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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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Methodology

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.

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.

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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.

Cite this Scribbr article

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George, T. (2023, November 20). Exploratory Research | Definition, Guide, & Examples. Scribbr. Retrieved September 16, 2024, from https://www.scribbr.com/methodology/exploratory-research/

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Tegan George

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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.

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Methodology
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.

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.

Prevent plagiarism, run a free check.

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

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.

Step 5: Avenues for future 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.

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.

Cite this Scribbr article

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

George, T. (2023, January 20). Exploratory Research | Definition, Guide, & Examples. Scribbr. Retrieved 16 September 2024, from https://www.scribbr.co.uk/research-methods/exploratory-research-design/

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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

Open access
Published: 28 May 2018

Exploratory studies to decide whether and how to proceed with full-scale evaluations of public health interventions: a systematic review of guidance

Britt Hallingberg ORCID: orcid.org/0000-0001-8016-5793 1 ,
Ruth Turley 1 , 4 ,
Jeremy Segrott 1 , 2 ,
Daniel Wight 3 ,
Peter Craig 3 ,
Laurence Moore 3 ,
Simon Murphy 1 ,
Michael Robling 1 , 2 ,
Sharon Anne Simpson 3 &
Graham Moore 1

Pilot and Feasibility Studies volume 4 , Article number: 104 ( 2018 ) Cite this article

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Evaluations of complex interventions in public health are frequently undermined by problems that can be identified before the effectiveness study stage. Exploratory studies, often termed pilot and feasibility studies, are a key step in assessing the feasibility and value of progressing to an effectiveness study. Such studies can provide vital information to support more robust evaluations, thereby reducing costs and minimising potential harms of the intervention. This systematic review forms the first phase of a wider project to address the need for stand-alone guidance for public health researchers on designing and conducting exploratory studies. The review objectives were to identify and examine existing recommendations concerning when such studies should be undertaken, questions they should answer, suitable methods, criteria for deciding whether to progress to an effectiveness study and appropriate reporting.

We searched for published and unpublished guidance reported between January 2000 and November 2016 via bibliographic databases, websites, citation tracking and expert recommendations. Included papers were thematically synthesized.

The search retrieved 4095 unique records. Thirty papers were included, representing 25 unique sources of guidance/recommendations. Eight themes were identified: pre-requisites for conducting an exploratory study, nomenclature, guidance for intervention assessment, guidance surrounding any future evaluation study design, flexible versus fixed design, progression criteria to a future evaluation study, stakeholder involvement and reporting of exploratory studies. Exploratory studies were described as being concerned with the intervention content, the future evaluation design or both. However, the nomenclature and endorsed methods underpinning these aims were inconsistent across papers. There was little guidance on what should precede or follow an exploratory study and decision-making surrounding this.

Conclusions

Existing recommendations are inconsistent concerning the aims, designs and conduct of exploratory studies, and guidance is lacking on the evidence needed to inform when to proceed to an effectiveness study.

Trial registration

PROSPERO 2016, CRD42016047843

Peer Review reports

Improving public health and disrupting complex problems such as smoking, obesity and mental health requires complex, often multilevel, interventions. Such interventions are often costly and may cause unanticipated harms and therefore require evaluation using the most robust methods available. However, pressure to identify effective interventions can lead to premature commissioning of large effectiveness studies of poorly developed interventions, wasting finite research resources [ 1 , 2 , 3 ]. In the development of pharmaceutical drugs over 80% fail to reach ‘Phase III’ effectiveness trials, even after considerable investment [ 4 ]. With public health interventions, the historical tendency to rush to full evaluation has in some cases led to evaluation failures due to issues which could have been identified at an earlier stage, such as difficulties recruiting sufficient participants [ 5 ]. There is growing consensus that improving the effectiveness of public health interventions relies on attention to their design and feasibility [ 3 , 6 ]. However, what constitutes good practice when deciding when a full evaluation is warranted, what uncertainties should be addressed to inform this decision and how, is unclear. This systematic review aims to synthesize existing sources of guidance for ‘exploratory studies’ which we broadly define as studies intended to generate evidence needed to decide whether and how to proceed with a full-scale effectiveness study. They do this by optimising or assessing the feasibility of the intervention and/or evaluation design that the effectiveness study would use. Hence, our definition includes studies variously referred to throughout the literature as ‘pilot studies’, ‘feasibility studies’ or ‘exploratory trials’. Our definition is consistent with previous work conducted by Eldridge et al. [ 7 , 8 ], who define feasibility as an overarching concept [ 8 ] which assesses; ‘… whether the future trial can be done, should be done, and, if so, how’ (p. 2) [ 7 ]. However, our definition also includes exploratory studies to inform non-randomised evaluations, rather than a sole focus on trials.

The importance of thoroughly establishing the feasibility of intervention and evaluation plans prior to embarking on an expensive, fully powered evaluation was indicated in the Medical Research Council’s (MRC) framework for the development and evaluation of complex interventions to improve health [ 9 , 10 ]. This has triggered shifts in the practice of researchers and funders toward seeking and granting funding for an ever growing number of studies to address feasibility issues. Such studies are however in themselves often expensive [ 11 , 12 ]. While there is a compelling case for such studies, the extent to which this substantial investment in exploratory studies has to date improved the effectiveness and cost-effectiveness of evidence production remains to be firmly established. Where exploratory studies are conducted poorly, this investment may simply lead to expenditure of large amounts of additional public money, and several years’ delay in getting evidence into the hands of decision-makers, without necessarily increasing the likelihood that a future evaluation will provide useful evidence.

The 2000 MRC guidance used the term ‘exploratory trial’ for work conducted prior to a ‘definitive trial’, indicating that it should primarily address issues concerning the optimisation, acceptability and delivery of the intervention [ 13 ]. This included adaptation of the intervention, consideration of variants of the intervention, testing and refinement of delivery method or content, assessment of learning curves and implementation strategies and determining the counterfactual. Other possible purposes of exploratory trials included preliminary assessment of effect size in order to calculate the sample size for the main trial and other trial design parameters, including methods of recruitment, randomisation and follow-up. Updated MRC guidance in 2008 moved away from the sole focus on RCTs (randomised controlled trials) of its predecessor reflecting recognition that not all interventions can be tested using an RCT and that the next most robust methods may sometimes be the best available option [ 10 , 14 ]. Guidance for exploratory studies prior to a full evaluation have, however, often been framed as relevant only where the main evaluation is to be an RCT [ 13 , 15 ].

