches, along with a detailed explanation of the action research process, including planning, implementing, observing, reflecting, and sharing results. The authors highlight a case study delineating the iterative process within the school counseling field to provide readers with knowledge of the action research process. Additionally, authors share examples of current school counseling research to bring action research to life. School counselors and SCEs will understand how to utilize action research across the educational ecosystems to ignite change.

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Action Research

Action research can be defined as “an approach in which the action researcher and a client collaborate in the diagnosis of the problem and in the development of a solution based on the diagnosis” [1] . In other words, one of the main characteristic traits of action research relates to collaboration between researcher and member of organisation in order to solve organizational problems.

Action study assumes social world to be constantly changing, both, researcher and research being one part of that change. [2] Generally, action researches can be divided into three categories: positivist, interpretive and critical.

Positivist approach to action research , also known as ‘classical action research’ perceives research as a social experiment. Accordingly, action research is accepted as a method to test hypotheses in a real world environment.

Interpretive action research , also known as ‘contemporary action research’ perceives business reality as socially constructed and focuses on specifications of local and organisational factors when conducting the action research.

Critical action research is a specific type of action research that adopts critical approach towards business processes and aims for improvements.

The following features of action research need to be taken into account when considering its suitability for any given study:

• It is applied in order to improve specific practices.  Action research is based on action, evaluation and critical analysis of practices based on collected data in order to introduce improvements in relevant practices.
• This type of research is facilitated by participation and collaboration of number of individuals with a common purpose
• Such a research focuses on specific situations and their context

Advantages of Action Research

• High level of practical relevance of the business research;
• Can be used with quantitative, as well as, qualitative data;
• Possibility to gain in-depth knowledge about the problem.

Disadvantages of Action Research

• Difficulties in distinguishing between action and research and ensure the application of both;
• Delays in completion of action research due to a wide range of reasons are not rare occurrences
• Lack of repeatability and rigour

It is important to make a clear distinction between action research and consulting. Specifically, action research is greater than consulting in a way that action research includes both action and research, whereas business activities of consulting are limited action without the research.

Action Research Spiral

Action study is a participatory study consisting of spiral of following self-reflective cycles:

• Planning in order to initiate change
• Implementing the change (acting) and observing the process of implementation and consequences
• Reflecting on processes of change and re-planning
• Acting and observing

Kemmis and McTaggart (2000) do acknowledge that individual stages specified in Action Research Spiral model may overlap, and initial plan developed for the research may become obselete in short duration of time due to a range of factors.

The main advantage of Action Research Spiral model relates to the opportunity of analysing the phenomenon in a greater depth each time, consequently resulting in grater level of understanding of the problem.

Disadvantages of Action Research Spiral model include its assumption each process takes long time to be completed which may not always be the case.

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance  offers practical assistance to complete a dissertation with minimum or no stress. The e-book covers all stages of writing a dissertation starting from the selection to the research area to submitting the completed version of the work within the deadline.

References 

[1] Bryman, A. & Bell, E. (2011) “Business Research Methods” 3 rd  edition, Oxford University Press

[2] Collis, J. & Hussey, R. (2003) “Business Research. A Practical Guide for Undergraduate and Graduate Students” 2nd edition, Palgrave Macmillan

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Action Research

What is action research.

Action research is a methodology that emphasizes collaboration between researchers and participants to identify problems, develop solutions and implement changes. Designers plan, act, observe and reflect, and aim to drive positive change in a specific context. Action research prioritizes practical solutions and improvement of practice, unlike knowledge generation, which is the priority of traditional methods.  

© New Mexico State University, Fair Use

Why is Action Research Important in UX Design?

Action research stands out as a unique approach in user experience design (UX design), among other types of research methodologies and fields. It has a hands-on, practical focus, so UX designers and researchers who engage in it devise and execute research that not only gathers data but also leads to actionable insights and solid real-world solutions. 

The concept of action research dates back to the 1940s, with its roots in the work of social psychologist Kurt Lewin. Lewin emphasized the importance of action in understanding and improving human systems. The approach rapidly gained popularity across various fields, including education, healthcare, social work and community development.  

Kurt Lewin, the Founder of social psychology.

© Wikimedia Commons, Fair Use

In UX design, the incorporation of action research appeared with the rise of human-centered design principles. As UX design started to focus more on users' needs and experiences, the participatory and problem-solving nature of action research became increasingly significant. Action research bridges the gap between theory and practice in UX design. It enables designers to move beyond hypothetical assumptions and base their design decisions on concrete, real-world data. This not only enhances the effectiveness of the design but also boosts its credibility and acceptance among users—vital bonuses for product designers and service designers. 

At its core, action research is a systematic, participatory and collaborative approach to research . It emphasizes direct engagement with specific issues or problems and aims to bring about positive change within a particular context. Traditional research methodologies tend to focus solely on the generation of theoretical knowledge. Meanwhile, action research aims to solve real-world problems and generate knowledge simultaneously .  

Action research helps designers and design teams gather first-hand insights so they can deeply understand their users' needs, preferences and behaviors. With it, they can devise solutions that genuinely address their users’ problems—and so design products or services that will resonate with their target audiences. As designers actively involve users in the research process, they can gather authentic insights and co-create solutions that are both effective and user-centric.  

Moreover, the iterative nature of action research aligns perfectly with the UX design process. It allows designers to continuously learn from users' feedback, adapt their designs accordingly, and test their effectiveness in real-world contexts. This iterative loop of planning, acting, observing and reflecting ensures that the final design solution is user-centric. However, it also ensures that actual user behavior and feedback validates the solution that a design team produces, which helps to make action research studies particularly rewarding for some brands. 

Designers can continuously learn from users’ feedback in action research and iterate accordingly.

© Fauxels, Fair Use

What is The Action Research Process?

Action research in UX design involves several stages. Each stage contributes to the ultimate goal: to create effective and user-centric design solutions. Here is a step-by-step breakdown of the process:  

1. Identify the Problem

This could be a particular pain point users are facing, a gap in the current UX design, or an opportunity for improvement.  

2. Plan the Action

Designers might need to devise new design features, modify existing ones or implement new user interaction strategies.  

3. Implement the Action

Designers put their planned actions into practice. They might prototype the new design, implement the new features or test the new user interaction strategies.  

4. Observe and Collect Data

As designers implement the action they’ve decided upon, it's crucial to observe its effects and collect data. This could mean that designers track user behaviors, collect user feedback, conduct usability tests or use other data collection methods.  

5. Reflect on the Results

From the collected data, designers reflect on the results, analyze the effectiveness of the action and draw insights. If the action has led to positive outcomes, they can further refine it and integrate it into the final design. If not, they can go back to plan new actions and repeat the process.  

An action research example could be where designers do the following: 

Identification : Designers observe a high abandonment rate during a checkout process for an e-commerce website. 

Planning : They analyze the checkout flow to identify potential friction points.  

Action : They isolate these points, streamline the checkout process, introduce guest checkout and optimize form fields.  

Observation : They monitor changes in abandonment rates and collect user feedback.  

Reflection : They assess the effectiveness of the changes as these reduce checkout abandonment.  

Outcome : The design team notices a significant decrease in checkout abandonment, which leads to higher conversion rates as more users successfully purchase goods.  

What Types of Action Research are there?

Action research splits into three main types: technical, collaborative and critical reflection.  

1. Technical Action Research

Technical action research focuses on improving the efficiency and effectiveness of a system or process. Designers often use it in organizational contexts to address specific issues or enhance operations. This could be where designers improve the usability of a website, optimize the load time of an application or enhance the accessibility of a digital product.  

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2. Collaborative Action Research

Collaborative action research emphasizes the active participation of stakeholders in the research process. It's about working together to identify issues, co-create solutions and implement changes. In the context of UX design, this could mean that designers collaborate with users to co-design a new feature, work with developers to optimize a process, or partner with business stakeholders to align the UX strategy with business goals.  

3. Critical Reflection Action Research

Critical reflection action research aims to challenge dominant power structures and social injustices within a particular context. It emphasizes the importance of where designers and design teams reflect on the underlying assumptions and values that drive research and decision-making processes. In UX design, this could be where designers question the design biases, challenge the stereotypes, and promote inclusivity and diversity in design decisions.  

What are the Benefits and Challenges of Action Research?

Like any UX research method or approach, action research comes with its own set of benefits and challenges.  

Benefits of Action Research

Real-world solutions.

Action research focuses on solving real-world problems. This quality makes it highly relevant and practical. It allows UX designers to create solutions that are not just theoretically sound but also valid in real-world contexts.  

User Involvement

Action research involves users in the research process, which lets designers gather first-hand insights into users' needs, preferences and behaviors. This not only enhances the accuracy and reliability of the research but also fosters user engagement and ownership long before user testing of high-fidelity prototypes.  

Continuous Learning

The iterative nature of action research promotes continuous learning and improvement. It enables designers to adapt their designs based on users' feedback and learn from their successes and failures. They can fine-tune better tools and deliverables, such as more accurate user personas, from their findings.

Author and Human-Computer Interaction Expert, Professor Alan Dix explains personas and why they are important: 

Challenges of Action Research

Time- and resource-intensive.

Action research involves multiple iterations of planning, acting, observing and reflecting, which can be time- and resource-intensive. 

Complexity of Real-world Contexts

It can be difficult to implement changes and observe their effects in real-world contexts. This is due to the complexity and unpredictability of real-world situations.  

Risk of Subjectivity

Since action research involves close collaboration with stakeholders, there's a risk of subjectivity and bias influencing the research outcomes. It's crucial for designers to maintain objectivity and integrity throughout the research process. 

Ethical Considerations

It can be a challenge to ensure all participants understand the nature of the research and agree to participate willingly. Also, it’s vital to safeguard the privacy of participants and sensitive data.  

Scope Creep

The iterative nature of action research might lead to expanding goals, and make the project unwieldy.  

Generalizability

The contextual focus of action research may limit the extent to which designers can generalize findings from field studies to other settings.  

Best Practices and Tips for Successful Action Research

1. define clear objectives.

To begin, designers should define clear objectives. They should ask the following: 

What is the problem to try to solve? 

What change is desirable as an outcome?  

To have clear objectives will guide their research process and help them stay focused.  

2. Involve Users

It’s vital to involve users in the research process. Designers should collaborate with them to identify issues, co-create solutions and implement changes in real time. This will not only enhance the relevance of the research but also foster user engagement and ownership.  

3. Use a Variety of Data Collection Methods

To conduct action research means to observe the effects of changes in real-world contexts. This requires a variety of data collection methods. Designers should use methods like surveys, user interviews, observations and usability tests to gather diverse and comprehensive data. 

UX Strategist and Consultant, William Hudson explains the value of usability testing in this video: 

4. Reflect and Learn

Action research is all about learning from action. Designers should reflect on the outcomes of their actions, analyze the effectiveness of their solutions and draw insights. They can use these insights to inform their future actions and continuously improve the design.  

5. Communicate and Share Findings

Lastly, designers should communicate and share their findings with all stakeholders. This not only fosters transparency and trust but also facilitates collective learning and improvement.  

What are Other Considerations to Bear in Mind with Action Research?

Quantitative data.

Action research involves both qualitative and quantitative data, but it's important to remember to place emphasis on qualitative data. While quantitative data can provide useful insights, designers who rely too heavily on it may find a less holistic view of the user experience. 

Professor Alan Dix explains the difference between quantitative and qualitative data in this video: 

User Needs and Preferences

Designers should focus action research on understanding user needs and preferences. If they ignore these in favor of more technical considerations, the resulting design solutions may not meet users' expectations or provide them with a satisfactory experience.  

User Feedback

It's important to seek user feedback at each stage of the action research process. Without this feedback, designers may not optimize design solutions for user needs. For example, they may find the information architecture confusing. Additionally, without user feedback, it can be difficult to identify any unexpected problems that may arise during the research process.  

Time Allocation

Action research requires time and effort to ensure successful outcomes. If designers or design teams don’t permit enough time for the research process, it can lead to rushed decisions and sloppy results. It's crucial to plan ahead and set aside enough time for each stage of the action research process—and ensure that stakeholders understand the time-consuming nature of research and digesting research findings, and don’t push for premature results. 

Contextual Factors

Contextual factors such as culture, environment and demographics play an important role in UX design. If designers ignore these factors, it can lead to ineffective design solutions that don't properly address users' needs and preferences or consider their context.  

Professor Alan Dix explains the need to consider users’ culture in design, in this video: 

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Overall, in the ever-evolving field of UX design, this is one methodology that can serve as a powerful research tool for driving positive change and promoting continuous learning. Since to do action research means to actively involve users in the research process and research projects, and focus on real-world problem-solving, it allows designers to create more user-centered designs. These digital solutions and services will be more likely to resonate with the target users and deliver exceptional user experiences.  

Despite its challenges, the benefits of action research far outweigh the risks. Action research is therefore a valuable approach for UX designers who are keen on creating a wide range of impactful and sustainable design solutions. The biggest lesson with action research is to ensure that user needs and preferences are at the center of the research process. 

Learn More about Action Research  

Take our User Research: Methods and Best Practices course.  

Take our Master Class Radical Participatory Design: Insights From NASA’s Service Design Lead with Victor Udoewa, Service Design Lead, NASA SBIR/STTR Program. 

Read more in-depth information in 3 things design thinking can learn from action research by Amin Mojtahedi, PhD . 

Find additional insights in What Technical Communicators and UX Designers Can Learn From Participatory Action Research by Guiseppe . 

Discover more insights and tips in Action Research: Steps, Benefits, and Tips by Lauren Stewart .

Questions related to Action Research

Action research and design thinking are both methodologies to solve problems and implement changes, but they have different approaches and emphases. Here's how they differ:  

Objectives  

Action research aims to solve specific problems within a community or organization through a cycle of planning, action, observation and reflection. It focuses on iterative learning and solving real-world problems through direct intervention.  

Design thinking focuses on addressing complex problems by understanding the user's needs, re-framing the problem in human-centric ways, creating many ideas in brainstorming sessions, and adopting a hands-on approach in prototyping and testing. It emphasizes innovation and the creation of solutions that are desirable, feasible and viable.  

Process  

Action research involves a cyclic process that includes:  

- Identify a problem.  

- Plan an action.  

- Implement the action.  

- Observe and evaluate the outcomes.  

- Reflect on the findings and plan the next cycle. 

Design thinking follows a non-linear, iterative process that typically includes five phases:  

- Empathize: Understand the needs of those you're designing for.  

- Define: Clearly articulate the problem you want to solve.  

- Ideate: Brainstorm a range of creative solutions.  

- Prototype: Build a representation of one or more of your ideas.  

- Test: Return to your original user group and test your idea for feedback.  

User Involvement  

Action research actively involves participants in the research process. The participants are co-researchers and have a direct stake in the problem at hand.  

Design thinking prioritizes empathy with users and stakeholders to ensure that the solutions are truly user-centered. While users are involved, especially in the empathy and testing phases, they may not be as deeply engaged in the entire process as they are in action research.  

Outcome  

Action research typically aims for practical outcomes that directly improve practices or address issues within the specific context studied. Its success is measurable by the extent of problem resolution or improvement.  

Design thinking seeks to generate innovative solutions that may not only solve the identified problem but also provide a basis for new products, services or ways of thinking. The success is often measurable in terms of innovation, user satisfaction and feasibility of implementation.  

In summary, while both action research and design thinking are valuable in addressing problems, action research is more about participatory problem-solving within specific contexts, and design thinking is about innovative solution-finding with a strong emphasis on user needs. 

Take our Design Thinking: The Ultimate Guide course. 

To define the research question in an action research project, start by identifying a specific problem or area of interest in your practice or work setting. Reflect on this issue deeply to understand its nuances and implications. Then, narrow your focus to a question that is both actionable and researchable. This question should aim to explore ways to improve, change or understand the problem better. Ensure the question is clear, concise and aligned with the goals of your project. It must invite inquiry and suggest a path towards finding practical solutions or gaining deeper insights. 

For instance, if you notice a decline in user engagement with a product, your research question could be, "How can we modify the user interface of our product to enhance user engagement?" This question clearly targets an improvement, focuses on a specific aspect (the user interface) and implies actionable outcomes (modifications to enhance engagement). 

Take our Master Class Radical Participatory Design: Insights From NASA’s Service Design Lead with Victor Udoewa, Service Design Lead, NASA SBIR/STTR Program.  

