what is a project design in research

What Is Research Design?

A Plain-Language Explainer (With Examples)

By: Derek Jansen (MBA) | Reviewers: Eunice Rautenbach (DTech) & Kerryn Warren (PhD) | April 2023

Overview: Research Design 101

What is research design.

• Research design types for quantitative studies
• Video explainer : quantitative research design
• Research design types for qualitative studies
• Video explainer : qualitative research design
• How to choose a research design
• Key takeaways

Research design refers to the overall plan, structure or strategy that guides a research project , from its conception to the final data analysis. A good research design serves as the blueprint for how you, as the researcher, will collect and analyse data while ensuring consistency, reliability and validity throughout your study.

Understanding different types of research designs is essential as helps ensure that your approach is suitable  given your research aims, objectives and questions , as well as the resources you have available to you. Without a clear big-picture view of how you’ll design your research, you run the risk of potentially making misaligned choices in terms of your methodology – especially your sampling , data collection and data analysis decisions.

The problem with defining research design…

One of the reasons students struggle with a clear definition of research design is because the term is used very loosely across the internet, and even within academia.

Some sources claim that the three research design types are qualitative, quantitative and mixed methods , which isn’t quite accurate (these just refer to the type of data that you’ll collect and analyse). Other sources state that research design refers to the sum of all your design choices, suggesting it’s more like a research methodology . Others run off on other less common tangents. No wonder there’s confusion!

In this article, we’ll clear up the confusion. We’ll explain the most common research design types for both qualitative and quantitative research projects, whether that is for a full dissertation or thesis, or a smaller research paper or article.

Research Design: Quantitative Studies

Quantitative research involves collecting and analysing data in a numerical form. Broadly speaking, there are four types of quantitative research designs: descriptive , correlational , experimental , and quasi-experimental .

As the name suggests, descriptive research design focuses on describing existing conditions, behaviours, or characteristics by systematically gathering information without manipulating any variables. In other words, there is no intervention on the researcher’s part – only data collection.

For example, if you’re studying smartphone addiction among adolescents in your community, you could deploy a survey to a sample of teens asking them to rate their agreement with certain statements that relate to smartphone addiction. The collected data would then provide insight regarding how widespread the issue may be – in other words, it would describe the situation.

The key defining attribute of this type of research design is that it purely describes the situation . In other words, descriptive research design does not explore potential relationships between different variables or the causes that may underlie those relationships. Therefore, descriptive research is useful for generating insight into a research problem by describing its characteristics . By doing so, it can provide valuable insights and is often used as a precursor to other research design types.

Correlational Research Design

Correlational design is a popular choice for researchers aiming to identify and measure the relationship between two or more variables without manipulating them . In other words, this type of research design is useful when you want to know whether a change in one thing tends to be accompanied by a change in another thing.

For example, if you wanted to explore the relationship between exercise frequency and overall health, you could use a correlational design to help you achieve this. In this case, you might gather data on participants’ exercise habits, as well as records of their health indicators like blood pressure, heart rate, or body mass index. Thereafter, you’d use a statistical test to assess whether there’s a relationship between the two variables (exercise frequency and health).

As you can see, correlational research design is useful when you want to explore potential relationships between variables that cannot be manipulated or controlled for ethical, practical, or logistical reasons. It is particularly helpful in terms of developing predictions , and given that it doesn’t involve the manipulation of variables, it can be implemented at a large scale more easily than experimental designs (which will look at next).

Need a helping hand?

Experimental research design is used to determine if there is a causal relationship between two or more variables . With this type of research design, you, as the researcher, manipulate one variable (the independent variable) while controlling others (dependent variables). Doing so allows you to observe the effect of the former on the latter and draw conclusions about potential causality.

For example, if you wanted to measure if/how different types of fertiliser affect plant growth, you could set up several groups of plants, with each group receiving a different type of fertiliser, as well as one with no fertiliser at all. You could then measure how much each plant group grew (on average) over time and compare the results from the different groups to see which fertiliser was most effective.

Overall, experimental research design provides researchers with a powerful way to identify and measure causal relationships (and the direction of causality) between variables. However, developing a rigorous experimental design can be challenging as it’s not always easy to control all the variables in a study. This often results in smaller sample sizes , which can reduce the statistical power and generalisability of the results.

Moreover, experimental research design requires random assignment . This means that the researcher needs to assign participants to different groups or conditions in a way that each participant has an equal chance of being assigned to any group (note that this is not the same as random sampling ). Doing so helps reduce the potential for bias and confounding variables . This need for random assignment can lead to ethics-related issues . For example, withholding a potentially beneficial medical treatment from a control group may be considered unethical in certain situations.

Quasi-Experimental Research Design

Quasi-experimental research design is used when the research aims involve identifying causal relations , but one cannot (or doesn’t want to) randomly assign participants to different groups (for practical or ethical reasons). Instead, with a quasi-experimental research design, the researcher relies on existing groups or pre-existing conditions to form groups for comparison.

For example, if you were studying the effects of a new teaching method on student achievement in a particular school district, you may be unable to randomly assign students to either group and instead have to choose classes or schools that already use different teaching methods. This way, you still achieve separate groups, without having to assign participants to specific groups yourself.

Naturally, quasi-experimental research designs have limitations when compared to experimental designs. Given that participant assignment is not random, it’s more difficult to confidently establish causality between variables, and, as a researcher, you have less control over other variables that may impact findings.

Research Design: Qualitative Studies

There are many different research design types when it comes to qualitative studies, but here we’ll narrow our focus to explore the “Big 4”. Specifically, we’ll look at phenomenological design, grounded theory design, ethnographic design, and case study design.

Phenomenological design involves exploring the meaning of lived experiences and how they are perceived by individuals. This type of research design seeks to understand people’s perspectives , emotions, and behaviours in specific situations. Here, the aim for researchers is to uncover the essence of human experience without making any assumptions or imposing preconceived ideas on their subjects.

For example, you could adopt a phenomenological design to study why cancer survivors have such varied perceptions of their lives after overcoming their disease. This could be achieved by interviewing survivors and then analysing the data using a qualitative analysis method such as thematic analysis to identify commonalities and differences.

Phenomenological research design typically involves in-depth interviews or open-ended questionnaires to collect rich, detailed data about participants’ subjective experiences. This richness is one of the key strengths of phenomenological research design but, naturally, it also has limitations. These include potential biases in data collection and interpretation and the lack of generalisability of findings to broader populations.

Grounded Theory Research Design

Grounded theory (also referred to as “GT”) aims to develop theories by continuously and iteratively analysing and comparing data collected from a relatively large number of participants in a study. It takes an inductive (bottom-up) approach, with a focus on letting the data “speak for itself”, without being influenced by preexisting theories or the researcher’s preconceptions.

As an example, let’s assume your research aims involved understanding how people cope with chronic pain from a specific medical condition, with a view to developing a theory around this. In this case, grounded theory design would allow you to explore this concept thoroughly without preconceptions about what coping mechanisms might exist. You may find that some patients prefer cognitive-behavioural therapy (CBT) while others prefer to rely on herbal remedies. Based on multiple, iterative rounds of analysis, you could then develop a theory in this regard, derived directly from the data (as opposed to other preexisting theories and models).

Grounded theory typically involves collecting data through interviews or observations and then analysing it to identify patterns and themes that emerge from the data. These emerging ideas are then validated by collecting more data until a saturation point is reached (i.e., no new information can be squeezed from the data). From that base, a theory can then be developed .

Ethnographic design involves observing and studying a culture-sharing group of people in their natural setting to gain insight into their behaviours, beliefs, and values. The focus here is on observing participants in their natural environment (as opposed to a controlled environment). This typically involves the researcher spending an extended period of time with the participants in their environment, carefully observing and taking field notes .

All of this is not to say that ethnographic research design relies purely on observation. On the contrary, this design typically also involves in-depth interviews to explore participants’ views, beliefs, etc. However, unobtrusive observation is a core component of the ethnographic approach.

As an example, an ethnographer may study how different communities celebrate traditional festivals or how individuals from different generations interact with technology differently. This may involve a lengthy period of observation, combined with in-depth interviews to further explore specific areas of interest that emerge as a result of the observations that the researcher has made.

As you can probably imagine, ethnographic research design has the ability to provide rich, contextually embedded insights into the socio-cultural dynamics of human behaviour within a natural, uncontrived setting. Naturally, however, it does come with its own set of challenges, including researcher bias (since the researcher can become quite immersed in the group), participant confidentiality and, predictably, ethical complexities . All of these need to be carefully managed if you choose to adopt this type of research design.

Case Study Design

With case study research design, you, as the researcher, investigate a single individual (or a single group of individuals) to gain an in-depth understanding of their experiences, behaviours or outcomes. Unlike other research designs that are aimed at larger sample sizes, case studies offer a deep dive into the specific circumstances surrounding a person, group of people, event or phenomenon, generally within a bounded setting or context .

As an example, a case study design could be used to explore the factors influencing the success of a specific small business. This would involve diving deeply into the organisation to explore and understand what makes it tick – from marketing to HR to finance. In terms of data collection, this could include interviews with staff and management, review of policy documents and financial statements, surveying customers, etc.

While the above example is focused squarely on one organisation, it’s worth noting that case study research designs can have different variation s, including single-case, multiple-case and longitudinal designs. As you can see in the example, a single-case design involves intensely examining a single entity to understand its unique characteristics and complexities. Conversely, in a multiple-case design , multiple cases are compared and contrasted to identify patterns and commonalities. Lastly, in a longitudinal case design , a single case or multiple cases are studied over an extended period of time to understand how factors develop over time.

How To Choose A Research Design

Having worked through all of these potential research designs, you’d be forgiven for feeling a little overwhelmed and wondering, “ But how do I decide which research design to use? ”. While we could write an entire post covering that alone, here are a few factors to consider that will help you choose a suitable research design for your study.

Data type: The first determining factor is naturally the type of data you plan to be collecting – i.e., qualitative or quantitative. This may sound obvious, but we have to be clear about this – don’t try to use a quantitative research design on qualitative data (or vice versa)!

Research aim(s) and question(s): As with all methodological decisions, your research aim and research questions will heavily influence your research design. For example, if your research aims involve developing a theory from qualitative data, grounded theory would be a strong option. Similarly, if your research aims involve identifying and measuring relationships between variables, one of the experimental designs would likely be a better option.

Time: It’s essential that you consider any time constraints you have, as this will impact the type of research design you can choose. For example, if you’ve only got a month to complete your project, a lengthy design such as ethnography wouldn’t be a good fit.

Resources: Take into account the resources realistically available to you, as these need to factor into your research design choice. For example, if you require highly specialised lab equipment to execute an experimental design, you need to be sure that you’ll have access to that before you make a decision.

Keep in mind that when it comes to research, it’s important to manage your risks and play as conservatively as possible. If your entire project relies on you achieving a huge sample, having access to niche equipment or holding interviews with very difficult-to-reach participants, you’re creating risks that could kill your project. So, be sure to think through your choices carefully and make sure that you have backup plans for any existential risks. Remember that a relatively simple methodology executed well generally will typically earn better marks than a highly-complex methodology executed poorly.

Recap: Key Takeaways

We’ve covered a lot of ground here. Let’s recap by looking at the key takeaways:

• Research design refers to the overall plan, structure or strategy that guides a research project, from its conception to the final analysis of data.
• Research designs for quantitative studies include descriptive , correlational , experimental and quasi-experimenta l designs.
• Research designs for qualitative studies include phenomenological , grounded theory , ethnographic and case study designs.
• When choosing a research design, you need to consider a variety of factors, including the type of data you’ll be working with, your research aims and questions, your time and the resources available to you.

If you need a helping hand with your research design (or any other aspect of your research), check out our private coaching services .

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15 Comments

Is there any blog article explaining more on Case study research design? Is there a Case study write-up template? Thank you.

Thanks this was quite valuable to clarify such an important concept.

Thanks for this simplified explanations. it is quite very helpful.

This was really helpful. thanks

Thank you for your explanation. I think case study research design and the use of secondary data in researches needs to be talked about more in your videos and articles because there a lot of case studies research design tailored projects out there.

Please is there any template for a case study research design whose data type is a secondary data on your repository?

This post is very clear, comprehensive and has been very helpful to me. It has cleared the confusion I had in regard to research design and methodology.

This post is helpful, easy to understand, and deconstructs what a research design is. Thanks

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how to cite this page

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how can I put this blog as my reference(APA style) in bibliography part?

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• What is project design? 7 steps with ex ...

What is project design? 7 steps with expert tips

Project design is an early phase of the project lifecycle where ideas, processes, resources, and deliverables are planned out in seven steps. With detailed resources and visual elements, find out how project design can streamline your team’s efficiency.

When it comes to managing projects, it can be hard to get everyone on the same page. With multiple moving parts, different deliverables, and cross-departmental collaboration, sometimes an initial project meeting just isn’t enough. 

We’ll go over the basics of project design, lay out the seven steps to create a project design, and provide expert tips to help you better understand the process. 

How project design works

Project design is an early phase of the project lifecycle where ideas, processes, resources, and deliverables are planned out. A project design comes before a project plan as it’s a broad overview whereas a project plan includes more detailed information. 

There are seven steps involved when creating a project design, including defining goals and using a visual aid to communicate objectives.

These visual elements include a variety of methods such as Gantt charts, Kanban boards, and flowcharts. Providing a visual representation of your project strategy can help create transparency between stakeholders and clarify different aspects of the project, including its overall feasibility. 

The 7 steps of project design

There are seven steps that make up a successful project design process. These include everything from defining goals and baseline objectives to strengthening your strategy to help you stay organized while managing a new project.

Let’s go over each of the steps needed to create a project design. 

Step 1. Define project goals

In the first step, define your project goals. To begin, lead an initial ideation meeting where you document the general project timeline and deliverables.

To start, consider the needs of the project and stakeholders. What is it you’re trying to solve? Begin writing a short description of the project and who is involved. 

Once you’ve outlined the basic goals of the project, determine the more concrete objectives in detail.

Pro tip: Use SMART goals when starting your project design to better visualize where you’re going. SMART is an acronym that stands for s pecific, m easurable, a chievable, r ealistic, and t ime-bound. 

 Step 2. Determine outcomes

Next, narrow down the outcomes of the project. These are usually more detailed than the initial goal planning phase and include the specific tasks you will complete during the project.

For example, imagine you’re working on a project to add a new landing page to your website. One of your outcomes may be to add an email signup form. 

Document the outcomes and major deliverables needed alongside the project goals to begin building a timeframe. It’s a good idea to reference popular project management methodologies to decide which one fits the needs of your project. 

Pro tip: For complex projects, use the Agile methodology with iterations to break large tasks into short sprints. For more traditional projects, use the waterfall method which provides a thorough step-by-step approach.

