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• Exploratory Research | Definition, Guide, & Examples

Exploratory Research | Definition, Guide, & Examples

Published on December 6, 2021 by Tegan George . Revised on November 20, 2023.

Exploratory research is a methodology approach that investigates research questions that have not previously been studied in depth.

Exploratory research is often qualitative and primary in nature. However, a study with a large sample conducted in an exploratory manner can be quantitative as well. It is also often referred to as interpretive research or a grounded theory approach due to its flexible and open-ended nature.

Table of contents

When to use exploratory research, exploratory research questions, exploratory research data collection, step-by-step example of exploratory research, exploratory vs. explanatory research, advantages and disadvantages of exploratory research, other interesting articles, frequently asked questions about exploratory research.

Exploratory research is often used when the issue you’re studying is new or when the data collection process is challenging for some reason.

You can use this type of research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

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Exploratory research questions are designed to help you understand more about a particular topic of interest. They can help you connect ideas to understand the groundwork of your analysis without adding any preconceived notions or assumptions yet.

Here are some examples:

• What effect does using a digital notebook have on the attention span of middle schoolers?
• What factors influence mental health in undergraduates?
• What outcomes are associated with an authoritative parenting style?
• In what ways does the presence of a non-native accent affect intelligibility?
• How can the use of a grocery delivery service reduce food waste in single-person households?

Collecting information on a previously unexplored topic can be challenging. Exploratory research can help you narrow down your topic and formulate a clear hypothesis and problem statement , as well as giving you the “lay of the land” on your topic.

Data collection using exploratory research is often divided into primary and secondary research methods, with data analysis following the same model.

Primary research

In primary research, your data is collected directly from primary sources : your participants. There is a variety of ways to collect primary data.

Some examples include:

• Survey methodology: Sending a survey out to the student body asking them if they would eat vegan meals
• Focus groups: Compiling groups of 8–10 students and discussing what they think of vegan options for dining hall food
• Interviews: Interviewing students entering and exiting the dining hall, asking if they would eat vegan meals

Secondary research

In secondary research, your data is collected from preexisting primary research, such as experiments or surveys.

Some other examples include:

• Case studies : Health of an all-vegan diet
• Literature reviews : Preexisting research about students’ eating habits and how they have changed over time
• Online polls, surveys, blog posts, or interviews; social media: Have other schools done something similar?

For some subjects, it’s possible to use large- n government data, such as the decennial census or yearly American Community Survey (ACS) open-source data.

How you proceed with your exploratory research design depends on the research method you choose to collect your data. In most cases, you will follow five steps.

We’ll walk you through the steps using the following example.

Therefore, you would like to focus on improving intelligibility instead of reducing the learner’s accent.

Step 1: Identify your problem

The first step in conducting exploratory research is identifying what the problem is and whether this type of research is the right avenue for you to pursue. Remember that exploratory research is most advantageous when you are investigating a previously unexplored problem.

Step 2: Hypothesize a solution

The next step is to come up with a solution to the problem you’re investigating. Formulate a hypothetical statement to guide your research.

Step 3. Design your methodology

Next, conceptualize your data collection and data analysis methods and write them up in a research design.

Step 4: Collect and analyze data

Next, you proceed with collecting and analyzing your data so you can determine whether your preliminary results are in line with your hypothesis.

In most types of research, you should formulate your hypotheses a priori and refrain from changing them due to the increased risk of Type I errors and data integrity issues. However, in exploratory research, you are allowed to change your hypothesis based on your findings, since you are exploring a previously unexplained phenomenon that could have many explanations.

Step 5: Avenues for future research

Decide if you would like to continue studying your topic. If so, it is likely that you will need to change to another type of research. As exploratory research is often qualitative in nature, you may need to conduct quantitative research with a larger sample size to achieve more generalizable results.

It can be easy to confuse exploratory research with explanatory research. To understand the relationship, it can help to remember that exploratory research lays the groundwork for later explanatory research.

Exploratory research investigates research questions that have not been studied in depth. The preliminary results often lay the groundwork for future analysis.

Explanatory research questions tend to start with “why” or “how”, and the goal is to explain why or how a previously studied phenomenon takes place.

Like any other research design , exploratory studies have their trade-offs: they provide a unique set of benefits but also come with downsides.

• It can be very helpful in narrowing down a challenging or nebulous problem that has not been previously studied.
• It can serve as a great guide for future research, whether your own or another researcher’s. With new and challenging research problems, adding to the body of research in the early stages can be very fulfilling.
• It is very flexible, cost-effective, and open-ended. You are free to proceed however you think is best.

Disadvantages

• It usually lacks conclusive results, and results can be biased or subjective due to a lack of preexisting knowledge on your topic.
• It’s typically not externally valid and generalizable, and it suffers from many of the challenges of qualitative research .
• Since you are not operating within an existing research paradigm, this type of research can be very labor-intensive.

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

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

Research bias

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

Exploratory research is a methodology approach that explores research questions that have not previously been studied in depth. It is often used when the issue you’re studying is new, or the data collection process is challenging in some way.

Exploratory research aims to explore the main aspects of an under-researched problem, while explanatory research aims to explain the causes and consequences of a well-defined problem.

You can use exploratory research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

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.

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Home » Exploratory Research – Types, Methods and Examples

Exploratory Research – Types, Methods and Examples

Table of Contents

Exploratory Research

Definition:

Exploratory research is a type of research design that is used to investigate a research question when the researcher has limited knowledge or understanding of the topic or phenomenon under study.

The primary objective of exploratory research is to gain insights and gather preliminary information that can help the researcher better define the research problem and develop hypotheses or research questions for further investigation.

Exploratory Research Methods

There are several types of exploratory research, including:

Literature Review

This involves conducting a comprehensive review of existing published research, scholarly articles, and other relevant literature on the research topic or problem. It helps to identify the gaps in the existing knowledge and to develop new research questions or hypotheses.

Pilot Study

A pilot study is a small-scale preliminary study that helps the researcher to test research procedures, instruments, and data collection methods. This type of research can be useful in identifying any potential problems or issues with the research design and refining the research procedures for a larger-scale study.

This involves an in-depth analysis of a particular case or situation to gain insights into the underlying causes, processes, and dynamics of the issue under investigation. It can be used to develop a more comprehensive understanding of a complex problem, and to identify potential research questions or hypotheses.

Focus Groups

Focus groups involve a group discussion that is conducted to gather opinions, attitudes, and perceptions from a small group of individuals about a particular topic. This type of research can be useful in exploring the range of opinions and attitudes towards a topic, identifying common themes or patterns, and generating ideas for further research.

Expert Opinion

This involves consulting with experts or professionals in the field to gain their insights, expertise, and opinions on the research topic. This type of research can be useful in identifying the key issues and concerns related to the topic, and in generating ideas for further research.

Observational Research

Observational research involves gathering data by observing people, events, or phenomena in their natural settings to gain insights into behavior and interactions. This type of research can be useful in identifying patterns of behavior and interactions, and in generating hypotheses or research questions for further investigation.

Open-ended Surveys

Open-ended surveys allow respondents to provide detailed and unrestricted responses to questions, providing valuable insights into their attitudes, opinions, and perceptions. This type of research can be useful in identifying common themes or patterns, and in generating ideas for further research.

Data Analysis Methods

Exploratory Research Data Analysis Methods are as follows:

Content Analysis

This method involves analyzing text or other forms of data to identify common themes, patterns, and trends. It can be useful in identifying patterns in the data and developing hypotheses or research questions. For example, if the researcher is analyzing social media posts related to a particular topic, content analysis can help identify the most frequently used words, hashtags, and topics.

Thematic Analysis

This method involves identifying and analyzing patterns or themes in qualitative data such as interviews or focus groups. The researcher identifies recurring themes or patterns in the data and then categorizes them into different themes. This can be helpful in identifying common patterns or themes in the data and developing hypotheses or research questions. For example, a thematic analysis of interviews with healthcare professionals about patient care may identify themes related to communication, patient satisfaction, and quality of care.

Cluster Analysis

This method involves grouping data points into clusters based on their similarities or differences. It can be useful in identifying patterns in large datasets and grouping similar data points together. For example, if the researcher is analyzing customer data to identify different customer segments, cluster analysis can be used to group similar customers together based on their demographic, purchasing behavior, or preferences.

Network Analysis

This method involves analyzing the relationships and connections between data points. It can be useful in identifying patterns in complex datasets with many interrelated variables. For example, if the researcher is analyzing social network data, network analysis can help identify the most influential users and their connections to other users.

Grounded Theory

This method involves developing a theory or explanation based on the data collected during the exploratory research process. The researcher develops a theory or explanation that is grounded in the data, rather than relying on pre-existing theories or assumptions. This can be helpful in developing new theories or explanations that are supported by the data.

Applications of Exploratory Research

Exploratory research has many practical applications across various fields. Here are a few examples:

• Marketing Research : In marketing research, exploratory research can be used to identify consumer needs, preferences, and behavior. It can also help businesses understand market trends and identify new market opportunities.
• Product Development: In product development, exploratory research can be used to identify customer needs and preferences, as well as potential design flaws or issues. This can help companies improve their product offerings and develop new products that better meet customer needs.
• Social Science Research: In social science research, exploratory research can be used to identify new areas of study, as well as develop new theories and hypotheses. It can also be used to identify potential research methods and approaches.
• Healthcare Research : In healthcare research, exploratory research can be used to identify new treatments, therapies, and interventions. It can also be used to identify potential risk factors or causes of health problems.
• Education Research: In education research, exploratory research can be used to identify new teaching methods and approaches, as well as identify potential areas of study for further research. It can also be used to identify potential barriers to learning or achievement.

Examples of Exploratory Research

Here are some more examples of exploratory research from different fields:

• Social Science : A researcher wants to study the experience of being a refugee, but there is limited existing research on this topic. The researcher conducts exploratory research by conducting in-depth interviews with refugees to better understand their experiences, challenges, and needs.
• Healthcare : A medical researcher wants to identify potential risk factors for a rare disease but there is limited information available. The researcher conducts exploratory research by reviewing medical records and interviewing patients and their families to identify potential risk factors.
• Education : A teacher wants to develop a new teaching method to improve student engagement, but there is limited information on effective teaching methods. The teacher conducts exploratory research by reviewing existing literature and interviewing other teachers to identify potential approaches.
• Technology : A software developer wants to develop a new app, but is unsure about the features that users would find most useful. The developer conducts exploratory research by conducting surveys and focus groups to identify user preferences and needs.
• Environmental Science : An environmental scientist wants to study the impact of a new industrial plant on the surrounding environment, but there is limited existing research. The scientist conducts exploratory research by collecting and analyzing soil and water samples, and conducting interviews with residents to better understand the impact of the plant on the environment and the community.

How to Conduct Exploratory Research

Here are the general steps to conduct exploratory research:

• Define the research problem: Identify the research problem or question that you want to explore. Be clear about the objective and scope of the research.
• Review existing literature: Conduct a review of existing literature and research on the topic to identify what is already known and where gaps in knowledge exist.
• Determine the research design : Decide on the appropriate research design, which will depend on the nature of the research problem and the available resources. Common exploratory research designs include case studies, focus groups, interviews, and surveys.
• Collect data: Collect data using the chosen research design. This may involve conducting interviews, surveys, or observations, or collecting data from existing sources such as archives or databases.
• Analyze data: Analyze the data collected using appropriate qualitative or quantitative techniques. This may include coding and categorizing qualitative data, or running descriptive statistics on quantitative data.
• I nterpret and report findings: Interpret the findings of the analysis and report them in a way that is clear and understandable. The report should summarize the findings, discuss their implications, and make recommendations for further research or action.
• Iterate : If necessary, refine the research question and repeat the process of data collection and analysis to further explore the topic.