Designers use several tools and methods in action research to explore problems and implement solutions. Surveys allow them to gather feedback from a broad audience quickly. Interviews offer deep insights through personal conversations, focusing on users' experiences and needs. Observations help designers understand how people interact with products or services in real environments. Prototyping enables the testing of ideas and concepts through tangible models, and allows for immediate feedback and iteration. Finally, case studies provide detailed analysis of specific instances and offer valuable lessons and insights. 

These tools and methods empower designers to collect data, analyze findings and make informed decisions. When designers employ a combination of these approaches, they ensure a comprehensive understanding of the issues at hand and develop effective solutions. 

CEO of Experience Dynamics, Frank Spillers explains the need to be clear about the problem that designers should address: 

To engage stakeholders in an action research project, first identify all individuals or groups with an interest in the project's outcome. These might include users, team members, clients or community representatives. Clearly communicate the goals, benefits and expected outcomes of the project to them. Use presentations, reports, or informal meetings to share your vision and how their involvement adds value. 

Involve stakeholders early and often by soliciting their feedback through surveys, interviews or workshops. This inclusion not only provides valuable insights but also fosters a sense of ownership and commitment to the project. Establish regular update meetings or newsletters to keep stakeholders informed about progress, challenges and successes. Finally, ensure there are clear channels for stakeholders to share their input and concerns throughout the project. 

This approach creates a collaborative environment where stakeholders feel valued and engaged, leading to more meaningful and impactful outcomes. 

To measure the impact of an action research project, start by defining clear, measurable objectives at the beginning. These objectives should align with the goals of your project and provide a baseline against which you can measure progress. Use quantitative metrics such as increased user engagement, sales growth or improved performance scores for a tangible assessment of impact. Incorporate qualitative data as well, such as user feedback and case studies, to understand the subjective experiences and insights gained through the project. 

Conduct surveys or interviews before and after the project to compare results and identify changes. Analyze this data to assess how well the project met its objectives and what effect it had on the target issue or audience. Document lessons learned and unexpected outcomes to provide a comprehensive view of the project's impact. This approach ensures a holistic evaluation, combining numerical data and personal insights to gauge the success and influence of your action research project effectively. 

Take our Master Class Design KPIs: From Insights to Impact with Vitaly Friedman, Senior UX consultant, European Parliament, and Creative Lead, Smashing Magazine. 

When unexpected results or obstacles emerge during action research, first, take a step back and assess the situation. Identify the nature of the unexpected outcome or obstacle and analyze its potential impact on your project. This step is crucial for understanding the issue at hand. 

Next, communicate with your team and stakeholders about the situation. Open communication ensures everyone understands the issue and can contribute to finding a solution. 

Then, consider adjusting your research plan or design strategy to accommodate the new findings or to overcome the obstacles. This might involve revisiting your research questions, methods or even the design problem you are addressing. 

Always document these changes and the reasons behind them. This documentation will be valuable for understanding the project's evolution and for future reference. 

Finally, view these challenges as learning opportunities. Unexpected results can lead to new insights and innovations that strengthen your project in the long run. 

By remaining flexible, communicating effectively, and being willing to adjust your approach, you can navigate the uncertainties of action research and continue making progress towards your goals. 

Professor Alan Dix explains externalization, a creative process that can help designers to adapt to unexpected roadblocks and find a good way forward: 

Action research can significantly contribute to inclusive and accessible design by directly involving users with diverse needs in the research and design process. When designers engage individuals from various backgrounds, abilities and experiences, they can gain a deeper understanding of the wide range of user requirements and preferences. This approach ensures that the products or services they develop cater to a broader audience, including those with disabilities. 

Furthermore, action research allows for iterative testing and feedback loops with users. This quality enables designers to identify and address accessibility challenges early in the design process. The continuous engagement helps in refining designs to be more user-friendly and inclusive. 

Additionally, action research fosters a culture of empathy and understanding within design teams, as it emphasizes the importance of seeing the world from the users' perspectives. This empathetic approach leads to more thoughtful and inclusive design decisions, ultimately resulting in products and services that are accessible to everyone. 

By prioritizing inclusivity and accessibility through action research, designers can create more equitable and accessible solutions that enhance the user experience for all. 

Take our Master Class How to Design for Neurodiversity: Inclusive Content and UX with Katrin Suetterlin, UX Content Strategist, Architect and Consultant. 

To ensure the reliability and validity of data in action research, follow these steps: 

Define clear research questions: Start with specific, clear research questions to guide your data collection. This clarity helps in gathering relevant and focused data. 

Use multiple data sources: Collect data from various sources to cross-verify information. This triangulation strengthens the reliability of your findings. 

Apply consistent methods: Use consistent data collection methods throughout your research. If conducting surveys or interviews, keep questions consistent across participants to ensure comparability. 

Engage in peer review: Have peers or experts review your research design and data analysis. Feedback can help identify biases or errors, and enhance the validity of your findings. 

Document the process: Keep detailed records of your research process, including how you collected and analyzed data. Documentation allows others to understand and validate your research methodology. 

Test and refine instruments: If you’re using surveys or assessment tools, test them for reliability and validity before using them extensively. Pilot testing helps refine these instruments, and ensures they accurately measure what they intend to. 

When you adhere to these principles, you can enhance the reliability and validity of your action research data, leading to more trustworthy and impactful outcomes. 

Take our Data-Driven Design: Quantitative Research for UX course.  

To analyze data collected during an action research project, follow these steps: 

Organize the data: Begin by organizing your data, categorizing information based on types, sources or research questions. This organization makes the data manageable and prepares you for in-depth analysis. 

Identify patterns and themes: Look for patterns, trends and themes within your data. This might mean to code qualitative data or use statistical tools for quantitative data to uncover recurring elements or significant findings. 

Compare findings to objectives: Match your findings against the research objectives. Assess how the data answers your research questions or addresses the issues you set out to explore. 

Use software tools: Consider using data analysis software, especially for complex or large data sets. Tools like NVivo for qualitative data or SPSS for quantitative data can simplify analysis and help in identifying insights. 

Draw conclusions: Based on your analysis, draw conclusions about what the data reveals. Look for insights that answer your research questions or offer solutions to the problem you are investigating. 

Reflect and act: Reflect on the implications of your findings. Consider how they impact your understanding of the research problem and what actions they suggest for improvement or further investigation. 

This approach to data analysis ensures a thorough understanding of the collected data, allowing you to draw meaningful conclusions and make informed decisions based on your action research project. 

Professor Ann Blandford, Professor of Human-Computer Interaction, UCL explains valuable aspects of data collection in this video: 

Baskerville, R. L., & Wood-Harper, A. T. (1996). A critical perspective on action research as a method for information systems research . Journal of Information Technology, 11(3), 235-246.   

This influential paper examines the philosophical underpinnings of action research and its application in information systems research, which is closely related to UX design. It highlights the strengths of action research in addressing complex, real-world problems, as well as the challenges in maintaining rigor and achieving generalizability. The paper helped establish action research as a valuable methodology in the information systems and UX design fields.  

Di Mascio, T., & Tarantino, L. (2015). New Design Techniques for New Users: An Action Research-Based Approach . In Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct (pp. 83-96). ACM. 

This paper describes an action research project that aimed to develop a novel data gathering technique for understanding the context of use of a technology-enhanced learning system for children. The authors argue that traditional laboratory experiments struggle to maintain relevance to the real world, and that action research, with its focus on solving practical problems, is better suited to addressing the needs of new ICT products and their users. The paper provides insights into the action research process and reflects on its value in defining new methods for solving complex, real-world problems. The work is influential in demonstrating the applicability of action research in the field of user experience design, particularly for designing for new and underserved user groups. 

Villari, B. (2014). Action research approach in design research . In Proceedings of the 5th STS Italia Conference A Matter of Design: Making Society through Science and Technology (pp. 306-316). STS Italia Publishing.  

This paper explores the application of action research in the field of design research. The author argues that design is a complex practice that requires interdisciplinary skills and the ability to engage with diverse communities. Action research is presented as a research strategy that can effectively merge theory and practice, linking the reflective dimension to practical activities. The key features of action research highlighted in the paper are its context-dependent nature, the close relationship between researchers and the communities involved, and the iterative process of examining one's own practice and using research insights to inform future actions. The paper is influential in demonstrating the value of action research in addressing the challenges of design research, particularly in terms of bridging the gap between theory and practice and fostering collaborative, user-centered approaches to design.  

Brandt, E. (2004). Action research in user-centred product development . AI & Society, 18(2), 113-133.  

This paper reports on the use of action research to introduce new user-centered work practices in two commercial product development projects. The author argues that the growing complexity of products and the increasing importance of quality, usability, and customization demand new collaborative approaches that involve customers and users directly in the development process. The paper highlights the value of using action research to support these new ways of working, particularly in terms of creating and reifying design insights in representations that can foster collaboration and continuity throughout the project. The work is influential in demonstrating the applicability of action research in the context of user-centered product development, where the need to bridge theory and practice and engage diverse stakeholders is paramount. The paper provides valuable insights into the practical challenges and benefits of adopting action research in this domain. 

1. Reason, P., & Bradbury, H. (Eds.). (2001). Handbook of action research: Participative inquiry and practice . SAGE Publications.  

This comprehensive handbook is considered a seminal work in the field of action research. It provides a thorough overview of the history, philosophical foundations, and diverse approaches to action research. The book features contributions from leading scholars and practitioners, covering topics such as participatory inquiry, critical action research, and the role of action research in organizational change and community development. It has been highly influential in establishing action research as a rigorous and impactful research methodology across various disciplines. 

 2. Stringer, E. T. (2013). Action Research (4th ed.) . SAGE Publications.  

This book by Ernest T. Stringer is a widely recognized and accessible guide to conducting action research. It provides clear, step-by-step instructions on the action research process, including gathering information, interpreting and explaining findings, and taking action to address practical problems. The book is particularly valuable for novice researchers and practitioners in fields such as education, social work, and community development, where action research is commonly applied. Its practical approach and real-life examples have made it a go-to resource for those seeking to engage in collaborative, solution-oriented research. 

3. McNiff, J. (2017). Action Research: All You Need to Know (1st ed.) . SAGE Publications.   

This book by Jean McNiff provides a comprehensive guide to conducting action research projects. It covers the key steps of the action research process, including identifying a problem, developing an action plan, implementing changes, and reflecting on the outcomes. The book is influential in the field of action research as it offers practical advice and strategies for practitioners across various disciplines, such as education, healthcare, and organizational development. It emphasizes the importance of critical reflection, collaboration, and the integration of theory and practice, making it a valuable resource for those seeking to engage in rigorous, transformative research. 

Answer a Short Quiz to Earn a Gift

What is a primary characteristic of action research in UX design?

• It drives practical changes through iterative cycles.
• It focuses solely on theoretical knowledge.
• It relies on external consultants to dictate changes.

Which type of action research improves system efficiency and effectiveness?

• Collaborative Action Research
• Critical Reflection Action Research
• Technical Action Research

What role do stakeholders play in collaborative action research?

• They participate actively in co-creating solutions.
• They provide financial support only.
• They review and approve final designs.

How do users in action research benefit the design process?

• They help make sure designs meet actual user needs and preferences.
• They help speed up the design process significantly.
• They limit the scope of design innovations.

What is the purpose of the reflection stage in the action research process?

• To document the research process for publication only
• To evaluate the effectiveness of actions and plan further improvements
• To finalize the product design without further changes

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Literature on Action Research

Here’s the entire UX literature on Action Research by the Interaction Design Foundation, collated in one place:

Learn more about Action Research

Take a deep dive into Action Research with our course User Research – Methods and Best Practices .

How do you plan to design a product or service that your users will love , if you don't know what they want in the first place? As a user experience designer, you shouldn't leave it to chance to design something outstanding; you should make the effort to understand your users and build on that knowledge from the outset. User research is the way to do this, and it can therefore be thought of as the largest part of user experience design .

In fact, user research is often the first step of a UX design process—after all, you cannot begin to design a product or service without first understanding what your users want! As you gain the skills required, and learn about the best practices in user research, you’ll get first-hand knowledge of your users and be able to design the optimal product—one that’s truly relevant for your users and, subsequently, outperforms your competitors’ .

This course will give you insights into the most essential qualitative research methods around and will teach you how to put them into practice in your design work. You’ll also have the opportunity to embark on three practical projects where you can apply what you’ve learned to carry out user research in the real world . You’ll learn details about how to plan user research projects and fit them into your own work processes in a way that maximizes the impact your research can have on your designs. On top of that, you’ll gain practice with different methods that will help you analyze the results of your research and communicate your findings to your clients and stakeholders—workshops, user journeys and personas, just to name a few!

By the end of the course, you’ll have not only a Course Certificate but also three case studies to add to your portfolio. And remember, a portfolio with engaging case studies is invaluable if you are looking to break into a career in UX design or user research!

We believe you should learn from the best, so we’ve gathered a team of experts to help teach this course alongside our own course instructors. That means you’ll meet a new instructor in each of the lessons on research methods who is an expert in their field—we hope you enjoy what they have in store for you!

All open-source articles on Action Research

An Introduction to Action Research

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Cognitive Maps in UX | IxDF

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• Types of Research Designs Compared | Guide & Examples

Types of Research Designs Compared | Guide & Examples

Published on June 20, 2019 by Shona McCombes . Revised on June 22, 2023.

When you start planning a research project, developing research questions and creating a  research design , you will have to make various decisions about the type of research you want to do.

There are many ways to categorize different types of research. The words you use to describe your research depend on your discipline and field. In general, though, the form your research design takes will be shaped by:

• The type of knowledge you aim to produce
• The type of data you will collect and analyze
• The sampling methods , timescale and location of the research

This article takes a look at some common distinctions made between different types of research and outlines the key differences between them.

Table of contents

Types of research aims, types of research data, types of sampling, timescale, and location, other interesting articles.

The first thing to consider is what kind of knowledge your research aims to contribute.

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The next thing to consider is what type of data you will collect. Each kind of data is associated with a range of specific research methods and procedures.

Finally, you have to consider three closely related questions: how will you select the subjects or participants of the research? When and how often will you collect data from your subjects? And where will the research take place?

Keep in mind that the methods that you choose bring with them different risk factors and types of research bias . Biases aren’t completely avoidable, but can heavily impact the validity and reliability of your findings if left unchecked.

Choosing between all these different research types is part of the process of creating your research design , which determines exactly how your research will be conducted. But the type of research is only the first step: next, you have to make more concrete decisions about your research methods and the details of the study.

Read more about creating a research design

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

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

Research bias

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

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McCombes, S. (2023, June 22). Types of Research Designs Compared | Guide & Examples. Scribbr. Retrieved August 26, 2024, from https://www.scribbr.com/methodology/types-of-research/

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Research Methodology and Design

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Action Research by Discipline

Selected Videos

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• Action Research Professor Eileen Piggot-Irvine explains action research as research that doesn't conclude with data collection, but continues through an action in response to the research findings. She discusses how action research can be utilized best and where it is going in the future. Piggot-Irvine also discusses some of the drawbacks to using action research.
• Action Research More and more schools are engaging in action research as part of their school improvement plans. But what exactly is 'action research' and is it a good thing? To answer these questions we've filmed three case studies.
• David Coghlan Discusses Action Research Professor David Coghlan explains action research as an approach that crosses many academic disciplines yet has a shared focus on taking action to address a problem. He describes the difference between this approach and empirical scientific approaches, particularly highlighting the challenge of getting action research to be taken seriously by academic journals.
• Jean McNiff Discusses Action Research Professor Jean McNiff talks about action research, the responsibility innate to knowledge, and the emerging nature of reality. She highlights key thinkers in the area of emergence and growth. She also discusses issues of empowerment, regarding both students and researched communities.
• Michelle Fine Discusses Community Based Participatory Action Research Professor Michelle Fine discusses her work in participatory action research, an approach to research that is tied to community activism. She explains the core components of PAR as including a variety of expertise; shaping research questions collaboratively; pooling knowledge and evidence; situating research in history, theory, and action; and community ownership of research data.
• Researching Racism in Schools Using Participatory Action Research Dr. Meagan Call-Cummings presents a participatory action research project that had three aims: to uncover and understand racism in schools, to empower marginalized students, and to determine the effectiveness of participatory action research as a means to effect social change.
• Researching Substance Abuse Using Community-Based Participatory Research Methods Professor Liliane Windsor discusses her research on substance abuse using community-based participatory research methods. In community-based participatory research, members of the community partner with academics to conduct the research. Windsor discusses community preparation and brainstorming, her research findings, and community collaborative boards
• Task-Based Language Learning and Teaching: An Action Research Study Megan Calvert, an ESL teacher, describes how she designed, tested, and adjusted a task-based learning exercise for a mixed-level English language course.