Step 3. Identify risks and constraints

Once you’ve identified the outcomes, consider your project risks and constraints. Evaluate the aspects of your project that could lead to risk in order to prevent wasted resources down the line. 

In order to identify risks and constraints, determine the resource management tools, funds, and timeframe needed. Work to resolve these constraints before the project begins by following up with relevant stakeholders and project teams. 

Pro tip: Use a risk register to analyze, document, and solve project risks that arise. 

Step 4. Refine your project strategy with a visual aid

A project strategy is a visual roadmap of your project . This helps communicate purpose to team members. Create your strategy by choosing a visual aid that you can share with stakeholders. 

There are many types of visual aids you can choose from, some of which include:

Flowchart: A flowchart is a visual representation of the steps and decisions needed to perform a process. Flowcharts are particularly helpful ways to visualize step-by-step approaches and effectively organize project deliverables. 

Gantt chart: A Gantt chart is a horizontal bar chart used to illustrate a timeline of a project. The bars in a Gantt chart represent the steps in the project and the length of the bars represent the amount of time they will take to be completed.

Work breakdown structure (WBS): A WBS is the breakdown of all tasks within a given project. Project managers use work breakdown structures to help teams visualize deliverables while keeping objectives top of mind. 

Mind map: A mind map is a hierarchy diagram used to visualize projects and tasks. It allows project managers to link deliverables around a central concept or idea such as a specific team goal. 

PERT chart: A PERT chart or diagram is a tool used to schedule, organize, and map out tasks. It can be helpful for complex projects and estimating the time needed to complete tasks.

Since each visual tool differs slightly, the aid you choose is up to your team preferences. While a work breakdown structure that details dependencies works well for large teams, a flowchart works well for smaller teams with less complex projects.

Pro tip: Examine the features of components of each of the visual aids before adding one to your project design. You can do this by reviewing each based on the amount of detail included, usability, and visual appearance. This way you can find the one that best fits your needs. 

Step 5. Estimate your budget

Next, estimate your project budget to begin resource allocation . Your budget will incorporate the project’s profitability, resources available, and outsourced work needed. It may also be a set number determined by leadership that you’ll need to work around when it comes to being able to execute each deliverable. 

Your budget may need to be approved or revised based on leadership signoff. Once finalized, you can begin assigning beneficiaries, design documents, and tasks for your project. 

Pro tip: When it comes to resource allocation, implementing automated processes with automation software can improve efficiency and reduce project errors. 

Step 6. Create a contingency plan

To begin assigning tasks, create a contingency plan. A contingency plan is a backup plan for the risks and constraints outlined earlier in the process. Having an organized plan when issues arise helps to resolve them in real time and streamline efficiency. 

To create one, organize your risks using a Gantt chart or timeline tool and determine a plan for each risk. For example, if one of your risks involves materials not arriving in time, your contingency plan may be to source materials from elsewhere or start on a different part of the project while waiting for materials. 

Once you’ve outlined a plan for each risk, you’re ready to begin executing your project. 

Pro tip: Use Asana to view lists, timelines, and Gantt charts to better visualize your project plan . 

Step 7. Document your milestones

For the final step, document your team’s milestones. This is done to ensure work is being completed on time and to easily identify inconsistencies as they arise. 

You can do this using project management software where stakeholders can access the information and progress. It’s a good idea to manage these milestones until the end of the project to ensure tasks are completed on time. 

Pro tip: Connect with project stakeholders frequently to keep track of task dependencies and ensure short term goals are met. 

3 expert tips to improve your project design

Building a project design that improves collaboration and empowers efficiency is no easy task. Along with the seven steps that make up the project design process, here are a few tips that can take your design one step further. 

Keep these three tips in mind when building a project design of your own:

Communicate with stakeholders early and often: Communication is key no matter the project you’re working on. Collaborating early on in the project can ensure all stakeholders are on the same page and understand the most important objectives. You can do this by leading meetings through the entirety of the project and using workflows to streamline teamwork.

Keep your goals top of mind: Connecting your goals to project deliverables can ensure objectives are being met every step of the way. You can do this with the help of timeline software where you can easily connect goals with the work needed to complete them. 

Use visual elements to track milestones: While a business case and daily to-dos are helpful, visual elements help stakeholders see the bigger picture. From Gantt charts to PERT charts, there are a number of ways to visualize your project work. 

Beyond these three tips, always keep your team’s best interests in mind. Providing the necessary information and scheduling work within reasonable deadlines will keep your team engaged and efficient. 

Use project design to tell a story

Project design is an important piece of executing a successful project. From gathering the necessary information and resources to coordinating with team members, your job is to bring the details to life. With the right project design, you and your team can tackle anything that comes your way. 

Take the art of project planning one step further with work management software. From streamlining work to improving visibility, Asana can help your team achieve more with clarity and confidence.

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Ever felt like a hamster on a research wheel fast, spinning with a million questions but going nowhere? You've got your topic; you're brimming with curiosity, but... what next? So, forget the research rut and get your papers! This ultimate guide to "what is research design?" will have you navigating your project like a pro, uncovering answers and avoiding dead ends. Know the features of good research design, what you mean by research design, elements of research design, and more.

What is Research Design?

Before starting with the topic, do you know what is research design? Research design is the structure of research methods and techniques selected to conduct a study. It refines the methods suited to the subject and ensures a successful setup. Defining a research topic clarifies the type of research (experimental, survey research, correlational, semi-experimental, review) and its sub-type (experimental design, research problem, descriptive case-study).

There are three main types of designs for research:

1. Data Collection

2. Measurement

3. Data Analysis

Elements of Research Design 

Now that you know what is research design, it is important to know the elements and components of research design. Impactful research minimises bias and enhances data accuracy. Designs with minimal error margins are ideal. Key elements include:

1. Accurate purpose statement

2. Techniques for data collection and analysis

3. Methods for data analysis

4. Type of research methodology

5. Probable objections to research

6. Research settings

7. Timeline

8. Measurement of analysis

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Characteristics of Research Design

Research design has several key characteristics that contribute to the validity, reliability, and overall success of a research study. To know the answer for what is research design, it is important to know the characteristics. These are-

1. Reliability

A reliable research design ensures that each study’s results are accurate and can be replicated. This means that if the research is conducted again under the same conditions, it should yield similar results.

2. Validity

A valid research design uses appropriate measuring tools to gauge the results according to the research objective. This ensures that the data collected and the conclusions drawn are relevant and accurately reflect the phenomenon being studied.

3. Neutrality

A neutral research design ensures that the assumptions made at the beginning of the research are free from bias. This means that the data collected throughout the research is based on these unbiased assumptions.

4. Generalizability

A good research design draws an outcome that can be applied to a large set of people and is not limited to the sample size or the research group.

Research Design Process

What is research design? A good research helps you do a really good study that gives fair, trustworthy, and useful results. But it's also good to have a bit of wiggle room for changes. If you’re wondering how to conduct a research in just 5 mins , here's a breakdown and examples to work even better.

1. Consider Aims and Approaches

Define the research questions and objectives, and establish the theoretical framework and methodology.

2. Choose a Type of Research Design

Select the suitable research design, such as experimental, correlational, survey, case study, or ethnographic, according to the research questions and objectives.

3. Identify Population and Sampling Method

Determine the target population and sample size, and select the sampling method, like random, stratified random sampling, or convenience sampling.

4. Choose Data Collection Methods

Decide on the data collection methods, such as surveys, interviews, observations, or experiments, and choose the appropriate instruments for data collection.

5. Plan Data Collection Procedures

Create a plan for data collection, detailing the timeframe, location, and personnel involved, while ensuring ethical considerations are met.

6. Decide on Data Analysis Strategies

Select the appropriate data analysis techniques, like statistical analysis, content analysis, or discourse analysis, and plan the interpretation of the results.

What are the Types of Research Design?

A researcher must grasp various types to decide which model to use for a study. There are different research designs that can be broadly classified into quantitative and qualitative.

Qualitative Research

Qualitative research identifies relationships between collected data and observations through mathematical calculations. Statistical methods validate or refute theories about natural phenomena. This research method answers "why" a theory exists and explores respondents' perspectives.

Quantitative Research

Quantitative research is essential when statistical conclusions are needed to gather actionable insights. Numbers provide clarity for critical business decisions. This method is crucial for organizational growth, with insights from complex numerical data guiding future business decisions.

Qualitative Research vs Quantitative Research

While researching, it is important to know the difference between qualitative and quantitative research. Here's a quick difference between the two:

The research types can be further divided into 5 categories:

1. Descriptive Research

Descriptive research design focuses on detailing a situation or case. It's a theory-driven method that involves gathering, analysing, and presenting data. This approach offers insights into the reasons and mechanisms behind a research subject, enhancing understanding of the research's importance. When the problem statement is unclear, exploratory research can be conducted.

2. Experimental Research

Experimental research design investigates cause-and-effect relationships. It’s a causal design where the impact of an independent variable on a dependent variable is observed. For example, the effect of price on customer satisfaction. This method efficiently addresses problems by manipulating independent variables to see their effect on dependent variables. Often used in social sciences, it involves analysing human behaviour by studying changes in one group's actions and their impact on another group.

3. Correlational Research

Correlational research design is a non-experimental technique that identifies relationships between closely linked variables. It uses statistical analysis to determine these relationships without assumptions. This method requires two different groups. A correlation coefficient between -1 and +1 indicates the strength and direction of the relationship, with +1 showing a positive correlation and -1 a negative correlation.

4. Diagnostic Research

Diagnostic research design aims to identify the underlying causes of specific issues. This method delves into factors creating problematic situations and has three phases: 

• Issue inception
• Issue diagnosis
• Issue resolution

5. Explanatory Research

Explanatory research design builds on a researcher’s ideas to explore theories further. It seeks to explain the unexplored aspects of a subject, addressing the what, how, and why of research questions.

Benefits of Research Design

After learning about what is research design and the process, it is important to know the key benefits of a well-structured research design:

1. Minimises Risk of Errors: A good research design minimises the risk of errors and reduces inaccuracy. It ensures that the study is carried out in the right direction and that all the team members are on the same page.

2. Efficient Use of Resources: It facilitates a concrete research plan for the efficient use of time and resources. It helps the researcher better complete all the tasks, even with limited resources.

3. Provides Direction: The purpose of the research design is to enable the researcher to proceed in the right direction without deviating from the tasks. It helps to identify the major and minor tasks of the study.

4. Ensures Validity and Reliability: A well-designed research enhances the validity and reliability of the findings and allows for the replication of studies by other researchers. The main advantage of a good research design is that it provides accuracy, reliability, consistency, and legitimacy to the research.

5. Facilitates Problem-Solving: A researcher can easily frame the objectives of the research work based on the design of experiments (research design). A good research design helps the researcher find the best solution for the research problems.

6. Better Documentation: It helps in better documentation of the various activities while the project work is going on.

That's it! You've explored all the answers for what is research design in research? Remember, it's not just about picking a fancy method – it's about choosing the perfect tool to answer your burning questions. By carefully considering your goals and resources, you can design a research plan that gathers reliable information and helps you reach clear conclusions. 

Frequently Asked Questions

What are the key components of a research design, how can i choose the best research design for my study, what are some common pitfalls in research design, and how can they be avoided, how does research design impact the validity and reliability of a study, what ethical considerations should be taken into account in research design.

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Home » Research Project – Definition, Writing Guide and Ideas

Research Project – Definition, Writing Guide and Ideas

Table of Contents

Research Project

Definition :

Research Project is a planned and systematic investigation into a specific area of interest or problem, with the goal of generating new knowledge, insights, or solutions. It typically involves identifying a research question or hypothesis, designing a study to test it, collecting and analyzing data, and drawing conclusions based on the findings.

Types of Research Project

Types of Research Projects are as follows:

Basic Research

This type of research focuses on advancing knowledge and understanding of a subject area or phenomenon, without any specific application or practical use in mind. The primary goal is to expand scientific or theoretical knowledge in a particular field.

Applied Research

Applied research is aimed at solving practical problems or addressing specific issues. This type of research seeks to develop solutions or improve existing products, services or processes.

Action Research

Action research is conducted by practitioners and aimed at solving specific problems or improving practices in a particular context. It involves collaboration between researchers and practitioners, and often involves iterative cycles of data collection and analysis, with the goal of improving practices.

Quantitative Research

This type of research uses numerical data to investigate relationships between variables or to test hypotheses. It typically involves large-scale data collection through surveys, experiments, or secondary data analysis.

Qualitative Research

Qualitative research focuses on understanding and interpreting phenomena from the perspective of the people involved. It involves collecting and analyzing data in the form of text, images, or other non-numerical forms.

Mixed Methods Research

Mixed methods research combines elements of both quantitative and qualitative research, using multiple data sources and methods to gain a more comprehensive understanding of a phenomenon.

Longitudinal Research

This type of research involves studying a group of individuals or phenomena over an extended period of time, often years or decades. It is useful for understanding changes and developments over time.

Case Study Research

Case study research involves in-depth investigation of a particular case or phenomenon, often within a specific context. It is useful for understanding complex phenomena in their real-life settings.

Participatory Research

Participatory research involves active involvement of the people or communities being studied in the research process. It emphasizes collaboration, empowerment, and the co-production of knowledge.

Research Project Methodology

Research Project Methodology refers to the process of conducting research in an organized and systematic manner to answer a specific research question or to test a hypothesis. A well-designed research project methodology ensures that the research is rigorous, valid, and reliable, and that the findings are meaningful and can be used to inform decision-making.

There are several steps involved in research project methodology, which are described below:

Define the Research Question

The first step in any research project is to clearly define the research question or problem. This involves identifying the purpose of the research, the scope of the research, and the key variables that will be studied.

Develop a Research Plan

Once the research question has been defined, the next step is to develop a research plan. This plan outlines the methodology that will be used to collect and analyze data, including the research design, sampling strategy, data collection methods, and data analysis techniques.

Collect Data

The data collection phase involves gathering information through various methods, such as surveys, interviews, observations, experiments, or secondary data analysis. The data collected should be relevant to the research question and should be of sufficient quantity and quality to enable meaningful analysis.

Analyze Data

Once the data has been collected, it is analyzed using appropriate statistical techniques or other methods. The analysis should be guided by the research question and should aim to identify patterns, trends, relationships, or other insights that can inform the research findings.

Interpret and Report Findings

The final step in the research project methodology is to interpret the findings and report them in a clear and concise manner. This involves summarizing the results, discussing their implications, and drawing conclusions that can be used to inform decision-making.

