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Case Study – Methods, Examples and Guide

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

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

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

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

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

Multiple-Case Study

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

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

Exploratory Case Study

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

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

Descriptive Case Study

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

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

Instrumental Case Study

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

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

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

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

Observations

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

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

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

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

How to conduct Case Study Research

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

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

Examples of Case Study

Here are some examples of case study research:

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

Application of Case Study

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

Business and Management

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

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

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

Social Sciences

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

Law and Ethics

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

Purpose of Case Study

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

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

Case studies can also serve other purposes, including:

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

Advantages of Case Study Research

There are several advantages of case study research, including:

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

Limitations of Case Study Research

There are several limitations of case study research, including:

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

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Muhammad Hassan

Researcher, Academic Writer, Web developer

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What is the difference between quantitative and qualitative?

The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed in numerical terms. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.

Qualitative research , on the other hand, collects non-numerical data such as words, images, and sounds. The focus is on exploring subjective experiences, opinions, and attitudes, often through observation and interviews.

Qualitative research aims to produce rich and detailed descriptions of the phenomenon being studied, and to uncover new insights and meanings.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human.  Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography.

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions.  This allows the respondent to talk in some depth, choosing their own words.  This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis .

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded .

Key Features

• Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
• Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
• The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
• The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
• The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

• Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
• The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
• Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
• The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

• Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
• Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
• Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
• Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things.  However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms. 

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

• Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
• The research aims for objectivity (i.e., without bias) and is separated from the data.
• The design of the study is determined before it begins.
• For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
• Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

• Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
• Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
• Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
• Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

• Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
• Useful for testing and validating already constructed theories.
• Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
• Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
• Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

• Mixed methods research
• Designing qualitative research
• Methods of data collection and analysis
• Introduction to quantitative and qualitative research
• Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
• Qualitative research in health care: Analysing qualitative data
• Qualitative data analysis: the framework approach
• Using the framework method for the analysis of
• Qualitative data in multi-disciplinary health research
• Content Analysis
• Grounded Theory
• Thematic Analysis

Related Articles

Research Methodology

Mixed Methods Research

Conversation Analysis

Discourse Analysis

Phenomenology In Qualitative Research

Ethnography In Qualitative Research

Narrative Analysis In Qualitative Research

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Methodology

• Qualitative vs. Quantitative Research | Differences, Examples & Methods

Qualitative vs. Quantitative Research | Differences, Examples & Methods

Published on April 12, 2019 by Raimo Streefkerk . Revised on June 22, 2023.

When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.

Quantitative research is at risk for research biases including information bias , omitted variable bias , sampling bias , or selection bias . Qualitative research Qualitative research is expressed in words . It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.

Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.

Table of contents

The differences between quantitative and qualitative research, data collection methods, when to use qualitative vs. quantitative research, how to analyze qualitative and quantitative data, other interesting articles, frequently asked questions about qualitative and quantitative research.

Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions.

Quantitative and qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).

Many data collection methods can be either qualitative or quantitative. For example, in surveys, observational studies or case studies , your data can be represented as numbers (e.g., using rating scales or counting frequencies) or as words (e.g., with open-ended questions or descriptions of what you observe).

However, some methods are more commonly used in one type or the other.

Quantitative data collection methods

• Surveys :  List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).
• Experiments : Situation in which different types of variables are controlled and manipulated to establish cause-and-effect relationships.
• Observations : Observing subjects in a natural environment where variables can’t be controlled.

Qualitative data collection methods

• Interviews : Asking open-ended questions verbally to respondents.
• Focus groups : Discussion among a group of people about a topic to gather opinions that can be used for further research.
• Ethnography : Participating in a community or organization for an extended period of time to closely observe culture and behavior.
• Literature review : Survey of published works by other authors.

A rule of thumb for deciding whether to use qualitative or quantitative data is:

• Use quantitative research if you want to confirm or test something (a theory or hypothesis )
• Use qualitative research if you want to understand something (concepts, thoughts, experiences)

For most research topics you can choose a qualitative, quantitative or mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach ; your research question(s) ; whether you’re doing experimental , correlational , or descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.

Quantitative research approach

You survey 300 students at your university and ask them questions such as: “on a scale from 1-5, how satisfied are your with your professors?”

You can perform statistical analysis on the data and draw conclusions such as: “on average students rated their professors 4.4”.

Qualitative research approach

You conduct in-depth interviews with 15 students and ask them open-ended questions such as: “How satisfied are you with your studies?”, “What is the most positive aspect of your study program?” and “What can be done to improve the study program?”

Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.

Mixed methods approach

You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.

It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analyzing quantitative data

Quantitative data is based on numbers. Simple math or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

• Average scores ( means )
• The number of times a particular answer was given
• The correlation or causation between two or more variables
• The reliability and validity of the results

Analyzing qualitative data

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analyzing qualitative data include:

• Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
• Thematic analysis : Closely examining the data to identify the main themes and patterns
• Discourse analysis : Studying how communication works in social contexts

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.

• Chi square goodness of fit test
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

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

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organize your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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Action Research vs. Case Study

What's the difference.

Action research and case study are both research methodologies used in social sciences to investigate and understand complex phenomena. However, they differ in their approach and purpose. Action research is a collaborative and participatory approach that involves researchers and practitioners working together to identify and solve practical problems in real-world settings. It aims to bring about positive change and improvement in the context being studied. On the other hand, case study is an in-depth and detailed examination of a particular individual, group, or situation. It focuses on understanding the unique characteristics and dynamics of the case being studied and often involves extensive data collection and analysis. While action research emphasizes practical application and problem-solving, case study emphasizes detailed exploration and understanding of a specific case.

Further Detail

Introduction.

Action research and case study are two widely used research methodologies in various fields. While both approaches aim to gain insights and understanding, they differ in their focus, design, and implementation. This article will explore the attributes of action research and case study, highlighting their similarities and differences.

Action Research

Action research is a participatory approach that involves collaboration between researchers and practitioners to address real-world problems. It emphasizes the active involvement of stakeholders in the research process, aiming to bring about practical change and improvement. Action research typically follows a cyclical process, consisting of planning, action, observation, and reflection.

One of the key attributes of action research is its focus on generating knowledge that is directly applicable to the context in which it is conducted. It aims to bridge the gap between theory and practice by actively involving practitioners in the research process. This participatory nature allows for a deeper understanding of the complexities and nuances of the problem being investigated.

Action research often involves multiple iterations, with each cycle building upon the insights gained from the previous one. This iterative approach allows for continuous learning and adaptation, enabling researchers to refine their interventions and strategies based on the feedback received. It also promotes a sense of ownership and empowerment among the participants, as they actively contribute to the research process.