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Organizing Academic Research Papers: Types of Research Designs

• Purpose of Guide
• Design Flaws to Avoid
• Glossary of Research Terms
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• Executive Summary
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tertiary Sources
• What Is Scholarly vs. Popular?
• Qualitative Methods
• Quantitative Methods
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Annotated Bibliography
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• How to Manage Group Projects
• Multiple Book Review Essay
• Reviewing Collected Essays
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Research Proposal
• Acknowledgements

Introduction

Before beginning your paper, you need to decide how you plan to design the study .

The research design refers to the overall strategy that you choose to integrate the different components of the study in a coherent and logical way, thereby, ensuring you will effectively address the research problem; it constitutes the blueprint for the collection, measurement, and analysis of data. Note that your research problem determines the type of design you can use, not the other way around!

General Structure and Writing Style

Action research design, case study design, causal design, cohort design, cross-sectional design, descriptive design, experimental design, exploratory design, historical design, longitudinal design, observational design, philosophical design, sequential design.

Kirshenblatt-Gimblett, Barbara. Part 1, What Is Research Design? The Context of Design. Performance Studies Methods Course syllabus . New York University, Spring 2006; Trochim, William M.K. Research Methods Knowledge Base . 2006.

The function of a research design is to ensure that the evidence obtained enables you to effectively address the research problem as unambiguously as possible. In social sciences research, obtaining evidence relevant to the research problem generally entails specifying the type of evidence needed to test a theory, to evaluate a program, or to accurately describe a phenomenon. However, researchers can often begin their investigations far too early, before they have thought critically about about what information is required to answer the study's research questions. Without attending to these design issues beforehand, the conclusions drawn risk being weak and unconvincing and, consequently, will fail to adequate address the overall research problem.

 Given this, the length and complexity of research designs can vary considerably, but any sound design will do the following things:

• Identify the research problem clearly and justify its selection,
• Review previously published literature associated with the problem area,
• Clearly and explicitly specify hypotheses [i.e., research questions] central to the problem selected,
• Effectively describe the data which will be necessary for an adequate test of the hypotheses and explain how such data will be obtained, and
• Describe the methods of analysis which will be applied to the data in determining whether or not the hypotheses are true or false.

Kirshenblatt-Gimblett, Barbara. Part 1, What Is Research Design? The Context of Design. Performance Studies Methods Course syllabus . New Yortk University, Spring 2006.

Definition and Purpose

The essentials of action research design follow a characteristic cycle whereby initially an exploratory stance is adopted, where an understanding of a problem is developed and plans are made for some form of interventionary strategy. Then the intervention is carried out (the action in Action Research) during which time, pertinent observations are collected in various forms. The new interventional strategies are carried out, and the cyclic process repeats, continuing until a sufficient understanding of (or implement able solution for) the problem is achieved. The protocol is iterative or cyclical in nature and is intended to foster deeper understanding of a given situation, starting with conceptualizing and particularizing the problem and moving through several interventions and evaluations.

What do these studies tell you?

• A collaborative and adaptive research design that lends itself to use in work or community situations.
• Design focuses on pragmatic and solution-driven research rather than testing theories.
• When practitioners use action research it has the potential to increase the amount they learn consciously from their experience. The action research cycle can also be regarded as a learning cycle.
• Action search studies often have direct and obvious relevance to practice.
• There are no hidden controls or preemption of direction by the researcher.

What these studies don't tell you?

• It is harder to do than conducting conventional studies because the researcher takes on responsibilities for encouraging change as well as for research.
• Action research is much harder to write up because you probably can’t use a standard format to report your findings effectively.
• Personal over-involvement of the researcher may bias research results.
• The cyclic nature of action research to achieve its twin outcomes of action (e.g. change) and research (e.g. understanding) is time-consuming and complex to conduct.

Gall, Meredith. Educational Research: An Introduction . Chapter 18, Action Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Kemmis, Stephen and Robin McTaggart. “Participatory Action Research.” In Handbook of Qualitative Research . Norman Denzin and Yvonna S. Locoln, eds. 2nd ed. (Thousand Oaks, CA: SAGE, 2000), pp. 567-605.; Reason, Peter and Hilary Bradbury. Handbook of Action Research: Participative Inquiry and Practice . Thousand Oaks, CA: SAGE, 2001.

A case study is an in-depth study of a particular research problem rather than a sweeping statistical survey. It is often used to narrow down a very broad field of research into one or a few easily researchable examples. The case study research design is also useful for testing whether a specific theory and model actually applies to phenomena in the real world. It is a useful design when not much is known about a phenomenon.

• Approach excels at bringing us to an understanding of a complex issue through detailed contextual analysis of a limited number of events or conditions and their relationships.
• A researcher using a case study design can apply a vaiety of methodologies and rely on a variety of sources to investigate a research problem.
• Design can extend experience or add strength to what is already known through previous research.
• Social scientists, in particular, make wide use of this research design to examine contemporary real-life situations and provide the basis for the application of concepts and theories and extension of methods.
• The design can provide detailed descriptions of specific and rare cases.
• A single or small number of cases offers little basis for establishing reliability or to generalize the findings to a wider population of people, places, or things.
• The intense exposure to study of the case may bias a researcher's interpretation of the findings.
• Design does not facilitate assessment of cause and effect relationships.
• Vital information may be missing, making the case hard to interpret.
• The case may not be representative or typical of the larger problem being investigated.
• If the criteria for selecting a case is because it represents a very unusual or unique phenomenon or problem for study, then your intepretation of the findings can only apply to that particular case.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 4, Flexible Methods: Case Study Design. 2nd ed. New York: Columbia University Press, 1999; Stake, Robert E. The Art of Case Study Research . Thousand Oaks, CA: SAGE, 1995; Yin, Robert K. Case Study Research: Design and Theory . Applied Social Research Methods Series, no. 5. 3rd ed. Thousand Oaks, CA: SAGE, 2003.

Causality studies may be thought of as understanding a phenomenon in terms of conditional statements in the form, “If X, then Y.” This type of research is used to measure what impact a specific change will have on existing norms and assumptions. Most social scientists seek causal explanations that reflect tests of hypotheses. Causal effect (nomothetic perspective) occurs when variation in one phenomenon, an independent variable, leads to or results, on average, in variation in another phenomenon, the dependent variable.

Conditions necessary for determining causality:

• Empirical association--a valid conclusion is based on finding an association between the independent variable and the dependent variable.
• Appropriate time order--to conclude that causation was involved, one must see that cases were exposed to variation in the independent variable before variation in the dependent variable.
• Nonspuriousness--a relationship between two variables that is not due to variation in a third variable.
• Causality research designs helps researchers understand why the world works the way it does through the process of proving a causal link between variables and eliminating other possibilities.
• Replication is possible.
• There is greater confidence the study has internal validity due to the systematic subject selection and equity of groups being compared.
• Not all relationships are casual! The possibility always exists that, by sheer coincidence, two unrelated events appear to be related [e.g., Punxatawney Phil could accurately predict the duration of Winter for five consecutive years but, the fact remains, he's just a big, furry rodent].
• Conclusions about causal relationships are difficult to determine due to a variety of extraneous and confounding variables that exist in a social environment. This means causality can only be inferred, never proven.
• If two variables are correlated, the cause must come before the effect. However, even though two variables might be causally related, it can sometimes be difficult to determine which variable comes first and therefore to establish which variable is the actual cause and which is the  actual effect.

Bachman, Ronet. The Practice of Research in Criminology and Criminal Justice . Chapter 5, Causation and Research Designs. 3rd ed.  Thousand Oaks, CA: Pine Forge Press, 2007; Causal Research Design: Experimentation. Anonymous SlideShare Presentation ; Gall, Meredith. Educational Research: An Introduction . Chapter 11, Nonexperimental Research: Correlational Designs. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Trochim, William M.K. Research Methods Knowledge Base . 2006.

Often used in the medical sciences, but also found in the applied social sciences, a cohort study generally refers to a study conducted over a period of time involving members of a population which the subject or representative member comes from, and who are united by some commonality or similarity. Using a quantitative framework, a cohort study makes note of statistical occurrence within a specialized subgroup, united by same or similar characteristics that are relevant to the research problem being investigated, r ather than studying statistical occurrence within the general population. Using a qualitative framework, cohort studies generally gather data using methods of observation. Cohorts can be either "open" or "closed."

• Open Cohort Studies [dynamic populations, such as the population of Los Angeles] involve a population that is defined just by the state of being a part of the study in question (and being monitored for the outcome). Date of entry and exit from the study is individually defined, therefore, the size of the study population is not constant. In open cohort studies, researchers can only calculate rate based data, such as, incidence rates and variants thereof.
• Closed Cohort Studies [static populations, such as patients entered into a clinical trial] involve participants who enter into the study at one defining point in time and where it is presumed that no new participants can enter the cohort. Given this, the number of study participants remains constant (or can only decrease).
• The use of cohorts is often mandatory because a randomized control study may be unethical. For example, you cannot deliberately expose people to asbestos, you can only study its effects on those who have already been exposed. Research that measures risk factors  often relies on cohort designs.
• Because cohort studies measure potential causes before the outcome has occurred, they can demonstrate that these “causes” preceded the outcome, thereby avoiding the debate as to which is the cause and which is the effect.
• Cohort analysis is highly flexible and can provide insight into effects over time and related to a variety of different types of changes [e.g., social, cultural, political, economic, etc.].
• Either original data or secondary data can be used in this design.
• In cases where a comparative analysis of two cohorts is made [e.g., studying the effects of one group exposed to asbestos and one that has not], a researcher cannot control for all other factors that might differ between the two groups. These factors are known as confounding variables.
• Cohort studies can end up taking a long time to complete if the researcher must wait for the conditions of interest to develop within the group. This also increases the chance that key variables change during the course of the study, potentially impacting the validity of the findings.
• Because of the lack of randominization in the cohort design, its external validity is lower than that of study designs where the researcher randomly assigns participants.

Healy P, Devane D. “Methodological Considerations in Cohort Study Designs.” Nurse Researcher 18 (2011): 32-36;  Levin, Kate Ann. Study Design IV: Cohort Studies. Evidence-Based Dentistry 7 (2003): 51–52; Study Design 101 . Himmelfarb Health Sciences Library. George Washington University, November 2011; Cohort Study . Wikipedia.

Cross-sectional research designs have three distinctive features: no time dimension, a reliance on existing differences rather than change following intervention; and, groups are selected based on existing differences rather than random allocation. The cross-sectional design can only measure diffrerences between or from among a variety of people, subjects, or phenomena rather than change. As such, researchers using this design can only employ a relative passive approach to making causal inferences based on findings.

• Cross-sectional studies provide a 'snapshot' of the outcome and the characteristics associated with it, at a specific point in time.
• Unlike the experimental design where there is an active intervention by the researcher to produce and measure change or to create differences, cross-sectional designs focus on studying and drawing inferences from existing differences between people, subjects, or phenomena.
• Entails collecting data at and concerning one point in time. While longitudinal studies involve taking multiple measures over an extended period of time, cross-sectional research is focused on finding relationships between variables at one moment in time.
• Groups identified for study are purposely selected based upon existing differences in the sample rather than seeking random sampling.
• Cross-section studies are capable of using data from a large number of subjects and, unlike observational studies, is not geographically bound.
• Can estimate prevalence of an outcome of interest because the sample is usually taken from the whole population.
• Because cross-sectional designs generally use survey techniques to gather data, they are relatively inexpensive and take up little time to conduct.
• Finding people, subjects, or phenomena to study that are very similar except in one specific variable can be difficult.
• Results are static and time bound and, therefore, give no indication of a sequence of events or reveal historical contexts.
• Studies cannot be utilized to establish cause and effect relationships.
• Provide only a snapshot of analysis so there is always the possibility that a study could have differing results if another time-frame had been chosen.
• There is no follow up to the findings.

Hall, John. “Cross-Sectional Survey Design.” In Encyclopedia of Survey Research Methods. Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 173-174; Helen Barratt, Maria Kirwan. Cross-Sectional Studies: Design, Application, Strengths and Weaknesses of Cross-Sectional Studies . Healthknowledge, 2009. Cross-Sectional Study . Wikipedia.

Descriptive research designs help provide answers to the questions of who, what, when, where, and how associated with a particular research problem; a descriptive study cannot conclusively ascertain answers to why. Descriptive research is used to obtain information concerning the current status of the phenomena and to describe "what exists" with respect to variables or conditions in a situation.

• The subject is being observed in a completely natural and unchanged natural environment. True experiments, whilst giving analyzable data, often adversely influence the normal behavior of the subject.
• Descriptive research is often used as a pre-cursor to more quantitatively research designs, the general overview giving some valuable pointers as to what variables are worth testing quantitatively.
• If the limitations are understood, they can be a useful tool in developing a more focused study.
• Descriptive studies can yield rich data that lead to important recommendations.
• Appoach collects a large amount of data for detailed analysis.
• The results from a descriptive research can not be used to discover a definitive answer or to disprove a hypothesis.
• Because descriptive designs often utilize observational methods [as opposed to quantitative methods], the results cannot be replicated.
• The descriptive function of research is heavily dependent on instrumentation for measurement and observation.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 5, Flexible Methods: Descriptive Research. 2nd ed. New York: Columbia University Press, 1999;  McNabb, Connie. Descriptive Research Methodologies . Powerpoint Presentation; Shuttleworth, Martyn. Descriptive Research Design , September 26, 2008. Explorable.com website.

A blueprint of the procedure that enables the researcher to maintain control over all factors that may affect the result of an experiment. In doing this, the researcher attempts to determine or predict what may occur. Experimental Research is often used where there is time priority in a causal relationship (cause precedes effect), there is consistency in a causal relationship (a cause will always lead to the same effect), and the magnitude of the correlation is great. The classic experimental design specifies an experimental group and a control group. The independent variable is administered to the experimental group and not to the control group, and both groups are measured on the same dependent variable. Subsequent experimental designs have used more groups and more measurements over longer periods. True experiments must have control, randomization, and manipulation.

• Experimental research allows the researcher to control the situation. In so doing, it allows researchers to answer the question, “what causes something to occur?”
• Permits the researcher to identify cause and effect relationships between variables and to distinguish placebo effects from treatment effects.
• Experimental research designs support the ability to limit alternative explanations and to infer direct causal relationships in the study.
• Approach provides the highest level of evidence for single studies.
• The design is artificial, and results may not generalize well to the real world.
• The artificial settings of experiments may alter subject behaviors or responses.
• Experimental designs can be costly if special equipment or facilities are needed.
• Some research problems cannot be studied using an experiment because of ethical or technical reasons.
• Difficult to apply ethnographic and other qualitative methods to  experimental designed research studies.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 7, Flexible Methods: Experimental Research. 2nd ed. New York: Columbia University Press, 1999; Chapter 2: Research Design, Experimental Designs . School of Psychology, University of New England, 2000; Experimental Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Trochim, William M.K. Experimental Design . Research Methods Knowledge Base. 2006; Rasool, Shafqat. Experimental Research . Slideshare presentation.

An exploratory design is conducted about a research problem when there are few or no earlier studies to refer to. The focus is on gaining insights and familiarity for later investigation or undertaken when problems are in a preliminary stage of investigation.

The goals of exploratory research are intended to produce the following possible insights:

• Familiarity with basic details, settings and concerns.
• Well grounded picture of the situation being developed.
• Generation of new ideas and assumption, development of tentative theories or hypotheses.
• Determination about whether a study is feasible in the future.
• Issues get refined for more systematic investigation and formulation of new research questions.
• Direction for future research and techniques get developed.
• Design is a useful approach for gaining background information on a particular topic.
• Exploratory research is flexible and can address research questions of all types (what, why, how).
• Provides an opportunity to define new terms and clarify existing concepts.
• Exploratory research is often used to generate formal hypotheses and develop more precise research problems.
• Exploratory studies help establish research priorities.
• Exploratory research generally utilizes small sample sizes and, thus, findings are typically not generalizable to the population at large.
• The exploratory nature of the research inhibits an ability to make definitive conclusions about the findings.
• The research process underpinning exploratory studies is flexible but often unstructured, leading to only tentative results that have limited value in decision-making.
• Design lacks rigorous standards applied to methods of data gathering and analysis because one of the areas for exploration could be to determine what method or methodologies could best fit the research problem.