Research Project Writing Guide

Here are some guidelines to help you in writing a successful research project:

• Choose a topic: Choose a topic that you are interested in and that is relevant to your field of study. It is important to choose a topic that is specific and focused enough to allow for in-depth research and analysis.
• Conduct a literature review : Conduct a thorough review of the existing research on your topic. This will help you to identify gaps in the literature and to develop a research question or hypothesis.
• Develop a research question or hypothesis : Based on your literature review, develop a clear research question or hypothesis that you will investigate in your study.
• Design your study: Choose an appropriate research design and methodology to answer your research question or test your hypothesis. This may include choosing a sample, selecting measures or instruments, and determining data collection methods.
• Collect data: Collect data using your chosen methods and instruments. Be sure to follow ethical guidelines and obtain informed consent from participants if necessary.
• Analyze data: Analyze your data using appropriate statistical or qualitative methods. Be sure to clearly report your findings and provide interpretations based on your research question or hypothesis.
• Discuss your findings : Discuss your findings in the context of the existing literature and your research question or hypothesis. Identify any limitations or implications of your study and suggest directions for future research.
• Write your project: Write your research project in a clear and organized manner, following the appropriate format and style guidelines for your field of study. Be sure to include an introduction, literature review, methodology, results, discussion, and conclusion.
• Revise and edit: Revise and edit your project for clarity, coherence, and accuracy. Be sure to proofread for spelling, grammar, and formatting errors.
• Cite your sources: Cite your sources accurately and appropriately using the appropriate citation style for your field of study.

Examples of Research Projects

Some Examples of Research Projects are as follows:

• Investigating the effects of a new medication on patients with a particular disease or condition.
• Exploring the impact of exercise on mental health and well-being.
• Studying the effectiveness of a new teaching method in improving student learning outcomes.
• Examining the impact of social media on political participation and engagement.
• Investigating the efficacy of a new therapy for a specific mental health disorder.
• Exploring the use of renewable energy sources in reducing carbon emissions and mitigating climate change.
• Studying the effects of a new agricultural technique on crop yields and environmental sustainability.
• Investigating the effectiveness of a new technology in improving business productivity and efficiency.
• Examining the impact of a new public policy on social inequality and access to resources.
• Exploring the factors that influence consumer behavior in a specific market.

Characteristics of Research Project

Here are some of the characteristics that are often associated with research projects:

• Clear objective: A research project is designed to answer a specific question or solve a particular problem. The objective of the research should be clearly defined from the outset.
• Systematic approach: A research project is typically carried out using a structured and systematic approach that involves careful planning, data collection, analysis, and interpretation.
• Rigorous methodology: A research project should employ a rigorous methodology that is appropriate for the research question being investigated. This may involve the use of statistical analysis, surveys, experiments, or other methods.
• Data collection : A research project involves collecting data from a variety of sources, including primary sources (such as surveys or experiments) and secondary sources (such as published literature or databases).
• Analysis and interpretation : Once the data has been collected, it needs to be analyzed and interpreted. This involves using statistical techniques or other methods to identify patterns or relationships in the data.
• Conclusion and implications : A research project should lead to a clear conclusion that answers the research question. It should also identify the implications of the findings for future research or practice.
• Communication: The results of the research project should be communicated clearly and effectively, using appropriate language and visual aids, to a range of audiences, including peers, stakeholders, and the wider public.

Importance of Research Project

Research projects are an essential part of the process of generating new knowledge and advancing our understanding of various fields of study. Here are some of the key reasons why research projects are important:

• Advancing knowledge : Research projects are designed to generate new knowledge and insights into particular topics or questions. This knowledge can be used to inform policies, practices, and decision-making processes across a range of fields.
• Solving problems: Research projects can help to identify solutions to real-world problems by providing a better understanding of the causes and effects of particular issues.
• Developing new technologies: Research projects can lead to the development of new technologies or products that can improve people’s lives or address societal challenges.
• Improving health outcomes: Research projects can contribute to improving health outcomes by identifying new treatments, diagnostic tools, or preventive strategies.
• Enhancing education: Research projects can enhance education by providing new insights into teaching and learning methods, curriculum development, and student learning outcomes.
• Informing public policy : Research projects can inform public policy by providing evidence-based recommendations and guidance on issues related to health, education, environment, social justice, and other areas.
• Enhancing professional development : Research projects can enhance the professional development of researchers by providing opportunities to develop new skills, collaborate with colleagues, and share knowledge with others.

Research Project Ideas

Following are some Research Project Ideas:

Field: Psychology

• Investigating the impact of social support on coping strategies among individuals with chronic illnesses.
• Exploring the relationship between childhood trauma and adult attachment styles.
• Examining the effects of exercise on cognitive function and brain health in older adults.
• Investigating the impact of sleep deprivation on decision making and risk-taking behavior.
• Exploring the relationship between personality traits and leadership styles in the workplace.
• Examining the effectiveness of cognitive-behavioral therapy (CBT) for treating anxiety disorders.
• Investigating the relationship between social comparison and body dissatisfaction in young women.
• Exploring the impact of parenting styles on children’s emotional regulation and behavior.
• Investigating the effectiveness of mindfulness-based interventions for treating depression.
• Examining the relationship between childhood adversity and later-life health outcomes.

Field: Economics

• Analyzing the impact of trade agreements on economic growth in developing countries.
• Examining the effects of tax policy on income distribution and poverty reduction.
• Investigating the relationship between foreign aid and economic development in low-income countries.
• Exploring the impact of globalization on labor markets and job displacement.
• Analyzing the impact of minimum wage laws on employment and income levels.
• Investigating the effectiveness of monetary policy in managing inflation and unemployment.
• Examining the relationship between economic freedom and entrepreneurship.
• Analyzing the impact of income inequality on social mobility and economic opportunity.
• Investigating the role of education in economic development.
• Examining the effectiveness of different healthcare financing systems in promoting health equity.

Field: Sociology

• Investigating the impact of social media on political polarization and civic engagement.
• Examining the effects of neighborhood characteristics on health outcomes.
• Analyzing the impact of immigration policies on social integration and cultural diversity.
• Investigating the relationship between social support and mental health outcomes in older adults.
• Exploring the impact of income inequality on social cohesion and trust.
• Analyzing the effects of gender and race discrimination on career advancement and pay equity.
• Investigating the relationship between social networks and health behaviors.
• Examining the effectiveness of community-based interventions for reducing crime and violence.
• Analyzing the impact of social class on cultural consumption and taste.
• Investigating the relationship between religious affiliation and social attitudes.

Field: Computer Science

• Developing an algorithm for detecting fake news on social media.
• Investigating the effectiveness of different machine learning algorithms for image recognition.
• Developing a natural language processing tool for sentiment analysis of customer reviews.
• Analyzing the security implications of blockchain technology for online transactions.
• Investigating the effectiveness of different recommendation algorithms for personalized advertising.
• Developing an artificial intelligence chatbot for mental health counseling.
• Investigating the effectiveness of different algorithms for optimizing online advertising campaigns.
• Developing a machine learning model for predicting consumer behavior in online marketplaces.
• Analyzing the privacy implications of different data sharing policies for online platforms.
• Investigating the effectiveness of different algorithms for predicting stock market trends.

Field: Education

• Investigating the impact of teacher-student relationships on academic achievement.
• Analyzing the effectiveness of different pedagogical approaches for promoting student engagement and motivation.
• Examining the effects of school choice policies on academic achievement and social mobility.
• Investigating the impact of technology on learning outcomes and academic achievement.
• Analyzing the effects of school funding disparities on educational equity and achievement gaps.
• Investigating the relationship between school climate and student mental health outcomes.
• Examining the effectiveness of different teaching strategies for promoting critical thinking and problem-solving skills.
• Investigating the impact of social-emotional learning programs on student behavior and academic achievement.
• Analyzing the effects of standardized testing on student motivation and academic achievement.

Field: Environmental Science

• Investigating the impact of climate change on species distribution and biodiversity.
• Analyzing the effectiveness of different renewable energy technologies in reducing carbon emissions.
• Examining the impact of air pollution on human health outcomes.
• Investigating the relationship between urbanization and deforestation in developing countries.
• Analyzing the effects of ocean acidification on marine ecosystems and biodiversity.
• Investigating the impact of land use change on soil fertility and ecosystem services.
• Analyzing the effectiveness of different conservation policies and programs for protecting endangered species and habitats.
• Investigating the relationship between climate change and water resources in arid regions.
• Examining the impact of plastic pollution on marine ecosystems and biodiversity.
• Investigating the effects of different agricultural practices on soil health and nutrient cycling.

Field: Linguistics

• Analyzing the impact of language diversity on social integration and cultural identity.
• Investigating the relationship between language and cognition in bilingual individuals.
• Examining the effects of language contact and language change on linguistic diversity.
• Investigating the role of language in shaping cultural norms and values.
• Analyzing the effectiveness of different language teaching methodologies for second language acquisition.
• Investigating the relationship between language proficiency and academic achievement.
• Examining the impact of language policy on language use and language attitudes.
• Investigating the role of language in shaping gender and social identities.
• Analyzing the effects of dialect contact on language variation and change.
• Investigating the relationship between language and emotion expression.

Field: Political Science

• Analyzing the impact of electoral systems on women’s political representation.
• Investigating the relationship between political ideology and attitudes towards immigration.
• Examining the effects of political polarization on democratic institutions and political stability.
• Investigating the impact of social media on political participation and civic engagement.
• Analyzing the effects of authoritarianism on human rights and civil liberties.
• Investigating the relationship between public opinion and foreign policy decisions.
• Examining the impact of international organizations on global governance and cooperation.
• Investigating the effectiveness of different conflict resolution strategies in resolving ethnic and religious conflicts.
• Analyzing the effects of corruption on economic development and political stability.
• Investigating the role of international law in regulating global governance and human rights.

Field: Medicine

• Investigating the impact of lifestyle factors on chronic disease risk and prevention.
• Examining the effectiveness of different treatment approaches for mental health disorders.
• Investigating the relationship between genetics and disease susceptibility.
• Analyzing the effects of social determinants of health on health outcomes and health disparities.
• Investigating the impact of different healthcare delivery models on patient outcomes and cost effectiveness.
• Examining the effectiveness of different prevention and treatment strategies for infectious diseases.
• Investigating the relationship between healthcare provider communication skills and patient satisfaction and outcomes.
• Analyzing the effects of medical error and patient safety on healthcare quality and outcomes.
• Investigating the impact of different pharmaceutical pricing policies on access to essential medicines.
• Examining the effectiveness of different rehabilitation approaches for improving function and quality of life in individuals with disabilities.

Field: Anthropology

• Analyzing the impact of colonialism on indigenous cultures and identities.
• Investigating the relationship between cultural practices and health outcomes in different populations.
• Examining the effects of globalization on cultural diversity and cultural exchange.
• Investigating the role of language in cultural transmission and preservation.
• Analyzing the effects of cultural contact on cultural change and adaptation.
• Investigating the impact of different migration policies on immigrant integration and acculturation.
• Examining the role of gender and sexuality in cultural norms and values.
• Investigating the impact of cultural heritage preservation on tourism and economic development.
• Analyzing the effects of cultural revitalization movements on indigenous communities.

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• Knowledge Base
• Methodology

Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

• Your overall aims and approach
• The type of research design you’ll use
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

Prevent plagiarism, run a free check.

Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

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

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

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What Is a Research Design? | Definition, Types & Guide

Introduction

Parts of a research design, types of research methodology in qualitative research, narrative research designs, phenomenological research designs, grounded theory research designs.

• Ethnographic research designs

Case study research design

Important reminders when designing a research study.

A research design in qualitative research is a critical framework that guides the methodological approach to studying complex social phenomena. Qualitative research designs determine how data is collected, analyzed, and interpreted, ensuring that the research captures participants' nuanced and subjective perspectives. Research designs also recognize ethical considerations and involve informed consent, ensuring confidentiality, and handling sensitive topics with the utmost respect and care. These considerations are crucial in qualitative research and other contexts where participants may share personal or sensitive information. A research design should convey coherence as it is essential for producing high-quality qualitative research, often following a recursive and evolving process.

Theoretical concepts and research question

The first step in creating a research design is identifying the main theoretical concepts. To identify these concepts, a researcher should ask which theoretical keywords are implicit in the investigation. The next step is to develop a research question using these theoretical concepts. This can be done by identifying the relationship of interest among the concepts that catch the focus of the investigation. The question should address aspects of the topic that need more knowledge, shed light on new information, and specify which aspects should be prioritized before others. This step is essential in identifying which participants to include or which data collection methods to use. Research questions also put into practice the conceptual framework and make the initial theoretical concepts more explicit. Once the research question has been established, the main objectives of the research can be specified. For example, these objectives may involve identifying shared experiences around a phenomenon or evaluating perceptions of a new treatment.

Methodology

After identifying the theoretical concepts, research question, and objectives, the next step is to determine the methodology that will be implemented. This is the lifeline of a research design and should be coherent with the objectives and questions of the study. The methodology will determine how data is collected, analyzed, and presented. Popular qualitative research methodologies include case studies, ethnography , grounded theory , phenomenology, and narrative research . Each methodology is tailored to specific research questions and facilitates the collection of rich, detailed data. For example, a narrative approach may focus on only one individual and their story, while phenomenology seeks to understand participants' lived common experiences. Qualitative research designs differ significantly from quantitative research, which often involves experimental research, correlational designs, or variance analysis to test hypotheses about relationships between two variables, a dependent variable and an independent variable while controlling for confounding variables.

Literature review

After the methodology is identified, conducting a thorough literature review is integral to the research design. This review identifies gaps in knowledge, positioning the new study within the larger academic dialogue and underlining its contribution and relevance. Meta-analysis, a form of secondary research, can be particularly useful in synthesizing findings from multiple studies to provide a clear picture of the research landscape.

Data collection

The sampling method in qualitative research is designed to delve deeply into specific phenomena rather than to generalize findings across a broader population. The data collection methods—whether interviews, focus groups, observations, or document analysis—should align with the chosen methodology, ethical considerations, and other factors such as sample size. In some cases, repeated measures may be collected to observe changes over time.

Data analysis

Analysis in qualitative research typically involves methods such as coding and thematic analysis to distill patterns from the collected data. This process delineates how the research results will be systematically derived from the data. It is recommended that the researcher ensures that the final interpretations are coherent with the observations and analyses, making clear connections between the data and the conclusions drawn. Reporting should be narrative-rich, offering a comprehensive view of the context and findings.

Overall, a coherent qualitative research design that incorporates these elements facilitates a study that not only adds theoretical and practical value to the field but also adheres to high quality. This methodological thoroughness is essential for achieving significant, insightful findings. Examples of well-executed research designs can be valuable references for other researchers conducting qualitative or quantitative investigations. An effective research design is critical for producing robust and impactful research outcomes.