Furthermore, action research is characterized by its emphasis on collaboration and co-learning. It encourages the exchange of ideas and knowledge between researchers and practitioners, fostering a sense of shared responsibility and collective action. This collaborative approach not only enhances the quality of the research but also increases the likelihood of successful implementation of the findings.

In summary, action research is a participatory and iterative approach that aims to generate practical knowledge through collaboration between researchers and practitioners. It focuses on addressing real-world problems and promoting positive change within specific contexts.

Case study, on the other hand, is an in-depth investigation of a particular phenomenon, event, or individual. It involves the detailed examination of a specific case or cases to gain a comprehensive understanding of the subject under study. Case studies can be conducted using various research methods, such as interviews, observations, and document analysis.

One of the key attributes of case study research is its ability to provide rich and detailed insights into complex phenomena. By focusing on a specific case, researchers can delve deep into the intricacies and unique aspects of the subject, uncovering valuable information that may not be easily captured through other research methods.

Case studies are often used to explore and understand real-life situations in their natural settings. They allow researchers to examine the context and dynamics surrounding the case, providing a holistic view of the phenomenon under investigation. This contextual understanding is crucial for gaining a comprehensive and nuanced understanding of the subject.

Furthermore, case studies are particularly useful when the boundaries between the phenomenon and its context are not clearly defined. They allow for the exploration of complex and multifaceted issues, enabling researchers to capture the interplay of various factors and variables. This holistic approach enhances the validity and reliability of the findings.

Moreover, case studies can be exploratory, descriptive, or explanatory in nature, depending on the research questions and objectives. They can be used to generate hypotheses, provide detailed descriptions, or test theoretical frameworks. This versatility makes case study research applicable in various fields, including psychology, sociology, business, and education.

In summary, case study research is an in-depth investigation of a specific phenomenon, providing rich and detailed insights into complex situations. It focuses on understanding the context and dynamics surrounding the case, allowing for a comprehensive exploration of multifaceted issues.

Similarities

While action research and case study differ in their focus and design, they also share some common attributes. Both approaches aim to gain insights and understanding, albeit through different means. They both involve the collection and analysis of data to inform decision-making and improve practice.

Furthermore, both action research and case study can be conducted in naturalistic settings, allowing for the examination of real-life situations. They both emphasize the importance of context and seek to understand the complexities and nuances of the phenomena under investigation.

Moreover, both methodologies can involve multiple data collection methods, such as interviews, observations, and document analysis. They both require careful planning and design to ensure the validity and reliability of the findings.

Additionally, both action research and case study can contribute to theory development. While action research focuses on generating practical knowledge, it can also inform and contribute to theoretical frameworks. Similarly, case studies can provide empirical evidence that can be used to refine and expand existing theories.

In summary, action research and case study share common attributes, including their aim to gain insights and understanding, their focus on real-life situations, their emphasis on context, their use of multiple data collection methods, and their potential contribution to theory development.

Action research and case study are two distinct research methodologies that offer unique approaches to gaining insights and understanding. Action research emphasizes collaboration, participation, and practical change, while case study focuses on in-depth investigation and contextual understanding. Despite their differences, both approaches contribute to knowledge generation and have the potential to inform theory and practice. Researchers should carefully consider the nature of their research questions and objectives to determine which approach is most suitable for their study.

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Quantitative vs. Qualitative Research in Psychology

Anabelle Bernard Fournier is a researcher of sexual and reproductive health at the University of Victoria as well as a freelance writer on various health topics.

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

• Key Differences

Quantitative Research Methods

Qualitative research methods.

• How They Relate

In psychology and other social sciences, researchers are faced with an unresolved question: Can we measure concepts like love or racism the same way we can measure temperature or the weight of a star? Social phenomena⁠—things that happen because of and through human behavior⁠—are especially difficult to grasp with typical scientific models.

At a Glance

Psychologists rely on quantitative and quantitative research to better understand human thought and behavior.

• Qualitative research involves collecting and evaluating non-numerical data in order to understand concepts or subjective opinions.
• Quantitative research involves collecting and evaluating numerical data. 

This article discusses what qualitative and quantitative research are, how they are different, and how they are used in psychology research.

Qualitative Research vs. Quantitative Research

In order to understand qualitative and quantitative psychology research, it can be helpful to look at the methods that are used and when each type is most appropriate.

Psychologists rely on a few methods to measure behavior, attitudes, and feelings. These include:

• Self-reports , like surveys or questionnaires
• Observation (often used in experiments or fieldwork)
• Implicit attitude tests that measure timing in responding to prompts

Most of these are quantitative methods. The result is a number that can be used to assess differences between groups.

However, most of these methods are static, inflexible (you can't change a question because a participant doesn't understand it), and provide a "what" answer rather than a "why" answer.

Sometimes, researchers are more interested in the "why" and the "how." That's where qualitative methods come in.

Qualitative research is about speaking to people directly and hearing their words. It is grounded in the philosophy that the social world is ultimately unmeasurable, that no measure is truly ever "objective," and that how humans make meaning is just as important as how much they score on a standardized test.

Used to develop theories

Takes a broad, complex approach

Answers "why" and "how" questions

Explores patterns and themes

Used to test theories

Takes a narrow, specific approach

Answers "what" questions

Explores statistical relationships

Quantitative methods have existed ever since people have been able to count things. But it is only with the positivist philosophy of Auguste Comte (which maintains that factual knowledge obtained by observation is trustworthy) that it became a "scientific method."

The scientific method follows this general process. A researcher must:

• Generate a theory or hypothesis (i.e., predict what might happen in an experiment) and determine the variables needed to answer their question
• Develop instruments to measure the phenomenon (such as a survey, a thermometer, etc.)
• Develop experiments to manipulate the variables
• Collect empirical (measured) data
• Analyze data

Quantitative methods are about measuring phenomena, not explaining them.

Quantitative research compares two groups of people. There are all sorts of variables you could measure, and many kinds of experiments to run using quantitative methods.

These comparisons are generally explained using graphs, pie charts, and other visual representations that give the researcher a sense of how the various data points relate to one another.

Basic Assumptions

Quantitative methods assume:

• That the world is measurable
• That humans can observe objectively
• That we can know things for certain about the world from observation

In some fields, these assumptions hold true. Whether you measure the size of the sun 2000 years ago or now, it will always be the same. But when it comes to human behavior, it is not so simple.

As decades of cultural and social research have shown, people behave differently (and even think differently) based on historical context, cultural context, social context, and even identity-based contexts like gender , social class, or sexual orientation .

Therefore, quantitative methods applied to human behavior (as used in psychology and some areas of sociology) should always be rooted in their particular context. In other words: there are no, or very few, human universals.

Statistical information is the primary form of quantitative data used in human and social quantitative research. Statistics provide lots of information about tendencies across large groups of people, but they can never describe every case or every experience. In other words, there are always outliers.