When to use Exploratory Research

Exploratory research is appropriate in situations where there is limited existing knowledge or understanding of a topic, and where the goal is to generate insights and ideas that can guide further research. Here are some specific situations where exploratory research may be particularly useful:

• New product development: When developing a new product, exploratory research can be used to identify consumer needs and preferences, as well as potential design flaws or issues.
• Emerging technologies: When exploring emerging technologies, exploratory research can be used to identify potential uses and applications, as well as potential challenges or limitations.
• Developing research hypotheses: When developing research hypotheses, exploratory research can be used to identify potential relationships or patterns that can be further explored through more rigorous research methods.
• Understanding complex phenomena: When trying to understand complex phenomena, such as human behavior or societal trends, exploratory research can be used to identify underlying patterns or factors that may be influencing the phenomenon.
• Developing research methods : When developing new research methods, exploratory research can be used to identify potential issues or limitations with existing methods, and to develop new methods that better capture the phenomena of interest.

Purpose of Exploratory Research

The purpose of exploratory research is to gain insights and understanding of a research problem or question where there is limited existing knowledge or understanding. The objective is to explore and generate ideas that can guide further research, rather than to test specific hypotheses or make definitive conclusions.

Exploratory research can be used to:

• Identify new research questions: Exploratory research can help to identify new research questions and areas of inquiry, by providing initial insights and understanding of a topic.
• Develop hypotheses: Exploratory research can help to develop hypotheses and testable propositions that can be further explored through more rigorous research methods.
• Identify patterns and trends : Exploratory research can help to identify patterns and trends in data, which can be used to guide further research or decision-making.
• Understand complex phenomena: Exploratory research can help to provide a deeper understanding of complex phenomena, such as human behavior or societal trends, by identifying underlying patterns or factors that may be influencing the phenomena.
• Generate ideas: Exploratory research can help to generate new ideas and insights that can be used to guide further research, innovation, or decision-making.

Characteristics of Exploratory Research

The following are the main characteristics of exploratory research:

• Flexible and open-ended : Exploratory research is characterized by its flexible and open-ended nature, which allows researchers to explore a wide range of ideas and perspectives without being constrained by specific research questions or hypotheses.
• Qualitative in nature : Exploratory research typically relies on qualitative methods, such as in-depth interviews, focus groups, or observation, to gather rich and detailed data on the research problem.
• Limited scope: Exploratory research is generally limited in scope, focusing on a specific research problem or question, rather than attempting to provide a comprehensive analysis of a broader phenomenon.
• Preliminary in nature : Exploratory research is preliminary in nature, providing initial insights and understanding of a research problem, rather than testing specific hypotheses or making definitive conclusions.
• I terative process : Exploratory research is often an iterative process, where the research design and methods may be refined and adjusted as new insights and understanding are gained.
• I nductive approach : Exploratory research typically takes an inductive approach to data analysis, seeking to identify patterns and relationships in the data that can guide further research or hypothesis development.

Advantages of Exploratory Research

The following are some advantages of exploratory research:

• Provides initial insights: Exploratory research is useful for providing initial insights and understanding of a research problem or question where there is limited existing knowledge or understanding. It can help to identify patterns, relationships, and potential hypotheses that can guide further research.
• Flexible and adaptable : Exploratory research is flexible and adaptable, allowing researchers to adjust their methods and approach as they gain new insights and understanding of the research problem.
• Qualitative methods : Exploratory research typically relies on qualitative methods, such as in-depth interviews, focus groups, and observation, which can provide rich and detailed data that is useful for gaining insights into complex phenomena.
• Cost-effective : Exploratory research is often less costly than other research methods, such as large-scale surveys or experiments. It is typically conducted on a smaller scale, using fewer resources and participants.
• Useful for hypothesis generation : Exploratory research can be useful for generating hypotheses and testable propositions that can be further explored through more rigorous research methods.
• Provides a foundation for further research: Exploratory research can provide a foundation for further research by identifying potential research questions and areas of inquiry, as well as providing initial insights and understanding of the research problem.

Limitations of Exploratory Research

The following are some limitations of exploratory research:

• Limited generalizability: Exploratory research is typically conducted on a small scale and uses non-random sampling techniques, which limits the generalizability of the findings to a broader population.
• Subjective nature: Exploratory research relies on qualitative methods and is therefore subject to researcher bias and interpretation. The findings may be influenced by the researcher’s own perceptions, beliefs, and assumptions.
• Lack of rigor: Exploratory research is often less rigorous than other research methods, such as experimental research, which can limit the validity and reliability of the findings.
• Limited ability to test hypotheses: Exploratory research is not designed to test specific hypotheses, but rather to generate initial insights and understanding of a research problem. It may not be suitable for testing well-defined research questions or hypotheses.
• Time-consuming : Exploratory research can be time-consuming and resource-intensive, particularly if the researcher needs to gather data from multiple sources or conduct multiple rounds of data collection.
• Difficulty in interpretation: The open-ended nature of exploratory research can make it difficult to interpret the findings, particularly if the researcher is unable to identify clear patterns or relationships in the data.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Exploratory Research

Exploratory research, as the name implies, intends merely to explore the research questions and does not intend to offer final and conclusive solutions to existing problems. This type of research is usually conducted to study a problem that has not been clearly defined yet. Conducted in order to determine the nature of the problem, exploratory research is not intended to provide conclusive evidence, but helps us to have a better understanding of the problem.

When conducting exploratory research, the researcher ought to be willing to change his/her direction as a result of revelation of new data and new insights. [1] Accordingly, exploratory studies are often conducted using interpretive research methods and they answer to questions such as what, why and how.

Exploratory research design does not aim to provide the final and conclusive answers to the research questions, but merely explores the research topic with varying levels of depth. It has been noted that “exploratory research is the initial research, which forms the basis of more conclusive research. It can even help in determining the research design, sampling methodology and data collection method” [2] . Exploratory research “tends to tackle new problems on which little or no previous research has been done” [3] .

Unstructured interviews are the most popular primary data collection method with exploratory studies. Additionally, surveys , focus groups and observation methods can be used to collect primary data for this type of studies.

Examples of Exploratory Research Design

The following are some examples for studies with exploratory research design in business studies:

• A study into the role of social networking sites as an effective marketing communication channel
• An investigation into the ways of improvement of quality of customer services within hospitality sector in London
• An assessment of the role of corporate social responsibility on consumer behaviour in pharmaceutical industry in the USA

Differences between Exploratory and Conclusive Research

The difference between exploratory and conclusive research is drawn by Sandhursen (2000) [4] in a way that exploratory studies result in a range of causes and alternative options for a solution of a specific problem, whereas, conclusive studies identify the final information that is the only solution to an existing research problem.

In other words, exploratory research design simply explores the research questions, leaving room for further researches, whereas conclusive research design is aimed to provide final findings for the research.

Moreover, it has been stated that “an exploratory study may not have as rigorous as methodology as it is used in conclusive studies, and sample sizes may be smaller. But it helps to do the exploratory study as methodically as possible, if it is going to be used for major decisions about the way we are going to conduct our next study” [5] (Nargundkar, 2003, p.41).

Exploratory studies usually create scope for future research and the future research may have a conclusive design. For example, ‘a study into the implications of COVID-19 pandemic into the global economy’ is an exploratory research. COVID-19 pandemic is a recent phenomenon and the study can generate an initial knowledge about economic implications of the phenomenon.

A follow-up study, building on the findings of this research ‘a study into the effects of COVID-19 pandemic on tourism revenues in Morocco’ is a causal conclusive research. The second research can produce research findings that can be of a practical use for decision making.

Advantages of Exploratory Research

• Lower costs of conducting the study
• Flexibility and adaptability to change
• Exploratory research is effective in laying the groundwork that will lead to future studies.
• Exploratory studies can potentially save time by determining at the earlier stages the types of research that are worth pursuing

Disadvantages of Exploratory Research

• Inclusive nature of research findings
• Exploratory studies generate qualitative information and interpretation of such type of information is subject to bias
• These types of studies usually make use of a modest number of samples that may not adequately represent the target population. Accordingly, findings of exploratory research cannot be generalized to a wider population.
• Findings of such type of studies are not usually useful in decision making in a practical level.

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance  contains discussions of theory and application of research designs. The e-book also explains all stages of the  research process  starting from the  selection of the research area  to writing personal reflection. Important elements of dissertations such as  research philosophy ,  research approach ,  methods of data collection ,  data analysis  and  sampling  are explained in this e-book in simple words.

John Dudovskiy

[1] Source: Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6 th  edition, Pearson Education Limited

[2] Singh, K. (2007) “Quantitative Social Research Methods” SAGE Publications, p.64

[3] Brown, R.B. (2006) “Doing Your Dissertation in Business and Management: The Reality of Research and Writing” Sage Publications, p.43

[4] Sandhusen, R.L. (2000) “Marketing” Barrons

[5] Nargundkar, R. (2008) “Marketing Research: Text and Cases” 3 rd edition, p.38

Exploratory Research: Definition, Types, Examples

Appinio Research · 12.10.2023 · 28min read

Are you ready to unlock the power of exploration in research? In this guide, we'll navigate the fascinating realm of exploratory research, demystifying its techniques and shedding light on its real-world applications.

Whether you're a seasoned researcher seeking to broaden your methodological toolkit or a novice embarking on your first research endeavor, this guide will equip you with the knowledge and insights to harness the full potential of exploratory research. Join us as we dive deep into the intricacies of understanding, planning, conducting, and reporting exploratory research, with real-life examples illuminating the way.

What is Exploratory Research?

Exploratory Research is an investigative method used in the early stages of a research project to delve into a topic when little to no existing knowledge or information is available. It is a dynamic and flexible approach aimed at gaining insights, uncovering trends, and generating initial hypotheses. The primary purposes of exploratory research are:

• Understanding Complexity: Exploratory research helps researchers understand the intricate and multifaceted nature of a research topic, especially when the subject matter is not well-defined.
• Idea Generation: It serves as a fertile ground for generating new ideas, hypotheses, and research questions that can guide more focused studies in the future.
• Problem Identification: It helps identify research problems or gaps in existing knowledge, allowing researchers to refine their research objectives.
• Decision Support: Exploratory research provides valuable information for making informed decisions about the direction and scope of a research project.

Importance of Exploratory Research

Exploratory research holds immense significance in the world of research and problem-solving for several reasons:

• Risk Reduction: By exploring a topic before committing to a specific research path, exploratory research helps reduce the risk of pursuing unproductive or irrelevant research.
• Informed Research: It lays the groundwork for subsequent phases of research, ensuring that subsequent studies are well-informed and more likely to yield meaningful results.
• Creative Exploration: It encourages creative and open-minded exploration of topics, making it particularly useful when dealing with novel or emerging issues.
• Adaptability: Exploratory research methods are adaptable and can be tailored to the unique characteristics of a research question or problem.

Types of Exploratory Research

Exploratory research encompasses various methodologies, each designed to suit specific research objectives and contexts. Let's explore these types in more detail:

Literature Review

Literature Review involves a systematic examination of existing research, publications, and sources related to a specific topic. It serves as a comprehensive exploration of the current state of knowledge.

• Purpose: To identify existing theories, concepts, and gaps in the literature related to a research topic.
• Methods: Researchers review academic papers, books, articles, and other scholarly sources. They synthesize and analyze the findings and theories presented in these sources.
• Benefits: A literature review provides a solid foundation for understanding the historical context and key debates surrounding a topic. It helps researchers identify areas where further investigation is needed.

Pilot Studies

Pilot Studies are small-scale research projects conducted before a full-scale study. They serve as test runs to assess the feasibility of research methods and data collection tools.

• Purpose: To test research procedures, instruments, and methodologies in a controlled environment.
• Methods: Researchers select a smaller sample and conduct data collection and analysis as if it were a full study.
• Benefits: Pilot studies help identify potential problems, refine research designs, and improve the quality of data collection.

Case Studies

Case Studies involve an in-depth examination of a specific individual, group, organization, or event. They offer a holistic view of a particular phenomenon.

• Purpose: To explore real-life contexts and understand complex, unique situations.
• Methods: Researchers gather data through interviews, observations, and document analysis, providing rich, contextual insights.
• Benefits: Case studies provide a deep understanding of specific instances, allowing researchers to extract valuable lessons or generate hypotheses for broader research.

Focus Groups

Focus Groups bring together a small group of participants to engage in open and structured discussions about a particular topic.