Cuthill, Michael. “Exploratory Research: Citizen Participation, Local Government, and Sustainable Development in Australia.” Sustainable Development 10 (2002): 79-89; Taylor, P. J., G. Catalano, and D.R.F. Walker. “Exploratory Analysis of the World City Network.” Urban Studies 39 (December 2002): 2377-2394; Exploratory Research . Wikipedia.

The purpose of a historical research design is to collect, verify, and synthesize evidence from the past to establish facts that defend or refute your hypothesis. It uses secondary sources and a variety of primary documentary evidence, such as, logs, diaries, official records, reports, archives, and non-textual information [maps, pictures, audio and visual recordings]. The limitation is that the sources must be both authentic and valid.

• The historical research design is unobtrusive; the act of research does not affect the results of the study.
• The historical approach is well suited for trend analysis.
• Historical records can add important contextual background required to more fully understand and interpret a research problem.
• There is no possibility of researcher-subject interaction that could affect the findings.
• Historical sources can be used over and over to study different research problems or to replicate a previous study.
• The ability to fulfill the aims of your research are directly related to the amount and quality of documentation available to understand the research problem.
• Since historical research relies on data from the past, there is no way to manipulate it to control for contemporary contexts.
• Interpreting historical sources can be very time consuming.
• The sources of historical materials must be archived consistentally to ensure access.
• Original authors bring their own perspectives and biases to the interpretation of past events and these biases are more difficult to ascertain in historical resources.
• Due to the lack of control over external variables, historical research is very weak with regard to the demands of internal validity.
• It rare that the entirety of historical documentation needed to fully address a research problem is available for interpretation, therefore, gaps need to be acknowledged.

Savitt, Ronald. “Historical Research in Marketing.” Journal of Marketing 44 (Autumn, 1980): 52-58;  Gall, Meredith. Educational Research: An Introduction . Chapter 16, Historical Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007.

A longitudinal study follows the same sample over time and makes repeated observations. With longitudinal surveys, for example, the same group of people is interviewed at regular intervals, enabling researchers to track changes over time and to relate them to variables that might explain why the changes occur. Longitudinal research designs describe patterns of change and help establish the direction and magnitude of causal relationships. Measurements are taken on each variable over two or more distinct time periods. This allows the researcher to measure change in variables over time. It is a type of observational study and is sometimes referred to as a panel study.

• Longitudinal data allow the analysis of duration of a particular phenomenon.
• Enables survey researchers to get close to the kinds of causal explanations usually attainable only with experiments.
• The design permits the measurement of differences or change in a variable from one period to another [i.e., the description of patterns of change over time].
• Longitudinal studies facilitate the prediction of future outcomes based upon earlier factors.
• The data collection method may change over time.
• Maintaining the integrity of the original sample can be difficult over an extended period of time.
• It can be difficult to show more than one variable at a time.
• This design often needs qualitative research to explain fluctuations in the data.
• A longitudinal research design assumes present trends will continue unchanged.
• It can take a long period of time to gather results.
• There is a need to have a large sample size and accurate sampling to reach representativness.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 6, Flexible Methods: Relational and Longitudinal Research. 2nd ed. New York: Columbia University Press, 1999; Kalaian, Sema A. and Rafa M. Kasim. "Longitudinal Studies." In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 440-441; Ployhart, Robert E. and Robert J. Vandenberg. "Longitudinal Research: The Theory, Design, and Analysis of Change.” Journal of Management 36 (January 2010): 94-120; Longitudinal Study . Wikipedia.

This type of research design draws a conclusion by comparing subjects against a control group, in cases where the researcher has no control over the experiment. There are two general types of observational designs. In direct observations, people know that you are watching them. Unobtrusive measures involve any method for studying behavior where individuals do not know they are being observed. An observational study allows a useful insight into a phenomenon and avoids the ethical and practical difficulties of setting up a large and cumbersome research project.

• Observational studies are usually flexible and do not necessarily need to be structured around a hypothesis about what you expect to observe (data is emergent rather than pre-existing).
• The researcher is able to collect a depth of information about a particular behavior.
• Can reveal interrelationships among multifaceted dimensions of group interactions.
• You can generalize your results to real life situations.
• Observational research is useful for discovering what variables may be important before applying other methods like experiments.
• Observation researchd esigns account for the complexity of group behaviors.
• Reliability of data is low because seeing behaviors occur over and over again may be a time consuming task and difficult to replicate.
• In observational research, findings may only reflect a unique sample population and, thus, cannot be generalized to other groups.
• There can be problems with bias as the researcher may only "see what they want to see."
• There is no possiblility to determine "cause and effect" relationships since nothing is manipulated.
• Sources or subjects may not all be equally credible.
• Any group that is studied is altered to some degree by the very presence of the researcher, therefore, skewing to some degree any data collected (the Heisenburg Uncertainty Principle).

Atkinson, Paul and Martyn Hammersley. “Ethnography and Participant Observation.” In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 248-261; Observational Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Patton Michael Quinn. Qualitiative Research and Evaluation Methods . Chapter 6, Fieldwork Strategies and Observational Methods. 3rd ed. Thousand Oaks, CA: Sage, 2002; Rosenbaum, Paul R. Design of Observational Studies . New York: Springer, 2010.

Understood more as an broad approach to examining a research problem than a methodological design, philosophical analysis and argumentation is intended to challenge deeply embedded, often intractable, assumptions underpinning an area of study. This approach uses the tools of argumentation derived from philosophical traditions, concepts, models, and theories to critically explore and challenge, for example, the relevance of logic and evidence in academic debates, to analyze arguments about fundamental issues, or to discuss the root of existing discourse about a research problem. These overarching tools of analysis can be framed in three ways:

• Ontology -- the study that describes the nature of reality; for example, what is real and what is not, what is fundamental and what is derivative?
• Epistemology -- the study that explores the nature of knowledge; for example, on what does knowledge and understanding depend upon and how can we be certain of what we know?
• Axiology -- the study of values; for example, what values does an individual or group hold and why? How are values related to interest, desire, will, experience, and means-to-end? And, what is the difference between a matter of fact and a matter of value?
• Can provide a basis for applying ethical decision-making to practice.
• Functions as a means of gaining greater self-understanding and self-knowledge about the purposes of research.
• Brings clarity to general guiding practices and principles of an individual or group.
• Philosophy informs methodology.
• Refine concepts and theories that are invoked in relatively unreflective modes of thought and discourse.
• Beyond methodology, philosophy also informs critical thinking about epistemology and the structure of reality (metaphysics).
• Offers clarity and definition to the practical and theoretical uses of terms, concepts, and ideas.
• Limited application to specific research problems [answering the "So What?" question in social science research].
• Analysis can be abstract, argumentative, and limited in its practical application to real-life issues.
• While a philosophical analysis may render problematic that which was once simple or taken-for-granted, the writing can be dense and subject to unnecessary jargon, overstatement, and/or excessive quotation and documentation.
• There are limitations in the use of metaphor as a vehicle of philosophical analysis.
• There can be analytical difficulties in moving from philosophy to advocacy and between abstract thought and application to the phenomenal world.

Chapter 4, Research Methodology and Design . Unisa Institutional Repository (UnisaIR), University of South Africa;  Labaree, Robert V. and Ross Scimeca. “The Philosophical Problem of Truth in Librarianship.” The Library Quarterly 78 (January 2008): 43-70; Maykut, Pamela S. Beginning Qualitative Research: A Philosophic and Practical Guide . Washington, D.C.: Falmer Press, 1994; Stanford Encyclopedia of Philosophy . Metaphysics Research Lab, CSLI, Stanford University, 2013.

• The researcher has a limitless option when it comes to sample size and the sampling schedule.
• Due to the repetitive nature of this research design, minor changes and adjustments can be done during the initial parts of the study to correct and hone the research method. Useful design for exploratory studies.
• There is very little effort on the part of the researcher when performing this technique. It is generally not expensive, time consuming, or workforce extensive.
• Because the study is conducted serially, the results of one sample are known before the next sample is taken and analyzed.
• The sampling method is not representative of the entire population. The only possibility of approaching representativeness is when the researcher chooses to use a very large sample size significant enough to represent a significant portion of the entire population. In this case, moving on to study a second or more sample can be difficult.
• Because the sampling technique is not randomized, the design cannot be used to create conclusions and interpretations that pertain to an entire population. Generalizability from findings is limited.
• Difficult to account for and interpret variation from one sample to another over time, particularly when using qualitative methods of data collection.

Rebecca Betensky, Harvard University, Course Lecture Note slides ; Cresswell, John W. Et al. “Advanced Mixed-Methods Research Designs.” In Handbook of Mixed Methods in Social and Behavioral Research . Abbas Tashakkori and Charles Teddle, eds. (Thousand Oaks, CA: Sage, 2003), pp. 209-240; Nataliya V. Ivankova. “Using Mixed-Methods Sequential Explanatory Design: From Theory to Practice.” Field Methods 18 (February 2006): 3-20; Bovaird, James A. and Kevin A. Kupzyk. “Sequential Design.” In Encyclopedia of Research Design . Neil J. Salkind, ed. Thousand Oaks, CA: Sage, 2010; Sequential Analysis . Wikipedia.  

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Qualitative Principles in Action

This workshop delves into the real-world application of qualitative principles in research. Denise Lillvis, PhD, discusses her qualitative research on children in acute healthcare settings. The session includes applicative examples to concepts discussed earlier in the series. 

Participants are invited to bring questions and ideas to share with the group during the session, offering an opportunity for collaborative learning as well as questions about individual projects.

DATE: Wednesday, October 30, 2024 TIME: 9:00 a.m. – 10:30 a.m. LOCATION:  Room 7002, Clinical and Translational Research Center, 875 Ellicott St., Buffalo

*Attendance will be limited to the first 35 registrants (waitlist available).

Denise Lillvis, PhD, MPA Assistant Professor Department of Epidemiology and Environmental Health School of Public Health and Health Professions, UB CTSI K Scholar 2022-2024

For more information, contact [email protected] or 716-844-9282. 

• Open access
• Published: 28 August 2024

The design, implementation, and evaluation of a blended (in-person and virtual) Clinical Competency Examination for final-year nursing students

• Rita Mojtahedzadeh 1 ,
• Tahereh Toulabi 2 , 3 &
• Aeen Mohammadi 1  

BMC Medical Education volume  24 , Article number:  936 ( 2024 ) Cite this article

Metrics details

Introduction

Studies have reported different results of evaluation methods of clinical competency tests. Therefore, this study aimed to design, implement, and evaluate a blended (in-person and virtual) Competency Examination for final-year Nursing Students.

This interventional study was conducted in two semesters of 2020–2021 using an educational action research method in the nursing and midwifery faculty. Thirteen faculty members and 84 final-year nursing students were included in the study using a census method. Eight programs and related activities were designed and conducted during the examination process. Students completed the Spielberger Anxiety Inventory before the examination, and both faculty members and students completed the Acceptance and Satisfaction questionnaire.

The results of the analysis of focused group discussions and reflections indicated that the virtual CCE was not capable of adequately assessing clinical skills. Therefore, it was decided that the CCE for final-year nursing students would be conducted using a blended method. The activities required for performing the examination were designed and implemented based on action plans. Anxiety and satisfaction were also evaluated as outcomes of the study. There was no statistically significant difference in overt, covert, and overall anxiety scores between the in-person and virtual sections of the examination ( p  > 0.05). The mean (SD) acceptance and satisfaction scores for students in virtual, in-person, and blended sections were 25.49 (4.73), 27.60 (4.70), and 25.57 (4.97), respectively, out of 30 points, in which there was a significant increase in the in-person section compared to the other sections. ( p  = 0.008). The mean acceptance and satisfaction scores for faculty members were 30.31 (4.47) in the virtual, 29.86 (3.94) in the in-person, and 30.00 (4.16) out of 33 in the blended, and there was no significant difference between the three sections ( p  = 0.864).

Evaluating nursing students’ clinical competency using a blended method was implemented and solved the problem of students’ graduation. Therefore, it is suggested that the blended method be used instead of traditional in-person or entirely virtual exams in epidemics or based on conditions, facilities, and human resources. Also, the use of patient simulation, virtual reality, and the development of necessary virtual and in-person training infrastructure for students is recommended for future research. Furthermore, considering that the acceptance of traditional in-person exams among students is higher, it is necessary to develop virtual teaching strategies.

Peer Review reports

The primary mission of the nursing profession is to educate competent, capable, and qualified nurses with the necessary knowledge and skills to provide quality nursing care to preserve and improve the community’s health [ 1 ]. Clinical education is one of the most essential and fundamental components of nursing education, in which students gain clinical experience by interacting with actual patients and addressing real problems. Therefore, assessing clinical skills is very challenging. The main goal of educational evaluation is to improve, ensure, and enhance the quality of the academic program. In this regard, evaluating learners’ performance is one of the critical and sensitive aspects of the teaching and learning process. It is considered one of the fundamental elements of the educational program [ 2 ]. The study area is educational evaluation.

Various methods are used to evaluate nursing students. The Objective Structured Clinical Examination (OSCE) is a valid and reliable method for assessing clinical competence [ 1 , 2 ]. In the last twenty years, the use of OSCE has increased significantly in evaluating medical and paramedical students to overcome the limitations of traditional practical evaluation systems [ 3 , 4 ]. The advantages of this method include providing rapid feedback, uniformity for all examinees, and providing conditions close to reality. However, the time-consuming nature and the need for a lot of personnel and equipment are some disadvantages of OSCE [ 5 , 6 ]. Additionally, some studies have shown that this method is anxiety-provoking for some students and, due to time constraints, being observed by the evaluator and other factors can cause dissatisfaction among students [ 7 , 8 ].

However, some studies have also reported that this method is not only not associated with high levels of stress among students [ 9 ] but also has higher satisfaction than traditional evaluation methods [ 4 ]. In addition, during the COVID-19 pandemic, problems such as overcrowding and student quarantine during the exam have arisen. Therefore, reducing time and costs, eliminating or reducing the tiring quarantine time, optimizing the exam, utilizing all facilities for simulating the clinical environment, using innovative methods for conducting the exam, reducing stress, increasing satisfaction, and ultimately preventing the transmission of COVID-19 are significant problems that need to be further investigated.

Studies show that using virtual space as an alternative solution is strongly felt [ 10 , 11 , 12 ]. In the fall of 2009, following the outbreak of H1N1, educational classes in the United States were held virtually [ 13 ]. Also, in 2005, during Hurricane Katrina, 27 universities in the Gulf of Texas used emergency virtual education and evaluation [ 14 ].

One of the challenges faced by healthcare providers in Iran, like most countries in the world, especially during the COVID-19 outbreak, was the shortage of nursing staff [ 15 , 16 ]. Also, in evaluating and conducting CCE for final-year students and subsequent job seekers in the Clinical Skills Center, problems such as student overcrowding and the need for quarantine during the implementation of OSCE existed. This problem has been reported not only for us but also in other countries [ 17 ]. The intelligent use of technology can solve many of these problems. Therefore, almost all educational institutions have quickly started changing their policies’ paradigms to introduce online teaching and evaluation methods [ 18 , 19 ].

During the COVID-19 pandemic, for the first time, this exam was held virtually in our school. However, feedback from professors and students and the experiences of researchers have shown that the virtual exam can only partially evaluate clinical and practical skills in some stations, such as basic skills, resuscitation, and pediatrics [ 20 ].

Additionally, using OSCE in skills assessment facilitates the evaluation of psychological-motor knowledge and attitudes and helps identify strengths and weaknesses [ 21 ]. Clinical competency is a combination of theoretical knowledge and clinical skills. Therefore, using an effective blended method focusing on the quality and safety of healthcare that measures students’ clinical skills and theoretical expertise more accurately in both in-person and virtual environments is essential. The participation of students, professors, managers, education and training staff, and the Clinical Skills Center was necessary to achieve this important and inevitable goal. Therefore, the Clinical Competency Examination (CCE) for nursing students in our nursing and midwifery school was held in the form of an educational action research process to design, implement, and evaluate a blended method. Implementing this process during the COVID-19 pandemic, when it was impossible to hold an utterly in-person exam, helped improve the quality of the exam and address its limitations and weaknesses while providing the necessary evaluation for students.