Correlation and Causation

A basic principle of statistics is that correlation is not causation. Researchers can only claim a cause-and-effect relationship under certain conditions:

• The study was a true experiment.
• The independent variable can be manipulated (for example, researchers cannot manipulate gender, but they can change the primer a study subject sees, such as a picture of nature or of a building).
• The dependent variable can be measured through a ratio or a scale.

So when you read a report that "gender was linked to" something (like a behavior or an attitude), remember that gender is NOT a cause of the behavior or attitude. There is an apparent relationship, but the true cause of the difference is hidden.

Pitfalls of Quantitative Research

Quantitative methods are one way to approach the measurement and understanding of human and social phenomena. But what's missing from this picture?

As noted above, statistics do not tell us about personal, individual experiences and meanings. While surveys can give a general idea, respondents have to choose between only a few responses. This can make it difficult to understand the subtleties of different experiences.

Quantitative methods can be helpful when making objective comparisons between groups or when looking for relationships between variables. They can be analyzed statistically, which can be helpful when looking for patterns and relationships.

Qualitative data are not made out of numbers but rather of descriptions, metaphors, symbols, quotes, analysis, concepts, and characteristics. This approach uses interviews, written texts, art, photos, and other materials to make sense of human experiences and to understand what these experiences mean to people.

While quantitative methods ask "what" and "how much," qualitative methods ask "why" and "how."

Qualitative methods are about describing and analyzing phenomena from a human perspective. There are many different philosophical views on qualitative methods, but in general, they agree that some questions are too complex or impossible to answer with standardized instruments.

These methods also accept that it is impossible to be completely objective in observing phenomena. Researchers have their own thoughts, attitudes, experiences, and beliefs, and these always color how people interpret results.

Qualitative Approaches

There are many different approaches to qualitative research, with their own philosophical bases. Different approaches are best for different kinds of projects. For example:

• Case studies and narrative studies are best for single individuals. These involve studying every aspect of a person's life in great depth.
• Phenomenology aims to explain experiences. This type of work aims to describe and explore different events as they are consciously and subjectively experienced.
• Grounded theory develops models and describes processes. This approach allows researchers to construct a theory based on data that is collected, analyzed, and compared to reach new discoveries.
• Ethnography describes cultural groups. In this approach, researchers immerse themselves in a community or group in order to observe behavior.

Qualitative researchers must be aware of several different methods and know each thoroughly enough to produce valuable research.

Some researchers specialize in a single method, but others specialize in a topic or content area and use many different methods to explore the topic, providing different information and a variety of points of view.

There is not a single model or method that can be used for every qualitative project. Depending on the research question, the people participating, and the kind of information they want to produce, researchers will choose the appropriate approach.

Interpretation

Qualitative research does not look into causal relationships between variables, but rather into themes, values, interpretations, and meanings. As a rule, then, qualitative research is not generalizable (cannot be applied to people outside the research participants).

The insights gained from qualitative research can extend to other groups with proper attention to specific historical and social contexts.

Relationship Between Qualitative and Quantitative Research

It might sound like quantitative and qualitative research do not play well together. They have different philosophies, different data, and different outputs. However, this could not be further from the truth.

These two general methods complement each other. By using both, researchers can gain a fuller, more comprehensive understanding of a phenomenon.

For example, a psychologist wanting to develop a new survey instrument about sexuality might and ask a few dozen people questions about their sexual experiences (this is qualitative research). This gives the researcher some information to begin developing questions for their survey (which is a quantitative method).

After the survey, the same or other researchers might want to dig deeper into issues brought up by its data. Follow-up questions like "how does it feel when...?" or "what does this mean to you?" or "how did you experience this?" can only be answered by qualitative research.

By using both quantitative and qualitative data, researchers have a more holistic, well-rounded understanding of a particular topic or phenomenon.

Qualitative and quantitative methods both play an important role in psychology. Where quantitative methods can help answer questions about what is happening in a group and to what degree, qualitative methods can dig deeper into the reasons behind why it is happening. By using both strategies, psychology researchers can learn more about human thought and behavior.

Gough B, Madill A. Subjectivity in psychological science: From problem to prospect . Psychol Methods . 2012;17(3):374-384. doi:10.1037/a0029313

Pearce T. “Science organized”: Positivism and the metaphysical club, 1865–1875 . J Hist Ideas . 2015;76(3):441-465.

Adams G. Context in person, person in context: A cultural psychology approach to social-personality psychology . In: Deaux K, Snyder M, eds. The Oxford Handbook of Personality and Social Psychology . Oxford University Press; 2012:182-208.

Brady HE. Causation and explanation in social science . In: Goodin RE, ed. The Oxford Handbook of Political Science. Oxford University Press; 2011. doi:10.1093/oxfordhb/9780199604456.013.0049

Chun Tie Y, Birks M, Francis K. Grounded theory research: A design framework for novice researchers .  SAGE Open Med . 2019;7:2050312118822927. doi:10.1177/2050312118822927

Reeves S, Peller J, Goldman J, Kitto S. Ethnography in qualitative educational research: AMEE Guide No. 80 . Medical Teacher . 2013;35(8):e1365-e1379. doi:10.3109/0142159X.2013.804977

Salkind NJ, ed. Encyclopedia of Research Design . Sage Publishing.

Shaughnessy JJ, Zechmeister EB, Zechmeister JS.  Research Methods in Psychology . McGraw Hill Education.

By Anabelle Bernard Fournier Anabelle Bernard Fournier is a researcher of sexual and reproductive health at the University of Victoria as well as a freelance writer on various health topics.

Qualitative Research Design

Ai generator.

Qualitative Research Design is a method focused on understanding and interpreting the experiences of individuals or groups. Unlike quantitative research , which quantifies data and identifies patterns through statistical analysis, Qualitative Research Design explores phenomena in depth using interviews, focus groups, and observations. This approach gathers rich narratives that provide insights into thoughts, feelings, and behaviors, uncovering underlying reasons and motivations. Essential in fields like social sciences, education, and health, a strong Qualitative Research Proposal or Qualitative Research Plan must carefully consider the Research Design and relevant Research Terms for a comprehensive approach.

What is Qualitative Research Design?

Qualitative Research Design is a method that aims to understand and interpret the meaning and experiences of individuals or groups. It employs in-depth techniques like interviews, focus groups, and observations to gather detailed, rich narratives. Unlike quantitative research, which uses statistical analysis to identify patterns, qualitative research seeks to uncover the underlying reasons and motivations behind thoughts, feelings, and behaviors.

Types of Qualitative Research Design

1. Ethnography

Ethnography involves the detailed study of cultures or social groups through direct observation and participation. Researchers immerse themselves in the group’s daily life to understand their customs, behaviors, and social interactions. This method is often used to study communities, workplaces, or organizations. Example : Observing and interviewing members of a remote community to understand their social practices and traditions.