• Purpose: To explore group dynamics, collective opinions, and shared perceptions on a specific subject.
• Methods: Researchers facilitate group discussions with carefully designed questions, encouraging participants to express their thoughts and experiences.
• Benefits: Focus groups reveal diverse perspectives, uncover latent issues, and provide qualitative data for further investigation.

In-depth Interviews

In-depth Interviews involve one-on-one conversations between a researcher and a participant, allowing for detailed exploration of experiences, opinions, and perceptions.

• Purpose: To gain in-depth insights into individual perspectives and experiences.
• Methods: Researchers use open-ended questions to guide interviews, creating a conversational and exploratory atmosphere.
• Benefits: In-depth interviews provide rich, nuanced data and are well-suited for studying sensitive topics or personal experiences.

Observational Research

Observational Research entails the systematic observation and recording of behaviors, events, or phenomena in their natural settings.

• Purpose: To understand behavior or phenomena as they naturally occur in their real-world context.
• Methods: Researchers select settings, define variables, and record data through direct observations.
• Benefits: Observational research captures authentic behavior and context, offering insights that might be missed in controlled environments.

Content Analysis

Content Analysis is a method for analyzing textual, visual, or audio content to uncover patterns, themes, or trends.

• Purpose: To explore and understand the content and communication surrounding a particular topic or media.
• Methods: Researchers define coding categories, code content based on these categories, and analyze the frequency and patterns of codes.
• Benefits: Content analysis provides quantitative and qualitative insights into the content of documents, media, or communication channels.

These various types of exploratory research methods offer researchers a versatile toolkit for diving into the unknown and gaining valuable insights, setting the stage for further investigation and discovery.

How to Plan and Design Exploratory Research?

In the planning and design phase of exploratory research, careful consideration of key elements is crucial to ensure the research objectives are met effectively. Let's delve into these elements:

1. Research Objectives

Before embarking on exploratory research, it's essential to define clear and specific research objectives.

• Purpose: Research objectives should clarify what you aim to achieve through your exploratory study. Are you looking to understand a phenomenon, generate hypotheses, identify research gaps, or explore new concepts?
• Specificity: Objectives should be well-defined, leaving no room for ambiguity. They should guide your research process and serve as a benchmark for success.
• Alignment: Ensure that your research objectives align with the broader goals of your research project and contribute to the generation of valuable insights.

2. Data Collection Methods

Selecting appropriate data collection methods is a critical step in planning exploratory research.

The choice of methods should align with your research objectives.

• Method Suitability: Consider the nature of your research question. Qualitative methods like interviews and focus groups are ideal for exploring subjective experiences, while quantitative methods may be more suitable for gathering numerical data.
• Data Sources: Identify the sources of data you will tap into, whether it's primary data (collected directly) or secondary data (existing sources).
• Data Collection Tools: Determine the specific tools and instruments you will use for data collection. This may include interview guides, questionnaires, or observation protocols.

3. Sampling Techniques

Choosing the proper sampling techniques is crucial to ensure that your exploratory research represents the target population or context effectively.

• Purposeful Sampling: When using qualitative methods like interviews and focus groups, purposeful or selective sampling helps identify participants who can provide valuable insights based on specific criteria, such as expertise or experience.
• Random Sampling: If your exploratory research involves quantitative data collection, consider random sampling methods to ensure that your sample is representative of the larger population.
• Snowball Sampling: In cases where it's challenging to identify participants through traditional methods, snowball sampling allows initial participants to refer others, creating a chain of referrals.

4. Data Analysis Approaches

Determining the data analysis approaches is essential for making sense of the information collected during exploratory research.

• Qualitative Data Analysis: For qualitative data, approaches like thematic analysis , content analysis, or narrative analysis help identify patterns, themes, and trends within the data.
• Quantitative Data Analysis: If you have quantitative data, statistical analysis and data visualization techniques can reveal trends, correlations, and significant findings.
• Mixed-Methods Analysis: In cases where both qualitative and quantitative data are collected, a mixed-methods analysis approach can provide a more comprehensive understanding.

5. Ethical Considerations

Ethical considerations are paramount in exploratory research, as they ensure the well-being and rights of participants are protected.

• Informed Consent: Obtain informed consent from participants, explaining the purpose of the research, their role, and the potential risks and benefits. Consent forms should be clear and voluntary.
• Privacy and Anonymity: Protect the confidentiality and anonymity of participants by avoiding disclosing personal or sensitive information without explicit consent.
• Data Security: Safeguard research data to prevent unauthorized access or breaches of confidentiality.
• Conflict of Interest: Disclose any conflicts of interest or potential biases that may affect the research process or findings.
• Compliance: Adhere to ethical guidelines and regulations established by relevant institutions or governing bodies, such as institutional review boards (IRBs).

With a well-planned approach that includes clearly defined research objectives, appropriate data collection methods, thoughtful sampling techniques, robust data analysis approaches, and ethical considerations, you can set the stage for a successful exploratory research endeavor.

How to Conduct Exploratory Research?

In this section, we will delve into the practical aspects of conducting exploratory research, which involves data collection and analysis. These steps are vital to uncover insights and generate hypotheses. Let's explore each component in detail:

Data Collection

Effective data collection is the cornerstone of exploratory research. Here are various methods you can use to collect data:

1. Literature Review Process

Literature review is the process of systematically searching, reviewing, and summarizing existing academic literature related to your research topic. This step is crucial as it provides a foundation for understanding the current state of knowledge and identifying research gaps:

• Identify Relevant Sources: Begin by searching for relevant academic papers, books, articles, and reports. Online databases like PubMed, Google Scholar, and academic library catalogs are excellent resources.
• Synthesize Information: Summarize the essential findings and ideas from the sources you've collected. Create a literature review matrix or summary to organize your results and identify common themes.
• Identify Research Gaps: As you review the literature, pay attention to areas where there's a lack of research or conflicting findings. These gaps can inform your exploratory research objectives.

2. Conducting Pilot Studies

Pilot studies are small-scale research projects designed to test and refine your research methods and instruments. They provide valuable insights and help identify potential issues before embarking on a full-scale study.

• Define Objectives: Clearly define the objectives of your pilot study. What specific aspects of your research design are you testing? What do you hope to learn from the pilot?
• Select Sample: Choose a small, representative sample for your pilot study. This sample should reflect your target population as closely as possible.
• Collect Data: Implement your research methods on the selected sample. Pay close attention to any challenges or issues that arise during data collection.
• Analyze Results: After collecting data, analyze the results. Look for any anomalies or unexpected findings that may require adjustments to your research design.

3. Running Case Studies

Case studies involve in-depth investigations into specific individuals, groups, organizations, or events. They provide rich, contextual data.

• Select a Case: Choose a relevant case that aligns with your research objectives. Consider cases that offer unique insights or perspectives on your topic.
• Gather Data: Collect data through a combination of interviews, observations, and document analysis. Triangulate your data sources for a comprehensive view.
• Analyze Data: Analyze the collected data to identify patterns, themes, and insights. Use coding or thematic analysis to categorize information.

4. Organizing Focus Groups

Focus groups bring together a small group of participants to engage in open and structured discussions about a particular topic.

• Recruit Participants: Recruit a diverse group of participants who can provide valuable insights into your research questions. Ensure that the group dynamics are conducive to open discussion.
• Design Questions: Prepare a set of open-ended questions that guide the discussion. Encourage participants to share their perspectives and experiences.
• Conduct the Session: Facilitate the focus group session, making sure everyone has an opportunity to speak. Take detailed notes and consider using audio or video recording.
• Analyze Findings: Transcribe and analyze the focus group discussions. Look for common themes, opinions, and areas of agreement or disagreement among participants.

5. Performing In-depth Interviews

In-depth interviews involve one-on-one conversations between a researcher and a participant, allowing for detailed exploration of experiences, opinions, and perceptions.

• Prepare Interview Guide: Develop a structured interview guide with open-ended questions that align with your research objectives. The guide provides a framework for the interview.
• Select Participants: Choose participants who can offer in-depth insights into your research questions. Establish rapport and build trust during the interviews.
• Conduct Interviews: Conduct one-on-one interviews, following the interview guide but allowing for flexibility to explore unexpected topics. Encourage participants to share their thoughts and experiences.
• Transcribe and Analyze: Transcribe the interviews and analyze the responses. Look for common themes, patterns, and noteworthy quotes that support your research objectives.

6. Observational Research Techniques

Observational research involves the systematic observation and recording of behaviors, events, or phenomena in their natural settings.

• Select the Setting: Choose a setting that allows for unobtrusive observation of the behavior or phenomena you're studying. Ensure that your presence does not influence the behavior.
• Define Variables: Clearly define the behaviors or phenomena you're observing. Create an observation checklist or coding scheme to record data systematically.
• Record Data: Systematically record your observations, either in real-time or through video/audio recordings. Be objective and avoid making interpretations during the observation.
• Analyze Data: After data collection, analyze the recorded observations to identify patterns, trends, and any noteworthy behaviors. Consider interrater reliability if multiple observers are involved.

7. Content Analysis Methods

Content analysis is a method for systematically analyzing textual, visual, or audio content to uncover patterns, themes, or trends.

• Define Coding Categories: Determine the coding categories or themes that align with your research objectives. Create a coding scheme that can be applied consistently.
• Code Content: Apply the coding scheme to the content you're analyzing. This may involve categorizing text passages, images, or audio segments based on predefined criteria.
• Record and Analyze Data: Record the coded data systematically and analyze it to identify patterns, trends, or recurring themes. Consider using software tools to assist in content analysis.

Data Analysis

After collecting data through the various methods, it's essential to analyze it effectively to extract meaningful insights:

1. Qualitative Data Analysis

Qualitative data analysis involves the examination of non-numeric data, such as text, interviews, and observations.

• Data Coding: Begin by coding the qualitative data, which involves categorizing information into themes or codes. This step helps organize the data for analysis.
• Thematic Analysis: Conduct thematic analysis to identify recurring themes, patterns, and trends within the data. Look for connections and relationships between themes.
• Constant Comparison: Use constant comparison, where you compare new data with existing codes and themes to refine your understanding of the data.
• Interpretation: Interpret the qualitative data in the context of your research objectives. Explore the implications of your findings and consider how they contribute to your research goals.

2. Quantitative Data Analysis

Quantitative data analysis involves the examination of numerical data gathered through surveys, experiments, or other structured methods.

• Data Cleaning: Begin by cleaning the data and addressing any missing values, outliers, or inconsistencies. Ensure that the data is in a usable format for analysis.
• Descriptive Analysis : Perform descriptive analysis to summarize the main characteristics of the data. This includes calculating measures like mean, median, and standard deviation.
• Inferential Analysis: If applicable, conduct inferential analysis to test hypotheses or determine relationships between variables. Common statistical tests include t-tests, ANOVA, and regression analysis.
• Data Visualization: Create visual representations of your quantitative data using charts, graphs, and tables to illustrate key findings.

3. Identifying Patterns and Themes

Across both qualitative and quantitative data analysis, the process of identifying patterns and themes is essential.

• Pattern Recognition: Look for recurring patterns, trends, or regularities in the data. These patterns may be related to your research objectives or unexpected discoveries.
• Theme Identification: In qualitative data analysis, identify themes or categories that emerge from the data. Themes represent commonalities in participants' responses or behaviors.
• Cross-Referencing Data: Compare findings from different data collection methods (e.g., interviews, surveys) to triangulate your results and gain a more comprehensive understanding.
• Iterative Process: Data analysis is often an iterative process. You may revisit and refine your analysis as you uncover new insights or refine your research questions.

By effectively collecting and analyzing data, you can extract meaningful insights, identify trends, and generate hypotheses that will guide your exploratory research and inform future research endeavors.

How to Report and Present Exploratory Research Findings?

Effectively reporting and presenting exploratory research findings is vital to communicate insights and guide future actions. Let's explore the components of this phase in more detail.

Structure of Research Reports

Creating a well-structured research report ensures that your exploratory findings are communicated clearly and effectively.