However, the goals of exploratory studies advocated by research funders have to date varied substantially. For instance, the National Institute for Health Research Evaluation Trials and Studies Coordinating Centre (NETSCC) definitions of feasibility and pilot studies do not include examination of intervention design, delivery or acceptability and do not suggest that modifications to the intervention prior to full-scale evaluation will arise from these phases. However, the NIHR (National Institute of Health Research) portfolio of funded studies indicates various uses of terms such as ‘feasibility trial’, ‘pilot trial’ and ‘exploratory trial’ to describe studies with similar aims, while it is rare for such studies not to include a focus on intervention parameters [ 16 , 17 , 18 ]. Within the research literature, there is considerable divergence over what exploratory studies should be called, what they should achieve, what they should entail, whether and how they should determine progression to future studies and how they should be reported [ 7 , 8 , 19 , 20 , 21 ].

This paper presents a systematic review of the existing recommendations and guidance on exploratory studies relevant to public health, conducted as the first stage of a project to develop new MRC guidance on exploratory studies. This review aims to produce a synthesis of current guidance/recommendations in relation to the definition, purpose and content of exploratory studies, and what is seen as ‘good’ and ‘bad’ practice as presented by the authors. It will provide an overview of key gaps and areas in which there is inconsistency within and between documents. The rationale for guidance and recommendations are presented, as well as the theoretical perspectives informing them. In particular, we examine how far the existing recommendations answer the following questions:

When is it appropriate to conduct an exploratory study?

What questions should such studies address?

What are the key methodological considerations in answering these questions?

What criteria should inform a decision on whether to progress to an effectiveness study?

How should exploratory studies be reported?

This review is reported in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement [ 22 ] as evidenced in the PRISMA checklist (see Additional file 1 : Table S1). The review protocol is registered on PROSPERO (registration number: CRD42016047843; www.crd.york.ac.uk/prospero ).

Literature search

A comprehensive search (see Additional file 2 : Appendix) was designed and completed during August to November 2016 to identify published and grey literature reported between January 2000 and November 2016 that contained guidance and recommendations on exploratory studies that could have potential relevance to public health. Bibliographic databases were CINAHL, Embase, MEDLINE, MEDLINE-In-process, PsycINFO, Web of Science and PubMed. Supplementary searches included key websites (see Additional file 2 : Appendix) and forward and backward citation tracking of included papers, as well as contacting experts in the field. The first MRC guidance on developing and evaluating complex interventions in health was published in 2000; we therefore excluded guidance published before this year.

Selection of included papers

Search results were exported into reference management software Endnote and clearly irrelevant or duplicate records removed by an information specialist. Eligibility criteria were applied to abstracts and potentially relevant full-text papers by two reviewers working independently in duplicate (BH, JS). Discrepancies were agreed by consensus or by a third reviewer if necessary. Full criteria are shown in Table 1 . During screening of eligible studies, it became evident that determining whether or not guidance was applicable to public health was not always clear. The criteria in Table 1 were agreed by the team after a list of potentially eligible publications were identified.

Quality assessment of included papers

Given the nature of publications included (expert guidance or methodological discussion papers) quality assessment was not applicable.

Data extraction and thematic synthesis

A thematic synthesis of guidance within included documents was performed [ 23 ]. This involved the use of an a priori coding framework (based on the projects aims and objectives), developed by RT, JS and DW ([ 24 ], see Additional file 2 : Appendix). Data were extracted using this schema in qualitative analytic software NVivo by one reviewer (BH). A 10% sample of coded papers was checked by a second reviewer (JS). Data were then conceptualised into final themes by agreement (BH, JS, DW, RT).

Review statistics

Four thousand ninety-five unique records were identified of which 93 were reviewed in full text (see Fig. 1 ). In total, 30 documents were included in the systematic review representing 25 unique sets of guidance. Most sources of guidance did not explicitly identify an intended audience and guidance varied in its relevance to public health. Table 2 presents an overview of all sources of guidance included in the review with sources of guidance more or less relevant to public health identified as well as those which specifically applied to exploratory studies with a randomised design.

Flow diagram

Findings from guidance

The included guidance reported a wide range of recommendations on the process of conducting and reporting exploratory studies. We categorised these into eight themes that capture: pre-requisites for conducting an exploratory study, nomenclature, guidance for intervention assessment, guidance surrounding the future evaluation study design, adaptive vs rigid designs, progression criteria for exploratory studies, stakeholder involvement and reporting.

Narrative description of themes

Theme 1: pre-requisites for conducting an exploratory study.

Where mentioned, pre-requisite activities included determining the evidence base, establishing the theoretical basis for the intervention, identifying the intervention components as well as modelling of the intervention in order to understand how intervention components interact and impact on final outcomes [ 9 , 25 , 26 , 27 ]. These were often discussed within the context of the MRC’s intervention development-evaluation cycle [ 6 , 9 , 10 , 13 , 25 , 26 , 27 , 28 ]. Understanding how intervention components interact with various contextual settings [ 6 , 27 , 29 ] and identifying unintended harms [ 6 , 29 ] as well as potential implementation issues [ 6 , 9 , 10 , 30 ] were also highlighted. There was an absence of detail in judging when these above conditions were met sufficiently for moving onto an exploratory study.

Theme 2: nomenclature

A wide range of terms were used, sometimes interchangeably, to describe exploratory studies with the most common being pilot trial/study. Table 3 shows the frequency of the terms used in guidance including other terms endorsed.