2. Grounded Theory

Grounded theory aims to generate a theory grounded in the data collected from participants. Researchers gather data through interviews, observations, and other methods, then use coding techniques to develop a theory. This approach is useful for studying processes, actions, and interactions, such as developing a theory on how people cope with job loss. Example : Analyzing interviews with employees to develop a theory about workplace motivation.

3. Focus Groups

Focus groups involve guided discussions with a small group of participants to explore their perceptions, opinions, and attitudes towards a particular topic. This method allows researchers to gather a wide range of insights and observe group dynamics. Focus groups are commonly used in market research, social science studies, and product development. Example : Conducting focus groups with parents to understand their views on remote learning during the COVID-19 pandemic.

4. Interviews

Interviews are one-on-one conversations between the researcher and the participant, designed to gather in-depth information on the participant’s experiences, thoughts, and feelings. Interviews can be structured, semi-structured, or unstructured, allowing flexibility in exploring the research topic. This method is widely used across various qualitative research studies. Example : Conducting semi-structured interviews with veterans to explore their reintegration experiences into civilian life.

5. Narrative Research

Narrative research focuses on the stories and personal accounts of individuals. Researchers collect narratives through interviews, journals, letters, or autobiographies and analyze them to understand how people make sense of their experiences. This type of research might explore life stories, personal journeys, or historical accounts. Example : Collecting and analyzing life stories of refugees to understand their migration experiences.

6. Action Research

Action research is a participatory approach that involves researchers and participants working together to address a problem or improve a situation. This method focuses on practical solutions and often includes cycles of planning, action, observation, and reflection. It is commonly used in educational settings to improve teaching practices, school policies, or community development projects. Example : Teachers working together to implement and assess a new curriculum in their school.

Qualitative Research Design Methods

Interviews are one-on-one conversations designed to gather in-depth information about a participant’s experiences, thoughts, and feelings. They can be structured, semi-structured, or unstructured, allowing flexibility in exploring topics. Example : Semi-structured interviews with veterans to explore their reintegration experiences into civilian life.

Focus Groups

Focus groups involve guided discussions with small groups to explore their perceptions, opinions, and attitudes on a topic. This method gathers diverse insights and observes group dynamics. Example : Focus groups with parents to understand their views on remote learning during the COVID-19 pandemic.

Observational Studies

Observational studies involve systematically watching and recording behaviors and interactions in natural settings without interference. Example : Observing children in a playground to study social development and peer relationships.

Discussion Boards

Discussion boards are online forums where participants post responses and engage in discussions. This method collects data from participants in different locations over time. Example : Analyzing posts on a discussion board for chronic illness patients to understand their coping strategies and support systems.

Difference between Qualitative Research vs. Quantitative Research

Characteristics of Qualitative Research Design

• Naturalistic Inquiry: Conducted in natural settings where participants experience the issue or phenomenon under study.
• Contextual Understanding: Emphasizes understanding the cultural, social, and historical contexts of participants.
• Participant Perspectives: Prioritizes the views, feelings, and interpretations of participants.
• Flexibility and Adaptiveness: Designs are flexible and can be adjusted as new insights emerge.
• Rich, Descriptive Data: Collects detailed data in words, images, and objects for comprehensive understanding.
• Inductive Approach: Develops theories and patterns from the data collected rather than testing predefined theories.
• Emergent Design: Research design evolves during the study based on emerging themes and insights.
• Multiple Data Sources: Uses various data sources like interviews, focus groups, observations, and document analysis.
• Subjectivity and Reflexivity: Researchers acknowledge their influence on the research process and examine their biases and assumptions.
• Holistic Perspective: Considers the entire phenomenon and its complexity, looking at interrelated components.
• Iterative Process: Data collection and analysis occur simultaneously in an iterative manner.
• Ethical Considerations: Ensures informed consent, confidentiality, and sensitivity to participants’ needs and well-being.
• Detailed Reporting: Results are reported in a detailed narrative style, often using direct quotes from participants.

How to Find Qualitative Research Design

1. identify the research problem.

Define the specific problem or phenomenon you want to study. For example, you might explore the experiences of first-generation college students.

2. Conduct a Literature Review

Review existing research to understand what has been studied and identify gaps. This helps to build a foundation for your research.

3. Formulate Research Questions

Create open-ended questions to guide your study. Example: “What challenges do first-generation college students face?”

4. Choose a Qualitative Research Approach

Select a methodology that fits your research question, such as phenomenology, grounded theory, ethnography, case study, or narrative research.

5. Select the Research Setting

Decide where you will conduct your study, such as a university campus or online forums relevant to your topic.

6. Identify and Recruit Participants

Determine criteria for participant selection and recruit individuals who meet these criteria, such as first-generation college students.

7. Choose Data Collection Methods

Select methods like interviews, focus groups, observations, or document analysis to gather rich data.

8. Collect and Analyze Data

Gather your data and analyze it by identifying patterns and themes. Use coding and software tools if necessary.

9. Validate Findings

Ensure the credibility of your research through techniques like triangulation, member checking, and peer debriefing.

FAQ’s

How does qualitative research differ from quantitative research.

Qualitative research focuses on understanding meaning and experiences, while quantitative research measures variables and uses statistical analysis to test hypotheses.

What is the purpose of qualitative research?

The purpose is to gain in-depth insights into people’s behaviors, motivations, and social interactions to understand complex phenomena.

What methods are commonly used in qualitative research?

Common methods include interviews, focus groups, participant observation, and content analysis of texts and media.

What is a case study in qualitative research?

A case study is an in-depth exploration of a single case or multiple cases within a real-life context to uncover detailed insights.

What is narrative research in qualitative research?

Narrative research explores the stories and personal accounts of individuals to understand how they make sense of their experiences.

How is data analyzed in qualitative research?

Data analysis involves coding and categorizing data to identify patterns, themes, and meanings, often using software like NVivo or manual methods.

What is the role of the researcher in qualitative research?

The researcher acts as a primary instrument for data collection and analysis, often engaging closely with participants and their contexts.

What are the strengths of qualitative research?

Strengths include rich, detailed data, the ability to explore complex issues, and flexibility in data collection and analysis.

What are the limitations of qualitative research?

Limitations include potential researcher bias, time-consuming data collection, and challenges in generalizing findings to larger populations.

How is validity ensured in qualitative research?

Validity is ensured through strategies like triangulation, member checking, prolonged engagement, and reflexivity to enhance credibility and trustworthiness.