• Title Page: Begin with a title page that includes the title of the report, your name, affiliation, and the date of publication.
• Executive Summary: Provide a concise summary of the research objectives, methods, key findings, and recommendations. This section should be informative yet brief.
• Table of Contents: Include a table of contents to help readers navigate through the report easily.
• Introduction: Introduce the research topic, objectives, and the importance of exploratory research in addressing your research questions.
• Methodology: Describe the methods used for data collection, including sampling techniques, data analysis approaches, and ethical considerations.
• Findings: Present your research findings, organized by research method (e.g., literature review, pilot study, focus groups, interviews, etc.).
• Discussion: Interpret your findings, discuss their implications, and relate them to your research objectives. Consider addressing any limitations.
• Recommendations: Offer recommendations based on your exploratory research. What actions or further research should be pursued?
• Conclusion: Summarize the key points of your study, emphasizing its significance.
• Appendices: Include any supplementary materials, such as interview transcripts, survey questionnaires, or additional data.
• References: Cite all the sources you referenced in your report using a consistent citation style (e.g., APA, MLA).

Visualizing Data

Effective data visualization enhances the understanding of your exploratory findings.

• Tables: Organize data in tabular format for easy comparison.
• Charts and Graphs: Use bar charts, line graphs, pie charts, or scatter plots to represent quantitative data.
• Infographics: Create visual summaries of key findings using infographics.
• Images and Visuals: Include relevant images, photographs, or screenshots to illustrate points.

Interpreting Results

Interpreting your exploratory research results involves:

• Contextualizing Findings: Explain the significance of your findings within the broader context of your research objectives.
• Discussing Implications: Consider the practical implications of your findings. How do they impact the research area or field?
• Addressing Limitations: Acknowledge any limitations or constraints in your study, such as sample size or data collection challenges.
• Comparing with Hypotheses: If applicable, compare your findings with any initial hypotheses you may have developed during the exploratory phase.
• Suggesting Future Research: Identify areas where further research is needed, building upon the insights gained in your exploratory study.

Making Recommendations

Based on your exploratory research, provide actionable recommendations.

• Practical Steps: Offer specific actions or decisions that can be made based on your findings.
• Policy Recommendations: If relevant, suggest changes or improvements to policies or practices.
• Further Research: Highlight areas where more in-depth research is required to build upon your exploratory findings.
• Implementation Plan: Outline a plan for implementing the recommendations, if applicable.

Remember that the clarity of your report and the persuasiveness of your recommendations are crucial in making your exploratory research valuable to your audience. Effective communication ensures that your insights lead to informed decisions and further exploration in your field of study.

Exploratory Research Advantages and Limitations

Exploratory research offers valuable insights into various aspects of a research topic, but it also comes with its own set of advantages and limitations. Understanding these factors is essential for making informed decisions about using exploratory research in your projects. Let's explore both sides of the coin.

Exploratory Research Advantages

• Insight Generation: Exploratory research excels at discovering the unknown. It allows you to explore and uncover new phenomena, trends, or perspectives that may have been previously unknown or overlooked.
• Hypothesis Generation: By investigating a topic with an open mind, you can generate hypotheses and research questions that can guide more focused research in the future. These initial hypotheses can serve as a valuable starting point.
• Flexibility: Exploratory research is well-suited for complex and multifaceted topics where a structured approach may not be appropriate. It provides the flexibility to adapt to evolving research objectives.
• Qualitative Understanding: Methods like interviews, focus groups, and content analysis provide rich qualitative data. This qualitative understanding is crucial for exploring nuances and complexities in human experiences and behaviors.
• Contextual Understanding: Exploratory research often takes place in real-world contexts. Case studies and observational research, for example, allow you to understand how phenomena operate in their natural environments, providing valuable context.
• Pilot Testing: Exploratory research, including pilot studies, helps in refining research methodologies and instruments. By uncovering potential issues early on, it reduces errors in subsequent studies.

Exploratory Research Limitations

• Lack of Generalizability: Exploratory research often uses small, non-representative samples. This makes it challenging to generalize findings to larger populations or broader contexts. The insights gained may be specific to the participants or conditions involved.
• Subjectivity: The qualitative nature of many exploratory research methods can introduce subjectivity in data analysis and interpretation. Researchers' biases and perspectives may influence the findings.
• Time and Resource Intensive: Some exploratory research methods, such as in-depth interviews or case studies, can be time-consuming and resource-intensive. This can limit the scalability of exploratory studies.
• Limited Quantitative Data: If your research requires precise numerical data, exploratory research may not be sufficient. It primarily focuses on qualitative insights and quantitative data may be limited in scope.
• Potential for Bias: The choice of research methods and participants can introduce bias into your findings. For example, purposive sampling in qualitative research may inadvertently select participants with similar perspectives.
• Incomplete Picture: Exploratory research may provide an insufficient or preliminary picture of a topic. It often requires further investigation for validation and a more comprehensive understanding.
• Ethical Challenges: The open-ended nature of exploratory research can raise ethical challenges, especially in sensitive research areas. Ensuring participant consent and privacy is essential.

Understanding these advantages and limitations is crucial for researchers to make informed decisions about when and how to apply exploratory research methods. It's essential to carefully consider these factors in the context of your research objectives and the specific challenges and opportunities presented by your research topic.

Exploratory Research Examples

Exploratory research is a versatile approach employed across various fields to gain insights, uncover trends, and generate hypotheses. Let's explore real-world examples of how different exploratory research methods have been applied effectively:

1. Real-Life Case Studies

Facebook's emotional contagion study.

Background: In 2014, Facebook conducted a controversial exploratory research study to investigate emotional contagion. The study involved manipulating the content that appeared in users' newsfeeds to measure how emotional content impacted their own posts.

Method: Facebook used large-scale data analysis to conduct this study, which involved over 689,000 users. They manipulated the visibility of positive and negative posts to examine whether emotional states could be influenced online.

Findings: The study found that when users saw fewer positive posts in their newsfeeds, they tended to post fewer positive updates themselves, and vice versa for negative posts. This research sparked discussions about ethical considerations in online experimentation and the power of social media platforms to influence emotions.

Harvard Business School's Airbnb Case Study

Background: Harvard Business School conducted an exploratory case study on Airbnb, a disruptive platform in the hospitality industry. The goal was to understand how Airbnb disrupted traditional lodging markets and its impact on the hotel industry.

Method: Researchers collected data from various sources, including interviews with Airbnb hosts, surveys of travelers, and publicly available data on Airbnb listings and hotel occupancy rates. They analyzed the data to identify trends and insights.

Findings: The study found that Airbnb significantly impacted the hotel industry by offering unique, affordable, and personalized lodging options. It also highlighted challenges such as regulatory issues and concerns about safety and quality control.

2. Focus Groups

Apple's product development.

Background: Apple Inc. frequently conducts exploratory research through focus groups to gather insights and opinions from potential users before launching new products or features.

Method: Apple assembles small groups of potential users and conducts moderated discussions. Participants are encouraged to share their thoughts, preferences, and concerns about prototypes or concepts.

Findings: Apple gains valuable feedback about user preferences and pain points by engaging with focus groups. For example, before launching the Apple Watch, focus groups provided insights into desired features like health tracking and customization.

Political Campaign Strategy

Background: In politics, campaign teams often use focus groups to explore voters' opinions, reactions to candidates, and key campaign issues.

Method: Focus groups consist of a diverse set of voters who engage in discussions about campaign messages, policies, and candidate attributes. Campaign teams use these insights to tailor their strategies.

Findings: Focus groups help political campaigns understand which messages resonate with different voter demographics. For instance, a focus group may reveal that a candidate's stance on a specific policy particularly appeals to a specific age group, influencing campaign messaging.

3. Content Analysis

Climate change discourse in media.

Background: Exploratory content analysis has been employed to study media coverage of climate change. Researchers aim to understand how different media outlets frame climate change issues.

Method: Researchers collect articles and news reports from various sources and then analyze the content to identify recurring themes, framing, and the use of language. This helps determine how climate change is portrayed in the media.

Findings: Content analysis has revealed that media outlets may use different frames when discussing climate change, such as "economic impact," "environmental consequences," or "scientific consensus." These frames can influence public perception and policy discussions.

Social Media Sentiment Analysis

Background: Companies and organizations use content analysis of social media posts to gauge public sentiment and gather insights into customer opinions and preferences.

Method: Automated tools are used to collect and analyze social media posts, comments, and mentions related to a specific brand, product, or topic. Natural language processing techniques identify sentiment (positive, negative, neutral) and key themes.

Findings: By analyzing social media content, companies can identify customer complaints, emerging trends, or public sentiment shifts in real time. For example, a restaurant chain may use sentiment analysis to track customer reactions to new menu items.

4. Observational Research

Supermarket shopping behavior.

Background: Observational research is frequently used in the retail industry to understand consumer behavior. One example is studying how shoppers navigate supermarkets.

Method: Researchers observe shoppers in a supermarket, noting their paths through the store, product choices, and interactions with displays. This data helps retailers optimize store layouts and product placement.

Findings: Observational research has shown that shoppers tend to follow predictable patterns in supermarkets, such as starting with fresh produce. Retailers use this data to design store layouts that encourage specific shopping behaviors and maximize sales.

Child Development Studies

Background: Observational research is crucial in child development studies to understand how children learn and develop through their interactions with the environment.

Method: Researchers use video recordings or live observations to document children's behaviors in various settings, such as classrooms or homes. They analyze these observations to identify developmental milestones and learning patterns.

Findings: Observational research in child development has contributed to our understanding of how children acquire language, social skills, and cognitive abilities. For example, it has revealed how peer interactions influence language development in preschoolers.

These real-world examples illustrate the diverse applications of exploratory research methods, from understanding user preferences for tech giants like Apple to analyzing media discourse on critical issues like climate change. Exploratory research empowers organizations and researchers with valuable insights that inform decision-making and shape future research directions.

Exploratory research is a dynamic tool that opens doors to discovery. It helps us uncover hidden insights, generate fresh ideas, and better understand the world around us. By delving into the unknown and embracing its flexibility, we can embark on journeys of exploration that enrich our knowledge and inform future endeavors.

So, whether you're exploring uncharted territories in academia, industry, or any field, remember that the spirit of curiosity and the methods of exploratory research can be your compass. With the right strategies and ethical considerations, you'll not only navigate the challenges but also uncover the treasures of knowledge that await. As you embark on your own exploratory research adventures, may you find answers to your questions, ignite new inquiries, and, above all, revel in the joy of discovery.

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Exploratory Research: Types & Characteristics

Consider a scenario where a juice bar owner feels that increasing the variety of juices will enable an increase in customers. However, he is not sure and needs more information. The owner intends to conduct exploratory research to find out; hence, he decides to do exploratory research to find out if expanding their juices selection will enable him to get more customers or if there is a better idea.

Another example of exploratory research is a podcast survey template that can be used to collect feedback about the podcast consumption metrics both from existing listeners as well as other podcast listeners that are currently not subscribed to this channel. This helps the author of the podcast create curated content that will gain a larger audience. Let’s explore this topic.

LEARN ABOUT: Research Process Steps

Content Index

Exploratory research: Definition

Primary research methods, secondary research methods, exploratory research: steps to conduct a research, characteristics of exploratory research, advantages of exploratory research, disadvantages of exploratory research, importance of exploratory research.

Exploratory research is defined as a research used to investigate a problem which is not clearly defined. It is conducted to have a better understanding of the existing research problem , but will not provide conclusive results. For such a research, a researcher starts with a general idea and uses this research as a medium to identify issues, that can be the focus for future research. An important aspect here is that the researcher should be willing to change his/her direction subject to the revelation of new data or insight. Such a research is usually carried out when the problem is at a preliminary stage. It is often referred to as grounded theory approach or interpretive research as it used to answer questions like what, why and how.

Types and methodologies of Exploratory research

While it may sound difficult to research something that has very little information about it, there are several methods which can help a researcher figure out the best research design, data collection methods and choice of subjects. There are two ways in which research can be conducted namely primary and secondary.. Under these two types, there are multiple methods which can used by a researcher. The data gathered from these research can be qualitative or quantitative . Some of the most widely used research designs include the following:

LEARN ABOUT: Best Data Collection Tools

Primary research is information gathered directly from the subject.  It can be through a group of people or even an individual. Such a research can be carried out directly by the researcher himself or can employ a third party to conduct it on their behalf. Primary research is specifically carried out to explore a certain problem which requires an in-depth study.