Different terminology did not appear to be consistently associated with specific study purposes (see theme 3), as illustrated in Table 2 . ‘Pilot’ and ‘feasibility’ studies were sometimes used interchangeably [ 10 , 20 , 25 , 26 , 27 , 28 , 31 ] while others made distinctions between the two according to design features or particular aims [ 7 , 8 , 19 , 29 , 32 , 33 , 34 ]. For example, some described pilot studies as a smaller version of a future RCT to run in miniature [ 7 , 8 , 19 , 29 , 32 , 33 , 34 ] and was sometimes associated with a randomised design [ 32 , 34 ], but not always [ 7 , 8 ]. In contrast, feasibility studies were used as an umbrella term by Eldridge et al. with pilot studies representing a subset of feasibility studies [ 7 , 8 ]: ‘We suggest that researchers view feasibility as an overarching concept, with all studies done in preparation for a main study open to being called feasibility studies, and with pilot studies as a subset of feasibility studies.’ (p. 18) [ 8 ].

Feasibility studies could focus on particular intervention and trial design elements [ 29 , 32 ] which may not include randomisation [ 32 , 34 ]. Internal pilot studies were primarily viewed as part of the full trial [ 8 , 32 , 35 , 36 , 37 , 38 ] and are therefore not depicted under nomenclature in Table 3 .

While no sources explicitly stated that an exploratory study should focus on one area and not the other, aims and associated methods of exploratory studies diverged into two separate themes. They pertained to either examining the intervention itself or the future evaluation design, and are detailed below in themes 3 and 4.

Theme 3: guidance for intervention assessment

Sources of guidance endorsed exploratory studies having formative purposes (i.e. refining the intervention and addressing uncertainties related to intervention implementation [ 13 , 15 , 29 , 31 , 39 ]) as well as summative goals (i.e. assessing the potential impact of an intervention or its promise [ 6 , 13 , 39 ]).

Refining the intervention and underlying theory

Some guidance suggested that changes could be made within exploratory studies to refine the intervention and underlying theory [ 15 , 29 , 31 ] and adapt intervention content to a new setting [ 39 ]. However, guidance was not clear on what constituted minor vs. major changes and implications for progression criteria (see theme 6). When making changes to the intervention or underlying theory, some guidance recommended this take place during the course of the exploratory study (see theme 5). Others highlighted the role of using a multi-arm design to select the contents of the intervention before a full evaluation [ 13 ] and to assess potential mechanisms of multiple different interventions or intervention components [ 29 ]. Several sources highlighted the role of qualitative research in optimising or refining an intervention, particularly for understanding the components of the logic model [ 29 ] and surfacing hidden aspects of the intervention important for delivering outcomes [ 15 ].

Intervention implementation

There was agreement across a wide range of guidance that exploratory studies could explore key uncertainties related to intervention implementation, such as acceptability, feasibility or practicality. Notably these terms were often ill-defined and used interchangeably. Acceptability was considered in terms of recipients’ reactions [ 7 , 8 , 29 , 32 , 39 ] while others were also attentive to feasibility from the perspective of intervention providers, deliverers and health professionals [ 6 , 9 , 29 , 30 , 34 , 39 ]. Implementation, feasibility, fidelity and ‘practicality’ explored the likelihood of being able to deliver in practice what was intended [ 25 , 26 , 27 , 30 , 39 ]. These were sometimes referred to as aims within an embedded process evaluation that took place alongside an exploratory study, although the term process evaluation was never defined [ 7 , 10 , 15 , 29 , 40 ].

Qualitative research was encouraged for assessment of intervention acceptability [ 21 ] or for implementation (e.g. via non-participant observation [ 15 ]). Caution was recommended with regards to focus groups where there is a risk of masking divergent views [ 15 ]. Others recommended quantitative surveys to examine retention rates and reasons for dropout [ 7 , 30 ]. Furthermore, several sources emphasised the importance of testing implementation in a range of contexts [ 15 , 29 , 39 , 41 ]—especially in less socioeconomically advantaged groups, to examine the risk of widening health inequalities [ 29 , 39 ].

One source of guidance considered whether randomisation was required for assessing intervention acceptability, believing this to be unnecessary but also suggesting it could ‘potentially depend on preference among interventions offered in the main trial’ ([ 21 ]; p. 9). Thus, issues of intervention acceptability, particularly within multi-arm trials, may relate to clinical equipoise and acceptability of randomisation procedures among participants [ 30 ].

Appropriateness of assessing intervention impact

Several sources of guidance discussed the need to understand the impact of the intervention, including harms, benefits or unintended consequences [ 6 , 7 , 15 , 29 , 39 ]. Much of the guidance focused on statistical tests of effectiveness with disagreement on the soundness of this aim, although qualitative methods were also recommended [ 15 , 42 ]. Some condemned statistically testing for effectiveness [ 7 , 20 , 29 , 32 , 41 ], as such studies are often underpowered, hence leading to imprecise and potentially misleading estimates of effect sizes [ 7 , 20 ]. Others argued that an estimate of likely effect size could evidence the intervention was working as intended and not having serious unintended harms [ 6 ] and thus be used to calculate the power for the full trial [ 13 ]. Later guidance from the MRC is more ambiguous than earlier guidance, stating that estimates should be interpreted with caution, while simultaneously stating ‘safe’ assumptions of effect sizes as a pre-requisite before continuing to a full evaluation [ 10 ]. NIHR guidance, which distinguished between pilot and feasibility studies, supported the assessment of a primary outcome in pilot studies, although it is unclear whether this is suggesting that a pilot should involve an initial test of changes in the primary outcome, or simply that the primary outcome should be measured in the same way as it would be in a full evaluation. By contrast, for ‘feasibility studies’, it indicated that an aim may include designing an outcome measure to be used in a full evaluation.

Others made the case for identifying evidence of potential effectiveness, including use of interim or surrogate endpoints [ 7 , 41 ], defined as ‘…variables on the causal pathway of what might eventually be the primary outcome in the future definitive RCT, or outcomes at early time points, in order to assess the potential for the intervention to affect likely outcomes in the future definitive RCT…’ [ 7 ] (p. 14).

Randomisation was implied as a design feature of exploratory studies when estimating an effect size estimate of the intervention as it maximised the likelihood that observed differences are due to intervention [ 9 , 39 ], with guidance mostly written from a starting assumption that full evaluation will take the form of an RCT and guidance focused less on exploratory studies for quasi-experimental or other designs. For studies that aim to assess potential effectiveness using a surrogate or interim outcome, using a standard sample size calculation was recommended to ensure adequate power, although it was noted that this aim is rare in exploratory studies [ 7 ].