Text prompt

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• Open access
• Published: 28 June 2024

Perceived efficacy of case analysis as an assessment method for clinical competencies in nursing education: a mixed methods study

• Basma Mohammed Al Yazeedi   ORCID: orcid.org/0000-0003-2327-6918 1 ,
• Lina Mohamed Wali Shakman 1 ,
• Sheeba Elizabeth John Sunderraj   ORCID: orcid.org/0000-0002-9171-7239 1 ,
• Harshita Prabhakaran   ORCID: orcid.org/0000-0002-5470-7066 1 ,
• Judie Arulappan 1 ,
• Erna Judith Roach   ORCID: orcid.org/0000-0002-5817-8886 1 ,
• Aysha Al Hashmi 1 , 2 &
• Zeinab Al Azri   ORCID: orcid.org/0000-0002-3376-9380 1  

BMC Nursing volume  23 , Article number:  441 ( 2024 ) Cite this article

Metrics details

Case analysis is a dynamic and interactive teaching and learning strategy that improves critical thinking and problem-solving skills. However, there is limited evidence about its efficacy as an assessment strategy in nursing education.

This study aimed to explore nursing students’ perceived efficacy of case analysis as an assessment method for clinical competencies in nursing education.

This study used a mixed methods design. Students filled out a 13-item study-advised questionnaire, and qualitative data from the four focus groups was collected. The setting of the study was the College of Nursing at Sultan Qaboos University, Oman. Descriptive and independent t-test analysis was used for the quantitative data, and the framework analysis method was used for the qualitative data.

The descriptive analysis of 67 participants showed that the mean value of the perceived efficacy of case analysis as an assessment method was 3.20 (SD = 0.53), demonstrating an 80% agreement rate. Further analysis indicated that 78.5% of the students concurred with the acceptability of case analysis as an assessment method (mean = 3.14, SD = 0.58), and 80.3% assented its association with clinical competencies as reflected by knowledge and cognitive skills (m = 3.21, SD = 0.60). No significant difference in the perceived efficacy between students with lower and higher GPAs (t [61] = 0.05, p  > 0.05) was identified Three qualitative findings were discerned: case analysis is a preferred assessment method for students when compared to MCQs, case analysis assesses students’ knowledge, and case analysis assesses students’ cognitive skills.

Conclusions

This study adds a potential for the case analysis to be acceptable and relevant to the clinical competencies when used as an assessment method. Future research is needed to validate the effectiveness of case analysis exams in other nursing clinical courses and examine their effects on academic and clinical performance.

Peer Review reports

Introduction

Nurses play a critical role in preserving human health by upholding core competencies [ 1 ]. Clinical competence in nursing involves a constant process of acquiring knowledge, values, attitudes, and abilities to deliver safe and high-quality care [ 2 , 3 ]. Nurses possessing such competencies can analyze and judge complicated problems, including those involving crucial patient care, ethical decision-making, and nurse-patient disputes, meeting the constantly altering health needs [ 4 , 5 ]. To optimize the readiness of the new graduates for the challenging clinical work environment needs, nurse leaders call for integrating clinical competencies into the nursing curriculum [ 6 , 7 ] In 2021, the American Association of Colleges of Nursing (AACN) released updated core competencies for professional nursing education [ 8 ]. These competencies were classified into ten fundamental essentials, including knowledge of nursing practice and person-centered care (e.g. integrate assessment skills in practice, diagnose actual or potential health problems and needs, develop a plan of care), representing clinical core competencies.

Nursing programs emphasize clinical competencies through innovative and effective teaching strategies, including case-based teaching (CBT) [ 9 ]. CBT is a dynamic teaching method that enhances the focus on learning goals and increases the chances of the instructor and students actively participating in teaching and learning [ 10 , 11 ]. Additionally, it improves the students’ critical thinking and problem-solving skills and enriches their capacity for independent study, cooperation capacity, and communication skills [ 12 , 13 , 14 , 15 ]. It also broadens students’ perspectives and helps develop greater creativity in fusing theory and practice [ 16 , 17 , 18 , 19 , 20 ]. As the learning environment significantly impacts the students’ satisfaction, case analysis fosters a supportive learning atmosphere and encourages active participation in learning, ultimately improving their satisfaction [ 21 , 22 ].

In addition to proper teaching strategies for clinical competencies, programs are anticipated to evaluate the students’ attainment of such competencies through effective evaluation strategies [ 23 ]. However, deploying objective assessment methods for the competencies remains challenging for most educators [ 24 ]. The standard assessment methods used in clinical nursing courses, for instance, include clinical evaluations (direct observation), skills checklists, Objective Structured Clinical Examination (OSCE), and multiple-choice questions (MCQs) written exams [ 25 ]. MCQs tend to test the recall of factual information rather than the application of knowledge and cognitive skills, potentially leading to assessment inaccuracies [ 26 ].

Given the aforementioned outcomes of CBT, the deployment of case analysis as a clinical written exam is more closely aligned with the course’s expected competencies. A mixed methods study was conducted among forty nursing students at the University of Southern Taiwan study concluded that the unfolding case studies create a safe setting where nursing students can learn and apply their knowledge to safe patient care [ 6 ]. In a case analysis, the patient’s sickness emerges in stages including the signs and symptoms of the disease, urgent care to stabilize the patient, and bedside care to enhance recovery. Thus, unfolding the case with several scenarios helps educators track students’ attained competencies [ 27 ]. However, case analysis as an assessment method is sparsely researched [ 28 ]. A literature review over the past five years yielded no studies investigating case analysis as an assessment method, necessitating new evidence. There remains uncertainty regarding its efficacy as an assessment method, particularly from the students’ perspectives [ 29 ]. In this study, we explored the undergraduate nursing students’ perceived efficacy of case analysis as an assessment method for clinical competencies. Results from this study will elucidate the position of case analysis as an assessment method in nursing education. The potential benefits are improved standardization of clinical assessment and the ability to efficiently evaluate a broad range of competencies.

Research design

Mixed-method research with a convergent parallel design was adopted in the study. This approach intends to converge two data types (quantitative and qualitative) at the interpretation stage to ensure an inclusive research problem analysis [ 30 ]. The quantitative aspect of the study was implemented through a cross-sectional survey. The survey captured the perceived efficacy of using case analysis as an assessment method in clinical nursing education. The qualitative part of the study was carried out through a descriptive qualitative method using focus groups to provide an in-depth understanding of the perceived strengths experienced by the students.

Study setting

Data were collected in the College of Nursing at Sultan Qaboos University (SQU), Oman, during the Spring and Fall semesters of 2023. At the end of each clinical course, the students have a clinical written exam and a clinical practical exam, which constitute their final exam. Most clinical courses use multiple-choice questions (MCQs) in their written exam. However, the child health clinical course team initiated the case analysis as an assessment method in the clinical written exam, replacing the MCQs format.