Each qualitative research design is unique, diverse, and meticulously tailored to answer specific research questions, meet distinct objectives, and explore the unique nature of the phenomenon under investigation. The methodology is the wider framework that a research design follows. Each methodology in a research design consists of methods, tools, or techniques that compile data and analyze it following a specific approach.

The methods enable researchers to collect data effectively across individuals, different groups, or observations, ensuring they are aligned with the research design. The following list includes the most commonly used methodologies employed in qualitative research designs, highlighting how they serve different purposes and utilize distinct methods to gather and analyze data.

The narrative approach in research focuses on the collection and detailed examination of life stories, personal experiences, or narratives to gain insights into individuals' lives as told from their perspectives. It involves constructing a cohesive story out of the diverse experiences shared by participants, often using chronological accounts. It seeks to understand human experience and social phenomena through the form and content of the stories. These can include spontaneous narrations such as memoirs or diaries from participants or diaries solicited by the researcher. Narration helps construct the identity of an individual or a group and can rationalize, persuade, argue, entertain, confront, or make sense of an event or tragedy. To conduct a narrative investigation, it is recommended that researchers follow these steps:

Identify if the research question fits the narrative approach. Its methods are best employed when a researcher wants to learn about the lifestyle and life experience of a single participant or a small number of individuals.

Select the best-suited participants for the research design and spend time compiling their stories using different methods such as observations, diaries, interviewing their family members, or compiling related secondary sources.

Compile the information related to the stories. Narrative researchers collect data based on participants' stories concerning their personal experiences, for example about their workplace or homes, their racial or ethnic culture, and the historical context in which the stories occur.

Analyze the participant stories and "restore" them within a coherent framework. This involves collecting the stories, analyzing them based on key elements such as time, place, plot, and scene, and then rewriting them in a chronological sequence (Ollerenshaw & Creswell, 2000). The framework may also include elements such as a predicament, conflict, or struggle; a protagonist; and a sequence with implicit causality, where the predicament is somehow resolved (Carter, 1993).

Collaborate with participants by actively involving them in the research. Both the researcher and the participant negotiate the meaning of their stories, adding a credibility check to the analysis (Creswell & Miller, 2000).

A narrative investigation includes collecting a large amount of data from the participants and the researcher needs to understand the context of the individual's life. A keen eye is needed to collect particular stories that capture the individual experiences. Active collaboration with the participant is necessary, and researchers need to discuss and reflect on their own beliefs and backgrounds. Multiple questions could arise in the collection, analysis, and storytelling of individual stories that need to be addressed, such as: Whose story is it? Who can tell it? Who can change it? Which version is compelling? What happens when narratives compete? In a community, what do the stories do among them? (Pinnegar & Daynes, 2006).

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A research design based on phenomenology aims to understand the essence of the lived experiences of a group of people regarding a particular concept or phenomenon. Researchers gather deep insights from individuals who have experienced the phenomenon, striving to describe "what" they experienced and "how" they experienced it. This approach to a research design typically involves detailed interviews and aims to reach a deep existential understanding. The purpose is to reduce individual experiences to a description of the universal essence or understanding the phenomenon's nature (van Manen, 1990). In phenomenology, the following steps are usually followed:

Identify a phenomenon of interest . For example, the phenomenon might be anger, professionalism in the workplace, or what it means to be a fighter.

Recognize and specify the philosophical assumptions of phenomenology , for example, one could reflect on the nature of objective reality and individual experiences.

Collect data from individuals who have experienced the phenomenon . This typically involves conducting in-depth interviews, including multiple sessions with each participant. Additionally, other forms of data may be collected using several methods, such as observations, diaries, art, poetry, music, recorded conversations, written responses, or other secondary sources.

Ask participants two general questions that encompass the phenomenon and how the participant experienced it (Moustakas, 1994). For example, what have you experienced in this phenomenon? And what contexts or situations have typically influenced your experiences within the phenomenon? Other open-ended questions may also be asked, but these two questions particularly focus on collecting research data that will lead to a textural description and a structural description of the experiences, and ultimately provide an understanding of the common experiences of the participants.

Review data from the questions posed to participants . It is recommended that researchers review the answers and highlight "significant statements," phrases, or quotes that explain how participants experienced the phenomenon. The researcher can then develop meaningful clusters from these significant statements into patterns or key elements shared across participants.

Write a textual description of what the participants experienced based on the answers and themes of the two main questions. The answers are also used to write about the characteristics and describe the context that influenced the way the participants experienced the phenomenon, called imaginative variation or structural description. Researchers should also write about their own experiences and context or situations that influenced them.

Write a composite description from the structural and textural description that presents the "essence" of the phenomenon, called the essential and invariant structure.

A phenomenological approach to a research design includes the strict and careful selection of participants in the study where bracketing personal experiences can be difficult to implement. The researcher decides how and in which way their knowledge will be introduced. It also involves some understanding and identification of the broader philosophical assumptions.

Grounded theory is used in a research design when the goal is to inductively develop a theory "grounded" in data that has been systematically gathered and analyzed. Starting from the data collection, researchers identify characteristics, patterns, themes, and relationships, gradually forming a theoretical framework that explains relevant processes, actions, or interactions grounded in the observed reality. A grounded theory study goes beyond descriptions and its objective is to generate a theory, an abstract analytical scheme of a process. Developing a theory doesn't come "out of nothing" but it is constructed and based on clear data collection. We suggest the following steps to follow a grounded theory approach in a research design:

Determine if grounded theory is the best for your research problem . Grounded theory is a good design when a theory is not already available to explain a process.

Develop questions that aim to understand how individuals experienced or enacted the process (e.g., What was the process? How did it unfold?). Data collection and analysis occur in tandem, so that researchers can ask more detailed questions that shape further analysis, such as: What was the focal point of the process (central phenomenon)? What influenced or caused this phenomenon to occur (causal conditions)? What strategies were employed during the process? What effect did it have (consequences)?

Gather relevant data about the topic in question . Data gathering involves questions that are usually asked in interviews, although other forms of data can also be collected, such as observations, documents, and audio-visual materials from different groups.

Carry out the analysis in stages . Grounded theory analysis begins with open coding, where the researcher forms codes that inductively emerge from the data (rather than preconceived categories). Researchers can thus identify specific properties and dimensions relevant to their research question.

Assemble the data in new ways and proceed to axial coding . Axial coding involves using a coding paradigm or logic diagram, such as a visual model, to systematically analyze the data. Begin by identifying a central phenomenon, which is the main category or focus of the research problem. Next, explore the causal conditions, which are the categories of factors that influence the phenomenon. Specify the strategies, which are the actions or interactions associated with the phenomenon. Then, identify the context and intervening conditions—both narrow and broad factors that affect the strategies. Finally, delineate the consequences, which are the outcomes or results of employing the strategies.

Use selective coding to construct a "storyline" that links the categories together. Alternatively, the researcher may formulate propositions or theory-driven questions that specify predicted relationships among these categories.

Develop and visually present a matrix that clarifies the social, historical, and economic conditions influencing the central phenomenon. This optional step encourages viewing the model from the narrowest to the broadest perspective.

Write a substantive-level theory that is closely related to a specific problem or population. This step is optional but provides a focused theoretical framework that can later be tested with quantitative data to explore its generalizability to a broader sample.

Allow theory to emerge through the memo-writing process, where ideas about the theory evolve continuously throughout the stages of open, axial, and selective coding.

The researcher should initially set aside any preconceived theoretical ideas to allow for the emergence of analytical and substantive theories. This is a systematic research approach, particularly when following the methodological steps outlined by Strauss and Corbin (1990). For those seeking more flexibility in their research process, the approach suggested by Charmaz (2006) might be preferable.

One of the challenges when using this method in a research design is determining when categories are sufficiently saturated and when the theory is detailed enough. To achieve saturation, discriminant sampling may be employed, where additional information is gathered from individuals similar to those initially interviewed to verify the applicability of the theory to these new participants. Ultimately, its goal is to develop a theory that comprehensively describes the central phenomenon, causal conditions, strategies, context, and consequences.

Ethnographic research design

An ethnographic approach in research design involves the extended observation and data collection of a group or community. The researcher immerses themselves in the setting, often living within the community for long periods. During this time, they collect data by observing and recording behaviours, conversations, and rituals to understand the group's social dynamics and cultural norms. We suggest following these steps for ethnographic methods in a research design:

Assess whether ethnography is the best approach for the research design and questions. It's suitable if the goal is to describe how a cultural group functions and to delve into their beliefs, language, behaviours, and issues like power, resistance, and domination, particularly if there is limited literature due to the group’s marginal status or unfamiliarity to mainstream society.

Identify and select a cultural group for your research design. Choose one that has a long history together, forming distinct languages, behaviours, and attitudes. This group often might be marginalized within society.

Choose cultural themes or issues to examine within the group. Analyze interactions in everyday settings to identify pervasive patterns such as life cycles, events, and overarching cultural themes. Culture is inferred from the group members' words, actions, and the tension between their actual and expected behaviours, as well as the artifacts they use.

Conduct fieldwork to gather detailed information about the group’s living and working environments. Visit the site, respect the daily lives of the members, and collect a diverse range of materials, considering ethical aspects such as respect and reciprocity.

Compile and analyze cultural data to develop a set of descriptive and thematic insights. Begin with a detailed description of the group based on observations of specific events or activities over time. Then, conduct a thematic analysis to identify patterns or themes that illustrate how the group functions and lives. The final output should be a comprehensive cultural portrait that integrates both the participants (emic) and the researcher’s (etic) perspectives, potentially advocating for the group’s needs or suggesting societal changes to better accommodate them.

Researchers engaging in ethnography need a solid understanding of cultural anthropology and the dynamics of sociocultural systems, which are commonly explored in ethnographic research. The data collection phase is notably extensive, requiring prolonged periods in the field. Ethnographers often employ a literary, quasi-narrative style in their narratives, which can pose challenges for those accustomed to more conventional social science writing methods.

Another potential issue is the risk of researchers "going native," where they become overly assimilated into the community under study, potentially jeopardizing the objectivity and completion of their research. It's crucial for researchers to be aware of their impact on the communities and environments they are studying.

The case study approach in a research design focuses on a detailed examination of a single case or a small number of cases. Cases can be individuals, groups, organizations, or events. Case studies are particularly useful for research designs that aim to understand complex issues in real-life contexts. The aim is to provide a thorough description and contextual analysis of the cases under investigation. We suggest following these steps in a case study design:

Assess if a case study approach suits your research questions . This approach works well when you have distinct cases with defined boundaries and aim to deeply understand these cases or compare multiple cases.

Choose your case or cases. These could involve individuals, groups, programs, events, or activities. Decide whether an individual or collective, multi-site or single-site case study is most appropriate, focusing on specific cases or themes (Stake, 1995; Yin, 2003).

Gather data extensively from diverse sources . Collect information through archival records, interviews, direct and participant observations, and physical artifacts (Yin, 2003).

Analyze the data holistically or in focused segments . Provide a comprehensive overview of the entire case or concentrate on specific aspects. Start with a detailed description including the history of the case and its chronological events then narrow down to key themes. The aim is to delve into the case's complexity rather than generalize findings.

Interpret and report the significance of the case in the final phase . Explain what insights were gained, whether about the subject of the case in an instrumental study or an unusual situation in an intrinsic study (Lincoln & Guba, 1985).

The investigator must carefully select the case or cases to study, recognizing that multiple potential cases could illustrate a chosen topic or issue. This selection process involves deciding whether to focus on a single case for deeper analysis or multiple cases, which may provide broader insights but less depth per case. Each choice requires a well-justified rationale for the selected cases. Researchers face the challenge of defining the boundaries of a case, such as its temporal scope and the events and processes involved. This decision in a research design is crucial as it affects the depth and value of the information presented in the study, and therefore should be planned to ensure a comprehensive portrayal of the case.

Qualitative and quantitative research designs are distinct in their approach to data collection and data analysis. Unlike quantitative research, which focuses on numerical data and statistical analysis, qualitative research prioritizes understanding the depth and richness of human experiences, behaviours, and interactions.

Qualitative methods in a research design have to have internal coherence, meaning that all elements of the research project—research question, data collection, data analysis, findings, and theory—are well-aligned and consistent with each other. This coherence in the research study is especially crucial in inductive qualitative research, where the research process often follows a recursive and evolving path. Ensuring that each component of the research design fits seamlessly with the others enhances the clarity and impact of the study, making the research findings more robust and compelling. Whether it is a descriptive research design, explanatory research design, diagnostic research design, or correlational research design coherence is an important element in both qualitative and quantitative research.

Finally, a good research design ensures that the research is conducted ethically and considers the well-being and rights of participants when managing collected data. The research design guides researchers in providing a clear rationale for their methodologies, which is crucial for justifying the research objectives to the scientific community. A thorough research design also contributes to the body of knowledge, enabling researchers to build upon past research studies and explore new dimensions within their fields. At the core of the design, there is a clear articulation of the research objectives. These objectives should be aligned with the underlying concepts being investigated, offering a concise method to answer the research questions and guiding the direction of the study with proper qualitative methods.

Carter, K. (1993). The place of a story in the study of teaching and teacher education. Educational Researcher, 22(1), 5-12, 18.

Charmaz, K. (2006). Constructing grounded theory. London: Sage.

Creswell, J. W., & Miller, D. L. (2000). Determining validity in qualitative inquiry. Theory Into Practice, 39(3), 124-130.

Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Newbury Park, CA: Sage.

Moustakas, C. (1994). Phenomenological research methods. Thousand Oaks, CA: Sage.

Ollerenshaw, J. A., & Creswell, J. W. (2000, April). Data analysis in narrative research: A comparison of two “restoring” approaches. Paper presented at the annual meeting of the American Educational Research Association, New Orleans, LA.

Stake, R. E. (1995). The art of case study research. Thousand Oaks, CA: Sage.

Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques. Newbury Park, CA: Sage.

van Manen, M. (1990). Researching lived experience: Human science for an action sensitive pedagogy. Ontario, Canada: University of Western Ontario.

Yin, R. K. (2003). Case study research: Design and methods (3rd ed.). Thousand Oaks, CA: Sage

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What is Research Design? Understand Types of Research Design, with Examples

Have you been wondering “ what is research design ?” or “what are some research design examples ?” Are you unsure about the research design elements or which of the different types of research design best suit your study? Don’t worry! In this article, we’ve got you covered!   

Table of Contents

What is research design?  

Have you been wondering “ what is research design ?” or “what are some research design examples ?” Don’t worry! In this article, we’ve got you covered!  

A research design is the plan or framework used to conduct a research study. It involves outlining the overall approach and methods that will be used to collect and analyze data in order to answer research questions or test hypotheses. A well-designed research study should have a clear and well-defined research question, a detailed plan for collecting data, and a method for analyzing and interpreting the results. A well-thought-out research design addresses all these features.  