Theme 4: guidance surrounding the future evaluation design

Sources consistently advocated assessing the feasibility of study procedures or estimating parameters of the future evaluation. Recommendations are detailed below.

Assessing feasibility of the future evaluation design

Assessing feasibility of future evaluation procedures was commonly recommended [ 6 , 7 , 10 , 15 , 30 , 32 , 33 , 34 , 37 , 41 ] to avert problems that could undermine the conduct or acceptability of future evaluation [ 6 , 15 , 30 ]. A wide range of procedures were suggested as requiring assessments of feasibility including data collection [ 20 , 30 , 34 , 36 , 41 ], participant retention strategies [ 13 ], randomisation [ 7 , 13 , 20 , 30 , 34 , 36 , 38 , 41 ], recruitment methods [ 13 , 30 , 32 , 34 , 35 , 38 , 41 ], running the full trial protocol [ 20 , 30 , 36 ], the willingness of participants to be randomised [ 30 , 32 ] and issues of contamination [ 30 ]. There was disagreement concerning the appropriateness of assessing blinding in exploratory studies [ 7 , 30 , 34 ], with one source noting double blinding is difficult when participants are assisted in changing their behaviour; although assessing single blinding may be possible [ 30 ].

Qualitative [ 15 , 30 , 34 ], quantitative [ 34 ] and mixed methods [ 7 ] were endorsed for assessing these processes. Reflecting the tendency for guidance of exploratory studies to be limited to studies in preparation for RCTs, discussion of the role of randomisation at the exploratory study stage featured heavily in guidance. Randomisation within an exploratory study was considered necessary for examining feasibility of recruitment, consent to randomisation, retention, contamination or maintenance of blinding in the control and intervention groups, randomisation procedures and whether all the components of a protocol can work together, although randomisation was not deemed necessary to assess outcome burden and participant eligibility [ 21 , 30 , 34 ]. While there was consensus about what issues could be assessed through randomisation, sources disagreed on whether randomisation should always precede a future evaluation study, even if that future study is to be an RCT. Contention seemed to be linked to variation in nomenclature and associated aims. For example, some defined pilot study as a study run in miniature to test how all its components work together, thereby dictating a randomised design [ 32 , 34 ]. Yet for feasibility studies, randomisation was only necessary if it reduced the uncertainties in estimating parameters for the future evaluation [ 32 , 34 ]. Similarly, other guidance highlighted an exploratory study (irrespective of nomenclature) should address the main uncertainties, and thus may not depend on randomisation [ 8 , 15 ].

Estimating parameters of the future evaluation design

A number of sources recommended exploratory studies should inform the parameters of the future evaluation design. Areas for investigation included estimating sample sizes required for the future evaluation (e.g. measuring outcomes [ 32 , 35 ]; power calculations [ 13 ]; derive effect size estimates [ 6 , 7 , 39 ]; estimating target differences [ 35 , 43 ]; deciding what outcomes to measure and how [ 9 , 20 , 30 , 36 ]; assessing quality of measures (e.g. for reliability/ validity/ feasibility/ sensitivity [ 7 , 20 , 30 ]; identification of control group [ 9 , 13 ]; recruitment, consent and retention rates [ 10 , 13 , 20 , 30 , 32 , 34 , 36 ]; and information on the cost of the future evaluation design [ 9 , 30 , 36 ].

While qualitative methods were deemed useful for selecting outcomes and their suitable measures [ 15 ], most guidance concentrated on quantitative methods for estimating future evaluation sample sizes. This was contentious due to the potential to over- or under-estimate sample sizes required in a future evaluation due to the lack of precision of estimates from a small pilot [ 20 , 30 , 41 ]. Estimating sample sizes from effect size estimates in an exploratory study was nevertheless argued by some to be useful if there was scant literature and the exploratory study used the same design and outcome as the future evaluation [ 30 , 39 ]. Cluster RCTs, which are common in public health interventions, were specifically earmarked as unsuitable for estimating parameters for sample size calculations (e.g. intra-cluster correlation coefficients) as well as recruitment and follow-up rates without additional information from other resources, because a large number of clusters and individual participants would be required [ 41 ]. Others referred to ‘rules of thumb’ when determining sample sizes in an exploratory study with numbers varying between 10 and 75 participants per trial arm in individually randomised studies [ 7 , 30 , 36 ]. Several also recommended the need to consider a desired meaningful difference in the health outcomes from a future evaluation and the appropriate sample size needed to detect this, rather than conducting sample size calculations using estimates of likely effect size from pilot data [ 30 , 35 , 38 , 43 ].

A randomised design was deemed unnecessary for estimating costs or selecting outcomes, although was valued for estimating recruitment and retention rates for intervention and control groups [ 21 , 34 ]. Where guidance indicated the estimation of an effect size appropriate to inform the sample size for a future evaluation, a randomised design was deemed necessary [ 9 , 39 ].

Theme 5: flexible vs. fixed design

Sources stated that exploratory studies could employ a rigid or flexible design. With the latter, the design can change during the course of the study, which is useful for making changes to the intervention, as well as the future evaluation design [ 6 , 13 , 15 , 31 ]. Here, qualitative data can be analysed as it is collected, shaping the exploratory study process, for instance sampling of subsequent data collection points [ 15 ], and clarifying implications for intervention effectiveness [ 31 ].

In contrast, fixed exploratory studies were encouraged when primarily investigating the future evaluation parameters and processes [ 13 ]. It may be that the nomenclature used in some guidance (e.g. pilot studies that are described as miniature versions of the evaluation) is suggesting a distinction between more flexible vs. more stringent designs. In some guidance, it was not mentioned whether changes should be made during the course of an exploratory study or afterwards, in order to get the best possible design for the future evaluation [ 6 , 7 , 21 ].