Participants

For this study, the investigators invited undergraduate students enrolled in the child health nursing clinical course in the Spring and Fall semesters of 2023. Currently, the only course that uses case analysis is child health. Other courses use MCQs. A total enumeration sampling technique was adopted. All the students enrolled in child health nursing clinical courses in the Spring and Fall 2023 semesters were invited to participate in the study. In the Spring, 36 students registered for the course, while 55 students were enrolled in the Fall. We included students who completed the case analysis as a final clinical written exam on the scheduled exam time. Students who did not show up for the exam during the scheduled time and students not enrolled in the course during the Spring and Fall of 2023 were excluded. Although different cases were used each semester, both had the same structure and level of complexity. Further, both cases were peer-reviewed.

Case analysis format

The format presents open-ended questions related to a clinical case scenario. It comprises three main sections: Knowledge, Emergency Room, and Ward. The questions in the sections varied in difficulty based on Bloom’s cognitive taxonomy levels, as presented in Table  1 . An answer key was generated to ensure consistency among course team members when correcting the exam. Three experts in child health nursing peer-reviewed both the case analysis exam paper and the answer key paper. The students were allocated two hours to complete the exam.

Study instruments

Quantitative stage.

The researchers developed a study questionnaire to meet the study objectives. It included two parts. The first was about the demographic data, including age, gender, type of residence, year in the program, and cumulative grade point average (GPA). The second part comprised a 13-item questionnaire assessing the perceived efficacy of case analysis as an assessment method. The perceived efficacy was represented by the acceptability of case analysis as an assessment method (Items 1–5 and 13) and the association with clinical competencies (Items 6 to 12). Acceptability involved format organization and clarity, time adequacy, alignment with course objectives, appropriateness to students’ level, and recommendation for implementation in other clinical nursing courses. Clinical competencies-related items were relevant to knowledge (motivation to prepare well for the exam, active learning, interest in topics, collaboration while studying) and cognitive skills (critical thinking, decision-making, and problem-solving skills) (The questionnaire is attached as a supplementary document).

The questionnaire is answered on a 4-point Likert scale: 1 = strongly disagree, 2 = disagree, 3 = agree, 4 = strongly agree. Higher scores indicated better perceived efficacy and vice versa. The tool underwent content validity testing with five experts in nursing clinical education, resulting in an item-content validity index ranging from 0.7 to 1. The Cronbach alpha was 0.83 for acceptability and 0.90 for clinical competencies.

Qualitative stage

For the focus group interviews, the investigators created a semi-structured interview guide to obtain an in-depth understanding of the students’ perceived strengths of case analysis as an assessment method. See Table  2 .

Data collection

Data was collected from the students after they gave their written informed consent. Students were invited to fill out the study questionnaire after they completed the case analysis as a clinical written exam.

All students in the child health course were invited to participate in focus group discussions. Students who approached the PI to participate in the focus group discussion were offered to participate in four different time slots. So, the students chose their time preferences. Four focus groups were conducted in private rooms at the College of Nursing. Two trained and bilingual interviewers attended the focus groups, one as a moderator while the other took notes on the group dynamics and non-verbal communication. The discussion duration ranged between 30 and 60 min. After each discussion, the moderator transcribed the audio recording. The transcriptions were rechecked against the audio recording for accuracy. Later, the transcriptions were translated into English by bilingual researchers fluent in Arabic and English for the analysis.

Rigor and trustworthiness

The rigor and trustworthiness of the qualitative method were enhanced using multiple techniques. Firstly, quantitative data, literature reviews, and focus groups were triangulated. Participants validated the summary after each discussion using member checking to ensure the moderator’s understanding was accurate. Third, the principal investigator (PI) reflected on her assumptions, experiences, expectations, and feelings weekly. In addition, the PI maintained a detailed audit trail of study details and progress. The nursing faculty conducted the study with experience in qualitative research and nursing education. This report was prepared following the Standard for Reporting Qualitative Research (SRQR) protocol [ 31 ].

Data analysis

Quantitative data were entered in SPSS version 24 and analyzed using simple descriptive analysis using means, standard deviations, and percentages. After computing the means of each questionnaire item, an average of the means was calculated to identify the perceived efficacy rate. A similar technique was used to calculate the rate of acceptability and clinical competencies. The percentage was calculated based on the mean: gained score/total score* 100. In addition, the investigators carried out an independent t-test to determine the relationship between the perceived efficacy and students’ GPA.

The qualitative data were analyzed using the framework analysis method. In our analysis, we followed the seven interconnected stages of framework analysis: (1) transcription, (2) familiarization with the interview, (3) coding, (4) developing a working analytical framework, (5) applying the analytical framework, (6) charting data into framework matrix and (7) interpreting the data [ 32 ]. Two members of the team separately analyzed the transcriptions. Then, they discussed the coding, and discrepancies were solved with discussion.

Mixed method integration

In our study, the quantitative and qualitative data were analyzed separately, and integration occurred at the interpretation level by merging the data [ 33 ]. As a measure of integration between qualitative and quantitative data, findings were assessed through confirmation, expansion, and discordance. If both data sets confirmed each other’s findings, it was considered confirmation, and if they expanded each other’s insight, it was considered expansion. Discordance was determined if the findings were contradictory.

Ethical considerations

Ethical approval was obtained from the Research and Ethics Committee of the College of Nursing, SQU (CON/NF/2023/18). Informed consent was collected, and no identifiable information was reported. For the focus group interviews, students were reassured that their grades were finalized, and their participation would not affect their grades. Also, the interviewers were instructed to maintain a non-judgmental and non-biased position during the interview. Data were saved in a locked cabinet inside a locked office room. The electronic data were saved in a password-protected computer.

The results section will present findings from the study’s quantitative and qualitative components. The integration of the two data types is described after each qualitative finding.

Quantitative findings

We analyzed the data of 67 participants, representing a 73.6% response rate. The mean age was 21.0 years old (SD 0.73) and 36.4% were male students. See Table  3 for more details.

The descriptive analysis showed that the mean value of the perceived efficacy of case analysis as an assessment method was 3.20 (SD = 0.53), demonstrating an 80% agreement rate. Further analysis indicated that 78.5% of the students concurred the acceptability of case analysis as an assessment method (mean = 3.14, SD = 0.58) and 80.3% (m = 3.21, SD = 0.60) assented the clinical competencies associated with it.

For the items representing acceptability, 81.8% of the students agreed that the case analysis was written clearly, and 80.3% reported that it was well organized. As per the questions, 81% described they were appropriate to their level, and 79.8% agreed upon their alignment with the course objectives. Moreover, the time allocated was adequate for 74.5% of the students, and 73.5% recommend using case analysis as an evaluation strategy for other clinical written examinations.