• Surveys/polls : Surveys /polls are used to gather information from a predefined group of respondents. It is one of the most important quantitative method. Various types of surveys  or polls can be used to explore opinions, trends, etc. With the advancement in technology, surveys can now be sent online and can be very easy to access. For instance, use of a survey app through tablets, laptops or even mobile phones. This information is also available to the researcher in real time as well. Nowadays, most organizations offer short length surveys and rewards to respondents, in order to achieve higher response rates.

LEARN ABOUT: Live polls for Classroom Experience

For example: A survey is sent to a given set of audience to understand their opinions about the size of mobile phones when they purchase one. Based on such information organization can dig deeper into the topic and make business related decision.

• Interviews: While you may get a lot of information from public sources, but sometimes an in person interview can give in-depth information on the subject being studied. Such a research is a qualitative research method . An interview with a subject matter expert can give you meaningful insights that a generalized public source won’t be able to provide. Interviews are carried out in person or on telephone which have open-ended questions to get meaningful information about the topic.

For example: An interview with an employee can give you more insights to find out the degree of job satisfaction, or an interview with a subject matter expert of quantum theory can give you in-depth information on that topic.

• Focus groups: Focus group is yet another widely used method in exploratory research. In such a method a group of people is chosen and are allowed to express their insights on the topic that is being studied. Although, it is important to make sure that while choosing the individuals in a focus group they should have a common background and have comparable experiences.

For example: A focus group helps a research identify the opinions of consumers if they were to buy a phone. Such a research can help the researcher understand what the consumer value while buying a phone. It may be screen size, brand value or even the dimensions. Based on which the organization can understand what are consumer buying attitudes, consumer opinions, etc.

• Observations: Observational research can be qualitative observation or quantitative observation . Such a research is done to observe a person and draw the finding from their reaction to certain parameters. In such a research, there is no direct interaction with the subject.

For example: An FMCG company wants to know how it’s consumer react to the new shape of their product. The researcher observes the customers first reaction and collects the data, which is then used to draw inferences from the collective information.

LEARN ABOUT: Causal Research

Secondary research is gathering information from previously published primary research. In such a research you gather information from sources likes case studies, magazines, newspapers, books, etc.

• Online research: In today’s world, this is one of the fastest way to gather information on any topic. A lot of data is readily available on the internet and the researcher can download it whenever he needs it. An important aspect to be noted for such a research is the genuineness and authenticity of the source websites that the researcher is gathering the information from.

For example: A researcher needs to find out what is the percentage of people that prefer a specific brand phone. The researcher just enters the information he needs in a search engine and gets multiple links with related information and statistics.

• Literature research : Literature research is one of the most inexpensive method used for discovering a hypothesis. There is tremendous amount of information available in libraries, online sources, or even commercial databases. Sources can include newspapers, magazines, books from library, documents from government agencies, specific topic related articles, literature, Annual reports, published statistics from research organizations and so on.

However, a few things have to be kept in mind while researching from these sources. Government agencies have authentic information but sometimes may come with a nominal cost. Also, research from educational institutions is generally overlooked, but in fact educational institutions carry out more number of research than any other entities.

Furthermore, commercial sources provide information on major topics like political agendas, demographics, financial information, market trends and information, etc.

For example: A company has low sales. It can be easily explored from available statistics and market literature if the problem is market related or organization related or if the topic being studied is regarding financial situation of the country, then research data can be accessed through government documents or commercial sources.

• Case study research: Case study research can help a researcher with finding more information through carefully analyzing existing cases which have gone through a similar problem. Such exploratory data analysis are very important and critical especially in today’s business world. The researcher just needs to make sure he analyses the case carefully in regards to all the variables present in the previous case against his own case. It is very commonly used by business organizations or social sciences sector or even in the health sector.

LEARN ABOUT: Level of Analysis

For example: A particular orthopedic surgeon has the highest success rate for performing knee surgeries. A lot of other hospitals or doctors have taken up this case to understand and benchmark the method in which this surgeon does the procedure to increase their success rate.

• Identify the problem : A researcher identifies the subject of research and the problem is addressed by carrying out multiple methods to answer the questions.
• Create the hypothesis : When the researcher has found out that there are no prior studies and the problem is not precisely resolved, the researcher will create a hypothesis based on the questions obtained while identifying the problem.
• Further research : Once the data has been obtained, the researcher will continue his study through descriptive investigation. Qualitative methods are used to further study the subject in detail and find out if the information is true or not.

LEARN ABOUT: Descriptive Analysis

• They are not structured studies
• It is usually low cost, interactive and open ended.
• It will enable a researcher answer questions like what is the problem? What is the purpose of the study? And what topics could be studied?
• To carry out exploratory research, generally there is no prior research done or the existing ones do not answer the problem precisely enough.
• It is a time consuming research and it needs patience and has risks associated with it.
• The researcher will have to go through all the information available for the particular study he is doing.
• There are no set of rules to carry out the research per se, as they are flexible, broad and scattered.
• The research needs to have importance or value. If the problem is not important in the industry the research carried out is ineffective.
• The research should also have a few theories which can support its findings as that will make it easier for the researcher to assess it and move ahead in his study
• Such a research usually produces qualitative data , however in certain cases quantitative data can be generalized for a larger sample through use of surveys and experiments.

LEARN ABOUT: Action Research

• The researcher has a lot of flexibility and can adapt to changes as the research progresses.
• It is usually low cost.
• It helps lay the foundation of a research, which can lead to further research.
• It enables the researcher understand at an early stage, if the topic is worth investing the time and resources  and if it is worth pursuing.
• It can assist other researchers to find out possible causes for the problem, which can be further studied in detail to find out, which of them is the most likely cause for the problem.
• Even though it can point you in the right direction towards what is the answer, it is usually inconclusive.
• The main disadvantage of exploratory research is that they provide qualitative data. Interpretation of such information can be judgmental and biased.
• Most of the times, exploratory research involves a smaller sample , hence the results cannot be accurately interpreted for a generalized population.
• Many a times, if the data is being collected through secondary research, then there is a chance of that data being old and is not updated.

LEARN ABOUT: Projective Techniques & Conformity Bias

Exploratory research is carried out when a topic needs to be understood in depth, especially if it hasn’t been done before. The goal of such a research is to explore the problem and around it and not actually derive a conclusion from it. Such kind of research will enable a researcher to  set a strong foundation for exploring his ideas, choosing the right research design and finding variables that actually are important for the in-depth analysis . Most importantly, such a research can help organizations or researchers save up a lot of time and resources, as it will enable the researcher to know if it worth pursuing.

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• > The Production of Knowledge
• > Exploratory Research

Book contents

• The Production of Knowledge
• Strategies for Social Inquiry
• Copyright page
• Detailed Contents
• Contributors
• Acknowledgments
• 1 Introduction
• Part I Discovery
• 2 Exploratory Research
• 3 Research Cycles
• Part II Publishing
• Part III Transparency and Reproducibility
• Part IV Appraisal
• Part V Diversity
• Part VI Conclusions

2 - Exploratory Research

from Part I - Discovery

Published online by Cambridge University Press:  11 March 2020

Exploratory research is an attempt to discover something new and interesting by working through a research topic and is the soul of good research. Exploratory studies, a type of exploratory research, tend to fall into two categories: those that make a tentative first analysis of a new topic and those that propose new ideas or generate new hypotheses on an old topic. This chapter examines the history of exploratory studies, offers a typology of exploratory studies, and proposes a new type of exploratory study that is especially helpful for theorizing empirical material at an early stage. It argues that exploratory studies are an important part of a social scientist’s toolkit.

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• Exploratory Research
• By Richard Swedberg
• Edited by Colin Elman , Syracuse University, New York , John Gerring , University of Texas, Austin , James Mahoney , Northwestern University, Illinois
• Book: The Production of Knowledge
• Online publication: 11 March 2020
• Chapter DOI: https://doi.org/10.1017/9781108762519.002

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10 Exploratory Research Examples

Exploratory research is research that explores new or interesting topics, often as a pioneering study, conducting research that hasn’t been attempted before.

Let’s examine some academic definitions of exploratory research – if you’re writing an essay or methodology chapter on this topic, you might want to use these expert quotes in your writing:

• “… research used to investigate an issue that is new, a problem which is not clearly defined, a topic on which there is little data” (Gozdziak & Chantavanich, 2022)
• “… initial research conducted to clarify and define the nature of the problem. It is done to help diagnose the situation, allow for screening of alternatives, and discover new ideas.” (Hutchison, Allen & Macy, 2012)
• “… the initial research into a hypothetical or theoretical idea. This is where the researcher has an idea and wishes to research a topic seeking to understand it more deeply. An exploratory research study is an attempt to lay the groundwork that could of will lead to future studies.” (Blecher, 2018)

Oftentimes, an exploratory study takes the form of a descriptive-qualitative design that precedes a larger project (Cargan, 2007). The exploratory section of the study seeks to describe the phenomena in detail and generate hypotheses that would later be tested. This is common, for example, in grounded research projects .

Approaches to Exploratory Research

Belcher (2018) highlights that there are two ways you could go about exploratory research. You could either approach an entirely new topic that’s not been examined before. Or, you could find a new angle to approach an old topic:

• New Topic: This could involve examining an entirely new, rare, or unique phenomenon that is yet to be explored.
• New Angle on an Old Topic: This could involve using a new theoretical perspective or a new methodological approach to examine a topic that has been studied before.

Exploratory Research Examples

1. Bee Population Decline and Farming

Proposed Methods: Qualitative Interviews, Observation

If a team of environmental scientists were to notice a decline in the bee population in a farming region, they could conduct exploratory research by interviewing local farmers and observing farming practices. Their potential findings might suggest a correlation between certain pesticide use and the decrease in bee numbers, which could then prompt a more detailed investigation into alternative farming methods to protect bee colonies.

2. Urban Green Spaces and Mental Health

Proposed Methods: Surveys, Focus Group Discussions

If urban planners and health researchers were to observe a potential link between the presence of green spaces in urban areas and residents’ mental well-being, they could initiate exploratory research by surveying city dwellers and hosting focus group discussions. Their initial insights might indicate that regular access to urban parks and gardens is associated with lower stress levels and improved mood among the population. This could lead to a comprehensive study on the design and distribution of green spaces to enhance urban mental health.

3. Effects of Screen Time on Sleep Patterns

Proposed Methods: Diary Studies, Qualitative Interviews

If health experts were to suspect a relationship between prolonged screen time and disrupted sleep among teenagers, they could undertake exploratory research by having participants maintain sleep diaries and conducting in-depth interviews. The gathered data might reveal that excessive exposure to screens before bedtime could correlate with difficulty falling asleep and reduced sleep quality. Such findings could pave the way for a more conclusive study on digital habits and sleep hygiene.

4. Traditional Medicines and Modern Healing

Proposed Methods: Ethnographic Studies, Expert Interviews

If medical anthropologists were curious about the efficacy of traditional medicines in contemporary health practices, they could embark on exploratory research by studying indigenous communities and interviewing traditional healers. Their preliminary observations might suggest that certain age-old remedies have potential benefits in treating modern ailments. This could inspire further research into integrating traditional knowledge with modern medical practices.

5. Sustainable Packaging and Consumer Preferences

Proposed Methods: Surveys, Product Testing

If market researchers were to speculate about the rising preference for sustainable packaging among consumers, they could conduct exploratory research through surveys and product testing sessions. Initial feedback might indicate that consumers are more inclined to purchase products with eco-friendly packaging due to environmental concerns. This could initiate a more extensive study on the potential market shift towards sustainable packaging solutions.

6. Music Therapy and Cognitive Development in Children

Proposed Methods: Observational Studies , Interviews with Therapists

If developmental psychologists were to ponder the effects of music therapy on cognitive growth in children, they could delve into exploratory research by observing therapy sessions and interviewing music therapists. Early insights might reveal that structured musical activities could enhance certain cognitive functions, such as memory and attention span. This could set the stage for a detailed investigation into the therapeutic benefits of music for cognitive development.