The innovation of this research lies in evaluating the clinical competency of final-year nursing students using a blended method that focuses on clinical and practical aspects. In the searches conducted, only a few studies have been done on virtual exams and simulations, and a similar study using a blended method was not found.

The research investigates the scientific and clinical abilities of nursing students through the clinical competency exam. This exam, traditionally administered in person, is a crucial milestone for final-year nursing students, marking their readiness for graduation. However, the unforeseen circumstances of the COVID-19 pandemic and the resulting restrictions rendered in-person exams impractical in 2020. This necessitated a swift and significant transition to an online format, a decision that has profound implications for the future of nursing education. While the adoption of online assessment was a necessary step to ensure student graduation and address the nursing workforce shortage during the pandemic, it was not without its challenges. The accurate assessment of clinical skills, such as dressing and CPR, proved to be a significant hurdle. This underscored the urgent need for a change in the exam format, prompting a deeper exploration of innovative solutions.

To address these problems, the research was conducted collaboratively with stakeholders, considering the context and necessity for change in exam administration. Employing an Action Research (AR) approach, a blend of online and in-person exam modalities was adopted. Necessary changes were implemented through a cyclic process involving problem identification, program design, implementation, reflection, and continuous evaluation.

The research began by posing the following questions:

What are the problems of conducting the CCE for final-year nursing students during COVID-19?

How can these problems be addressed?

What are the solutions and suggestions from the involved stakeholders?

How can the CCE be designed, implemented, and evaluated?

What is the impact of exam type on student anxiety and satisfaction?

These questions guided the research in exploring the complexities of administering the CCE amidst the COVID-19 pandemic and in devising practical solutions to ensure the validity and reliability of the assessment while meeting stakeholders’ needs.

Materials and methods

Research setting, expert panel members, job analysis, and role delineation.

This action research was conducted at the Nursing and Midwifery School of Lorestan University of Medical Sciences, with a history of approximately 40 years. The school accommodates 500 undergraduate and graduate nursing students across six specialized fields, with 84 students enrolled in their final year of undergraduate studies. Additionally, the school employs 26 full-time faculty members in nursing education departments.

An expert panel was assembled, consisting of faculty members specializing in various areas, including medical-surgical nursing, psychiatric nursing, community health nursing, pediatric nursing, and intensive care nursing. The panel also included educational department managers and the examination department supervisor. Through focused group discussions, the panel identified and examined issues regarding the exam format, and members proposed various solutions. Subsequently, after analyzing the proposed solutions and drawing upon the panel members’ experiences, specific roles for each member were delineated.

Sampling and participant selection

Given the nature of the research, purposive sampling was employed, ensuring that all individuals involved in the design, implementation, and evaluation of the exam participated in this study.

The participants in this study included final-year nursing students, faculty members, clinical skills center experts, the dean of the school, the educational deputy, group managers, and the exam department head. However, in the outcome evaluation phase, 13 faculty members participated in-person and virtually (26 times), and 84 final-year nursing students enrolled in the study using a census method in two semesters of 2020–2021 completed the questionnaires, including 37 females and 47 males. In addition, three male and ten female faculty members participated in this study; of this number, 2 were instructors, and 11 were assistant professors.

Data collection tools

In order to enhance the validity and credibility of the study and thoroughly examine the results, this study utilized a triangulation method consisting of demographic information, focus group discussions, the Spielberger Anxiety Scale questionnaire, and an Acceptance and Satisfaction Questionnaire.

Demographic information

A questionnaire was used to gather demographic information from both students and faculty members. For students, this included age, gender, and place of residence, while for faculty members, it included age, gender, field of study, and employment status.

Focus group discussion

Multiple focused group discussions were conducted with the participation of professors, administrators, experts, and students. These discussions were held through various platforms such as WhatsApp Skype, and in-person meetings while adhering to health protocols. The researcher guided the talks toward the research objectives and raised fundamental questions, such as describing the strengths and weaknesses of the previous exam, determining how to conduct the CCE considering the COVID-19 situation, deciding on virtual and in-person stations, specifying the evaluation checklists for stations, and explaining the weighting and scoring of each station.

Spielberger anxiety scale questionnaire

This study used the Spielberger Anxiety Questionnaire to measure students’ overt and covert anxiety levels. This questionnaire is an internationally standardized tool known as the STAI questionnaire that measures both overt (state) and covert (trait) anxiety [ 22 ]. The state anxiety scale (Form Y-1 of STAI) comprises twenty statements that assess the individual’s feelings at the moment of responding. The trait anxiety scale (Form Y-2 of STAI) also includes twenty statements that measure individuals’ general and typical feelings. The scores of each of the two scales ranged from 20 to 80 in the current study. The reliability coefficient of the test for the apparent and hidden anxiety scales, based on Cronbach’s alpha, was confirmed to be 0.9084 and 0.9025, respectively [ 23 , 24 ]. Furthermore, in the present study, Cronbach’s alpha value for the total anxiety questionnaire, overt anxiety, and covert anxiety scales were 0.935, 0.921, and 0.760, respectively.

Acceptance and satisfaction questionnaire

The Acceptability and Satisfaction Questionnaire for Clinical Competency Test was developed by Farajpour et al. (2012). The student questionnaire consists of ten questions, and the professor questionnaire consists of eleven questions, using a four-point Likert scale. Experts have confirmed the validity of these questionnaires, and their Cronbach’s alpha coefficients have been determined to be 0.85 and 0.87 for the professor and student questionnaires, respectively [ 6 ]. In the current study, ten medical education experts also confirmed the validity of the questionnaires. Regarding internal reliability, Cronbach’s alpha coefficients for the student satisfaction questionnaire for both virtual and in-person sections were 0.76 and 0.87, respectively. The professor satisfaction questionnaires were 0.84 and 0.87, respectively. An online platform was used to collect data for the virtual exam.

Data analysis and rigor of study

Qualitative data analysis was conducted using the method proposed by Graneheim and Lundman. Additionally, the criteria established by Lincoln and Guba (1985) were employed to confirm the rigor and validity of the data, including credibility, transferability, dependability, and confirmability [ 26 ].

In this research, data synthesis was performed by combining the collected data with various tools and methods. The findings of this study were reviewed and confirmed by participants, supervisors, mentors, and experts in qualitative research, reflecting their opinions on the alignment of findings with their experiences and perspectives on clinical competence examinations. Therefore, the member check method was used to validate credibility.

Moreover, efforts were made in this study to provide a comprehensive description of the research steps, create a suitable context for implementation, assess the views of others, and ensure the transferability of the results.

Furthermore, researchers’ interest in identifying and describing problems, reflecting, designing, implementing, and evaluating clinical competence examinations, along with the engagement of stakeholders in these examinations, was ensured by the researchers’ long-term engagement of over 25 years with the environment and stakeholders, seeking their opinions and considering their ideas and views. These factors contributed to ensuring confirmability.

In this research, by reflecting the results to the participants and making revisions by the researchers, problem clarification and solution presentation, design, implementation, and evaluation of operational programs with stakeholder participation and continuous presence were attempted to prevent biases, assumptions, and research hypotheses, and to confirm dependability.

Data analysis was performed using SPSS version 21, and descriptive statistical tests (absolute and relative frequency, mean, and standard deviation) and inferential tests (paired t-test, independent t-test, and analysis of variance) were used. The significance level was set at 0.05. Parametric tests were used based on the normality of the data according to the Kolmogorov-Smirnov statistical test.

Given that conducting the CCE for final-year nursing students required the active participation of managers, faculty members, staff, and students, and to answer the research question “How can the CCE for final-year nursing students be conducted?” and achieve the research objective of “designing, implementing, and evaluating the clinical competency exam,” the action research method was employed.

The present study was conducted based on the Dickens & Watkins model. There are four primary stages (Fig.  1 ) in the cyclical action research process: reflect, plan, act, observe, and then reflect to continue through the cycle [ 27 ].

The cyclical process of action research [ 27 ]

Stage 1: Reflection

Identification of the problem.

According to the educational regulations, final semester nursing students must complete the clinical competency exam. However, due to the COVID-19 pandemic and the critical situation in most provinces, inter-city travel restrictions, and insufficient dormitory space, conducting the CCE in-person was not feasible.

This exam was conducted virtually at our institution. However, based on the reflections from experts, researchers have found that virtual exams can only partially assess clinical and practical skills in certain stations, such as basic skills, resuscitation, and pediatrics. Furthermore, utilizing Objective Structured Clinical Examination (OSCE) in skills assessment facilitates the evaluation of psychomotor skills, knowledge, and attitudes, aiding in identifying strengths and weaknesses.

P3, “Due to the COVID-19 pandemic and the critical situation in most provinces, inter-city travel restrictions, and insufficient dormitory space, conducting the CCE in-person is not feasible.”

Stage 2: Planning

Based on the reflections gathered from the participants, the exam was designed using a blended approach (combining in-person and virtual components) as per the schedule outlined in Fig.  2 . All planned activities for the blended CCE for final-year nursing students were executed over two semesters.

P5, “Taking the exam virtually might seem easier for us and the students, but in my opinion, it’s not realistic. For instance, performing wound dressing or airway management is very practical, and it’s not possible to assess students with a virtual scenario. We need to see them in person.”

P6"I believe it’s better to conduct those activities that are highly practical in person, but for those involving communication skills like report writing, professional ethics, etc., we can opt for virtual assessment.”

Design and implementation of the blended CCE

Stage 3: Act

Cce implementation steps.

The CCE was conducted based on the flowchart in Fig.  3 and the following steps:

Steps for conducting the CCE for final-year nursing students using a blended method

Step 1: Designing the framework for conducting the blended Clinical Competency Examination

The panelists were guided to design the blended exam in focused group sessions and virtual panels based on the ADDIE (Analysis, Design, Development, Implementation, Evaluation) model [ 28 ]. Initially, needs assessment and opinion polling were conducted, followed by the operational planning of the exam, including the design of the blueprint table (Table  1 ), determination of station types (in-person or virtual), designing question stems in the form of scenarios, creating checklists and station procedure guides by expert panel groups based on participant analysis, and the development of exam implementation guidelines with participant input [ 27 ]. The design, execution, and evaluation were as follows:

In-person and virtual meetings with professors were held to determine the exam schedule, deadlines for submitting checklists, decision-making regarding the virtual or in-person nature of stations based on the type of skill (practical, communication), and presenting problems and solutions. Based on the decisions, primary skill stations, as well as cardiac and pediatric resuscitation stations, were held in person. In contrast, virtual stations for health, nursing ethics, nursing reports, nursing diagnosis, physical examinations, and psychiatric nursing were held.

News about the exam was communicated to students through the college website and text messages. Then, an online orientation session was held on Skype with students regarding the need assessment of pre-exam educational workshops, virtual and in-person exam standards, how to use exam software, how to conduct virtual exams, explaining the necessary infrastructure for participating in the exam by students, completing anxiety and satisfaction questionnaires, rules and regulations, how to deal with rejected individuals, and exam testing and Q&A. Additionally, a pre-exam in-person orientation session was held.

To inform students about the entire educational process, the resources and educational content recommended by the professors, including PDF files, photos and videos, instructions, and links, were shared through a virtual group on the social media messenger, and scientific information was also, questions were asked and answered through this platform.

Correspondence and necessary coordination were made with the university clinical skills center to conduct in-person workshops and exams.

Following the Test-centered approach, the Angoff Modified method [ 29 , 30 ] was used to determine the scoring criteria for each station by panelists tasked with assigning scores.

Additionally, in establishing standards for this blended CCE for fourth-year nursing students, for whom graduation was a prerequisite, the panelists, as experienced clinical educators familiar with the performance and future roles of these students and the assessment method of the blended exam, were involved [ 29 , 30 ](Table 1 ).

Step 2: Preparing the necessary infrastructure for conducting the exam

Software infrastructure.

The pre- and post-virtual exam questions, scenarios, and questionnaires were uploaded using online software.

The exam was conducted on a trial basis in multiple sessions with the participation of several faculty members, and any issues were addressed. Students were authenticated to enter the exam environment via email and personal information verification. The questions for each station were designed and entered into the software by the respective station instructors and the examination coordinator, who facilitated the exam. The questions were formatted as clinical scenarios, images, descriptive questions, and multiple-choice questions, emphasizing the clinical and practical aspects. This software had various features for administering different types of exams and various question formats, including multiple-choice, descriptive, scenario-based, image-based, video-based, matching, Excel output, and graphical and descriptive statistical analyses. It also had automatic questionnaire completion, notification emails, score addition to questionnaires, prevention of multiple answer submissions, and the ability to upload files up to 4 gigabytes. Student authentication was based on national identification numbers and student IDs, serving as user IDs and passwords. Students could enter the exam environment using their email and multi-level personal information verification. If the information did not match, individuals could not access the exam environment.

Checklists and questionnaires

A student list was prepared, and checklists for the in-person exam and anxiety and satisfaction questionnaires were reproduced.

Empowerment workshops for professors and education staff

Educational needs of faculty members and academic staff include conducting clinical competency exams using the OSCE method; simulating and evaluating OSCE exams; designing standardized questions, checklists, and scenarios; innovative approaches in clinical evaluations; designing physical spaces and setting up stations; and assessing ethics and professional commitment in clinical competency exams.

Student empowerment programs

According to the students’ needs assessment results, in-person workshops on cardiopulmonary resuscitation and airway management and online workshops were held on health, pediatrics, cardiopulmonary resuscitation, ethics, nursing diagnosis, and report writing through Skype messenger. In addition, vaccination notes, psychiatric nursing, and educational files on clinical examinations and basic skills were recorded by instructors and made available to students via virtual groups.

Step 3: CCE implementation

The CCE was held in two parts, in-person and virtual.

In-person exam

The OSCE method was used for this section of the exam. The basic skills station exam included dressing and injections, and the CPR and pediatrics stations were conducted in person. The students were divided into two groups of 21 each semester, and the exam was held in two shifts. While adhering to quarantine protocols, the students performed the procedures for seven minutes at each station, and instructors evaluated them using a checklist. An additional minute was allotted for transitioning to the next station.

Virtual exam

The professional ethics, nursing diagnosis, nursing report, health, psychiatric nursing, and physical examination stations were conducted virtually after the in-person exam. This exam was made available to students via a primary and a secondary link in a virtual space at the scheduled time. Students were first verified, and after the specified time elapsed, the ability to respond to inactive questions and submitted answers was sent. During the exam, full support was provided by the examination center.

The examination coordinator conducted the entire virtual exam process. The exam results were announced 48 h after the exam. A passing grade was considered to be a score higher than 60% in all stations. Students who failed in various stations were given the opportunity for remediation based on faculty feedback, either through additional study or participation in educational workshops. Subsequent exams were held one week apart from the initial exam. It was stipulated that students who failed in more than half of the stations would be evaluated in the following semester. If they failed in more than three sessions at a station, a decision would be made by the faculty’s educational council. However, no students met these situations.

Step 4: Evaluation

The evaluation of the exam was conducted by examiners using a checklist, and the results were announced as pass or fail.

Stage 4: Observation / evaluation

In this study, both process and outcome evaluations were conducted:

Process evaluation

All programs and activities implemented during the test design and administration process were evaluated in the process evaluation. This evaluation was based on operational program control and reflections received from participants through group discussion sessions and virtual groups.

Sample reflections received from faculty members, managers, experts, and students through group discussions and social messaging platforms after the changes:

P7: “The implementation of the blended virtual exam, in the conditions of the COVID-19 crisis where the possibility of holding in-person exams was not fully available, in my opinion, was able to improve the quality of exam administration and address the limitations and weaknesses of the exam entirely virtually.”

P5: “In my opinion, this blended method was able to better evaluate students in terms of clinical readiness for entering clinical practice.”

Outcomes evaluation

The study outcomes were student anxiety, student acceptance and satisfaction, and faculty acceptance and satisfaction. Before the start of the in-person and virtual exams, the Spielberger Anxiety Questionnaire was provided to students. Additionally, immediately after the exam, students and instructors completed the acceptance and satisfaction questionnaire for the relevant section. After the exam, students and instructors completed the acceptance and satisfaction questionnaire again for the entire exam process, including feasibility, satisfaction with its implementation, and educational impact.