Research design elements  

Research design elements include the following:  

• Clear purpose: The research question or hypothesis must be clearly defined and focused.  
• Sampling: This includes decisions about sample size, sampling method, and criteria for inclusion or exclusion. The approach varies for different research design types .  
• Data collection: This research design element involves the process of gathering data or information from the study participants or sources. It includes decisions about what data to collect, how to collect it, and the tools or instruments that will be used.  
• Data analysis: All research design types require analysis and interpretation of the data collected. This research design element includes decisions about the statistical tests or methods that will be used to analyze the data, as well as any potential confounding variables or biases that may need to be addressed.  
• Type of research methodology: This includes decisions about the overall approach for the study.  
• Time frame: An important research design element is the time frame, which includes decisions about the duration of the study, the timeline for data collection and analysis, and follow-up periods.  
• Ethical considerations: The research design must include decisions about ethical considerations such as informed consent, confidentiality, and participant protection.  
• Resources: A good research design takes into account decisions about the budget, staffing, and other resources needed to carry out the study.  

The elements of research design should be carefully planned and executed to ensure the validity and reliability of the study findings. Let’s go deeper into the concepts of research design .    

Characteristics of research design  

Some basic characteristics of research design are common to different research design types . These characteristics of research design are as follows:  

• Neutrality : Right from the study assumptions to setting up the study, a neutral stance must be maintained, free of pre-conceived notions. The researcher’s expectations or beliefs should not color the findings or interpretation of the findings. Accordingly, a good research design should address potential sources of bias and confounding factors to be able to yield unbiased and neutral results.   
•   Reliability : Reliability is one of the characteristics of research design that refers to consistency in measurement over repeated measures and fewer random errors. A reliable research design must allow for results to be consistent, with few errors due to chance.   
•   Validity : Validity refers to the minimization of nonrandom (systematic) errors. A good research design must employ measurement tools that ensure validity of the results.  
•   Generalizability: The outcome of the research design should be applicable to a larger population and not just a small sample . A generalized method means the study can be conducted on any part of a population with similar accuracy.   
•   Flexibility: A research design should allow for changes to be made to the research plan as needed, based on the data collected and the outcomes of the study  

A well-planned research design is critical for conducting a scientifically rigorous study that will generate neutral, reliable, valid, and generalizable results. At the same time, it should allow some level of flexibility.  

Different types of research design  

A research design is essential to systematically investigate, understand, and interpret phenomena of interest. Let’s look at different types of research design and research design examples .  

Broadly, research design types can be divided into qualitative and quantitative research.  

Qualitative research is subjective and exploratory. It determines relationships between collected data and observations. It is usually carried out through interviews with open-ended questions, observations that are described in words, etc.  

Quantitative research is objective and employs statistical approaches. It establishes the cause-and-effect relationship among variables using different statistical and computational methods. This type of research is usually done using surveys and experiments.  

Qualitative research vs. Quantitative research  

Qualitative research design types and qualitative research design examples  

The following will familiarize you with the research design categories in qualitative research:  

• Grounded theory: This design is used to investigate research questions that have not previously been studied in depth. Also referred to as exploratory design , it creates sequential guidelines, offers strategies for inquiry, and makes data collection and analysis more efficient in qualitative research.   

Example: A researcher wants to study how people adopt a certain app. The researcher collects data through interviews and then analyzes the data to look for patterns. These patterns are used to develop a theory about how people adopt that app.  

•   Thematic analysis: This design is used to compare the data collected in past research to find similar themes in qualitative research.  

Example: A researcher examines an interview transcript to identify common themes, say, topics or patterns emerging repeatedly.  

• Discourse analysis : This research design deals with language or social contexts used in data gathering in qualitative research.   

Example: Identifying ideological frameworks and viewpoints of writers of a series of policies.  

Quantitative research design types and quantitative research design examples  

Note the following research design categories in quantitative research:  

• Descriptive research design : This quantitative research design is applied where the aim is to identify characteristics, frequencies, trends, and categories. It may not often begin with a hypothesis. The basis of this research type is a description of an identified variable. This research design type describes the “what,” “when,” “where,” or “how” of phenomena (but not the “why”).   

Example: A study on the different income levels of people who use nutritional supplements regularly.  

• Correlational research design : Correlation reflects the strength and/or direction of the relationship among variables. The direction of a correlation can be positive or negative. Correlational research design helps researchers establish a relationship between two variables without the researcher controlling any of them.  

Example : An example of correlational research design could be studying the correlation between time spent watching crime shows and aggressive behavior in teenagers.  

•   Diagnostic research design : In diagnostic design, the researcher aims to understand the underlying cause of a specific topic or phenomenon (usually an area of improvement) and find the most effective solution. In simpler terms, a researcher seeks an accurate “diagnosis” of a problem and identifies a solution.  

Example : A researcher analyzing customer feedback and reviews to identify areas where an app can be improved.    

• Explanatory research design : In explanatory research design , a researcher uses their ideas and thoughts on a topic to explore their theories in more depth. This design is used to explore a phenomenon when limited information is available. It can help increase current understanding of unexplored aspects of a subject. It is thus a kind of “starting point” for future research.  

Example : Formulating hypotheses to guide future studies on delaying school start times for better mental health in teenagers.  

•   Causal research design : This can be considered a type of explanatory research. Causal research design seeks to define a cause and effect in its data. The researcher does not use a randomly chosen control group but naturally or pre-existing groupings. Importantly, the researcher does not manipulate the independent variable.   

Example : Comparing school dropout levels and possible bullying events.  

•   Experimental research design : This research design is used to study causal relationships . One or more independent variables are manipulated, and their effect on one or more dependent variables is measured.  

Example: Determining the efficacy of a new vaccine plan for influenza.  

Benefits of research design  

 T here are numerous benefits of research design . These are as follows:  

• Clear direction: Among the benefits of research design , the main one is providing direction to the research and guiding the choice of clear objectives, which help the researcher to focus on the specific research questions or hypotheses they want to investigate.  
• Control: Through a proper research design , researchers can control variables, identify potential confounding factors, and use randomization to minimize bias and increase the reliability of their findings.
• Replication: Research designs provide the opportunity for replication. This helps to confirm the findings of a study and ensures that the results are not due to chance or other factors. Thus, a well-chosen research design also eliminates bias and errors.  
• Validity: A research design ensures the validity of the research, i.e., whether the results truly reflect the phenomenon being investigated.  
• Reliability: Benefits of research design also include reducing inaccuracies and ensuring the reliability of the research (i.e., consistency of the research results over time, across different samples, and under different conditions).  
• Efficiency: A strong research design helps increase the efficiency of the research process. Researchers can use a variety of designs to investigate their research questions, choose the most appropriate research design for their study, and use statistical analysis to make the most of their data. By effectively describing the data necessary for an adequate test of the hypotheses and explaining how such data will be obtained, research design saves a researcher’s time.   

Overall, an appropriately chosen and executed research design helps researchers to conduct high-quality research, draw meaningful conclusions, and contribute to the advancement of knowledge in their field.

Frequently Asked Questions (FAQ) on Research Design

Q: What are th e main types of research design?

Broadly speaking there are two basic types of research design –

qualitative and quantitative research. Qualitative research is subjective and exploratory; it determines relationships between collected data and observations. It is usually carried out through interviews with open-ended questions, observations that are described in words, etc. Quantitative research , on the other hand, is more objective and employs statistical approaches. It establishes the cause-and-effect relationship among variables using different statistical and computational methods. This type of research design is usually done using surveys and experiments.

Q: How do I choose the appropriate research design for my study?

Choosing the appropriate research design for your study requires careful consideration of various factors. Start by clarifying your research objectives and the type of data you need to collect. Determine whether your study is exploratory, descriptive, or experimental in nature. Consider the availability of resources, time constraints, and the feasibility of implementing the different research designs. Review existing literature to identify similar studies and their research designs, which can serve as a guide. Ultimately, the chosen research design should align with your research questions, provide the necessary data to answer them, and be feasible given your own specific requirements/constraints.

Q: Can research design be modified during the course of a study?

Yes, research design can be modified during the course of a study based on emerging insights, practical constraints, or unforeseen circumstances. Research is an iterative process and, as new data is collected and analyzed, it may become necessary to adjust or refine the research design. However, any modifications should be made judiciously and with careful consideration of their impact on the study’s integrity and validity. It is advisable to document any changes made to the research design, along with a clear rationale for the modifications, in order to maintain transparency and allow for proper interpretation of the results.

Q: How can I ensure the validity and reliability of my research design?

Validity refers to the accuracy and meaningfulness of your study’s findings, while reliability relates to the consistency and stability of the measurements or observations. To enhance validity, carefully define your research variables, use established measurement scales or protocols, and collect data through appropriate methods. Consider conducting a pilot study to identify and address any potential issues before full implementation. To enhance reliability, use standardized procedures, conduct inter-rater or test-retest reliability checks, and employ appropriate statistical techniques for data analysis. It is also essential to document and report your methodology clearly, allowing for replication and scrutiny by other researchers.

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• The Workstream
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A Guide to Project Design in Project Management

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Project managers often face challenges when managing various project components and resources. However, a well-crafted project design can simplify project management and help teams collaborate. It lays the groundwork for your ideas, resources, and deliverables, setting a clear path before the project’s wheels are even in motion. An effective project design not only streamlines your preparatory work but also paves the way for more efficient project management. By establishing a coherent project design, teams can synchronize their understanding of the project’s vision, expected outcomes, and methodologies. This guide delves into the seven pivotal steps of project design, providing insights on crafting a design with precision using tools like Jira  and Confluence .

What is project design?

Project design is the process of planning a project’s objectives, structure, tasks, and deliverables and deciding on the definition of done . Project managers execute the design process before implementation to align teams on project objectives.  Developing alternative designs is helpful for stakeholders to decide on the best execution plan. A well-managed project design can ensure stakeholder buy-in. It’s important to get stakeholder buy-in sooner than later so you avoid getting their feedback late in the process, which can cause a roadblock.

How project design works

Project design happens early on in the five project management phases as a broad blueprint before any further detailed project planning. A project design uses Gantt charts and flowcharts to provide a project overview. It explains the project’s plan, timeline, and roadmap, establishing a baseline for the team and stakeholders. A project plan template outlines the project design.

Why is project design important?

Project design ensures the viability and success of a project and helps communicate project value to stakeholders. For example, you can demonstrate to stakeholders what your plans are and set expectations for the entire project.  Some other benefits of project design include: 

• Ensuring project success: Without taking stock of a project’s potential scope and resources beforehand, you’ll build a project plan in the dark. 
• Minimizing risks: A project design will take into account potential roadblocks. That way, you can figure out ways to circumvent them ahead of time. 
• Maximizing use of resources: With a project design in place, you’ll know what resources are available and how to utilize them better. 

The design phase of a project determines the resources required and ensures efficient resource utilization.

Steps in the project design process

The seven steps in the project design process are important for Agile teams to simplify the Agile project management process and plan how the project will unfold. For effective project design, teams must follow these seven steps:

Define goals

Project goals should be clear and achievable, never exceeding team members’ abilities.  Goals should align with the project purpose and business objectives. As a project manager, you should consider whether your project’s goals add value to your company’s products and customers. The SMART system —specific, measurable, achievable, relevant, and time-bound—is a proven method for establishing goals. You can use the template in Confluence to help you. Using the template will allow your team to set specific and measurable goals.

Establish outcomes

Outline the required project outcomes and align them with your project goals. Outcomes should resolve product problems for your users, such as functionality and usability. In short, they should further improve your product. For example, an outcome can be to improve the sales flow of the product.  It’s important to note that outcomes are not deliverables or work output. Instead, outcomes determine how customers will use deliverables and their value to customers and the company.  Outlining project outcomes provides a measure of success and a definition of done . From those outcomes, you can better assess their impact.

Identify risks

Risk management is essential to project design. Your job as a project manager is to anticipate problems. You’ll need to look for potential roadblocks, such as development’s current capacity, and determine its impact on the project. Risks include stretched resources, high costs, or scope creep. For example, once you have identified scope creep as a potential risk, you can mitigate this risk by creating clear project parameters and identifying and adhering to deliverables.

Create a project strategy

The strategy is the foundation of the project plan and ensures the team reaches its goals while adhering to project constraints. You should create the strategy at the same time as the project overview to ensure precision in your execution.  To create an excellent project strategy, study similar projects and learn from them. This can help unearth common pitfalls, allowing you to plan for them. Once you have identified several potential strategies, consider the pros and cons of each and apply your research to identify the best strategy. This process is part of continuous improvement .

Set a budget

The next step is to create a budget with the information gathered in the previous steps. The project budget will depend on the required project resources. The free budget template in Jira  is extremely useful for building a project budget.  Creating a budget helps to reduce the likelihood of cost increases and misallocated resources. Stakeholders appreciate project managers who stick to a budget.

Prepare a contingency plan

It’s important to create a contingency plan for all identified risks. For example, you may need to communicate a change to your customers, especially if the change fundamentally affects the product’s primary function. That kind of change could be a risk where you lose users if you don’t communicate the change to them properly. So, your contingency plan could include onboarding and customer success training, so you’re communicating any changes to customers.

Track deliverables

A well-rounded project design includes details on project deliverables. It’s important to monitor and track the progress of deliverables during the project to ensure the team stays on target, remains within budget, and meets deadlines.  Jira  helps project managers track deliverables using Gantt charts or Kanban boards to track project progress.

How to build the best project design

To build an effective product design for your business, there are a few important things to know, such as:

• Communicate effectively. Communication and transparency are critical to project success. Jira includes advanced roadmaps to facilitate communication. These enable teams to collaborate and visualize boards, projects, and filters for insight into project design. You can use Confluence to create the documentation for your project and organize the team. 
• Involve stakeholders. Getting stakeholder buy-in as soon as possible ensures a project will meet their expectations. 
• Adapt to change. Deal with changes promptly by reviewing the contingency plan and quickly resolving issues as they arise. Jira  allows you to execute your plan by highlighting any possible roadblocks ahead of time. Jira integrates with Confluence for a seamless project management experience.

Excel in project design with Jira

Now that you understand the concept behind project design, you can use the process for your next venture. Effective project design is the foundation of a successful project, ensuring projects are delivered on time and within budget. Jira helps you build an effective project design and assists your team with understanding and sharing project goals with other team members. Use Confluence and Jira to track your project and create your documentation.

Project design: Frequently asked questions

How do you define project scope.

The project scope lays out all aspects of a project, including deadlines and deliverables. It describes the project boundaries and helps communicate the exact nature of the project to key stakeholders. The project scope becomes a document that helps team members understand the project outcomes.

What is the difference between project scope and project objectives?