7. Urban Architecture and Social Interactions

Proposed Methods: Urban Ethnography, Resident Interviews

If urban sociologists were to hypothesize that the design of urban spaces influences social interactions among residents, they could embark on exploratory research through urban ethnography and resident interviews. Initial observations might suggest that open communal spaces foster more community interactions and strengthen neighborhood bonds. These findings could lead to a comprehensive study on designing urban spaces to promote social cohesion.

8. Plant-Based Diets and Athletic Performance

Proposed Methods: Dietary Logs, Performance Metrics Analysis

If sports nutritionists were curious about the impact of plant-based diets on athletes’ performance, they could initiate exploratory research by analyzing athletes’ dietary logs and comparing performance metrics. Preliminary results might indicate that a well-planned plant-based diet could sustain or even enhance athletic prowess. This could trigger further research into the optimal nutrition strategies for athletes favoring plant-based diets.

9. Virtual Reality and Learning Efficiency

Proposed Methods: Experimental Learning Sessions, Feedback Surveys

If educational technologists were to consider the potential of virtual reality (VR) in enhancing learning experiences, they could conduct exploratory research using experimental VR learning sessions followed by feedback surveys. Early feedback might suggest that immersive VR environments can improve understanding and retention of complex topics. This could lead to a broader study on the integration of VR tools in various educational settings.

10. Urban Farming and Food Security

Proposed Methods: Case Studies, Farmer Interviews

If agricultural experts were to contemplate the role of urban farming in ensuring food security in metropolitan areas, they could initiate exploratory research by conducting case studies of existing urban farms and interviewing urban farmers. Preliminary insights might indicate that urban farming can significantly contribute to local food supplies and reduce food transportation costs. This could pave the way for more expansive research on optimizing urban agricultural practices to enhance city-wide food security.

Strengths and Weaknesses of Exploratory Research

Exploratory research design is very useful for providing initial insights into a topic, describing phenomena in detail, and exploring a topic without the predetermined constraints of mere hypothesis testing.

But it’s not the best research design in all situations. For example, it might not be ideal if you were seeking to achieve clarity on well-worn topics, generate generalizable results that add to existing literature, or contribute to a specific set of existing scholarly discourse on a topic.

Below are some strengths and weaknesses of this research design:

Blecher, M. (2018). Israeli Settlements: Land Politics Beyond the Geneva Convention. Hamilton Books.

Cargan, L. (2007). Doing Social Research . Rowman & Littlefield Publishers.

Gozdziak, E. M., & Chantavanich, S. (2022). Africans in Thailand. In Gozdziak, E. M., & Chantavanich, S. (Eds.). African Migration to Thailand: Race, Mobility, and Integration. Taylor & Francis.

Hammond, M., & Wellington, J. J. (2013). Research Methods: The Key Concepts . Routledge.

Hutchison, T., Allen, P., & Macy, A. (2012). Record Label Marketing . Taylor & Francis.

Morrison, A. M. (2022). Tourism Marketing: In the Age of the Consumer . Taylor & Francis.

Swedberg, R. (2020). Exploratory Research. In Elman C, Gerring J, & Mahoney J. (Eds.) The Production of Knowledge: Enhancing Progress in Social Science. Cambridge: Cambridge University Press.

Tan, W. C. K. (2022). Research Methods: A Practical Guide For Students And Researchers (Second Edition). World Scientific Publishing Company.

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 15 Self-Actualization Examples (Maslow's Hierarchy)
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ Forest Schools Philosophy & Curriculum, Explained!
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ Montessori's 4 Planes of Development, Explained!
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ Montessori vs Reggio Emilia vs Steiner-Waldorf vs Froebel

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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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• Exploratory Research | Definition, Guide, & Examples

Exploratory Research | Definition, Guide, & Examples

Published on 6 May 2022 by Tegan George . Revised on 20 January 2023.

Exploratory research is a methodology approach that investigates topics and research questions that have not previously been studied in depth.

Exploratory research is often qualitative in nature. However, a study with a large sample conducted in an exploratory manner can be quantitative as well. It is also often referred to as interpretive research or a grounded theory approach due to its flexible and open-ended nature.

Table of contents

When to use exploratory research, exploratory research questions, exploratory research data collection, step-by-step example of exploratory research, exploratory vs explanatory research, advantages and disadvantages of exploratory research, frequently asked questions about exploratory research.

Exploratory research is often used when the issue you’re studying is new or when the data collection process is challenging for some reason.

You can use this type of research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

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Exploratory research questions are designed to help you understand more about a particular topic of interest. They can help you connect ideas to understand the groundwork of your analysis without adding any preconceived notions or assumptions yet.

Here are some examples:

• What effect does using a digital notebook have on the attention span of primary schoolers?
• What factors influence mental health in undergraduates?
• What outcomes are associated with an authoritative parenting style?
• In what ways does the presence of a non-native accent affect intelligibility?
• How can the use of a grocery delivery service reduce food waste in single-person households?

Collecting information on a previously unexplored topic can be challenging. Exploratory research can help you narrow down your topic and formulate a clear hypothesis , as well as giving you the ‘lay of the land’ on your topic.

Data collection using exploratory research is often divided into primary and secondary research methods, with data analysis following the same model.

Primary research

In primary research, your data is collected directly from primary sources : your participants. There is a variety of ways to collect primary data.

Some examples include:

• Survey methodology: Sending a survey out to the student body asking them if they would eat vegan meals
• Focus groups: Compiling groups of 8–10 students and discussing what they think of vegan options for dining hall food
• Interviews: Interviewing students entering and exiting the dining hall, asking if they would eat vegan meals

Secondary research

In secondary research, your data is collected from preexisting primary research, such as experiments or surveys.

Some other examples include:

• Case studies : Health of an all-vegan diet
• Literature reviews : Preexisting research about students’ eating habits and how they have changed over time
• Online polls, surveys, blog posts, or interviews; social media: Have other universities done something similar?

For some subjects, it’s possible to use large- n government data, such as the decennial census or yearly American Community Survey (ACS) open-source data.

How you proceed with your exploratory research design depends on the research method you choose to collect your data. In most cases, you will follow five steps.

We’ll walk you through the steps using the following example.

Therefore, you would like to focus on improving intelligibility instead of reducing the learner’s accent.

Step 1: Identify your problem

The first step in conducting exploratory research is identifying what the problem is and whether this type of research is the right avenue for you to pursue. Remember that exploratory research is most advantageous when you are investigating a previously unexplored problem.

Step 2: Hypothesise a solution

The next step is to come up with a solution to the problem you’re investigating. Formulate a hypothetical statement to guide your research.

Step 3. Design your methodology

Next, conceptualise your data collection and data analysis methods and write them up in a research design.

Step 4: Collect and analyse data

Next, you proceed with collecting and analysing your data so you can determine whether your preliminary results are in line with your hypothesis.

In most types of research, you should formulate your hypotheses a priori and refrain from changing them due to the increased risk of Type I errors and data integrity issues. However, in exploratory research, you are allowed to change your hypothesis based on your findings, since you are exploring a previously unexplained phenomenon that could have many explanations.

Step 5: Avenues for future research

Decide if you would like to continue studying your topic. If so, it is likely that you will need to change to another type of research. As exploratory research is often qualitative in nature, you may need to conduct quantitative research with a larger sample size to achieve more generalisable results.

It can be easy to confuse exploratory research with explanatory research. To understand the relationship, it can help to remember that exploratory research lays the groundwork for later explanatory research.

Exploratory research investigates research questions that have not been studied in depth. The preliminary results often lay the groundwork for future analysis.

Explanatory research questions tend to start with ‘why’ or ‘how’, and the goal is to explain why or how a previously studied phenomenon takes place.

Like any other research design , exploratory research has its trade-offs: it provides a unique set of benefits but also comes with downsides.

• It can be very helpful in narrowing down a challenging or nebulous problem that has not been previously studied.
• It can serve as a great guide for future research, whether your own or another researcher’s. With new and challenging research problems, adding to the body of research in the early stages can be very fulfilling.
• It is very flexible, cost-effective, and open-ended. You are free to proceed however you think is best.

Disadvantages

• It usually lacks conclusive results, and results can be biased or subjective due to a lack of preexisting knowledge on your topic.
• It’s typically not externally valid and generalisable, and it suffers from many of the challenges of qualitative research .
• Since you are not operating within an existing research paradigm, this type of research can be very labour-intensive.

Exploratory research is a methodology approach that explores research questions that have not previously been studied in depth. It is often used when the issue you’re studying is new, or the data collection process is challenging in some way.

You can use exploratory research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

Exploratory research explores the main aspects of a new or barely researched question.

Explanatory research explains the causes and effects of an already widely researched question.

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

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

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Organizing an Exploratory Essay

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Exploratory essays are very different from argumentative essays. In fact, an exploratory essay is likely different from any other essay you’ve written. Instead of writing to convince an audience of the validity of a thesis, you will be writing to find out about a problem and perhaps to form some preliminary conclusions about how it might be solved.

But there is another aspect the exploratory genre that is equally important. An exploratory essay is, in essence, a retrospective of your writing and thinking process as you work through a problem. It describes when, how, and why you completed certain types of research. This kind of writing is about how you work through problems that require writing and research. You will have to be introspective and think about your thinking process in order for your essay to turn out well.

Very roughly, then, your exploratory essay may follow this sort of structure:

Introduction

The introduction should outline the problem you explored and why it’s important. In addition, you should briefly discuss 1) some of the problem’s possible causes; 2) the institutions and people involved with the problem; 3) some of the possible solutions to the problem. A brief overview of the types of sources you researched during your inquiry.

Body Paragraphs

Body paragraphs should discuss the inquiry process you followed to research your problem. These paragraphs should include the following:

• Introduction of source (title, author, type of media, publisher, publication date, etc.) and why you chose to use it in your exploration
• Important information you found in the source regarding your problem
• Why the information is important and dependable in relation to the problem
• Some personal introspection on how the source helped you, allowed you to think differently about the problem, or even fell short of your expectations and led you in a new direction in your research, which forms a transition into your next source.

The conclusion should restate the problem you explored, outline some of its possible causes, review the institutions and people involved, and highlight some possible solutions. If you still have any questions about the problem (and it’s ok to have some), you will discuss them here. Talk about why you think you still have questions regarding the problem you explored, where you might look to answer these questions, and what other forms of research you would have to do.

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• Published: 11 June 2024

Psychometric assessment of the 10-item Thai version of the Experience in Close Relationship-Revised for Adolescents (ECR-R-10-AD)

• Tinakon Wongpakaran 1 , 2 , 5 ,
• Justin DeMaranville 2 ,
• Nahathai Wongpakaran 1 , 2 &
• Danny Wedding 2 , 3 , 4  

Scientific Reports volume  14 , Article number:  13408 ( 2024 ) Cite this article

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• Health care

The 18-item version of the Experiences in Close Relationships-revised (ECR-R-18) is a valid and reliable scale used among Thai adolescents. However, it revealed problematic items that impacted the scale’s internal consistency. The study aimed to achieve two objectives: (1) develop a new, shorter scale by retaining only highly loaded items equally between attachment anxiety and attachment avoidance, and (2) evaluate the psychometric properties of the shorter ECR-R version compared to the existing 18-item scale. Objective 1 was achieved through Study 1, involving 204 youths aged 16–18 years (64% female). All participants completed the 18-item ECR-R, and exploratory factor analysis was conducted to identify suitable items for the new ECR-R-AD. Objective 2 was fulfilled in Study 2, which included a total of 443 students in grades aged 15–18 years old (88% female) from Thai boarding schools in Northern Thailand. All participants completed both the 18-item ECR-R, and confirmatory factor analysis of both the existing 18-item and the new shorter scale was performed and compared. Additional measures including the Rosenberg Self-Esteem Scale, Perceived Stress Scale-10, and Relationship Questionnaire were completed alongside the ECR-R to assess convergent, discriminant, and criterion validity. The invariance test for the new ECR-R across genders was conducted using multigroup confirmatory factor analysis. For objective 1, Study 1 developed a new scale called "ECR-R-10-AD" with 10 items, comprising 5 for attachment anxiety and 5 for attachment avoidance. The McDonald’s omega values were 0.866 for avoidance and 0.823 for anxiety subscales. The corrected correlation between the ECR-R-18 and ECR-R-10-AD was significant. For objective 2, Study 2 found that the first-order two-factor solution model fit the data best for the ECR-R-10-AD. Convergent, discriminant, and criterion validity with other measurements and invariance tests based on sex were established for the ECR-R-AD. The ECR-R-10-AD provided sufficient psychometric properties among Thai adolescents. Factorial validity, convergent validity, and measurement invariance were established. As the ECR-R-10-AD is brief, it can be administered with less burden. Limitations and future research were discussed.