Design framework and implementation for the blended Clinical Competency Examination

The exam was planned using a blended method (part in-person, part virtual) according to the Fig.  2 schedule, and all planned programs for the blended CCE for final-year nursing students were implemented in two semesters.

Evaluation results

In this study, 84 final-year nursing students participated, including 37 females (44.05%) and 47 males (55.95%). Among them, 28 (33.3%) were dormitory residents, and 56 (66.7%) were non-dormitory residents.

In this study, both process and outcome evaluations were conducted.

All programs and activities implemented during the test design and administration process were evaluated in the process evaluation (Table  2 ). This evaluation was based on operational program control and reflections received from participants through group discussion sessions and virtual groups on social media.

Anxiety and satisfaction were examined and evaluated as study outcomes, and the results are presented below.

The paired t-test results in Table  3 showed no statistically significant difference in overt anxiety ( p  = 0.56), covert anxiety ( p  = 0.13), and total anxiety scores ( p  = 0.167) between the in-person and virtual sections before the blended Clinical Competency Examination.

However, the mean (SD) of overt anxiety in persons in males and females was 49.27 (11.16) and 43.63 (13.60), respectively, and this difference was statistically significant ( p  = 0.03). Also, the mean (SD) of overt virtual anxiety in males and females was 45.70 (11.88) and 51.00 (9.51), respectively, and this difference was statistically significant ( p  = 0.03). However, there was no significant difference between males and females regarding covert anxiety in the person ( p  = 0.94) and virtual ( p  = 0.60) sections. In addition, the highest percentage of overt anxiety was apparent in the virtual section among women (15.40%) and the in-person section among men (21.28%) and was prevalent at a moderate to high level.

According to Table  4 , One-way analysis of variance showed a significant difference between the virtual, in-person, and blended sections in terms of acceptance and satisfaction scores.

The results of the One-way analysis of variance showed that the mean (SD) acceptance and satisfaction scores of nursing students of the CCE in virtual, in-person, and blended sections were 25.49 (4.73), 27.60 (4.70), and 25.57 (4.97) out of 30, respectively. There was a significant difference between the three sections ( p  = 0.008).

In addition, 3 (7.23%) male and 10 (76.3%) female faculty members participated in this study; of this number, 2 (15.38%) were instructors, and 11 (84.62%) were assistant professors. Moreover, they were between 29 and 50 years old, with a mean (SD) of 41.37 (6.27). Furthermore, they had 4 to 20 years of work experience with a mean and standard deviation of 13.22(4.43).

The results of the analysis of variance showed that the mean (SD) acceptance and satisfaction scores of faculty members of the CCE in virtual, in-person, and blended sections were 30.31 (4.47), 29.86 (3.94), and 30.00 (4.16) out of 33, respectively. There was no significant difference between the three sections ( p  = 0.864).

This action research study showed that the blended CCE for nursing students is feasible and, depending on the conditions and objectives, evaluation stations can be designed and implemented virtually or in person.

The blended exam, combining in-person and virtual elements, managed to address some of the weaknesses of entirely virtual exams conducted in previous terms due to the COVID-19 pandemic. Given the pandemic conditions, the possibility of performing all in-person stations was not feasible due to the risk of students and evaluators contracting the virus, as well as the need for prolonged quarantine. Additionally, to meet the staffing needs of hospitals, nursing students needed to graduate. By implementing the blended exam idea and conducting in-person evaluations at clinical stations, the assessment of nursing students’ clinical competence was brought closer to reality compared to the entirely virtual method.

Furthermore, the need for human resources, station setup costs, and time spent was less than the entirely in-person method. Therefore, in pandemics or conditions where sufficient financial resources and human resources are not available, the blended approach can be utilized.

Additionally, the evaluation results showed that students’ total and overt anxiety in both virtual and in-person sections of the blended CCE did not differ significantly. However, the overt anxiety of female students in the virtual section and male students in the in-person section was considerably higher. Nevertheless, students’ covert anxiety related to personal characteristics did not differ in virtual and in-person exam sections. However, students’ acceptance and satisfaction in the in-person section were higher than in the virtual and blended sections, with a significant difference. The acceptance and satisfaction of faculty members from the CCE in in-person, virtual, and blended sections were the same and relatively high.

A blended CCE nursing competency exam was not found in the literature review. However, recent studies, especially during the COVID-19 pandemic, have designed and implemented this exam using virtual OSCE. Previously, the CCE was held in-person or through traditional OSCE methods.

During the COVID-19 pandemic, nursing schools worldwide faced difficulties administering clinical competency exams for students. The virtual simulation was used to evaluate clinical competency and develop nursing students’ clinical skills in the United States, including standard videos, home videos, and clinical scenarios. Additionally, an online virtual simulation program was designed to assess the clinical competency of senior nursing students in Hong Kong as a potential alternative to traditional clinical training [ 31 ].

A traditional in-person OSCE was also redesigned and developed through a virtual conferencing platform for nursing students at the University of Texas Medical Branch in Galveston. Survey findings showed that most professors and students considered virtual OSCE a highly effective tool for evaluating communication skills, obtaining a medical history, making differential diagnoses, and managing patients. However, professors noted that evaluating examination techniques in a virtual environment is challenging [ 32 ].

However, Biranvand reported that less than half of the nursing students believed the in-person OSCE was stressful [ 33 ]. At the same time, the results of another study showed that 96.2% of nursing students perceived the exam as anxiety-provoking [ 1 ]. Students believe that the stress of this exam is primarily related to exam time, complexity, and the execution of techniques, as well as confusion about exam methods [ 7 ]. In contrast to previous research results, in a study conducted in Egypt, 75% of students reported that the OSCE method has less stress than other examination methods [ 9 ]. However, there has yet to be a consensus across studies on the causes and extent of anxiety-provoking in the OSCE exam. In a study, the researchers found that in addition to the factors mentioned above, the evaluator’s presence could also be a cause of stress [ 34 ]. Another survey study showed that students perceived the OSCE method as more stressful than the traditional method, mainly due to the large number of stations, exam items, and time constraints [ 7 ]. Another study in Egypt, which designed two stages of the OSCE exam for 75 nursing students, found that 65.6% of students reported that the second stage exam was stressful due to the problem-solving station. In contrast, only 38.9% of participants considered the first-stage exam stressful [ 35 ]. Given that various studies have reported anxiety as one of the disadvantages of the OSCE exam, in this study, one of the outcomes evaluated was the anxiety of final-year nursing students. There was no significant difference in total anxiety and overt anxiety between students in the in-person and virtual sections of the blended Clinical Competency Examination. The overt anxiety was higher in male students in the in-person part and female students in the virtual section, which may be due to their personality traits, but further research is needed to confirm this. Moreover, since students’ total and overt anxiety in the in-person and virtual sections of the exam are the same in resource and workforce shortages or pandemics, the blended CCE is suggested as a suitable alternative to the traditional OSCE test. However, for generalization of the results, it is recommended that future studies consider three intervention groups, where all OSCE stations are conducted virtually in the first group, in-person in the second group, and a blend of in-person and virtual in the third group. Furthermore, the results of the study by Rafati et al. showed that the use of the OSCE clinical competency exam using the OSCE method is acceptable, valid, and reliable for assessing nursing skills, as 50% of the students were delighted, and 34.6% were relatively satisfied with the OSCE clinical competency exam. Additionally, 57.7% of the students believed the exam revealed learning weaknesses [ 1 ]. Another survey study showed that despite higher anxiety about the OSCE exam, students thought that this exam provides equal opportunities for everyone, is less complicated than the traditional method, and encourages the active participation of students [ 7 ]. In another study on maternal and infant care, 95% of the students believed the traditional exam only evaluates memory or practical skills. In contrast, the OSCE exam assesses knowledge, understanding, cognitive and analytical skills, communication, and emotional skills. They believed that explicit evaluation goals, appropriate implementation guidelines, appropriate scheduling, wearing uniforms, equipping the workroom, evaluating many skills, and providing fast feedback are among the advantages of this exam [ 36 ]. Moreover, in a survey study, most students were satisfied with the clinical environment offered by the OSCE CCE using the OSCE method, which is close to reality and involves a hypothetical patient in necessary situations that increase work safety. On the other hand, factors such as the scheduling of stations and time constraints have led to dissatisfaction among students [ 37 ].

Furthermore, another study showed that virtual simulations effectively improve students’ skills in tracheostomy suctioning, triage concepts, evaluation, life-saving interventions, clinical reasoning skills, clinical judgment skills, intravenous catheterization skills, role-based nursing care, individual readiness, critical thinking, reducing anxiety levels, and increasing confidence in the laboratory, clinical nursing education, interactive communication, and health evaluation skills. In addition to knowledge and skills, new findings indicate that virtual simulations can increase confidence, change attitudes and behaviors, and be an innovative, flexible, and hopeful approach for new nurses and nursing students [ 38 ].

Various studies have evaluated the satisfaction of students and faculty members with the OSCE Clinical Competency Examination. In this study, one of the evaluated outcomes was the acceptability and satisfaction of students and faculty members with implementing the CCE in blended, virtual, and in-person sections, which was relatively high and consistent with other studies. One crucial factor that influenced the satisfaction of this study was the provision of virtual justification sessions for students and coordination sessions with faculty members. Social messaging groups were formed through virtual and in-person communication, instructions were explained, expectations and tasks were clarified, and questions were answered. Students and faculty members could access the required information with minimal presence in medical education centers and time and cost constraints. Moreover, with the blended evaluation, the researcher’s communication with participants was more accessible. The written guidelines and uploaded educational content of the workshops enabled students to save the desired topics and review them later if needed. Students had easy access to scientific and up-to-date information, and the application of social messengers and Skype allowed for sending photos and videos, conducting workshops, and questions and answering questions. However, the clinical workshops and examinations were held in-person to ensure accuracy. The virtual part of the examination was conducted through online software, and questions focused on each station’s clinical and practical aspects. Students answered various questions, including multiple-choice, descriptive, scenario, picture, and puzzle questions, within a specified time. The blended examination evaluated clinical competency and did not delay these individuals’ entry into the job market. Moreover, during the severe human resource shortage faced by the healthcare system, the examination allowed several nurses to enter the country’s healthcare system. The blended examination can substitute in-person examination in pandemic and non-pandemic situations, saving facilities, equipment, and human resources. The results of this study can also serve as a model to guide other nursing departments that require appropriate planning and arrangements for Conducting Clinical Competency Examinations in blended formats. This examination can also be developed to evaluate students’ clinical performance.

One of the practical limitations of the study was the possibility that participants might need to complete the questionnaires accurately or be concerned about losing marks. Therefore, in a virtual session before the in-person exam, the objectives and importance of the study were explained. Participants were assured that it would not affect their evaluation and that they should not worry about losing marks. Additionally, active participation from all nursing students, faculty members, and staff was necessary for implementing this plan, achieved through prior coordination, virtual meetings, virtual group formation, and continuous reflection of results, creating the motivation for continued collaboration and participation.

Among other limitations of this study included the use of the Spielberger Anxiety Questionnaire to measure students’ anxiety. It is suggested that future studies use a dedicated anxiety questionnaire designed explicitly for pre-exam anxiety measurement. Another limitation of the current research was its implementation in nursing and midwifery faculty. Therefore, it is recommended that similar studies be conducted in nursing and midwifery faculties of other universities, as well as in related fields, and over multiple consecutive semesters. Additionally, for more precise effectiveness assessment, intervention studies in three separate virtual, in-person, and hybrid groups using electronic checklists are proposed. Furthermore, it is recommended that students be evaluated in terms of other dimensions and variables such as awareness, clinical skill acquisition, self-confidence, and self-efficacy.

Conducting in-person Clinical Competency Examination (CCE) during critical situations, such as the COVID-19 pandemic, is challenging. Instead of virtual exams, blended evaluation is a feasible approach to overcome the shortages of virtual ones and closely mimic in-person scenarios. Using a blended method in pandemics or resource shortages, it is possible to design, implement, and evaluate stations that evaluate basic and advanced clinical skills in in-person section, as well as stations that focus on communication, reporting, nursing diagnosis, professional ethics, mental health, and community health based on scenarios in a virtual section, and replace traditional OSCE exams. Furthermore, the use of patient simulators, virtual reality, virtual practice, and the development of virtual and in-person training infrastructure to improve the quality of clinical education and evaluation and obtain the necessary clinical competencies for students is recommended. Also, since few studies have been conducted using the blended method, it is suggested that future research be conducted in three intervention groups, over longer semesters, based on clinical evaluation models and influential on other outcomes such as awareness and clinical skill acquisition self-efficacy, confidence, obtained grades, and estimation of material and human resources costs. This approach reduced the need for physical space for in-person exams, ensuring participant quarantine and health safety with higher quality. Additionally, a more accurate assessment of nursing students’ practical abilities was achieved compared to a solely virtual exam.

Data availability

The datasets generated and analyzed during the current study are available on request from the corresponding author.

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Acknowledgements

We want to thank the Research and Technology deputy of Smart University of Medical Sciences, Tehran, Iran, the faculty members, staff, and officials of the School of Nursing and Midwifery, Lorestan University of Medical Sciences, Khorramabad, Iran, and all individuals who participated in this study.

All steps of the study, including study design and data collection, analysis, interpretation, and manuscript drafting, were supported by the Deputy of Research of Smart University of Medical Sciences.

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RM. Participating in study design, accrual of study participants, review of the manuscript, and critical revisions for important intellectual content. TT : The investigator; participated in study design, data collection, accrual of study participants, and writing and reviewing the manuscript. AM: Participating in study design, data analysis, accrual of study participants, and reviewing the manuscript. All authors read and approved the final version of the manuscript.

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This action research was conducted following the participatory method. All methods were performed according to the relevant guidelines and regulations in the Declaration of Helsinki (ethics approval and consent to participate). The study’s aims and procedures were explained to all participants, and necessary assurance was given to them for the anonymity and confidentiality of their information. The results were continuously provided as feedback to the participants. Informed consent (explaining the goals and methods of the study) was obtained from participants. The Smart University of Medical Sciences Ethics Committee approved the study protocol (IR.VUMS.REC.1400.011).

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Mojtahedzadeh, R., Toulabi, T. & Mohammadi, A. The design, implementation, and evaluation of a blended (in-person and virtual) Clinical Competency Examination for final-year nursing students. BMC Med Educ 24 , 936 (2024). https://doi.org/10.1186/s12909-024-05935-9

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This chapter addresses the peculiarities, characteristics, and major fallacies of action research design. This research design is a change-oriented approach. Its central assumption is that complex social processes can best be studied by introducing change into these processes and observing their effects. The fundamental basis for action research is taking actions to address organizational problems and their associated unsatisfactory conditions. Also, researchers find relevant information on how to write an action research paper and learn about typical methodologies used for this research design. The chapter closes with referring to overlapping and adjacent research designs.

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The Sustainable Development Goal (SDG) 11 underscores the imperative of creating inclusive, safe, resilient and sustainable cities and communities by 2030. Here we employ bibliometric techniques to assess the evolving landscape of SDG11 research. Using a comprehensive dataset of over 21,000 scholarly publications, we investigate publication trends, thematic focus areas, authorship patterns, keyword co-occurrences and citation networks related to SDG11 research. The results reveal a consistent increase in research output, reflecting the growing global interest in urban sustainability studies. We identify influential authors, organizations and countries shaping the research landscape, highlighting existing global collaborative networks and emerging research hubs. Core thematic areas emphasize critical topics and interdisciplinary connections. Citation networks underscore the impacts of disseminating research outputs, including seminal works. This study offers insights for policymakers, academics and practitioners to align their collective efforts toward sustainable, inclusive and climate-resilient urban development. Moreover, it advances SDG11 by noting opportunities for further research, knowledge dissemination and international collaboration.

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The growing interest in sustainable urban development is driven by challenges posed by urbanization, socioeconomic activities and environmental issues 1 . Urban areas contribute 80% of the world’s gross domestic product 2 , but also account for around 75% of global resource consumption, 65% of energy use and over 70% of carbon emissions 3 . The ecological footprint of urban environments, which measures the resources required to sustain socioeconomic activities, has been increasing 4 , 5 , and the global urban extent is projected to double by 2030 6 . Similarly, the global urban population is projected to reach 68% by 2050 7 , which could surpass the capacity of most urban areas 8 . Africa and Asia will host most of the future urban populations despite housing and infrastructure inadequacies 7 . Rapid urbanization, poverty and climate change (CC) further intensify the vulnerability of urban dwellers 9 .