Theme 6: progression criteria to a future evaluation study

Little guidance was provided on what should be considered when formulating progression criteria for continuing onto a future evaluation study. Some focussed on the relevant uncertainties of feasibility [ 32 , 39 ], while others highlight specific items concerning cost-effectiveness [ 10 ], refining causal hypotheses to be tested in a future evaluation [ 29 ] and meeting recruitment targets [ 20 , 34 ]. As discussed in themes 3 and 4, statistically testing for effectiveness and using effect sizes for power calculations was cautioned by some, and so criteria based on effect sizes were not specified [ 38 ].

Greater discussion was devoted to how to weight evidence from an exploratory study that addressed multiple aims and used different methods. Some explicitly stated progression criteria should not be judged as strict thresholds but as guidelines using, for example, a traffic lights system with varying levels of acceptability [ 7 , 41 ]. Others highlighted a realist approach, moving away from binary indicators to focusing on ‘what is feasible and acceptable for whom and under what circumstances’ [ 29 ]. In light of the difficulties surrounding interpretation of effect estimates, several sources recommended qualitative findings from exploratory studies should be more influential than quantitative findings [ 15 , 38 ].

Interestingly, there was ambiguity regarding progression when exploratory findings indicated substantial changes to the intervention or evaluation design. Sources considering this issue suggested that if ‘extensive changes’ or ‘major modifications’ are made to either (note they did not specify what qualified as such), researchers should return to the exploratory [ 21 , 30 ] or intervention development phases [ 15 ].

‘Alternatively, at the feasibility phase, researchers may identify fundamental problems with the intervention or trial conduct and return to the development phase rather than proceed to a full trial.’ (p. 1) [ 15 ].

As described previously, however, the threshold at which changes are determined to be ‘major’ remained ambiguous. While updated MRC guidance [ 10 ] moved to a more iterative model, accepting that movement back between feasibility/piloting and intervention development may sometimes be needed, there was no guidance on under what conditions movement between these two stages should take place.

Theme 7: stakeholder involvement

Several sources recommended a range of stakeholders (e.g. intervention providers, intervention recipients, public representatives as well as practitioners who might use the evidence produced by the full trial) be involved in the planning and running of the exploratory study to ensure exploratory studies reflect the realities of intervention setting [ 15 , 28 , 31 , 32 , 39 , 40 ]. In particular, community-based participatory approaches were recommended [ 15 , 39 ]. While many highlighted the value of stakeholders on Trial Steering Committees and other similar study groups [ 15 , 28 , 40 ], some warned about equipoise between researchers and stakeholders [ 15 , 40 ] and also cautioned against researchers conflating stakeholder involvement with qualitative research [ 15 ].

‘Although patient and public representatives on research teams can provide helpful feedback on the intervention, this does not constitute qualitative research and may not result in sufficiently robust data to inform the appropriate development of the intervention.’ (p. 8) [ 15 ].

Theme 8: reporting of exploratory studies

Detailed recommendations for reporting exploratory studies were recently provided in new Consolidated Standards of Reporting Trials (CONSORT) guidance by Eldridge et al. [ 7 ]. In addition to this, recurrent points were brought up by other sources of guidance. Most notably, it was recommended exploratory studies be published in peer-reviewed journals as this can provide useful information to other researchers on what has been done, what did not work and what might be most appropriate [ 15 , 30 ]. An exploratory study may also result in multiple publications, but should provide reference to other work carried out in the same exploratory study [ 7 , 15 ]. Several sources of guidance also highlight that exploratory studies should be appropriately labelled in the title/abstract to enable easy identification; however, the nomenclature suggested varied depending on guidance [ 7 , 8 , 15 ].

While exploratory studies—carried out to inform decisions about whether and how to proceed with an effectiveness study [ 7 , 8 ]—are increasingly recognised as important in the efficient evaluation of complex public health interventions, our findings suggest that this area remains in need of consistent standards to inform practice. At present, there are multiple definitions of exploratory studies, a lack of consensus on a number of key issues, and a paucity of detailed guidance on how to approach the main uncertainties such studies aim to address prior to proceeding to a full evaluation.

Existing guidance commonly focuses almost exclusively on testing methodological parameters [ 33 ], such as recruitment and retention, although in practice, it is unusual for such studies not to also focus on the feasibility of the intervention itself. Where intervention feasibility is discussed, there is limited guidance on when an intervention is ‘ready’ for an exploratory study and a lack of demarcation between intervention development and pre-evaluation work to understand feasibility. Some guidance recognised that an intervention continues to develop throughout an exploratory study, with distinctions made between ‘optimisation/refinement’ (i.e. minor refinements to the intervention) vs. ‘major changes’. However, the point at which changes become so substantial that movement back toward intervention development rather than forward to a full evaluation remains ambiguous. Consistent with past reviews which adopted a narrower focus on studies with randomised designs [ 21 ] or in preparation for a randomised trial [ 8 , 36 ] and limited searches of guidance in medical journals [ 19 , 36 ], terms to describe exploratory studies were inconsistent, with a distinction sometimes made between pilot and feasibility studies, though with others using these terms interchangeably.

The review identifies a number of key areas of disagreement or limited guidance in regards to the critical aims of exploratory studies and addressing uncertainties which might undermine a future evaluation, and how these aims should be achieved. There was much disagreement for example on whether exploratory studies should include a preliminary assessment of intervention effects to inform decisions on progression to a full evaluation, and the appropriateness of using estimates of effect from underpowered data (from non-representative samples and a study based on a not fully optimised version of the intervention) to power a future evaluation study. Most guidance focused purely on studies in preparation for RCTs; nevertheless, guidance varied on whether randomisation was a necessary feature of the exploratory study, even where a future evaluation study was an RCT. Guidance was often difficult to assess regarding its applicability to public health research, with many sources focusing on literature and practice primarily from clinical research, and limited consideration of the transferability of these problems and proposed solutions to complex social interventions, such as those in public health. Progression criteria were highlighted as important by some as a means of preventing biased post hoc cases for continuation. However, there was a lack of guidance on how to devise progression criteria and processes for assessing whether these had been sufficiently met. Where they had not been met, there was a lack of guidance on how to decide whether the exploratory study had generated sufficient insight about uncertainties that the expense of a further feasibility study would not be justified prior to large-scale evaluation.