Introduction

Attachment measurement in adolescents involves assessing the quality and nature of their emotional bonds and relationships with significant others, typically their parents or caregivers. Other attachment measurement tools for adolescents may include interviews, observations, and projective tests, which aim to explore attachment patterns and dynamics in greater depth. These measurements help researchers and clinicians understand how adolescents form and maintain emotional connections, which can have significant implications for their psychological well-being and social development. Understanding attachment patterns in adolescents can also provide valuable insights into how early relationships influence their future adult relationships and overall mental health. Despite its significance, attachment studies among adolescents in Thailand appear to be underexplored. There is a limited number of attachment measurements specifically developed for Thai adolescents.

Several assessments gauge attachment between parents and adolescents. Examples encompass the Inventory of Parent and Peer Attachment 1 , Attachment Q-Sort 2 , Parental Bonding Instrument 3 , Child Attachment Interview 4 , and Adolescent Attachment Questionnaire 5 . Additional details regarding the dimensions of the attachment measured are provided in the Supplementary File 1 .

Brennan and colleagues proposed two dimensions underlying attachment categories, labeled as anxiety and avoidance. These dimensions reflect an individual's level of discomfort and fear of abandonment in close relationships (anxiety) and their tendency to avoid emotional closeness and intimacy with others (avoidance). Later, they produced the Experiences in Close Relationships measure (ECR), a 36-item instrument assessing the two relatively orthogonal constructs of attachment anxiety and avoidance 6 . A revised version of the Experiences in Close Relationships (ECR-R) was subsequently developed by Fraley, Waller, and Brennan to improve the measure’s sensitivity across the range of possible scores 7 . The Thai version of the 36-item ECR-R was initially developed with permission from Fraley 8 . Subsequently, an 18-item version in Thai was later developed 9 .

The ECR-R is used for both adolescents and adults. The questionnaire consists of items that adolescents rate on a scale to indicate the extent to which each statement applies to them. In contrast to adults, where attachment styles are often assessed through relationships with romantic partners, attachment in adolescents is commonly measured within the context of their relationships with parents.

It is widely recognized that the use of questionnaires represents a valuable method for assessing the construct of attachment. Specifically, the anxiety and avoidance subscales have demonstrated a high level of validity in measuring this construct. Attachment-related anxiety refers to an individual's fear of being rejected by others, which is associated with a need for excessive attention and a tendency to exhibit intense stress reactions when a partner is unavailable or indifferent. On the other hand, attachment-related avoidance involves a tendency to reject dependency and interpersonal proximity, accompanied by self-absorption and a reluctance to disclose personal information. Individuals who receive high scores on one or both of these subscales are typically considered to have an insecure attachment style, while those who score low on both anxiety and avoidance subscales are generally regarded as having a secure attachment style 10 .

According to Fraley, simultaneous analysis of the two attachment dimensions in a regression framework enables interpretation of the results according to Bartholomew's four attachment prototypes: secure (low anxiety and avoidance), preoccupied (high anxiety and low avoidance), fearful (high anxiety and avoidance), and dismissing (low anxiety and high avoidance) 23 . The ECR-R has been employed in several research studies to predict psychological problems. One study indicated that change in adolescents' attachment anxiety and avoidance may be an important mechanism of change in adolescents' dysfunctional thinking patterns 11 , whereas another study demonstrated significant associations between childhood trauma exposure and risk of bipolar disorder 12 . A significant correlation between anorexia and insecure attachment measured by the ECR-R was also demonstrated 13 .

To address the challenge of the original ECR-R length, shortened versions were developed, though these were mostly in adult populations in various languages and settings. The number of items ranged from 12 to 18 14 , 15 , 16 , 17 . Our previous research has demonstrated which items of the ECR-R were suitable for inclusion in the abbreviated version for adults, focusing on the context of romantic partnerships 18 . For adolescents, Brenning and colleagues adapted the ECR-R to assess adolescents’ attachment with respect to their relationship with their parents (referred to as the ECR-RC). They argued that creating an attachment measurement from the ECR-R has some advantages. For example, ECR-R explicitly distinguishes between anxiety and avoidance instead of providing an overall assessment of attachment insecurity. It has a clear and interpretable factor structure and scales with strong internal consistency. Finally, it can be used in longitudinal research examining development in attachment from middle childhood to late adolescence and adulthood 19 .

The ECR-RC is a questionnaire that comprises of 36 statements related to the children's mother or father. It uses a scale from 1 (not at all) to 7 (very much) to measure the level of attachment anxiety or avoidance. The adaptation process included simplifying the item wording, removal of double negatives, and adjusting the content to be more relevant for children and their relationship with their parents. The results of the study suggest that the ECR-RC instrument is a promising tool 19 .

Brenning and colleagues then developed a brief, 12-item version of the ECR-RC that had very similar psychometric properties to those of the 36-item version. Specifically, the brief ECR-RC showed high levels of internal consistency, a stable two-factor structure, and virtually identical associations with external variables 20 .

In line with Brenning’s study, the Thai version of adult 18-ECR-R has been used in both clinical and nonclinical samples, with ages ranging from 18 to 95 years to predict psychological problems such as loneliness, anxiety, depression, and suicidality 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 . Recently, the adolescent version of the 18-item ECR-R has been developed based on the adult version 30 .

In some cases, using a more concise version of the 18-item Thai version of the ECR-R questionnaire may be beneficial without sacrificing its construct validity. A prior study found certain items in the original questionnaire to be problematic, negatively impacting the scale's reliability and overall validity 9 . Based on this, researchers recommend removing these items and adopting a shorter questionnaire version. Furthermore, many surveys in large community-based, school, or primary healthcare settings favor abbreviated versions of the ECR-R, given that attachment is often a central focus alongside mediators and outcomes 11 , 13 , 31 . Therefore, the length of the ECR-R questionnaire can pose difficulties for adolescents who have to fill out multiple questionnaires, especially if the ECR-R is lengthy.

In addition to the benefits of having a succinct and validated version of the ECR-R customized for adolescents, it's imperative to acknowledge the profound impact of cultural differences on respondents' interpretations of specific items 32 , 33 , 34 , 35 , particularly noticeable in Asian cultures, where individuals tend to exhibit attachment anxiety 27 , 35 , 36 . Notably, there is a research gap in the lack of any ECR-R specifically crafted for adolescents within an Asian cultural context.

To fill this gap, this study aims to derive a condensed scale version with robust internal consistency and predictive capability. This research was conducted by two studies; study 1, exploratory factor analysis was conducted on the 18-item ECR-R to find the most appropriate items for the short ECR-R (Sample 1, N = 204). Subsequently, in Sample 2 (N = 423), reliability analyses and Confirmatory Factor Analyses (CFA) were conducted to assess the psychometric properties of both the ECR-R-18 and the newly shorter ECR-R. Additionally, construct and criterion validity were evaluated for the new scale. The relationships between the shorter and existing ECR-R-18 versions were analyzed, and convergent validity of the both versions of the ECR-R and other relevant measurements were conducted.

Materials and methods

This study was a cross-sectional online survey involving two studies.

Sample size calculation

Comrey suggested a minimum sample size of 200 for factor analysis 37 . However, considering Mundform’s suggestion, the level of communality, and the variables per factor, the calculated minimum sample size was 70, based on 2 factors and 9 variables per factor 38 . This study analyzed two samples of 204 and 443 participants, ensuring sufficient statistical power.

Participants

To reduce the length of the ECR-R-18 questionnaire, a study was conducted which included 204 high school students aged 15–17. The participants had a mean age of 16.05 years with a standard deviation of 0.97. Additionally, 64% of the participants were female. All of the participants completed the 18-item ECR-R questionnaire. The aim of the study 1 was to evaluate the efficacy of shortening the questionnaire without compromising its validity and reliability.

In the second study, we enrolled a total of 443 high school students from Thai boarding schools in Northern Thailand for the confirmatory factor analysis test of the shortened version of ECR-R. Given COVID-19, convenient sampling was deemed appropriate and employed for this study. Students were invited to participate and provided consent before completing the questionnaire via Google Forms. The data were gathered through digitally administered questionnaires via the Internet or computer software. Participants responded to questions using electronic devices such as computers, tablets, or smartphones.

Prior to participation, we obtained informed consent from all students, However, in the case of a few students (5 out of 423), they mentioned that their parents were unavailable and requested the school director to sign the document on their behalf. While it can be confirmed that permission was obtained from all parents, it's important to note that only five parents communicated their consent verbally and requested the school director to handle the documentation process on their behalf. The study received ethical approval from the ethics committee at the Faculty of Medicine, Chiang Mai University.

Measurements

Adaptation of ecr-r-18 for adolescents.

In line with Brenning’s ECR-RC, in this adolescent version, the word “romantic partner” was replaced by “parents.” Instead of using a separate question for mother or father, the authors used the word “parents” for the respondent to make an overall impression on how he/she feels towards both parents rather than to father or mother specifically.

The following measurements were used along with the ECR-R in each study.

Rosenberg Self-Esteem Scale (RSES) , a 4-point Likert scale that measures participant’s self-reported self-esteem 39 . Each item is scored on a scale ranging from strongly agree to strongly disagree, with response options usually assigned numerical values (e.g., strongly agree = 4, agree = 3, disagree = 2, strongly disagree = 1). Higher scores indicate higher levels of self-esteem. The Thai RSES has good internal consistency and good construct and discriminant validity 40 . In this study, Cronbach’s alpha for the RSES was 0.82.

Perceived Stress Scale-10 (PSS-10) , an instrument that measures the degree to which life events are perceived as being stressful 41 . This is a 5-point Likert scale instrument. Each item on the PSS-10 is scored on a 5-point Likert scale, ranging from 0 (Never) to 4 (Very Often). Higher scores indicate higher levels of self-esteem. The Thai PSS-10 has good internal consistency and good construct and discriminant validity 42 . In this study, Cronbach’s alpha for the PSS-10 was 0.85.

Relationship Questionnaire (RQ) , The RQ was developed by Bartholomew and Horowitz (1991) and consists of four distinct categories of attachment styles: secure, fearful, preoccupied, and dismissing 43 . Unlike other measures, the RQ is a single-item measure that utilizes four short paragraphs. Each paragraph describes a typical attachment pattern as it pertains to close relationships in adulthood. The RQ questionnaire is divided into two parts: RQ1 and RQ2. In RQ1, participants are asked to select the paragraph that best describes them without providing a numerical rating. For example, one of the statements for secure attachment might read as follows: "It is easy for me to become emotionally close to others." In RQ2, participants are then asked to rate their agreement with each attachment prototype on a 7-point scale. The rating provided for the attachment prototype with the highest score is used to classify participants into their corresponding attachment categories. RQ provides insights into two dimensions: the model of the self and the model of the other. By employing the RQ, researchers can comprehensively understand individuals' attachment styles and perceptions of themselves and others within close relationships. RQ is a valid self-reported measurement as long as an agreement between RQ1 and RQ2 is established 23 .

Statistical analyses

Descriptive statistics were used to screen the data, ensuring that all items exhibited skewness and kurtosis values within the range of ± 2, as recommended by Nunnally and Bernstein 44 . Missing values were handled by replacing them with the mean of the respective item series.