Regarding the clinical competencies, 77.3% of students agreed that the case analysis motivated them to prepare well for the exam, 81.3% reported that it encouraged them to be active in learning, and 81.0% indicated that it stimulated their interest in the topics discussed in the course. Additionally, 76.5% of the students agreed that the case analysis encouraged them to collaborate with other students when studying for the exam. Among the students, 82.5% reported that the case analysis as an assessment method enhanced their critical thinking skills, 81.0% agreed that it helped them practice decision-making skills, and 81.8% indicated that it improved their problem-solving abilities. See Table  4 .

The independent t-test analysis revealed no significant difference in the perceived efficacy between students with lower and higher GPAs (t [61] = 0.05, p  > 0.05). Further analysis showed that the means of acceptability and clinical competencies were not significantly different between the lower GPA group and higher GPA group, t [62] = 0.72, p  > 0.05 and t [63] = -0.83, p  > 0.05, respectively (Table  5 ).

Qualitative findings

A total of 22 had participated in four focus groups, each group had 5–6 students. The qualitative framework analysis revealed three main findings; case analysis is a preferred assessment method to students when compared to MCQs, case analysis assesses students’ knowledge, and case analysis assesses students’ cognitive skills.

Qualitative Finding 1: case analysis is a preferred assessment method to students when compared to MCQs

Most of the students’ statements about the case analysis as an assessment method were positive. One student stated, “Previously, we have MCQs in clinical exams, but they look as if they are theory exams. This exam makes me deal with cases like a patient, which is good for clinical courses.” . At the same time, many students conveyed optimism about obtaining better grades with this exam format. A student stated, “Our grades, with case analysis format, will be better, … may be because we can write more in open-ended questions, so we can get some marks, in contrast to MCQs where we may get it right or wrong” . On the other hand, a few students suggested adding multiple-choice questions, deleting the emergency department section, and lessening the number of care plans in the ward section to secure better grades.

Although the case analysis was generally acceptable to students, they have repeatedly expressed a need to allocate more time for this type of exam. A student stated, “The limited time with the type of questions was a problem, …” . When further discussion was prompted to understand this challenge, we figured that students are not used to handwriting, which has caused them to be exhausted during the exam. An example is “writing is time-consuming and energy consuming in contrast to MCQs …” . These statements elucidate that the students don’t necessarily mind writing but recommend more practice as one student stated, “More experience of this type of examination is required, more examples during clinical practice are needed.” Some even recommended adopting this format with other clinical course exams by saying “It’s better to start this method from the first year for the new cohort and to apply it in all other courses.”

Mixed Methods Inference 1: Confirmation and Expansion

The abovementioned qualitative impression supports the high acceptability rate in quantitative analysis. In fact, there is a general agreement that the case analysis format surpasses the MCQs when it comes to the proper evaluation strategies for clinical courses. Expressions in the qualitative data revealed more details, such as the limited opportunities to practice handwriting, which negatively impacted the perceived adequacy of exam time.

Qualitative Finding 2: case analysis assesses students’ knowledge

Students conferred that they were reading more about the disease pathophysiology, lab values, and nursing care plans, which they did not usually do with traditional means of examination. Examples of statements include “… before we were not paying attention to the normal lab results but …in this exam, we went back and studied them which was good for our knowledge” and “we cared about the care plan. In previous exams, we were not bothered by these care plans”. Regarding the burden that could be perceived with this type of preparation, the students expressed that this has helped them prepare for the theory course exam; as one student said, “We also focus on theory lectures to prepare for this exam …. this was very helpful to prepare us for the theory final exam as well.” However, others have highlighted the risks of limiting the exam’s content to one case analysis. The argument was that some students may have not studied the case completely or been adequately exposed to the case in the clinical setting. To solve this risk, the students themselves advocated for frequent case group discussions in the clinical setting as stated by one student: “There could be some differences in the cases that we see during our clinical posting, for that I recommend that instructors allocate some time to gather all the students and discuss different cases.” Also, the participants advocated for more paper-based case analysis exercises as it is helpful to prepare them for the exams and enhance their knowledge and skills.

Mixed Methods Inferences 2: Confirmation and Expansion

The qualitative finding supports the quantitative data relevant to items 6, 7, and 8. Students’ expressions revealed more insights, including the acquisition of deeper knowledge, practicing concept mapping, and readiness for other course-related exams. At the same time, students recommended that faculty ensure all students’ exposure to common cases in the clinical setting for fair exam preparation.

Qualitative Finding 3. case analysis assesses students’ cognitive skills

Several statements conveyed how the case analysis format helped the students use their critical thinking and analysis skills. One student stated, “It, the case analysis format, enhanced our critical thinking skills as there is a case with given data and we analyze the case….” . Therefore, the case analysis format as an exam is potentially a valid means to assess the student’s critical thinking skills. Students also conveyed that the case analysis format helped them link theory to practice and provided them with the platform to think like real nurses and be professional. Examples of statements are: “…we connect our knowledge gained from theory with the clinical experience to get the answers…” and “The questions were about managing a case, which is what actual nurses are doing daily.” Another interesting cognitive benefit to case analysis described by the students was holistic thinking. For example, one student said, “Case analysis format helped us to see the case as a whole and not only from one perspective.”

Mixed Methods Inferences 3: Confirmation

The quantitative data indicated mutual agreement among the students that the case analysis enhanced their critical thinking, decision-making, and problem-solving skills. The students’ statements from the interviews, including critical thinking, linking theory to practice, and holistic thinking, further supported these presumptions.

This research presents the findings from a mixed methods study that explored undergraduate nursing students’ perceived efficacy of using case analysis as an assessment method. The perceived efficacy was reflected through acceptability and association with two core competencies: knowledge and cognitive skills. The study findings showed a high rate of perceived efficacy of case analysis as an assessment method among nursing students. Additionally, three findings were extracted from the qualitative data that further confirmed the perceived efficacy: (1) case analysis is a preferred assessment method to students compared to MCQs, (2) case analysis assesses students’ knowledge, and (3) case analysis assesses students’ cognitive skills. Moreover, the qualitative findings revealed details that expanded the understanding of the perceived efficacy among nursing students.

Previous literature reported students’ preference for case analysis as a teaching method. A randomized controlled study investigated student’s satisfaction levels with case-based teaching, in addition to comparing certain outcomes between a traditional teaching group and a case-based teaching group. They reported that most students favored the use of case-based teaching, whom at the same time had significantly better OSCE scores compared to the other group [ 34 ]. As noted, this favorable teaching method ultimately resulted in better learning outcomes and academic performance. Although it may be challenging since no answer options are provided, students appreciate the use of case analysis format in their exams because it aligns better with the course objectives and expected clinical competencies. The reason behind students’ preference for case analysis is that it allows them to interact with the teaching content and visualize the problem, leading to a better understanding. When case analysis is used as an assessment method, students can connect the case scenario presented in the exam to their clinical training, making it more relevant.