Although our review included a broad focus on guidance of exploratory studies from published and grey literature and moved beyond a focus on studies conducted in preparation for an RCT specifically, a number of limitations should be noted. Guidance from other areas of social intervention research where challenges may be similar to those in public health (e.g. education, social work and business) may not have been captured by our search strategy. We found few worked examples of exploratory studies in public health that provided substantial information from learned experience and practice. Hence, the review drew largely on recommendations from funding organisations, or relatively abstract guidance from teams of researchers, with fewer clear examples of how these recommendations are grounded in experience from the conduct of such studies. As such, it should be acknowledged that these documents represent one element within a complex system of research production and may not necessarily fully reflect what is taking place in the conduct of exploratory studies. Finally, treating sources of guidance as independent from each other does not reflect how some recommendations developed over time (see for example [ 7 , 8 , 20 , 36 , 41 ]).

There is inconsistent guidance, and for some key issues a lack of guidance, for exploratory studies of complex public health interventions. As this lack of guidance for researchers in public health continues, the implications and consequences could be far reaching. It is unclear how researchers use existing guidance to shape decision-making in the conduct of exploratory studies, and in doing so, how they adjudicate between various conflicting perspectives. This systematic review has aimed largely to identify areas of agreement and disagreement as a starting point in bringing order to this somewhat chaotic field of work. Following this systematic review, our next step is to conduct an audit of published public health exploratory studies in peer-reviewed journals, to assess current practice and how this reflects the reviewed guidance. As part of a wider study, funded by the MRC/NIHR Methodology Research Programme to develop GUidance for Exploratory STudies of complex public health interventions (GUEST; Moore L, et al. Exploratory studies to inform full scale evaluations of complex public health interventions: the need for guidance, submitted), the review has informed a Delphi survey of researchers, funders and publishers of public health research. In turn, this will contribute to a consensus meeting which aims to reach greater unanimity on the aims of exploratory studies, and how these can most efficiently address uncertainties which may undermine a full-scale evaluation.

Abbreviations

Consolidated Standards of Reporting Trials

GUidance for Exploratory STudies of complex public health interventions

Medical Research Council

National Institute of Health Research Evaluation Trials and Studies Coordinating Centre

National Institute for Health Research

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Randomised controlled trial

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Acknowledgements

We thank the Specialist Unit for Review Evidence (SURE) at Cardiff University, including Mala Mann, Helen Morgan, Alison Weightman and Lydia Searchfield, for their assistance with developing and conducting the literature search.

This study is supported by funding from the Methodology Research Panel (MR/N015843/1). LM, SS and DW are supported by the UK Medical Research Council (MC_UU_12017/14) and the Chief Scientist Office (SPHSU14). PC is supported by the UK Medical Research Council (MC_UU_12017/15) and the Chief Scientist Office (SPHSU15). The work was also undertaken with the support of The Centre for the Development and Evaluation of Complex Interventions for Public Health Improvement (DECIPHer), a UKCRC Public Health Research Centre of Excellence. Joint funding (MR/KO232331/1) from the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, the Welsh Government and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged.

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LM, GM, PC, MR, JS, RT and SS were involved in the development of the study. RT, JS, DW and BH were responsible for the data collection, overseen by LM and GM. Data analysis was undertaken by BH guided by RT, JS, DW and GM. The manuscript was prepared by BH, RT, DW, JS and GM. All authors contributed to the final version of the manuscript. LM is the principal investigator with overall responsibility for the project. GM is Cardiff lead for the project. All authors read and approved the final manuscript.

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Hallingberg, B., Turley, R., Segrott, J. et al. Exploratory studies to decide whether and how to proceed with full-scale evaluations of public health interventions: a systematic review of guidance. Pilot Feasibility Stud 4 , 104 (2018). https://doi.org/10.1186/s40814-018-0290-8

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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 .

Quantitative research questions	Quantitative research hypotheses
Descriptive research questions	Simple hypothesis
Comparative research questions	Complex hypothesis
Relationship research questions	Directional hypothesis
	Non-directional hypothesis
	Associative hypothesis
	Causal hypothesis
	Null hypothesis
	Alternative hypothesis
	Working hypothesis
	Statistical hypothesis
	Logical hypothesis
	Hypothesis-testing
Qualitative research questions	Qualitative research hypotheses
Contextual research questions	Hypothesis-generating
Descriptive research questions
Evaluation research questions
Explanatory research questions
Exploratory research questions
Generative research questions
Ideological research questions
Ethnographic research questions
Phenomenological research questions
Grounded theory questions
Qualitative case study questions

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 .

Quantitative research questions
Descriptive research question
	- Measures responses of subjects to variables
	- Presents variables to measure, analyze, or assess
	What is the proportion of resident doctors in the hospital who have mastered ultrasonography (response of subjects to a variable) as a diagnostic technique in their clinical training?
Comparative research question
	- Clarifies difference between one group with outcome variable and another group without outcome variable
	Is there a difference in the reduction of lung metastasis in osteosarcoma patients who received the vitamin D adjunctive therapy (group with outcome variable) compared with osteosarcoma patients who did not receive the vitamin D adjunctive therapy (group without outcome variable)?
	- Compares the effects of variables
	How does the vitamin D analogue 22-Oxacalcitriol (variable 1) mimic the antiproliferative activity of 1,25-Dihydroxyvitamin D (variable 2) in osteosarcoma cells?
Relationship research question
	- Defines trends, association, relationships, or interactions between dependent variable and independent variable
	Is there a relationship between the number of medical student suicide (dependent variable) and the level of medical student stress (independent variable) in Japan during the first wave of the COVID-19 pandemic?

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 .