Project scope is the overall outcome of the project. For example, you’ll outline all the tasks and deliverables for this particular project. Project objectives define the project outputs and what the team wants to achieve. For example, an objective might be a deliverable that increases product performance.

How does project design contribute to overall project success?

A well-designed project plan enhances efficiency, minimizes risk, and guides the project toward success. Project design brings project details together for clarity, giving the team confidence to execute the project effectively.

Related resources

• Project Management Resources
• Project Planning Resources

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How to plan a research project

Whether for a paper or a thesis, define your question, review the work of others – and leave yourself open to discovery.

by Brooke Harrington   + BIO

is professor of sociology at Dartmouth College in New Hampshire. Her research has won international awards both for scholarly quality and impact on public life. She has published dozens of articles and three books, most recently the bestseller Capital without Borders (2016), now translated into five languages.

Edited by Sam Haselby

Need to know

‘When curiosity turns to serious matters, it’s called research.’ – From Aphorisms (1880-1905) by Marie von Ebner-Eschenbach

Planning research projects is a time-honoured intellectual exercise: one that requires both creativity and sharp analytical skills. The purpose of this Guide is to make the process systematic and easy to understand. While there is a great deal of freedom and discovery involved – from the topics you choose, to the data and methods you apply – there are also some norms and constraints that obtain, no matter what your academic level or field of study. For those in high school through to doctoral students, and from art history to archaeology, research planning involves broadly similar steps, including: formulating a question, developing an argument or predictions based on previous research, then selecting the information needed to answer your question.

Some of this might sound self-evident but, as you’ll find, research requires a different way of approaching and using information than most of us are accustomed to in everyday life. That is why I include orienting yourself to knowledge-creation as an initial step in the process. This is a crucial and underappreciated phase in education, akin to making the transition from salaried employment to entrepreneurship: suddenly, you’re on your own, and that requires a new way of thinking about your work.

What follows is a distillation of what I’ve learned about this process over 27 years as a professional social scientist. It reflects the skills that my own professors imparted in the sociology doctoral programme at Harvard, as well as what I learned later on as a research supervisor for Ivy League PhD and MA students, and then as the author of award-winning scholarly books and articles. It can be adapted to the demands of both short projects (such as course term papers) and long ones, such as a thesis.

At its simplest, research planning involves the four distinct steps outlined below: orienting yourself to knowledge-creation; defining your research question; reviewing previous research on your question; and then choosing relevant data to formulate your own answers. Because the focus of this Guide is on planning a research project, as opposed to conducting a research project, this section won’t delve into the details of data-collection or analysis; those steps happen after you plan the project. In addition, the topic is vast: year-long doctoral courses are devoted to data and analysis. Instead, the fourth part of this section will outline some basic strategies you could use in planning a data-selection and analysis process appropriate to your research question.

Step 1: Orient yourself

Planning and conducting research requires you to make a transition, from thinking like a consumer of information to thinking like a producer of information. That sounds simple, but it’s actually a complex task. As a practical matter, this means putting aside the mindset of a student, which treats knowledge as something created by other people. As students, we are often passive receivers of knowledge: asked to do a specified set of readings, then graded on how well we reproduce what we’ve read.

Researchers, however, must take on an active role as knowledge producers . Doing research requires more of you than reading and absorbing what other people have written: you have to engage in a dialogue with it. That includes arguing with previous knowledge and perhaps trying to show that ideas we have accepted as given are actually wrong or incomplete. For example, rather than simply taking in the claims of an author you read, you’ll need to draw out the implications of those claims: if what the author is saying is true, what else does that suggest must be true? What predictions could you make based on the author’s claims?

In other words, rather than treating a reading as a source of truth – even if it comes from a revered source, such as Plato or Marie Curie – this orientation step asks you to treat the claims you read as provisional and subject to interrogation. That is one of the great pieces of wisdom that science and philosophy can teach us: that the biggest advances in human understanding have been made not by being correct about trivial things, but by being wrong in an interesting way . For example, Albert Einstein was wrong about quantum mechanics, but his arguments about it with his fellow physicist Niels Bohr have led to some of the biggest breakthroughs in science, even a century later.

Step 2: Define your research question

Students often give this step cursory attention, but experienced researchers know that formulating a good question is sometimes the most difficult part of the research planning process. That is because the precise language of the question frames the rest of the project. It’s therefore important to pose the question carefully, in a way that’s both possible to answer and likely to yield interesting results. Of course, you must choose a question that interests you, but that’s only the beginning of what’s likely to be an iterative process: most researchers come back to this step repeatedly, modifying their questions in light of previous research, resource limitations and other considerations.

Researchers face limits in terms of time and money. They, like everyone else, have to pose research questions that they can plausibly answer given the constraints they face. For example, it would be inadvisable to frame a project around the question ‘What are the roots of the Arab-Israeli conflict?’ if you have only a week to develop an answer and no background on that topic. That’s not to limit your imagination: you can come up with any question you’d like. But it typically does require some creativity to frame a question that you can answer well – that is, by investigating thoroughly and providing new insights – within the limits you face.

In addition to being interesting to you, and feasible within your resource constraints, the third and most important characteristic of a ‘good’ research topic is whether it allows you to create new knowledge. It might turn out that your question has already been asked and answered to your satisfaction: if so, you’ll find out in the next step of this process. On the other hand, you might come up with a research question that hasn’t been addressed previously. Before you get too excited about breaking uncharted ground, consider this: a lot of potentially researchable questions haven’t been studied for good reason ; they might have answers that are trivial or of very limited interest. This could include questions such as ‘Why does the area of a circle equal π r²?’ or ‘Did winter conditions affect Napoleon’s plans to invade Russia?’ Of course, you might be able to make the argument that a seemingly trivial question is actually vitally important, but you must be prepared to back that up with convincing evidence. The exercise in the ‘Learn More’ section below will help you think through some of these issues.

Finally, scholarly research questions must in some way lead to new and distinctive insights. For example, lots of people have studied gender roles in sports teams; what can you ask that hasn’t been asked before? Reinventing the wheel is the number-one no-no in this endeavour. That’s why the next step is so important: reviewing previous research on your topic. Depending on what you find in that step, you might need to revise your research question; iterating between your question and the existing literature is a normal process. But don’t worry: it doesn’t go on forever. In fact, the iterations taper off – and your research question stabilises – as you develop a firm grasp of the current state of knowledge on your topic.

Step 3: Review previous research

In academic research, from articles to books, it’s common to find a section called a ‘literature review’. The purpose of that section is to describe the state of the art in knowledge on the research question that a project has posed. It demonstrates that researchers have thoroughly and systematically reviewed the relevant findings of previous studies on their topic, and that they have something novel to contribute.

Your own research project should include something like this, even if it’s a high-school term paper. In the research planning process, you’ll want to list at least half a dozen bullet points stating the major findings on your topic by other people. In relation to those findings, you should be able to specify where your project could provide new and necessary insights. There are two basic rhetorical positions one can take in framing the novelty-plus-importance argument required of academic research:

• Position 1 requires you to build on or extend a set of existing ideas; that means saying something like: ‘Person A has argued that X is true about gender; this implies Y, which has not yet been tested. My project will test Y, and if I find evidence to support it, that will change the way we understand gender.’
• Position 2 is to argue that there is a gap in existing knowledge, either because previous research has reached conflicting conclusions or has failed to consider something important. For example, one could say that research on middle schoolers and gender has been limited by being conducted primarily in coeducational environments, and that findings might differ dramatically if research were conducted in more schools where the student body was all-male or all-female.

Your overall goal in this step of the process is to show that your research will be part of a larger conversation: that is, how your project flows from what’s already known, and how it advances, extends or challenges that existing body of knowledge. That will be the contribution of your project, and it constitutes the motivation for your research.

Two things are worth mentioning about your search for sources of relevant previous research. First, you needn’t look only at studies on your precise topic. For example, if you want to study gender-identity formation in schools, you shouldn’t restrict yourself to studies of schools; the empirical setting (schools) is secondary to the larger social process that interests you (how people form gender identity). That process occurs in many different settings, so cast a wide net. Second, be sure to use legitimate sources – meaning publications that have been through some sort of vetting process, whether that involves peer review (as with academic journal articles you might find via Google Scholar) or editorial review (as you’d find in well-known mass media publications, such as The Economist or The Washington Post ). What you’ll want to avoid is using unvetted sources such as personal blogs or Wikipedia. Why? Because anybody can write anything in those forums, and there is no way to know – unless you’re already an expert – if the claims you find there are accurate. Often, they’re not.

Step 4: Choose your data and methods

Whatever your research question is, eventually you’ll need to consider which data source and analytical strategy are most likely to provide the answers you’re seeking. One starting point is to consider whether your question would be best addressed by qualitative data (such as interviews, observations or historical records), quantitative data (such as surveys or census records) or some combination of both. Your ideas about data sources will, in turn, suggest options for analytical methods.

You might need to collect your own data, or you might find everything you need readily available in an existing dataset someone else has created. A great place to start is with a research librarian: university libraries always have them and, at public universities, those librarians can work with the public, including people who aren’t affiliated with the university. If you don’t happen to have a public university and its library close at hand, an ordinary public library can still be a good place to start: the librarians are often well versed in accessing data sources that might be relevant to your study, such as the census, or historical archives, or the Survey of Consumer Finances.

Because your task at this point is to plan research, rather than conduct it, the purpose of this step is not to commit you irrevocably to a course of action. Instead, your goal here is to think through a feasible approach to answering your research question. You’ll need to find out, for example, whether the data you want exist; if not, do you have a realistic chance of gathering the data yourself, or would it be better to modify your research question? In terms of analysis, would your strategy require you to apply statistical methods? If so, do you have those skills? If not, do you have time to learn them, or money to hire a research assistant to run the analysis for you?

Please be aware that qualitative methods in particular are not the casual undertaking they might appear to be. Many people make the mistake of thinking that only quantitative data and methods are scientific and systematic, while qualitative methods are just a fancy way of saying: ‘I talked to some people, read some old newspapers, and drew my own conclusions.’ Nothing could be further from the truth. In the final section of this guide, you’ll find some links to resources that will provide more insight on standards and procedures governing qualitative research, but suffice it to say: there are rules about what constitutes legitimate evidence and valid analytical procedure for qualitative data, just as there are for quantitative data.

Circle back and consider revising your initial plans

As you work through these four steps in planning your project, it’s perfectly normal to circle back and revise. Research planning is rarely a linear process. It’s also common for new and unexpected avenues to suggest themselves. As the sociologist Thorstein Veblen wrote in 1908 : ‘The outcome of any serious research can only be to make two questions grow where only one grew before.’ That’s as true of research planning as it is of a completed project. Try to enjoy the horizons that open up for you in this process, rather than becoming overwhelmed; the four steps, along with the two exercises that follow, will help you focus your plan and make it manageable.

Key points – How to plan a research project

• Planning a research project is essential no matter your academic level or field of study. There is no one ‘best’ way to design research, but there are certain guidelines that can be helpfully applied across disciplines.
• Orient yourself to knowledge-creation. Make the shift from being a consumer of information to being a producer of information.
• Define your research question. Your question frames the rest of your project, sets the scope, and determines the kinds of answers you can find.
• Review previous research on your question. Survey the existing body of relevant knowledge to ensure that your research will be part of a larger conversation.
• Choose your data and methods. For instance, will you be collecting qualitative data, via interviews, or numerical data, via surveys?
• Circle back and consider revising your initial plans. Expect your research question in particular to undergo multiple rounds of refinement as you learn more about your topic.

Good research questions tend to beget more questions. This can be frustrating for those who want to get down to business right away. Try to make room for the unexpected: this is usually how knowledge advances. Many of the most significant discoveries in human history have been made by people who were looking for something else entirely. There are ways to structure your research planning process without over-constraining yourself; the two exercises below are a start, and you can find further methods in the Links and Books section.

The following exercise provides a structured process for advancing your research project planning. After completing it, you’ll be able to do the following:

• describe clearly and concisely the question you’ve chosen to study
• summarise the state of the art in knowledge about the question, and where your project could contribute new insight
• identify the best strategy for gathering and analysing relevant data

In other words, the following provides a systematic means to establish the building blocks of your research project.

Exercise 1: Definition of research question and sources

This exercise prompts you to select and clarify your general interest area, develop a research question, and investigate sources of information. The annotated bibliography will also help you refine your research question so that you can begin the second assignment, a description of the phenomenon you wish to study.

Jot down a few bullet points in response to these two questions, with the understanding that you’ll probably go back and modify your answers as you begin reading other studies relevant to your topic:

• What will be the general topic of your paper?
• What will be the specific topic of your paper?

b) Research question(s)

Use the following guidelines to frame a research question – or questions – that will drive your analysis. As with Part 1 above, you’ll probably find it necessary to change or refine your research question(s) as you complete future assignments.

• Your question should be phrased so that it can’t be answered with a simple ‘yes’ or ‘no’.
• Your question should have more than one plausible answer.
• Your question should draw relationships between two or more concepts; framing the question in terms of How? or What? often works better than asking Why ?

c) Annotated bibliography

Most or all of your background information should come from two sources: scholarly books and journals, or reputable mass media sources. You might be able to access journal articles electronically through your library, using search engines such as JSTOR and Google Scholar. This can save you a great deal of time compared with going to the library in person to search periodicals. General news sources, such as those accessible through LexisNexis, are acceptable, but should be cited sparingly, since they don’t carry the same level of credibility as scholarly sources. As discussed above, unvetted sources such as blogs and Wikipedia should be avoided, because the quality of the information they provide is unreliable and often misleading.

To create an annotated bibliography, provide the following information for at least 10 sources relevant to your specific topic, using the format suggested below.

Name of author(s):

Publication date:

Title of book, chapter, or article:

If a chapter or article, title of journal or book where they appear:

Brief description of this work, including main findings and methods ( c 75 words):

Summary of how this work contributes to your project ( c 75 words):

Brief description of the implications of this work ( c 25 words):

Identify any gap or controversy in knowledge this work points up, and how your project could address those problems ( c 50 words):

Exercise 2: Towards an analysis

Develop a short statement ( c 250 words) about the kind of data that would be useful to address your research question, and how you’d analyse it. Some questions to consider in writing this statement include:

• What are the central concepts or variables in your project? Offer a brief definition of each.
• Do any data sources exist on those concepts or variables, or would you need to collect data?
• Of the analytical strategies you could apply to that data, which would be the most appropriate to answer your question? Which would be the most feasible for you? Consider at least two methods, noting their advantages or disadvantages for your project.

Links & books

One of the best texts ever written about planning and executing research comes from a source that might be unexpected: a 60-year-old work on urban planning by a self-trained scholar. The classic book The Death and Life of Great American Cities (1961) by Jane Jacobs (available complete and free of charge via this link ) is worth reading in its entirety just for the pleasure of it. But the final 20 pages – a concluding chapter titled ‘The Kind of Problem a City Is’ – are really about the process of thinking through and investigating a problem. Highly recommended as a window into the craft of research.