Sustainable urban development aims to balance economic production, environmental protection and social inclusiveness. It emerged as a response to the critique of modernist views that prioritized physical appearance and order in cities over context, equity and inclusion 6 . Due to the limited progress in achieving the Millennium Development Goals, the Sustainable Development Goals (SDGs) were established in 2015 to ensure that no country is left behind in achieving sustainable development by 2030 10 . Many of the SDGs are closely related to urban settings, where sustainability challenges are complex and interwoven 11 . SDG11 specifically focuses on urban challenges and aims to make ‘cities and human settlements inclusive, safe resilient and sustainable’ by reducing the negative effects of urban development while improving socioeconomic development 10 .

The importance of SDG11 stems from the principles of inclusive, safe and resilient city. An inclusive city is characterized by the idea that all individuals, irrespective of their economic status, gender, race, ethnicity or religion, have the ability and empowerment to actively engage in the social, economic and political opportunities available within urban environments 6 . It seeks to address environmental racism and promote inclusive and fair urban development through social justice and equitable distribution of environmental benefits and burdens. In such a city, everyone is afforded equal access and participation in the diverse aspects that cities provide. On the other hand, a safe city refers to a city that possesses the capacity to provide protection and security against potential dangers, harm or risks, while a resilient city denotes a city’s ability to recover and restore its fundamental functions and structures following natural disasters and crises caused by human activities 6 , 8 . SDG11 is significant because it aims to ensure that cities develop sustainably.

However, SDG11 has been criticized for its limited emphasis on urban inequalities, decentralization and funding for local authorities 6 . Other challenges include localizing the universal indicators 12 , governance issues 13 , data accessibility and comparability 14 and smart city development 12 , 15 . Nevertheless, SDG11 serves as a platform for directing and monitoring urban development, fostering socioeconomic development and ensuring equity, inclusion and environmental protection 16 . Therefore, it is crucial to assess the literature on progress toward SDG11 targets 10 , especially at the halfway point to the target year, to inform interventions necessary for their achievement 17 .

While SDG11 has attracted significant global research attention 18 , comprehensive reviews of SDG11 literature are limited. Existing studies have primarily focused on assessing all the SDGs 19 , 20 , which obscures specific challenges and makes it difficult to track progress or design targeted interventions for individual goals. Recent work has highlighted the insufficient achievement of the SDGs and the need for transformative governance and participatory approaches 21 . Other studies have underscored the gap between research and policies, the underutilization of cities as pivotal arenas for achieving SDGs 22 and the lack of indicators to measure progress toward implementing SDGs 15 . Some studies have assessed SDGs’ implementation in specific region 17 , their impacts on addressing risks 23 and crises 1 , and their implications for health and well-being 24 , environmental research 25 and private sector involvement 26 . Most of the SDG research emanates from developed countries, showing a gap in the coverage of developing countries 27 . The few SDG11 studies in the Global South have narrow focus. While one paper investigated the impact of SDG11 on forest-based livelihoods 28 , another study researched the challenges of SDG11 implementation using a single-country experience 6 . Therefore, an in-depth and broad review of SDG11 literature is necessary to bridge this knowledge gap and identify key challenges and opportunities as well as potential pathways for achieving the targets set in SDG11.

Therefore, this research aims to assess the SDG11 research trends and themes using a bibliometric technique. It is the first global and comprehensive scientometric study on the SDG11 domain. By focusing on research conducted since the formulation of the SDGs, the study addresses the following research questions: (1) what are the global trends in SDG11 research? (2) How has the thematic focus of SDG11 research evolved over time? (3) What are the challenges and priority areas for SDG11 research? The contributions of the study to theory and practice are to:

Identify significant thematic areas and trends in SDG11 research since the promulgation of the SDGs, which can inform researchers, policymakers and practitioners about the current state of knowledge within the field and highlight priority areas for SDG11 research.

Map research clusters, knowledge sharing and collaboration patterns, thereby providing insights into the dynamics of research networks and facilitating the formulation of strategies to foster research excellence, interdisciplinary and international collaborations and the effective allocating of research resources.

Underscore the knowledge gaps, emerging topics and challenges within SDG11 research, offering evidence-based insights to align urban development initiatives with SDG11 research frontiers, enhance the efficacy of interventions and contribute to the development of inclusive, safe, resilient and sustainable cities.

SDG11 research trends

Research on SDG11 has significantly grown in terms of annual publications and citations since 2016, indicating a rising interest in this field (Fig. 1 ). The number of publications has increased by 1.3-fold, and this upward trajectory is expected to continue. Notable emerging research areas include the institutionalization of SDGs within local and global settings 18 and the impact of smart cities on advancing the SDGs 12 , 15 . Previously, studies on the epistemology and challenges of urban population growth were prevalent 29 . However, SDG11 research has now evolved into multidisciplinary fields, driven by heightened attention to urban challenges such as CC, urbanization and population growth.

A total of 21,153 articles were published, receiving 229,182 citations. The number of publications rose from 9,238 in period 1 (2016–2019) to 11,915 in period 2 (2020–2022).

Source data

The increasing trend in SDG11 publications can be attributed to several factors, including the desire to improve institutional rankings, a supportive research environment, investments and endowments, faculty promotion requirements and advancements in information and communication technology. There are also socioeconomic factors, such as increasing urbanization rates and gross domestic product, urban expansion and transformation, a deeper understanding of urban dynamics and challenges. Additionally, the policy environments in different countries can influence academic interests and research in urban studies, shaping research priorities and collaborations. Other contributing factors include research challenges faced by low-income countries and research support by governments, the private sector, international development agencies and scholars, all focusing on sustainable urban development.

SDG11 research is further propelled by recent international summits and collaborations that highlight the urgency of protecting the ecosystem and ensuring human safety 1 . Since 2015, CC issues have received greater attention due to key factors. The adoption of the Paris Agreement raised awareness and urgency for action on CC, resulting in a greater focus on related issues in various sectors, including urban planning and policy 13 . Scientific consensus on CC impacts and the role of human activities has also strengthened over the years, with Intergovernmental Panel on Climate Change assessments emphasizing the significance of cities in addressing CC 23 . As a result, CC considerations are increasingly integrated into research, policy and planning processes.

Urban planning and development strategies have prioritized climate mitigation and adaptation measures, such as reducing greenhouse gas emissions, promoting renewable energy, enhancing resilience to extreme weather events and incorporating green infrastructure. The focus on CC has accelerated the transition toward low-carbon and resilient cities, with efforts directed toward sustainable transportation, energy-efficient buildings, green spaces and climate-responsive infrastructure 6 . Collaboration and international cooperation are essential in addressing climate change, with cities and countries sharing best practices, knowledge and resources to develop and implement climate action plans 24 . Initiatives such as the C40 Cities Climate Leadership Group facilitate knowledge exchange and collective action among cities 30 . The increased attention to CC signifies a shift toward more sustainable and resilient urban development, emphasizing the need for proactive measures to mitigate greenhouse gas emissions, adapt to climate risks and promote equitable and sustainable urban environments.

Thematic focus of SDG11 research

There is an imbalance in the attention given to research themes within SDG11 as revealed by co-occurrence map (Supplementary Fig. 1 ). The dominant themes are affordable housing (SDG11.1), urban transport (SDG11.2), policy and governance (SDG11.3) and access to public spaces (SDG11.7). Housing affordability issues have consistently remained a focal point in SDG11 research, with urban studies, policy development and community-driven efforts for finding solutions to these complex challenges 30 , 31 . These issues were highlighted in Habitat I (Vancouver, 1976), which emphasized the importance of shifting governance and planning paradigms to develop policies and strategies to address rapid urbanization challenges, including shelter shortages and urban inequalities, and promote affordable housing options 30 , 32 . Habitat I has laid the foundation for subsequent global efforts and policy frameworks, such as Habitat II (Istanbul, 1996) and the New Urban Agenda, which continue to prioritize housing as a pivotal component of sustainable urban development. The persistent focus on affordable housing shows that cities still face many challenges in providing adequate housing for all 30 .

Urban policy and governance are other significant terms, indicating scholarly focus on strategies for promoting inclusive and sustainable urban development, enhancing participatory, integrated and sustainable urban planning and management. However, many cities lack the capacity to address urban inequalities, provide adequate housing 31 , public spaces and other urban services, which disproportionately affect women and racial minorities 30 . Moreover, urban redevelopment practices that lead to gentrification exacerbate existing inequalities 32 . Governance-based approaches seek to improve collaboration between public agencies and civil society to prioritize the implementation of urban planning strategies that enhance livability standards while addressing challenges such as CC and sustainability 30 .

Urban transport, which is related to SDG11.2 aiming to ensure safe, affordable, accessible and sustainable transport systems for all, has emerged as a key research theme. Important issues related to mobility, transportation and urban form include increased automobile dependence amid growing urbanization and suburbanization, challenges faced by public transit systems, growing awareness of environmental concerns, shift toward sustainable and multimodal transportation, transit-oriented development, integration of technology in transportation systems and the relationship between transportation and urban densification, compact development, CC adaptation and resilience, equity and social inclusion, and shifts in policy and governance approaches 1 , 6 , 11 . This theme also emphasizes the importance of walkability, public transit infrastructure and their role in enhancing transportation accessibility and influencing mode choice 33 . The transportation cluster also suggests that improving accessibility through urban form and built environment interventions can impact the travel behavior of urban residents and offer cobenefits for human health and environmental sustainability 24 . Incorporating such cobenefits in SDG11.2 could provide more incentives for access to safe efficient, equitable and sustainable transport infrastructure and systems in cities.

The implications of urbanization and land-use changes for sustainability, resilience and CC adaptation and mitigation in cities are also major themes. SDG11.6 aims to reduce the environmental impacts of cities, particularly in relation to air pollution and waste. The literature suggests that regulating urban growth 6 , controlling land-use changes, conserving biodiversity 27 and promoting green infrastructure are essential for achieving this target 34 . These actions, when implemented within integrated planning frameworks, can also reduce vulnerability, enhance resilience and contribute to progress in CC adaptation and mitigation, as emphasized in SDG11.5 (ref. 6 ). Such integrated frameworks should recognize the interconnections between various urban systems, including water, food, energy, waste and transportation, to promote sustainable and resilient urban development 35 . Cities are adopting strategies to reduce their carbon footprint, enhance energy efficiency and prepare for climate risks.

Smart cities and innovation enabled by information and communication technologies have increasingly been utilized to tackle urban development challenges and facilitate innovative and transformative urban governance mechanisms that contribute to the SDGs 15 . The rapid development and integration of digital technologies, such as the Internet of Things, artificial intelligence, big data analytics and sensor networks, have opened new possibilities for improving urban services, infrastructure and quality of life 33 . Smart cities leverage these technologies to enhance efficiency, connectivity and sustainability. The interest in smart cities stems from the recognition that technology can play a transformative role in addressing urban challenges, improving quality of life, promoting sustainability and fostering economic growth 12 , 36 . However, it is important to ensure that smart city initiatives are inclusive, equitable and responsive to the needs and aspirations of all residents.

Comparing the co-occurrence maps of period 1 and period 2 reveals limited changes in key thematic areas, despite the emergence of the coronavirus disease 2019 (COVID-19) pandemic during period 2 (Fig. 2 ). The key thematic areas in period 2, including urban governance and policy, transportation, urban sustainability and resilience, and urbanization and urban growth, remain consistent with period 1, indicating the continued relevance of these topics in research, albeit with potential expansions. However, a closer analysis of the clusters reveals that COVID-19 has emerged as a new area of SDG11 research in period 2, as attention has shifted toward adapting to the pandemic’s detrimental effects on cities. The pandemic has triggered paradigm shifts in various SDG11 domains, including public health, remote work, digitalization, vulnerabilities, inequalities, resilience, sustainability, urban spaces, proximity-based planning approaches such as the 15-minute city and global cooperation 9 . These shifts have influenced work, health, social equity, environmental stewardship 2 and urban planning, shaping innovative approaches and priorities in the postpandemic world. Urban inequality terms, such as slums and informality, inadequate housing and poverty, are brought to the forefront by the pandemic. Controlling the pandemic and addressing the citizen demand in slums and informal settlements has received significant attention 37 , 38 , 39 , 40 . Mobility restrictions and lockdowns to curb the virus’s transmission have presented challenges for service accessibility, particularly in disadvantaged neighborhoods where vulnerable groups reside. Lastly, the connection between sustainability and resilience has strengthened in the postpandemic period. The pandemic has offered new insights into the susceptibility of cities to various stressors and highlighted the inseparable connections between urban resilience and SDG11 (ref. 28 ).

a , b , The key thematic areas in period 1 (2016–2019) ( a ) are urban governance and policy (red), transportation (blue), urban sustainability and resilience (green), and urbanization and urban growth (yellow), while period 2 (2020–2022) ( b ) primarily focuses on urban governance and policies (red), urban studies (red), transportation (blue) and urbanization (green), particularly after the pandemic.

However, three SDG11 targets are not well-represented in both periods. One such target is SDG11.4, which aims to enhance efforts in preserving and conserving natural heritage, vital for improving urban sustainability 41 . Another target, SDG11.a, which focuses on strengthening urban–rural linkages, is also not adequately reflected in Fig. 2 . The intrinsic connection between cities and their surrounding rural areas necessitates the incorporation and strengthening of ties between urban and rural regions to achieve SDG11 (ref. 6 ). Gaps related to rural–urban linkages include limited understanding of interdependencies, inadequate infrastructure and services in rural areas, weak governance and coordination mechanisms, and social and cultural disconnect 13 . These gaps hinder the development of integrated strategies, contribute to economic disparities, limit access to services, impact agricultural productivity and food security, and create environmental and social challenges. Lastly, there is a lack of research on SDG11.c, which aims to support least-developed nations in developing safe and resilient urban areas, which is not surprising as these countries are often underrepresented in urban studies research 30 .

Major contributors to SDG11 research

Various countries, institutions, journals and authors have contributed to SDG11 research between 2016 and 2022. China leads in terms of the number of publications and citations generated, followed by the United States and the United Kingdom (Supplementary Fig. 2 and Supplementary Table 1 ). Among the top 20 productive countries, 14 are from the Global North countries, with South Africa and Brazil as the sole representative of Africa and Latin America and the Caribbean, respectively (Supplementary Fig. 3 and Supplementary Table 2 ). Increasing research collaboration among the top countries (Fig. 3 ), research infrastructure and facilities, manpower and financial support significantly contribute to their high SDG11 research output.

China followed by the United States and the United Kingdom dominates SDG11 research collaborations. There are significant connections among European, North American and Asian institutions, while Africa is less connected with Asia and Latin America and the Caribbean. Freq, frequently.

A co-citation analysis (Supplementary Table 3 ) reveals that Chinese institutions, such as the Chinese Academy of Sciences, have the highest number of articles and citation counts, followed by University College London and the University of Melbourne. The leading affiliations have changed over time, highlighting the strengthening of research institutes and the correlation between research collaboration and societal impacts (Supplementary Table 4 ). In terms of influential journals for SDG11 research, ‘land’ followed by ‘cities and land use’ policy tops the list (Supplementary Tables 5 and 6 ), with a growing interest in fields related to smart and sustainable cities, transport policies, regional planning and environmentally conscious building practices (Supplementary Fig. 4 ). These journals also address multiple issues related to environmental concerns, technological advancements, economic benefits, quality of life, justice and public awareness, driving the development of smart and sustainable cities.

The 15 most published authors in both periods focused on urbanization and urban growth, and the implementation, challenges and achievements of SDG11 (Supplementary Fig 5 ). This indicates an increased recognition of the SDG11 targets and their implementation over time, with the contributions of these authors significantly increasing from 2002 to 2016. Supplementary Table 7 shows that Chinese authors dominate the SDG11 publications, which correlates with China’s lead in institutions, affiliations and collaborations related to SDG11 research. The most cited SDG11 articles are revealed in Supplementary Table 8 , while the prominent authors that influenced SDG11 research are reported in Supplementary Table 9 . The top cited papers by SDG11 research are presented in Supplementary Tables 10 and 11 .