In study 1, an exploratory factor with oblique rotation methods was conducted. Parallel analysis was performed to ascertain the number of factors by comparing the eigenvalues obtained from the actual data with those obtained from randomly generated data. This process aids in determining the number of factors to retain in factor analysis, considering only those factors with eigenvalues greater than the corresponding eigenvalues from the random data. Items for the new brief scale were chosen based on their factor loading levels (> 0.4). We ran a parallel analysis and scree plot in JASP 0.18.3 (2024).

In study 2, confirmatory factor analysis was conducted in both the original 18-item and short versions based on study 1. Model fit was evaluated using various indices, including the Comparative Fit Index (CFI) ≥ 0.95, Tucker-Lewis Index (TLI) ≥ 0.9, root-mean-square error of approximation (RMSEA) ≤ 0.6, and standardized root-mean-square residual (SRMR) ≤ 0.08, following the guidelines of Hu and Bentler 45 . Convergent and discriminant validity were determined by calculating Pearson's correlation coefficients between the ECR-R and other measures. To account for spurious correlations when evaluating the short-form, the corrected correlation coefficients obtained through Levy's method were used to calculate the correlation coefficients between the ECR-R-18 and the short ECR-R 46 . Internal consistency reliability was evaluated using McDonald's omega coefficient, with a reliability value greater than 0.70 considered acceptable.

Criterion validity was assessed by examining the regression model's predictive coefficients (B) of anxiety and avoidance for each attachment style. Following the theoretical model and a recommendation by Fraley, the expected B values for each attachment style are as follows: Secure Attachment: The B values for anxiety and avoidance should be negative (-B) and negative (-B), respectively. Fearful Attachment: The B values for anxiety and avoidance should both be positive (+ B). Preoccupied Attachment: The B value for anxiety should be positive (+ B), while the B value for avoidance should be zero (0B). Dismissing Attachment: The B value for anxiety should be zero (0B), while the B value for avoidance should be positive (+ B). These analyses were conducted using IBM SPSS version 22 and AMOS package version 22.

Multigroup confirmatory factor analysis was performed separately for males and females to examine the invariance of the new ECR-R. Measurement invariance analyses were conducted based on the criteria proposed by Byrne 47 , with CFI and TLI ≥ 0.90, and RMSEA ≤ 0.1 48 . Regarding the Measurement Invariance (MI), the original data consisted of 390 females and 53 males, with a ratio of 7.4:1. To address the extreme imbalance, we created a new dataset comprising 159 participants, with a ratio of 2:1 (106 females and 53 males), achieved through case-matching based on age. While the sample size remains modest, alternative model fit statistics, such as the Comparative Fit Index (CFI), can be utilized as they are less influenced by sample size. The results were comparable to the original results using the whole sample (n = 443) analysis.

Goodness-of-fit statistics were estimated for each model and compared to the less restricted model. Following the recommendations outlined by Byrne, three models were tested. These models progressively constrained the number of items and factors (configural invariance), factor loadings (metric invariance), and thresholds (scalar invariance) to be equal across groups. Maximum Likelihood Robust (MLR) estimator was used for multigroup confirmatory factor analysis. The differences between the adjustments of the most restricted and least restricted models were evaluated using Δχ2 (difference in chi-square value), ΔCFI, ΔTLI and ΔRMSEA. The values greater than 0.01 for ΔCFI and ΔTLI, and values larger than 0.015 for ΔRMSEA indicated a significant decline in fit 48 , 49 . Mplus 8.10 version was used to perform these analyses.

Ethics approval and consent to participate

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of the Faculty of Medicine, Chiang Mai University (EC: PSY-2564-08146, approved date 10 June 2021).

Study 1: Determining the suitable number of items for the new ECR-R

The exploratory factor analysis of the 18-item Thai ECR-R revealed that within the anxiety dimension, nine items exhibited factor loadings ranging from 0.462 to 0.755, while the avoidance dimension featured five items with factor loadings ranging from 0.333 to 0.856. The scree plot also suggested a two-factor solution model. In the parallel analysis, the first three eigenvalues from the raw data of the ECR-R-18 were 5.718, 2.589, and 1.163. Correspondingly, the first three 95th-percentile random-data eigenvalues were 1.361, 1.284, and 1.231, suggesting that two factors were the most suitable structure for the ECR-R-18 (refer to Supplementary Files 2 ). Considering loadings above 0.4, the avoidance dimension yielded five items with loadings ranging from 0.622 to 0.856. To ensure an even distribution within each dimension 50 , we selected five items for the anxiety dimension, with factor loadings ranging between 0.638 and 0.755. Consequently, there were five items for each dimension, totaling 10 items for the scale. This modified version of the ECR-R is denoted as ECR-R-10-AD henceforth (see Supplementary File 3 ).

Study 2: Validity and reliability of the ECR-R-10-AD

The characteristics of the respondents were as follows, 88% female, mean age 16.35 [SD 0.96]). The number of participants in each grade level were almost equal. The family income was almost equal between the two groups. Most of the participants were taken care of by their parents (Table 1 ).

Table 2 shows the mean and standard deviation of the perceived stress and Rosenberg self-esteem scores. The sample showed a low level of perceived stress, whereas a high level of self-esteem. Most participants reported having a secure attachment, and the type of insecurity was preoccupied.

Factor loading coefficients of each item and the correlation between latent scores of anxiety and avoidance subscale scores are presented in Table 3 . The factor loading coefficients ranged from 0.631 to 0.797 for anxiety and 0.574 to 0.906 for avoidance. The data fit the first-order two-factor solution model well, as indicated by χ 2 (df) = 94.380 (34), p < 0.001, CFI = 0.968, TLI = 0.957, RMSEA = 0.063 (0.048–0.079), and SRMR = 0.046.

Table 4 presents the mean and standard deviation of the ECR-R. A strong correlation between the long and short scales was observed, with Levy’s corrected correlation coefficients ranging from 0.757 to 0.777 for the avoidance and anxiety subscales, respectively. No significant differences were found in the correlation coefficients and corrected correlation coefficients between ECR-R-18 and ECR-R-10. Regarding McDonald’s Omega, the value for ECR-R avoidance was 0.778. However, this value increased to 0.838 when item #1 (I prefer not to show my parents how I feel deep down) was removed.

Table 5 displays the correlation coefficients between other measurements and both the ECR-R-18 and ECR-R-10-AD. Discrepancies were identified in the correlation coefficients between the avoidance and anxiety subscales of ECR-R-18 and ECR-R-10-AD, as well as the RSES and PSS. However, no significant differences were observed in the correlation coefficients between ECR-R-18, RSES, and PSS, or between ECR-R-10-AD, RSES, and PSS (statistical results not displayed).

Table 6 compares the unstandardized coefficients for anxiety and avoidance scores in predicting attachment styles. The ECR-R-10-AD demonstrates anticipated coefficients (B) compared to the ECR-R-18. For instance, in secure attachment, the coefficients were − 0.043 (p < 0.001) and − 0.183 (p = 0.090) for ECR-R-18, while for ECR-R-10-AD, they were − 0.255 (p < 0.001) and − 0.230 (p = 0.003), suggesting a theoretically sounder representation by ECR-R-10-AD. Unlike ECR-R-18, which could only confirm two types (i.e., Fearful and Preoccupied), ECR-R-10-AD provided relevant coefficients based on the respective attachment style as per the research question (RQ).

Table 7 presents the fit measures of the multi-group models used to test measurement invariance across sexes. No significant differences in Δχ2 were observed between metric and configural, between scalar and metric, and between configural and scalar models (all p > 0.05). The data supported the scalar invariance model. In addition, the ΔCFI, ΔTLI, and ΔRMSEA were below the cutoff values suggesting that the measurement invariance between male and female was established.

The abbreviated Thai version of the ECR-R-10-AD has shown significant improvement in its psychometric properties after excluding a poorly fitting item. The new version has surpassed the previous ECR-R-18 version and has the potential for wider application in relevant research and clinical settings.

The adolescent data have confirmed factorial validity by excellently fitting the two-factor solution model. Convergent validity with other measurements was established. In addition, the ECR-R-10-AD held better criterion validity against the relationship questionnaire than the ECR-R-10. Both versions demonstrated good internal consistency. Therefore, the ECR-R-10-AD is favorable because it has fewer items.

Consistent with other related studies, the ECR-R-10-AD demonstrated measure invariance across sexes, suggesting that the tool is measuring the same construct in a similar manner for both males and females 51 , 52 . The measurement's validity and reliability are not significantly influenced by gender differences, meaning that the scale's items are equally meaningful and relevant for both sexes. Any observed differences in the scores between sexes are not due to measurement bias or inconsistencies but rather reflect genuine differences in the construct being measured.

In line with the 12-item ECR-RC, the ECR-R-10-AD demonstrated relatively superior psychometric properties than the 18-ECR-R 20 , 53 . When comparing the items selected for the ECR-R-10-AD and the 12-item ECR-RC by Brenning and colleagues, it shows that 70% of the items of the ECR-R-10-AD were included in ECR-RC. However, the invalid item #1, “I prefer not to show my parents how I feel deep down,” of the ECR-R-10-AD, is found to be valid for the ECR-RC ( as well as the other short ECR-R) 54 . It is difficult to conclude whether the adolescent version of ECR-R is influenced by culture. The ECR-R-10-AD is developed from the ECR-R-18 tested in a young adult population, not from the 36-item ECR-R as in Brenning’s study. Despite that, over 70% are overlapping. Based on the previous study of cross-cultural attachment 35 , it might be possible that these two versions of the ECR-R-10-AD and the ECR-RC might be suitable for participants from different cultures (e.g., European and Asian).

Compared to the recent ECR-R-10 designed for adults 18 , it has been observed that they feature distinct sets of items. While all five items in the anxiety subscale remain consistent, there are differences in the avoidance subscale between adults and adolescents. In the adolescent version (ECR-R-10-AD), the items "I find it relatively easy to get close to my parents." and "I talk things over with my parents." are included, whereas these items are absent in the adult version (ECR-R-10). Instead, the adult version features items like "I find it easy to depend on romantic partners." and "It helps to turn to my romantic partner in times of need." These findings underscore the necessity for developing separate scales for these age groups, as the target relationships vary significantly.

Clinical implications

Given its robust psychometric properties, the 10-item version is a viable and recommended alternative to the 18-item questionnaire. It can be used in adolescent attachment research.

Limitations and future research

Despite the merits of brevity and wide use, the ECR-R-10-AD has some limitations. The sample used for analysis might not represent general adolescents because they were from boarding schools. As the sample size used for Measurement Invariance (MI) was small, there is a possibility of bias in the results. Therefore, interpretation should be approached with caution. Secondly, test–retest reliability has not been examined in all studies, and further investigation of this tool’s stability should be conducted. Finally, the fact that the adolescents’ attachment to their father or mother may be different, further investigation should be explored for different effects. Nonetheless, the current ECR-R-10-AD seems to be a promising brief instrument for measuring anxious and avoidant attachment representations in children and adolescents.

The ECR-R-10-AD provided sufficient psychometric properties among adolescents. Factorial validity, convergent validity and measurement invariance were established. As the ECR-R-10-AD is brief, it can be administered with less burden. However, test–retest reliability and measurement invariance test should be further investigated and confirmed.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Abbreviations

• Confirmatory factor analysis

Comparative Fit Index

Experience in Close Relationship-Revised

Perceived stress scale

Root Mean Square Error of Approximation

Relationship Questionnaire

Rosenberg Self-Esteem Scale

Standardized root-mean-square residual

Tucker–Lewis Index

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All authors (N.W., T.W., J.D., D.W.) contributed to this study’s conceptualization, methodology, formal analysis, and investigation. Nahathai Wongpakaran and Tinakon Wongpakaran wrote the original draft, which was reviewed and edited by all authors. Danny Wedding and Nahathai Wongpakaran provided resources and supervision.

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Wongpakaran, T., DeMaranville, J., Wongpakaran, N. et al. Psychometric assessment of the 10-item Thai version of the Experience in Close Relationship-Revised for Adolescents (ECR-R-10-AD). Sci Rep 14 , 13408 (2024). https://doi.org/10.1038/s41598-024-64437-2

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