Jacobs’s text references an essay on advancing human knowledge by the mathematician Warren Weaver. At the time, Weaver was director of the Rockefeller Foundation, in charge of funding basic research in the natural and medical sciences. Although the essay is titled ‘A Quarter Century in the Natural Sciences’ (1960) and appears at first blush to be merely a summation of one man’s career, it turns out to be something much bigger and more interesting: a meditation on the history of human beings seeking answers to big questions about the world. Weaver goes back to the 17th century to trace the origins of systematic research thinking, with enthusiasm and vivid anecdotes that make the process come alive. The essay is worth reading in its entirety, and is available free of charge via this link .

For those seeking a more in-depth, professional-level discussion of the logic of research design, the political scientist Harvey Starr provides insight in a compact format in the article ‘Cumulation from Proper Specification: Theory, Logic, Research Design, and “Nice” Laws’ (2005). Starr reviews the ‘research triad’, consisting of the interlinked considerations of formulating a question, selecting relevant theories and applying appropriate methods. The full text of the article, published in the scholarly journal Conflict Management and Peace Science , is available, free of charge, via this link .

Finally, the book Getting What You Came For (1992) by Robert Peters is not only an outstanding guide for anyone contemplating graduate school – from the application process onward – but it also includes several excellent chapters on planning and executing research, applicable across a wide variety of subject areas. It was an invaluable resource for me 25 years ago, and it remains in print with good reason; I recommend it to all my students, particularly Chapter 16 (‘The Thesis Topic: Finding It’), Chapter 17 (‘The Thesis Proposal’) and Chapter 18 (‘The Thesis: Writing It’).

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What is design research methodology and why is it important?

What is design research.

Design research is the process of gathering, analyzing and interpreting data and insights to inspire, guide and provide context for designs. It’s a research discipline that applies both quantitative and qualitative research methods to help make well-informed design decisions.

Not to be confused with user experience research – focused on the usability of primarily digital products and experiences – design research is a broader discipline that informs the entire design process across various design fields. Beyond focusing solely on researching with users, design research can also explore aesthetics, cultural trends, historical context and more.

Design research has become more important in business, as brands place greater emphasis on building high-quality customer experiences as a point of differentiation.

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Design research vs. market research

The two may seem like the same thing at face value, but really they use different methods, serve different purposes and produce different insights.

Design research focuses on understanding user needs, behaviors and experiences to inform and improve product or service design.  Market research , on the other hand, is more concerned with the broader market dynamics, identifying opportunities, and maximizing sales and profitability.

Both are essential for the success of a product or service, but cater to different aspects of its lifecycle.

Design research in action: A mini mock case study

A popular furniture brand, known for its sleek and simple designs, faced an unexpected challenge: dropping sales in some overseas markets. To address this, they turned to design research – using quantitative and qualitative methods – to build a holistic view of the issue.

Company researchers visited homes in these areas to interview members of their target audience and understand local living spaces and preferences. Through these visits, they realized that while the local customers appreciated quality, their choices in furniture were heavily influenced by traditions and regional aesthetics, which the company's portfolio wasn’t addressing.

To further their understanding, the company rolled out surveys, asking people about their favorite materials, colors and furniture functionalities. They discovered a consistent desire for versatile furniture pieces that could serve multiple purposes. Additionally, the preference leaned towards certain regional colors and patterns that echoed local culture.

Armed with these insights, the company took to the drawing board. They worked on combining their minimalist style with the elements people in those markets valued. The result was a refreshed furniture line that seamlessly blended the brand's signature simplicity with local tastes. As this new line hit the market, it resonated deeply with customers in the markets, leading to a notable recovery in sales and even attracting new buyers.

When to use design research

Like most forms of research, design research should be used whenever there are gaps in your understanding of your audience’s needs, behaviors or preferences. It’s most valuable when used throughout the product development and design process.

When differing opinions within a team can derail a design process, design research provides concrete data and evidence-based insights, preventing decisions based on assumptions.

Design research brings value to any product development and design process, but it’s especially important in larger, resource intensive projects to minimize risk and create better outcomes for all.

The benefits of design research

Design research may be perceived as time-consuming, but in reality it’s often a time – and money – saver that can. easily prove to be the difference between strong product-market fit and a product with no real audience.

Deeper customer knowledge

Understanding your audience on a granular level is paramount – without tapping into the nuances of their desires, preferences and pain points, you run the risk of misalignment.

Design research dives deep into these intricacies, ensuring that products and services don't just meet surface level demands. Instead, they can resonate and foster a bond between the user and the brand, building foundations for lasting loyalty.

Efficiency and cost savings

More often than not, designing products or services based on assumptions or gut feelings leads to costly revisions, underwhelming market reception and wasted resources.

Design research offers a safeguard against these pitfalls by grounding decisions in real, tangible insights directly from the target market – streamlining the development process and ensuring that every dollar spent yields maximum value.

New opportunities

Design research often brings to light overlooked customer needs and emerging trends. The insights generated can shift the trajectory of product development, open doors to new and novel solutions, and carve out fresh market niches.

Sometimes it's not just about avoiding mistakes – it can be about illuminating new paths of innovation.

Enhanced competitive edge

In today’s world, one of the most powerful ways to stand out as a business is to be relentlessly user focused. By ensuring that products and services are continuously refined based on user feedback, businesses can maintain a step ahead of competitors.

Whether it’s addressing pain points competitors might overlook, or creating user experiences that are not just satisfactory but delightful, design research can be the foundations for a sharpened competitive edge.

Design research methods

The broad scope of design research means it demands a variety of research tools, with both numbers-driven and people-driven methods coming into play. There are many methods to choose from, so we’ve outlined those that are most common and can have the biggest impact.

This stage is about gathering initial insights to set a clear direction.

Literature review

Simply put, this research method involves investigating existing secondary research, like studies and articles, in your design area. It's a foundational method that helps you understand current knowledge and identify any gaps – think of it like surveying the landscape before navigating through it.

Field observations

By observing people's interactions in real-world settings, we gather genuine insights. Field observations are about connecting the dots between observed behaviors and your design's intended purpose. This method proves invaluable as it can reveal how design choices can impact everyday experiences.

Stakeholder interviews

Talking to those invested in the design's outcome, be it users or experts, is key. These discussions provide first-hand feedback that can clarify user expectations and illuminate the path towards a design that resonates with its audience.

This stage is about delving deeper and starting to shape your design concepts based on what you’ve already discovered.

Design review

This is a closer look at existing designs in the market or other related areas. Design reviews are very valuable because they can provide an understanding of current design trends and standards – helping you see where there's room for innovation or improvement.

Without a design review, you could be at risk of reinventing the wheel.

Persona building

This involves creating detailed profiles representing different groups in your target audience using real data and insights.

Personas help bring to life potential users, ensuring your designs address actual needs and scenarios. By having these "stand-in" users, you can make more informed design choices tailored to specific user experiences.

Putting your evolving design ideas to the test and gauging their effectiveness in the real world.

Usability testing

This is about seeing how real users interact with a design.

In usability testing you observe this process, note where they face difficulties and moments of satisfaction. It's a hands-on way to ensure that the design is intuitive and meets user needs.

Benchmark testing

Benchmark testing is about comparing your design's performance against set standards or competitor products.

Doing this gives a clearer idea of where your design stands in the broader context and highlights areas for improvement or differentiation. With these insights you can make informed decisions to either meet or exceed those benchmarks.

This final stage is about gathering feedback once your design is out in the world, ensuring it stays relevant and effective.

Feedback surveys

After users have interacted with the design for some time, use feedback surveys to gather their thoughts. The results of these surveys will help to ensure that you have your finger on the pulse of user sentiment – enabling iterative improvements.

Remember, simple questions can reveal a lot about what's working and where improvements might be needed.

Focus groups

These are structured, moderator-led discussions with a small group of users . The aim is for the conversation to dive deep into their experiences with the design and extract rich insights – not only capturing what users think but also why.

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Karen Goldstein

Karen brings over 25 years of experience in B2C and B2B research, cultivating deep experience in Innovation research methods and tools.

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Project Design in Project Management: A Quick Guide

The project design phase is the first step when planning a project. It sets the stage for the project initiation and project planning phase and important documents like the project charter and project plan.

What Is Project Design?

Project design is a brainstorming process where the project management team starts thinking about the project from a high-level perspective, outlining goals, methodologies, resources and success criteria to establish a project approach that’ll be presented to stakeholders to then begin with the project initiation and project planning phases. In this project stage, the decisions about how to manage and govern are made.

After the project design phase, a project proposal, project charter and a project plan can be created. These project documents will then be used to manage the execution phase of the project life cycle.

The thinking that goes on during the project design, however, doesn’t focus on details as much as it works on a higher level in terms of managing the project. Project planning software can help organize both the high-level strategy and the specific details of a project design.

ProjectManager , for instance, has Gantt charts for making detailed schedules, but also kanban boards for easy collaboration for the strategic aspect of project design. Manage your strategy, plan, schedule, execution and reporting in one easy-to-use project management software. Try it for free today.

What Is the Purpose of the Project Design Process?

The project design defines the overall project methodology that’ll be used and an overview of the project. It describes the major deliverables , products or features that will be completed. The project design also roughly estimates the budget and outlines how to monitor and evaluate progress. There can be more than one design presented to stakeholders, who can then choose which they think best suits their needs.

Why Is the Project Design Phase Important?

Project design is a major first step toward a successful project. A project design is a strategic organization of ideas, materials and processes for the purpose of achieving a goal. Project managers rely on a good design to avoid pitfalls and provide parameters to maintain crucial aspects of the project, like the schedule and the budget.

Project Design Process: How to Design a Project Step-By-Step

There are steps to take for defining project designs and developing an implementation strategy, and they’re the most important steps in a project. Therefore, you want to involve your team and stakeholders in the process to ensure you’re covering all the bases. Take the time to complete this stage thoroughly.

1. Define Your Project Vision

What’s your vision for the project? This isn’t some far-fetched hope, but a vision statement, which envisions a problem that needs resolution. That means clarifying the reason for the project. The vision statement is a formal document that states the project’s potential. It’s presented to stakeholders to show the viability of the project and its benefits.

It isn’t a long, detailed document. You can have a short, idealistic vision in terms of the outcome of the project; after all, this is how you sell the project. So, paint a picture of the project’s success, and place it in a larger context.

2. State the Problem Your Project Will Solve

To support that vision document, you need to identify a problem that needs solving. A needs assessment is often required, so you can see the obstacles the business is encountering. This aligns the problem you’re addressing with the organization and its strategy. It’ll also provide you with the necessary data to design an optimal solution for the problem.

To begin, what information are you gathering? What sources are there for that information, and how will you then gather the information? Next, analyze and determine the problems that your project is being created to resolve. Collect those results in a document.

3. Estimate the Project Resources That’ll Be Needed

Next, you need to recognize the necessary resources to get the project done. Resources are anything from people to equipment to the facilities necessary to complete the project successfully.

A good way to determine the resources is the same way journalists approach a news story, with the five W’s: who, what, where, when and why. Who do you need to execute the project, what resource management tools are required, where will the work be done, when will the project start and end and why are these resources needed?

4. Outline Your Project Goals

You can’t achieve your goals if you haven’t identified them first. A goal is something at the end of the project that’s both observable and measurable and it coincides with the resolution of a problem.

Create a goal statement that explains how the goals are addressed in the project. To do this well, apply the SMART method , which stands for specific, measurable, achievable, realistic and time-relevant. Each goal should be defined by these terms.

5. Structure Your Project Strategy

To achieve the project goals, there must be a strategy in place. A strategy is a process to reach the goals of the project within the project constraints , such as its resources, schedule, budget, etc. How can a strategy be created to achieve the project goals?

Consider precedent and look back on similar projects from the past and what they might have shown in terms of the pros and cons of their applied strategies. Best practices for project management are always a good foundation and building a strategy incrementally, creating a pathway to success.

6. Prepare a Contingency Plan

Any project manager knows that very few things proceed as planned. There needs to be a backup plan to respond quickly and rightly to issues as they arise in a project. Therefore, this must be included in your project design.

Look for the negative risks inherent in the project. They’re embedded in various places, such as teams, which might lack skills, have unavoidable absences, turnover, etc. Schedules can be plagued with delays. The scope might have been poorly defined. Costs are underestimated or funds dry up. Have a plan to address these risks.

7. Establish an Evaluation Plan

A project must always be under evaluation. An evaluation plan will help you monitor the project, and maybe even alert you when it starts to veer off track. Use this plan to analyze the components of the project, the outcomes and the impacts.

Outcomes are measurable changes, while impacts are how well the project goals are being achieved. Therefore, the evaluation plan is a detailed document that defines criteria to determine the project’s effectiveness and efficiency by tracking progress on all aspects of the project.

8. Estimate Costs and Create a Project Budget

The budget outlines the financial resources that drive the project. A budget will assign a cost to each of the project’s requirements. Creating a project budget means formalizing financial resources that’ll be allocated to the project. This begins with choosing a way to estimate costs, identify impacts and report on the evaluation.

9. Create a Project Proposal

All of this leads to a project proposal to explain why the project should be executed and what its benefits are. The previous steps are summarized, writing out the vision of the project and a brief description of the problem that it speaks to. Then state the goals of the project and outline the strategy that will be used to achieve those goals.

Project Design Example

Project managers use project management tools such as Gantt charts to structure their project designs. Here’s a simple project design example that shows how the project design ideas are added to this project planning tool.

For this project design example, let’s take a look at a construction project . As you can see in the image below, during the project design phase, project managers can use Gantt charts to add the major tasks and deliverables as well as build the work breakdown structure of a project to outline the phases of the project execution.

ProjectManager’s Gantt charts have two major parts. On the left side, there’s a spreadsheet that allows project managers to enter information that’ll be used to automatically generate a project timeline on the right side. This timeline won’t only show the project tasks but also milestones, task dependencies and due dates for project deliverables.

What ProjectManager Can Do to Help Your Project Design

Designing a project takes a lot of work, but using project management tools facilitates the process of creating an outline that details these various parts of the project. Besides using Gantt charts to organize your project design ideas into a project timeline, you can also use kanban boards to manage workflow using ProjectManager .

Plan Workflows With Kanban Boards

ProjectManager has a kanban feature that was created to visualize workflows. The project design phase involves collaboration among members of the project management team who will need to share files and communicate in real-time, which can be achieved with ProjectManager’s kanban boards that let project teams better communicate and structure the project design.