Key facts from the bibliometric analysis

The research on SDG11 has gained significant prominence across various fields, including urban studies, environmental sciences, geography, transportation and urban governance (Supplementary Table 12 ). The increasing environmental concerns, urbanization and global economic growth have spurred academic interest in SDG11 research from disciplines such as human geography, transportation, forestry, CC and sustainability science (Supplementary Table 13 ). Key thematic areas within SDG11 research encompass urban governance, affordable housing, transportation, urban sustainability and resilience, smart cities, urbanization and urban growth, which align closely with SDG11 targets 18 , 20 , 42 , 43 . However, research focus on SDG11 has remained relatively stable, with limited attention given to urban inequalities, safeguarding cultural and natural heritage 41 and specific impacts of the COVID-19 pandemic on urban sustainability.

This study reveals a notable increase in the total SDG11 research output from 2016 to 2022, reflecting the growing emphasis on SDG11 research in recent years compared with earlier periods. China emerges as the leaders in terms of research outputs, citations, authors, institutions and collaborations, closely followed by the United States and the United Kingdom. These three countries contribute 47.71% of SDG11 research productivity within this period, which is higher than 31% reported in a previous similar study 28 .

The dominance of Global North countries in the top 20 countries with the highest number of publications and citations related to SDG11 research is expected given their strong institutional capacity, research funding, highly ranked universities and collaborations. China’s surge in publications on SDG11 can be attributed to rapid urbanization, economic growth, government support and active international collaborations 2 , 11 . Generally, the landscape of research on SDG11 demonstrates an Anglo–American hegemony, which may reinforce power asymmetries and have significant implications for sustainability and resilience 30 . It is concerning that while projections indicate that 90% of future urban population growth will occur in cities of the Global South, particularly Africa and Asia, there is limited research on urban development challenges in these regions 7 .

The debate about the politics of knowledge production in SDG11 research often revolves around the controls of knowledge production processes. Large, well-funded institutions in developed countries tend to dominate research agendas, focusing on themes and solutions relevant to their own contexts, overlooking the unique needs and challenges of the Global South, which perpetuate existing inequalities and privileging certain types of knowledge. Also, knowledge production involves recognizing and integrating diverse ways of knowing. While Western scientific paradigms have traditionally dominated SDG11 research, there is an increasing recognition of the importance of indigenous and non-Western knowledge systems. Integrating these diverse epistemologies enriches understanding and leads to more effective and culturally relevant solutions.

Additionally, SDG11 research is inherently interdisciplinary, involving fields such as urban planning, sociology, environmental science and public policy. However, interdisciplinary collaboration can be challenging due to differing terminologies, methodologies and research priorities. Navigating these differences becomes crucial in the politics of knowledge production to create cohesive and comprehensive research outputs. Finally, bridging the gap between knowledge production and its implementation faces political, economic and social barriers. Researchers and practitioners are increasingly considering how knowledge on urban sustainability can effectively influence policymaking and practice in diverse urban contexts. Mobilizing knowledge to address these barriers becomes a key consideration in the politics of knowledge production.

Challenges to achieving SDG11

There are several challenges to achieving SDG11 targets, including inadequate provision of affordable housing 31 , essential services 24 , green spaces 2 , 34 , efficient transportation 33 and conservation of cultural and natural assets 25 . Rapid urbanization 1 , 7 , CC impacts 44 , insufficient investment in public infrastructure 30 , poor governance 13 and widening livelihood, land and resources inequalities 43 further exacerbate these challenges. For example, rapid urbanization puts immense pressure on housing, infrastructure, services and resources, making it challenging to effectively manage urban growth and ensure sustainable urban development 11 . Inadequate urban planning and land-use policies lead to inefficient land utilization, urban sprawl and inadequate provision of basic services 7 , 21 . The existence of slums and informal settlements where a large portion of the urban dwellers live in substandard housing conditions without tenure security 14 and limited access to electricity, water, sanitation, education, healthcare and employment opportunities 23 , 37 , and marginalized and vulnerable populations facing social exclusion, add to the complexity.

Moreover, competing priorities and trade-offs, lack of integration among various urban sectors and agencies 35 , inadequate human, technical and material resources at local government levels 45 , and insufficient local indicators and methods for implementation and monitoring 46 often hamper the implementation of SDG11 targets. Additionally, limited awareness of SDG-related challenges for policy formulation and implementation hinders context-depended decision-making and targeted interventions 21 , 27 . Addressing social inequalities, ensuring inclusivity in urban development and synergy among multiple fields, including social, technical, environmental, policy and management are crucial for achieving SDG11 (refs. 14 , 26 , 46 ). A valuable lesson can be learned from the success of the framework for assessing the implementation of SDG11 targets at the local level in Japan 42 .

Conclusions

This study aims to enhance our understanding of urban sustainability and provide insights for future research, policies and actions needed to achieve SDG11 targets. By conducting a comprehensive bibliometric assessment of over 21,000 publications from 2016 to 2022, it significantly contributes to the existing body of knowledge, highlighting trends, thematic areas and knowledge gaps related to SDG11 research across countries, institutions, authors and journals. SDG11 research has evolved into a multidisciplinary field, encompassing diverse themes, such as transportation, housing, urban sustainability, smart cities, urbanization and urban governance and policy. However, there is a need to address the gaps in research on urban safety and inclusion, which are critical dimensions often overlooked in favor of environmental and economic aspects of sustainability. This imbalance in research thematic areas risks perpetuation of already existing disparities within SDG11 research and its goals.

China, the United States and the United Kingdom emerge as the top contributors to SDG11 research and collaboration. To foster more SDG11 research in low-income economies, it is essential to provide increased funding support, capacity building and training for scholars, promote collaboration and knowledge exchange, and improve research infrastructure and data collection. Despite global challenges such as armed conflicts, CC and the COVID-19 pandemic, progress toward achieving the SDGs will become apparent by 2030. However, there are still opportunities for further research, knowledge dissemination and international collaboration toward developing safe, sustainable and inclusive urban development. The following are priority areas for SDG11 research:

Urban policy and governance: reforms should focus on providing equitable access to basic services such as water, sanitation, electricity, healthcare and education; upgrading and formalizing informal settlements; and improving living conditions of over one billion people residing in slums 37 . Participatory governance, community engagement and empowerment can enhance social inclusion by considering the voices and needs of marginalized groups 13 , 23 . Urban policy should also prioritize preserving historic and natural resources, protecting vulnerable areas and implementing sustainable urban design principles 47 . Future studies can help understand the dynamics, challenges and opportunities and monitor progress toward SDG11 targets 15 .

Localizing SDG11 targets: spatial planning and land-use strategies should consider the needs of diverse urban populations, promote inclusive zoning and engage local communities and stakeholders in decision-making processes, crucial for fostering ownership, empowerment and social cohesion, leading to more sustainable and inclusive urban development 3 . However, enhancing the capacity for localizing SDG11 targets requires building the knowledge and skills of local governments, policymakers and practitioners. Capacity-building initiatives, such as training programs, workshops and knowledge exchange, can promote interdisciplinary understanding and sharing of best practices.

Concerted and collaborative efforts: the international community, academics, policymakers and stakeholders can work together to create inclusive, safe, resilient and sustainable communities. Collaborative efforts can facilitate a comprehensive understanding of urban challenges and potential solutions by integrating diverse perspectives, data and methodologies. Disseminating research findings contributes to evidence-based policy development and informed decision-making, enabling the learning of lessons and replication of successful interventions.

Breaking down silos: integrated and cross-sectoral approaches help narrow the gaps between sectors, local governments, policymakers and stakeholders, leveraging local resources and capacities while fostering communication, knowledge sharing and collaboration 31 . Cross-sectoral working groups, joint planning processes and integrated policy frameworks promote holistic and coordinated decision-making among various sectors, including urban planning, housing, transportation, health, education, environment and social welfare 47 .

Digitalization and smart city development: maximizing the benefits of digitalization and smart city solutions requires addressing challenges such as bridging digital divides and ensuring data access, privacy and security. Prioritizing citizen-centric approaches and public accessibility to technology 36 are essential for leveraging expertise and resources 15 . Interoperability, scalability, data-driven decision-making and inclusivity contribute to evidence-based planning and equitable access to smart city technologies 12 , 48 , 49 , 50 , 51 .

This study comprehensively assessed SDG11 research, emphasizing significant thematic areas, trends, challenges and suggestions for prioritizing SDG11, including effective urban policy and governance, localizing SDG11 targets, concerted and collaborative efforts, and digitalization and smart city development. To broaden the scope of SDG11 research, future bibliometric reviews should encompass non-Web of Science databases and gray literature, including publications from government and nongovernmental agencies. Despite its limitations, this study’s findings provide valuable references for further research on SDG11.

The present study utilized a bibliometric technique to analyze academic publication on SDG11, tracing the research trend, the evolving key themes and identifying contributing authors, institutions and countries. Bibliometrics is a quantitative technique that allows for the analysis of trends in scholarly publications, such as research articles, conference papers and books, and visualizes scholarly publication patterns 52 . This technique is instrumental in analyzing extensive literature sets by relying on statistical observations and text-mining capabilities, which qualitative review methods such as systematic reviews cannot accomplish 53 . Additionally, it presents a scientific landscape of authors, countries, organizations and collaborations that contribute to worldwide scientific literature.

Bibliometric analysis requires interpretation, introducing an element of subjectivity 54 . Therefore, a sensemaking approach was adopted to transition from describing the bibliometric results to interpreting them. Sensemaking helps derive insightful information from bibliometric analysis and can be integrated into systematic literature reviews 55 , 56 . It applies to various international indexing, abstracting and citation databases, such as Scopus, Web of Science, Dimensions, PubMed and Education Resources Information Center, which cover journals, books, reviews and conference proceedings from around the world and different regions. For this study, Web of Science was chosen as the database to obtain bibliographic data due to its wide range of topics in various fields of study such as natural sciences, health sciences, engineering, social science, computer science and materials sciences. It is one of the world’s largest peer-reviewed scientific literature databases, with 87 million indexed items.

Specialized bibliometrics software were employed, including VOSviewer (version 1.6.19) 52 , Biblioshiny (version 4.1.3) 55 and BibExcel (version 2017) 57 . VOSviewer, known for its user-friendly interface, was used to understand the thematic focus and evolution of research on SDG11. It generates networks of nodes and links, with node size representing the frequency of the studied item, and link width indicating the strength of connections between items. Clusters of intricately linked nodes are shown in distinct colors. The thematic focus was examined for two periods: period 1 (2016–2019) and period 2 (2020–2022), considering the time since the SDGs were introduced to the time of data collection in this study. Another reason for this categorization is that evidence shows that the pandemic has significantly affected progress toward achieving SDGs 58 . VOSviewer allows for various types of analysis, including term co-occurrence, co-citation, citation and bibliographic coupling 53 . A term co-occurrence analysis was used in this study to highlight key thematic areas. To ensure accuracy and avoid separate counting of synonyms, a thesaurus file was developed and added to the software before the analysis. A summary of the data, including the number of authors and journals, used in the analysis is presented in Table 1 and will be further explained below.

A comprehensive search query was formulated to retrieve relevant data on SDG11, and it was executed in the title, abstract and keywords fields (TS) in Web of Science on 5 July 2023. The initial query shown the following box resulted in a total of 334,224 documents. Co-citation analysis was employed to identify the most influential journals contributing to SDG11 research. Two works are considered co-cited when they are both mentioned in the works cited section of a subsequent publication 59 (Zhao, 2006).

TS = ((‘city’ OR ‘cities’ OR ‘human settlement*’ OR ‘urban’ OR ‘metropoli*’ OR ‘town*’ OR ‘municipal*’ OR ‘peri-urban*’ OR ‘urban-rural’ OR ‘rural-urban’) AND (‘gentrification’ OR ‘congestion’ OR ‘transport*’ OR ‘housing’ OR ‘slum*’ OR ‘informal settlement*’ OR ‘sendai framework’ OR ‘Disaster Risk Reduction’ OR ‘disaster’ OR ‘DRR’ OR ‘smart cit*’ OR ‘resilient building*’ OR ‘sustainable building*’ OR ‘building design’ OR ‘buildings design’ OR ‘urbani?ation’ OR ‘zero energy’ OR ‘zero-energy’ OR ‘basic service*’ OR ‘governance’ OR ‘citizen participation’ OR ‘collaborative planning’ OR ‘participatory planning’ OR ‘inclusiveness’ OR ‘cultural heritage’ OR ‘natural heritage’ OR ‘UNESCO’ OR ‘ecological footprint’ OR ‘environmental footprint’ OR ‘waste’ OR ‘pollution’ OR ‘pollutant*’ OR ‘waste water’ OR wastewater* OR waste-water* OR ‘recycling’ OR ‘circular economy’ OR ‘air quality’ OR ‘green space’ OR ‘green spaces’ OR ‘nature inclusive’ OR ‘nature inclusive building’ OR ‘nature inclusive buildings’ OR ‘resilient’ OR ‘resilience’ OR ‘healthy cit*’ OR ‘sustainable’ OR ‘sustainability’ OR ‘green’ OR ‘nature*’ OR ‘Green infrastructure*’ OR ‘nature-based solution*’ OR ‘nature based solution*’ OR ‘child*’ OR ‘wom?n’ OR ‘elderl*’ OR ‘disabl*’ OR ‘disabilit*’ OR ‘disabled’)) AND PY = (2016–2022) NOT PY = (2023)

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework was used to report document search and filtration process. The PRISMA framework is designed to help scholars transparently report why their review study is conducted, what activities are performed and what discoveries are made, ideal for both systematic reviews and bibliometric studies 60 . PRISMA presents the four stages of the above query’s overall searching and filtration process (Fig. 4 ). The identification stage yielded 334,224 records, which were then screened to select only article-type documents ( n  = 277,165). Subsequently, documents were further screened based on language, selecting only English documents ( n  = 257,374). In the final stage, documents were screened based on specific categories closely related to cities and SDG11, resulting in a selection of six major categories: urban studies, environmental studies, geography, urban and regional planning, architecture, transportation and physical geography ( n  = 21,168). Finally, 15 duplicated documents were removed, resulting in a final dataset of 21,153 documents.

A four-phase flow diagram of the data extraction and filtration process of SDG11 literature, adapted from Priyadarshini 57 . WoS, Web of Science.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The data that support the findings of this study are available as supplementary information. The steps for curating the data from the Web of Science have been provided in the text. If there is a further need, data are available on figshare at https://doi.org/10.6084/m9.figshare.26360125 . Source data are provided with this paper.

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Acknowledgements

A.I.A. acknowledges Imam Abdulrahman Bin Faisal University in Dammam, Saudi Arabia, for their support in conducting this study. A.S. acknowledges the support of the Japan Society for the Promotion of Science KAKENHI grant number 22K04493. We appreciate Hiroshima University for supporting the open-access publication of this article.

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A.I.A.: conceptualization, methodology, formal analysis, data curation, writing—original draft, writing—review and editing, investigation and project administration. A.S.: methodology, software, formal analysis, visualization and writing—original draft. Y.A.A.: conceptualization, writing—original draft, investigation and validation. S.A.: methodology, software, formal analysis, visualization and data curation. L.M.: writing—review and editing, and investigation. W.L.F.: writing—review and editing, and investigation. I.R.A.: writing—review and editing, investigation, supervision, validation and resources.

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Almulhim, A.I., Sharifi, A., Aina, Y.A. et al. Charting sustainable urban development through a systematic review of SDG11 research. Nat Cities (2024). https://doi.org/10.1038/s44284-024-00117-6

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Zhang, S.; Guo, K.; Yang, Q.; Xu, X. Review of Wind Field Characteristics of Downbursts and Wind Effects on Structures under Their Action. Buildings 2024 , 14 , 2653. https://doi.org/10.3390/buildings14092653

Zhang S, Guo K, Yang Q, Xu X. Review of Wind Field Characteristics of Downbursts and Wind Effects on Structures under Their Action. Buildings . 2024; 14(9):2653. https://doi.org/10.3390/buildings14092653

Zhang, Shi, Kexin Guo, Qingshan Yang, and Xiaoda Xu. 2024. "Review of Wind Field Characteristics of Downbursts and Wind Effects on Structures under Their Action" Buildings 14, no. 9: 2653. https://doi.org/10.3390/buildings14092653

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