Quantitative research hypotheses
Simple hypothesis
	- Predicts relationship between single dependent variable and single independent variable
	If the dose of the new medication (single independent variable) is high, blood pressure (single dependent variable) is lowered.
Complex hypothesis
	- Foretells relationship between two or more independent and dependent variables
	The higher the use of anticancer drugs, radiation therapy, and adjunctive agents (3 independent variables), the higher would be the survival rate (1 dependent variable).
Directional hypothesis
	- Identifies study direction based on theory towards particular outcome to clarify relationship between variables
	Privately funded research projects will have a larger international scope (study direction) than publicly funded research projects.
Non-directional hypothesis
	- Nature of relationship between two variables or exact study direction is not identified
	- Does not involve a theory
	Women and men are different in terms of helpfulness. (Exact study direction is not identified)
Associative hypothesis
	- Describes variable interdependency
	- Change in one variable causes change in another variable
	A larger number of people vaccinated against COVID-19 in the region (change in independent variable) will reduce the region’s incidence of COVID-19 infection (change in dependent variable).
Causal hypothesis
	- An effect on dependent variable is predicted from manipulation of independent variable
	A change into a high-fiber diet (independent variable) will reduce the blood sugar level (dependent variable) of the patient.
Null hypothesis
	- A negative statement indicating no relationship or difference between 2 variables
	There is no significant difference in the severity of pulmonary metastases between the new drug (variable 1) and the current drug (variable 2).
Alternative hypothesis
	- Following a null hypothesis, an alternative hypothesis predicts a relationship between 2 study variables
	The new drug (variable 1) is better on average in reducing the level of pain from pulmonary metastasis than the current drug (variable 2).
Working hypothesis
	- A hypothesis that is initially accepted for further research to produce a feasible theory
	Dairy cows fed with concentrates of different formulations will produce different amounts of milk.
Statistical hypothesis
	- Assumption about the value of population parameter or relationship among several population characteristics
	- Validity tested by a statistical experiment or analysis
	The mean recovery rate from COVID-19 infection (value of population parameter) is not significantly different between population 1 and population 2.
	There is a positive correlation between the level of stress at the workplace and the number of suicides (population characteristics) among working people in Japan.
Logical hypothesis
	- Offers or proposes an explanation with limited or no extensive evidence
	If healthcare workers provide more educational programs about contraception methods, the number of adolescent pregnancies will be less.
Hypothesis-testing (Quantitative hypothesis-testing research)
	- Quantitative research uses deductive reasoning.
	- This involves the formation of a hypothesis, collection of data in the investigation of the problem, analysis and use of the data from the investigation, and drawing of conclusions to validate or nullify the hypotheses.

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 research questions
Contextual research question
	- Ask the nature of what already exists
	- Individuals or groups function to further clarify and understand the natural context of real-world problems
	What are the experiences of nurses working night shifts in healthcare during the COVID-19 pandemic? (natural context of real-world problems)
Descriptive research question
	- Aims to describe a phenomenon
	What are the different forms of disrespect and abuse (phenomenon) experienced by Tanzanian women when giving birth in healthcare facilities?
Evaluation research question
	- Examines the effectiveness of existing practice or accepted frameworks
	How effective are decision aids (effectiveness of existing practice) in helping decide whether to give birth at home or in a healthcare facility?
Explanatory research question
	- Clarifies a previously studied phenomenon and explains why it occurs
	Why is there an increase in teenage pregnancy (phenomenon) in Tanzania?
Exploratory research question
	- Explores areas that have not been fully investigated to have a deeper understanding of the research problem
	What factors affect the mental health of medical students (areas that have not yet been fully investigated) during the COVID-19 pandemic?
Generative research question
	- Develops an in-depth understanding of people’s behavior by asking ‘how would’ or ‘what if’ to identify problems and find solutions
	How would the extensive research experience of the behavior of new staff impact the success of the novel drug initiative?
Ideological research question
	- Aims to advance specific ideas or ideologies of a position
	Are Japanese nurses who volunteer in remote African hospitals able to promote humanized care of patients (specific ideas or ideologies) in the areas of safe patient environment, respect of patient privacy, and provision of accurate information related to health and care?
Ethnographic research question
	- Clarifies peoples’ nature, activities, their interactions, and the outcomes of their actions in specific settings
	What are the demographic characteristics, rehabilitative treatments, community interactions, and disease outcomes (nature, activities, their interactions, and the outcomes) of people in China who are suffering from pneumoconiosis?
Phenomenological research question
	- Knows more about the phenomena that have impacted an individual
	What are the lived experiences of parents who have been living with and caring for children with a diagnosis of autism? (phenomena that have impacted an individual)
Grounded theory question
	- Focuses on social processes asking about what happens and how people interact, or uncovering social relationships and behaviors of groups
	What are the problems that pregnant adolescents face in terms of social and cultural norms (social processes), and how can these be addressed?
Qualitative case study question
	- Assesses a phenomenon using different sources of data to answer “why” and “how” questions
	- Considers how the phenomenon is influenced by its contextual situation.
	How does quitting work and assuming the role of a full-time mother (phenomenon assessed) change the lives of women in Japan?

Qualitative research hypotheses
Hypothesis-generating (Qualitative hypothesis-generating research)
	- Qualitative research uses inductive reasoning.
	- This involves data collection from study participants or the literature regarding a phenomenon of interest, using the collected data to develop a formal hypothesis, and using the formal hypothesis as a framework for testing the hypothesis.
	- Qualitative exploratory studies explore areas deeper, clarifying subjective experience and allowing formulation of a formal hypothesis potentially testable in a future quantitative approach.

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.

Variables	Unclear and weak statement (Statement 1)	Clear and good statement (Statement 2)	Points to avoid
Research question	Which is more effective between smoke moxibustion and smokeless moxibustion?	“Moreover, regarding smoke moxibustion versus smokeless moxibustion, it remains unclear which is more effective, safe, and acceptable to pregnant women, and whether there is any difference in the amount of heat generated.”	1) Vague and unfocused questions
			2) Closed questions simply answerable by yes or no
			3) Questions requiring a simple choice
Hypothesis	The smoke moxibustion group will have higher cephalic presentation.	“Hypothesis 1. The smoke moxibustion stick group (SM group) and smokeless moxibustion stick group (-SLM group) will have higher rates of cephalic presentation after treatment than the control group.	1) Unverifiable hypotheses
		Hypothesis 2. The SM group and SLM group will have higher rates of cephalic presentation at birth than the control group.	2) Incompletely stated groups of comparison
		Hypothesis 3. There will be no significant differences in the well-being of the mother and child among the three groups in terms of the following outcomes: premature birth, premature rupture of membranes (PROM) at < 37 weeks, Apgar score < 7 at 5 min, umbilical cord blood pH < 7.1, admission to neonatal intensive care unit (NICU), and intrauterine fetal death.”	3) Insufficiently described variables or outcomes
Research objective	To determine which is more effective between smoke moxibustion and smokeless moxibustion.	“The specific aims of this pilot study were (a) to compare the effects of smoke moxibustion and smokeless moxibustion treatments with the control group as a possible supplement to ECV for converting breech presentation to cephalic presentation and increasing adherence to the newly obtained cephalic position, and (b) to assess the effects of these treatments on the well-being of the mother and child.”	1) Poor understanding of the research question and hypotheses
Research objective			2) Insufficient description of population, variables, or study outcomes