In this study, students recognized the incorporation of nursing knowledge in the case analysis exam. They also acknowledged improved knowledge and learning abilities similar to those observed in case-based teaching. Boney et al. (2015) reported that students perceived increased learning gains and a better ability to identify links between different concepts and other aspects of life through case-based teaching [ 35 ]. Additionally, case analysis as an exam promotes students’ in-depth acquirement of knowledge through the type of preparation it entails. Literature suggested that case-based teaching promotes self-directed learning with high autonomous learning ability [ 34 , 36 ]. Thus, better achievement in the case analysis exam could be linked with a higher level of knowledge, making it a suitable assessment method for knowledge integration in nursing care.

The findings of this study suggest that case analysis can be a useful tool for evaluating students’ cognitive skills, such as critical thinking, decision-making, and problem-solving. A randomized controlled study implied better problem-solving abilities among the students in the case-based learning group compared to those in the traditional teaching methods group [ 12 ]. Moreover, students in our study conveyed that case analysis as an exam was an opportunity for them to think like real nurses. Similar to our findings, a qualitative study on undergraduate nutrition students found that case-based learning helped students develop professional competencies for their future practice, in addition to higher-level cognitive skills [ 37 ]. Therefore, testing students through case analysis allows educators to assess the student’s readiness for entry-level professional competencies, including the thinking process. Also, to evaluate students’ high-level cognitive skills according to Bloom’s taxonomy (analysis, synthesis, and evaluation), which educators often find challenging.

Case analysis as an assessment method for clinical courses is partially integrated in case presentation or OSCE evaluation methods. However, the written format is considered to be more beneficial for both assessment and learning processes. A qualitative study was conducted to examine the impact of paper-based case learning versus video-based case learning on clinical decision-making skills among midwifery students. The study revealed that students paid more attention and were able to focus better on the details when the case was presented in a paper format [ 38 ]. Concurrently, the students in our study recommended more paper-based exercises, which they believed would improve their academic performance.

This study has possible limitations. The sample size was small due to the limited experience of case analysis as a clinical written exam in the program. Future studies with larger sample sizes and diverse nursing courses are needed for better generalizability.

Implications

Little evidence relates to the efficacy of case analysis as an evaluation method, suggesting the novelty of this study. Despite the scarcity of case-based assessment studies, a reader can speculate from this study’s findings that there is a potential efficacy of case analysis as an assessment method in nursing education. Future research is warranted to validate the effectiveness of case-analysis assessment methods and investigate the effects of case-analysis exams on academic and clinical performance.

Overall, our findings are in accordance with the evidence suggesting students’ perceived efficacy of case analysis as a teaching method. This study adds a potential for the case analysis to be acceptable and relevant to the clinical competencies when used as an assessment method. Future research is needed to validate the effectiveness of case analysis exams in other nursing clinical courses and examine their effects on academic and clinical performance.

Data availability

The datasets used and/or analyzed during the current study are available fromthe Principal Investigator (BAY) upon reasonable request.

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Acknowledgements

The authors wish to thank the nursing students at SQU who voluntarily participated in this study.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Basma Mohammed Al Yazeedi, Lina Mohamed Wali Shakman, Sheeba Elizabeth John Sunderraj, Harshita Prabhakaran, Judie Arulappan, Erna Judith Roach, Aysha Al Hashmi & Zeinab Al Azri

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Contributions

Dr. Basma Mohammed Al Yazeedi contributed to conceptualization, methods, data collection, data analysis, writing the draft, and reviewing the final draft. Ms. Lina Mohamed Wali Shakman contributed to conceptualization, data collection, data analysis, writing the draft, and reviewing the final draft. Ms. Sheeba Elizabeth John Sunderraj contributed to conceptualization, methods, data collection, writing the draft, and reviewing the final draft.Ms. Harshita Prabhakaran contributed to conceptualization, data collection, writing the draft, and reviewing the final draft.Dr. Judie Arulappan contributed to conceptualization and reviewing the final draft.Dr. Erna Roach contributed to conceptualization writing the draft and reviewing the final draft.Ms. Aysha Al Hashmi contributed to the conceptualization and reviewing the final draft. Dr. Zeinab Al Azri contributed to data collection, data analysis, writing the draft, and reviewing the final draft.All auhors reviewed and approved the final version of the manuscirpt.

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The questionnaire used in this study is attached as a supplementary document.

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Yazeedi, B.M.A., Shakman, L.M.W., Sunderraj, S.E.J. et al. Perceived efficacy of case analysis as an assessment method for clinical competencies in nursing education: a mixed methods study. BMC Nurs 23 , 441 (2024). https://doi.org/10.1186/s12912-024-02102-9

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

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Enhancing urban–rural integration in china: a comparative case study of introducing small rural industries in huangyan-taizhou.

1. Introduction

2. literature review: urban–rural linkage and urban–rural integration, 3. methods and case selection, 3.1. mixed method research, 3.2. urban–rural interface as the focusing region for uri, 3.3. selected case region: taizhou in the yangtze river delta, 3.4. obtaining qualitative and quantitative data, 4. the changing role of rural industries in the trajectory of urbanisation in china, 4.1. an overview of relevant policies affecting rural industries, 4.2. inadequate rural land transfer limited rural industries, 4.3. rapid urban sprawl further ‘squeezed’ rural space for development, 4.4. transitory periods for rural industry development between the 1980s and 1990s, 4.5. small industries as the main approach of rural revitalisation guided by uri, 5. case study: village transformation under uri, 5.1. xiapuzheng village: driven by plastic manufacture and endogenous industry, 5.2. luoyu village: driven by industries related to global production chain, 5.3. waciyao village: driven by improvement in the physical environment and future rural tourism, 5.4. discussions, 6. conclusions, author contributions, data availability statement, acknowledgments, conflicts of interest, ethics statement.

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Huang, H.; Song, D.; Wang, L.; Yang, G.; Wang, Y.; Fei, L.; Lynam, A. Enhancing Urban–Rural Integration in China: A Comparative Case Study of Introducing Small Rural Industries in Huangyan-Taizhou. Land 2024 , 13 , 946. https://doi.org/10.3390/land13070946

Huang H, Song D, Wang L, Yang G, Wang Y, Fei L, Lynam A. Enhancing Urban–Rural Integration in China: A Comparative Case Study of Introducing Small Rural Industries in Huangyan-Taizhou. Land . 2024; 13(7):946. https://doi.org/10.3390/land13070946

Huang, Huang, Daijun Song, Liyao Wang, Guiqing Yang, Yizheng Wang, Liyuan Fei, and Ava Lynam. 2024. "Enhancing Urban–Rural Integration in China: A Comparative Case Study of Introducing Small Rural Industries in Huangyan-Taizhou" Land 13, no. 7: 946. https://doi.org/10.3390/land13070946

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