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

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

Variables	Unclear and weak statement (Statement 1)	Clear and good statement (Statement 2)	Points to avoid
Research question	Does disrespect and abuse (D&A) occur in childbirth in Tanzania?	How does disrespect and abuse (D&A) occur and what are the types of physical and psychological abuses observed in midwives’ actual care during facility-based childbirth in urban Tanzania?	1) Ambiguous or oversimplistic questions
Research question			2) Questions unverifiable by data collection and analysis
Hypothesis	Disrespect and abuse (D&A) occur in childbirth in Tanzania.	Hypothesis 1: Several types of physical and psychological abuse by midwives in actual care occur during facility-based childbirth in urban Tanzania.	1) Statements simply expressing facts
Hypothesis	Disrespect and abuse (D&A) occur in childbirth in Tanzania.	Hypothesis 2: Weak nursing and midwifery management contribute to the D&A of women during facility-based childbirth in urban Tanzania.	2) Insufficiently described concepts or variables
Research objective	To describe disrespect and abuse (D&A) in childbirth in Tanzania.	“This study aimed to describe from actual observations the respectful and disrespectful care received by women from midwives during their labor period in two hospitals in urban Tanzania.”	1) Statements unrelated to the research question and hypotheses
Research objective			2) Unattainable or unexplorable objectives

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 .

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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.

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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.

English teachers’ gamification satisfaction and perception scale (ETGSPS) development and validation

Published: 10 September 2024

Cite this article

Jakub Helvich ORCID: orcid.org/0000-0002-2787-0757 1 , 2 ,
Lukas Novak 3 ,
Petr Mikoska 4 ,
Stepan Hubalovsky 2 &
Katerina Juklova 4

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Over the years, gamification has played an important role in English education. Despite the promising results, there is a scarcity of research on gamified English teaching. Additionally, most studies addressing this topic used tools with problematic validity, posing challenges in interpreting their findings. Therefore, the objectives were to develop and validate a measure assessing the teacher-perceived applicability of gamification applications and the perceived effect on learners’ motivation and learning outcomes. Two samples of 278 (M = 41.2, SD = 9.38; 81.3% females) and 333 (M = 43.7, SD = 9.2; 87% females) participants were used for Exploratory and Confirmatory Factor Analyses, respectively. Network analysis examined the mutual dynamics between the items. Additionally, two retest samples were collected to explore the stability of the scale. Measurement invariance was examined between the samples and education levels. The construct validity was assessed by examining associations with other constructs using Spearman’s Rank correlations. The results supported the four-factor model (CFI = 0.863; TLI = 0.85; RMSEA = 0.076; SRMR = 0.077) with excellent internal consistency (Cronbach’s α = 0.91 and McDonald’s ω = 0.94) and excellent stability (ICC = 0.96). The network analysis identified 9 communities. The measurement invariance revealed that the scale measures the same across different education levels and samples. Spearman’s Rank correlations suggested statistically significant associations between individual subscales and selected constructs except between learning outcomes and general point averages. Altogether, the scale exhibits a high temporal and cross-level robustness, making it a valuable tool for gamification assessment in English teaching.

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Determinants of the perceived usefulness (PU) in the context of using gamification for classroom-based ESL teaching: A scale development study

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Digital Education and Educational Technology

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All supplementary materials, study code and research data, including the pre-registration form, were made publicly available on the Open Science Framework website: https://www.osf.io/6b4hc/ .

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Note. English version of ETGSPS translated via forward-backward method. The order should be always randomised. Lower scores indicate higher teacher-perceived effect on learner’s motivation, learning outcomes and teacher’s satisfaction with the gamification application.

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Helvich, J., Novak, L., Mikoska, P. et al. English teachers’ gamification satisfaction and perception scale (ETGSPS) development and validation. Educ Inf Technol (2024). https://doi.org/10.1007/s10639-024-13001-6

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Primary research

Secondary research

Step 1: Identify your problem

Step 2: Hypothesize a solution

Step 3. Design your methodology

Step 4: Collect and analyze data

Step 5: Avenues for future research

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Tegan George

Exploratory Research – Types, Methods and Examples

Exploratory Research

Exploratory Research Methods

Literature Review

Pilot Study

Focus Groups

Expert Opinion

Observational Research

Open-ended Surveys

Data Analysis Methods

Content Analysis

Thematic Analysis

Cluster Analysis

Network Analysis

Grounded Theory

Applications of Exploratory Research

Examples of Exploratory Research

How to Conduct Exploratory Research

When to use Exploratory Research

Purpose of Exploratory Research

Characteristics of Exploratory Research

Advantages of Exploratory Research

Limitations of Exploratory Research

About the author

Muhammad Hassan

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Exploratory Research | Definition, Guide, & Examples

Table of contents

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Primary research

Secondary research

Step 1: Identify your problem

Step 2: Hypothesise a solution

Step 3. Design your methodology

Step 4: Collect and analyse data

Step 5: Avenues for future research

Disadvantages

Cite this Scribbr article

Is this article helpful?

Tegan George

Exploratory Research

Examples of Exploratory Research Design

Differences between Exploratory and Conclusive Research

Advantages of Exploratory Research

Disadvantages of Exploratory Research

Exploratory studies to decide whether and how to proceed with full-scale evaluations of public health interventions: a systematic review of guidance

Conclusions

Trial registration

Literature search

Selection of included papers

Quality assessment of included papers