Track Projects With Real-Time Dashboards

ProjectManager’s real-time dashboards help project managers keep track of project costs, timelines and progress once the project design becomes a reality. These powerful dashboards can be used to track multiple projects in a portfolio. There are six key metrics that automatically update as changes are made across the software, making it easy to stay on track throughout your project or portfolio.

Only robust project management software can handle all the data needed for a good project design. ProjectManager is an online tool that has features, such as the online Gantt chart, to help schedule, as well as others, to assist with budget and resource allocation. See how it can help you by taking this free 30-day trial.

Deliver your projects on time and on budget

Start planning your projects.

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General guides.

Here are a few general guides to conducting qualitative research:

• SAGE Research Methods Research Methods is a tool created to help researchers, faculty and students with their research projects. Users can explore methods concepts to help them design research projects, understand particular methods or identify a new method, conduct their research, and write up their findings. Since SAGE Research Methods focuses on methodology rather than disciplines, it can be used across the social sciences, health sciences, and other areas of research.
• Qualitative inquiry & research design : choosing among five approaches / John W. Creswell Available in Van Pelt Library
• Handbook of research design & social measurement / Delbert C. Miller, Neil J. Salkind. Available in Van Pelt Library
• Case study research [electronic resource] / edited by Matthew David. Full text available online through the library
• Sage Benchmarks in Social Research Methods This links you to the library's Sage Benchmarks in Social Research Methods collection, which has e-resources on many different aspects of social sciences research.

Here is a list of books available in the library or online that offer guidance on designing interview questions:

• Qualitative Interview Design: A Practical Guide for Novice Investigators
• Interviewing and representation in qualitative research / John Schostak. Available in Van Pelt Library
• Handbook of interview research : context & method/ editors, Jaber F. Gubrium, James A. Holstein. Available in Van Pelt Library
• The research interview / Bill Gillham. Available in Van Pelt Library
• Interviewing [I] [electronic resource] / edited by Nigel Fielding. Full text available online
• How to conduct in-person interviews for surveys / Sabine Mertens Oishi.

Here are some resources on survey construction and design:

• Envisioning the survey interview of the future / edited by Frederick G. Conrad, Michael F. Schober. Available in Van Pelt Library
• Standardization and tacit knowledge : interaction and practice in the survey interview / editors, Douglas W. Maynard ... [et al.]. Available in Van Pelt Library
• Interaction and the standardized survey interview : the living questionnaire / Hanneke Houtkoop-Steenstra. Available in Van Pelt Library
• Questionnaires [electronic resource] / edited by Martin Bulmer. Full text available online

Focus Groups

Here are a few focus-group specific books for if you will be running focus groups:

• Focus group discussions [electronic resource] / Monique M. Hennink Electronic resource. This book is also available in print in Van Pelt. The call number is H61.28 .H45 2014.
• The Focus Group Kit Electronic resource. This is a multi-volume set that covers different aspects of utilizing focus groups for research. This link takes you to the Franklin results, where links are available to all volumes in the set.

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Evans D, Coad J, Cottrell K, et al. Public involvement in research: assessing impact through a realist evaluation. Southampton (UK): NIHR Journals Library; 2014 Oct. (Health Services and Delivery Research, No. 2.36.)

Public involvement in research: assessing impact through a realist evaluation.

Chapter 2 project design and methodology.

• Introduction

This project was initially designed by a group of academic researchers and research partners drawn from the Service User and Carer Involvement in Research (SUCIR) group at the University of the West of England (UWE). An outline application was submitted in May 2010 to a joint funding call for proposals from the NIHR Health Services and Delivery Research programme (HS&DR) and INVOLVE on public involvement in research (see Research brief ). The team were invited to submit a full proposal, which was submitted in October 2010 and approved in February 2011. The HS&DR Board asked the team to consider three points relating to the economic evaluation, the involvement of children and young people and the total number of interviews to be conducted, and changes were made in response in redrafting the project protocol in July 2011 prior to submission for ethical review. A second version of the protocol was drafted once the research fellow was in post in November 2011 and recruitment of case studies had been completed. The overall design and methodology remained similar, but some minor changes were made. In particular, the research fellow appointed was an anthropologist who argued the need for more informal visits at the beginning of the study and observation of case study processes. Because of the time between application, approval and commencing the project other factors became apparent that required additional minor modifications of the planned design. In particular the timescales for public involvement in the agreed case studies were not always optimal for our planned data collection processes and timescales and, as discussed below, research governance processes led to some delays in our starting data collection in some case studies.

Research brief

The NIHR HS&DR Programme and INVOLVE jointly invited proposals in 2010 to address the gap in evidence around the impact of public involvement in research. 15 A background paper summarised the evidence then available, particularly drawing on the reviews by Staley 11 and Brett et al. 12 The invitation expressed three key aims for the research: to collect evidence on the impact of public involvement in research, to identify methods of evaluating this involvement, and to identify effective ways of involving the public in research (implementation). The call was open to a range of methodological approaches.

• Methodology

Realist evaluation framework

Our research design was based on the application of realist theory of evaluation, particularly drawing on the work of Ray Pawson, 13 , 16 , 17 which argues that social programmes (in this case public involvement in research) are driven by an underlying vision of change – a ‘programme theory’ of how the programme is supposed to work. The role of the evaluator is to compare the theory and the practice: ‘It is the realist evaluator’s task, and the added value of social science, to identify and explain the precise circumstances under which each theory holds.’ 17 Moreover, the outcomes of social programmes can be understood by identifying regularities of CMO. Thus the key question for the evaluator is ‘What works for whom in what circumstances . . . and why?’ 17 The realist approach is increasingly used in the evaluation of complex health programmes, and producing useful analyses. 18 , 19 After our study began, Staley et al. published a paper calling for the application of realist evaluation to the study of the impact of public involvement in research. 20 The development of our realist theory of public involvement in research over the course of our study is described in more detail in Chapter 3 .

Our realist theory of public involvement in research was based on the two recently published literature reviews, 11 , 12 which allowed us to identify a number of contextual factors and mechanisms that we believe were intended by policy-makers and other stakeholders in research policy to enable desired outcomes to be achieved. There has not previously been a robust testing of the underlying ‘programme theory’ of public involvement in research; our study was designed to allow an independent prospective testing of this underlying programme theory for the first time. We included an economic evaluation, designed to complement a realist evaluation design, estimating the resources used for public involvement across eight case studies.

Case study sampling

The setting for this project was within organisations hosting health and social care-related research studies (i.e. universities, NHS trusts and third-sector organisations) in the west of England. Our aim was to recruit a methodologically diverse sample of eight case studies which would have significant elements of public involvement during the period January to December 2012. There was no existing database or other source of routinely available data that enabled such upcoming studies to be identified. To meet our aims the studies needed only to be diverse, not representative, so we took the pragmatic decision to sample through our existing knowledge of studies with public involvement in the west of England and to ‘snowball’ through our existing networks, including the People and Research West of England consortium.

We developed a pro forma to identify from network stakeholders upcoming studies they were involved in or aware of with what they identified as ‘significant’ elements of public involvement. Our key inclusion criterion was evidence of some ongoing public involvement in key stages of the research process (design, recruitment, data collection, analysis, dissemination). A key exclusion criterion was that no study would be included unless both the principal investigator (PI) and at least one research partner agreed to take part. In order to identify generalisable regularities of CMO for public involvement in research, we wanted to identify a maximum variety sample of studies in terms of study type, stages of the research process and public involved. In a relatively small-scale study such as this, however, we knew we would not be able to achieve full diversity in all three dimensions. We therefore prioritised diversity of study type, as different study types can drive very different priorities for public involvement (e.g. emphasis on participant information and recruitment in clinical trials). We also prioritised including some studies involving young people and families with children because they make up a substantial minority of health service users but are underrepresented in the literature on public involvement in research. Our case studies are described in Chapter 4 .

In deciding the number of case studies to undertake we recognise that there is always a trade-off between the depth of exploration (which suggests a small number of case studies) and identification of regularities (which benefits from a larger number). There are many ways to categorise research studies (e.g. basic science vs. applied, qualitative vs. quantitative, pilot studies vs. full trials, clinical vs. epidemiological, primary vs. secondary data, action research, translational research) and we could not hope to cover the full diversity in our case studies. From previous experience of case study research, 21 we believed that eight case studies would enable us both to examine the CMO regularities in depth and to look for generalisable regularities across the case studies. This number of case studies did not enable us to examine all potential types of research study, but did enable us to include the most common, for example qualitative, mixed methods, feasibility and clinical trials. We received agreement from four PIs with appropriate funded studies taking place in the west of England at the application stage of our study, and the final four between approval and the early months of our study.

Case study data collection

The first stage of data collection involved initial mapping of the eight case studies through informal visits, encompassing observation of research settings and team meetings (where possible) and unstructured interviews.

Intelligence from the informal visits, together with previous findings from the two literature reviews and the CMO configuration, was then used to design an interview guide for semistructured interviews with case study project stakeholders. For each case study we aimed to carry out semistructured interviews with approximately five stakeholders (PIs, other researchers, research managers and two research partners) on three occasions over the course of the year of data collection, January–December 2012 (three interviews × five participants × eight case studies = 120 interviews in total during the year). Potential interviewees were identified in discussion with PIs and invitations forwarded via the PI or an administrative member of the PI’s team.

Interviews were broadly structured around our CMO hypothesis. Data collected include measurable elements (e.g. resources allocated for supporting public involvement and actual spend) and stakeholder perceptions (e.g. respective views of researchers and research partners on whether research partner contributions influenced project decisions). In addition, some of the stakeholders were given a resource log to record over 2 weeks, chosen at random, the amount of time spent contributing to a range of activities linked to public involvement in each case study. These were then costed using prices taken from published or recognised sources (see Chapter 7 ). Interviews were intended to take place at three broadly evenly spaced times over the 12-month data collection period.

In practice the number and timing of interviews varied widely across the case studies for a variety of reasons including delays in research governance approvals, illness among case study participants and research team members, delays in one research project commencing, and general logistical issues. In two case studies it was possible to carry out only two rounds of interviews rather than three, and the total number of interviews completed was 88 with 42 participants rather than the 120 with 40 participants initially envisaged. Table 1 summarises the total number of interviews (and research partner interviews) undertaken in each round across the case studies.

Total number of interviews (research partners) conducted per case study per round

Case study 4 was exceptional in that, unexpectedly, no public involvement activity took place during the year. Thus the PI, a research manager and one research partner were interviewed initially and only the research manager at the end of the year. The other case studies where numbers of interviews were relatively low were case study 6, which started much later in the year than expected and where only one research partner chose to participate, and case study 7, where the research team was relatively small, there was relatively little involvement activity, and illness prevented final interviews with the two research partners. The relatively low completion rates on the initially planned 120 interviews were not a problem in themselves, so much as a symptom of lack of involvement activity for long periods in some of the case studies.

Given the small numbers of research partners overall, and the fact that some case studies targeted particular socioeconomic or age groups, we do not believe it would be meaningful to present demographic data on these participants. Our perception was, however, that our experience echoed other reports that those members of the public who choose to get involved in research tend to have attained a higher educational level than the population as a whole.

We recognise that a few interviewees do not fall easily into the categories of researcher, research manager or research partner, but we have kept to a limited number of categories to ensure anonymity.

Each case study was intended to be conducted by pairing an academic researcher and a research partner, under the overall supervision of the PI and co-ordinated by the research fellow. In one case, for logistical reasons, the research fellow undertook the data collection on his own. In the other cases, interviews were conducted by both an academic and research partner, usually separately but on occasion interviewing together.

The first round of interviews focused particularly on understanding the context of the case study and the mechanisms for public involvement planned for the remainder of the year. The second round of interviews was ‘light touch’, intended to capture developments in public involvement since the first round and to identify members of the research team able to nominate at least one research partner per case study who could be approached to complete the resource logs for economic costing. The final round of interviews focused on capturing outcomes and learning from the year, to enable us to assess how the researchers’ initial intentions and aspirations for public involvement turned out in practice. In addition to the semistructured interviews, a flexible approach to capturing data included observation of meetings where possible and/or other group tasks directly related to public involvement, and collection of project documents related to involvement processes. Observations were carried out in case studies 1, 2, 5, 7 and 8 but were not possible in case studies 3, 4 or 6, either because of internal case study project considerations or because no public involvement activity took place during the study period.

Developing a methodology for the economic costing of public involvement

There has been minimal exploration and there is little evidence for the costs and benefits of public involvement in research. El Ansari and Andersson conclude that analysis of the costs and benefits of participatory activities should form part of an overall evaluation of public participation. 22 They state that, for participation to move forward as a field, a broader ‘set of analytical frameworks is required, which captures the richness and unique qualities of participation, [and] that recognises and values the different perspectives that led to its initial development.’ 22

Our work here is an attempt to develop an analytical framework of how to assess the economic costs of involvement in research. Planning the budget for public involvement in research at the outset is crucial. The budget needs to include all planned research involvement work to be completed by research partners (for example participating in patient advisory groups or undertaking data analysis) as well as time for academics to facilitate research partners. Two key aspects of budgeting for public involvement are the researcher and research partner relationship and contingency planning. For example, research partners may be asked to contribute their expertise to respond to problems arising during a research project, for example poor recruitment of participants to a study (there were several examples of this among our case studies). These contributions generally arose during the research process and were not foreseen.

Payment and reward issues have generally proved controversial. At our second consensus event our case study participants debated the nature of payment and reward for public involvement vigorously, revealing a wide range of strongly held views on this subject. INVOLVE has developed guidelines on payments for involvement research work to respond to these issues. A recent document outlines the issues to bear in mind in paying research partners, gives examples of payments and provides general tips about issues connected with payment and ‘payments in kind’ that need to be carefully considered by project managers. 23 A range of pay rates for different research activities connected with public involvement are mentioned in INVOLVE documents, including a flat rate payment of £19.40 per hour. 23

Our economic analysis aimed to collect data from each case study team, in order to:

• identify all activities relating to public involvement
• measure the amounts of activities using a resource log
• value or put a price on these activities using prices from published or established sources.

Identifying and measuring involvement activity

To gather data from our eight case studies for our economic analysis, we asked selected members of the case study teams (researchers, research managers and research partners) to log all the resources that were used in public involvement work/activities over a snapshot 2-week period. During the 2 weeks each person recorded/logged:

• all involvement-related activities
• length of time spent on each activity.

We asked them to include all activities (or inputs) that were undertaken as contributing to or enabling the central objective (or output) of public involvement in research. A sample log sheet for research partners on 1 day is in Appendix 1 . Our ethical approval letter stipulated that research staff within each case study were to nominate research partners to provide our data, so we were dependent on these nominations being made successfully from within our case studies, as we were not able to make direct contact with research partners.

We issued user-friendly guidance for completing our resource log, and supported respondents over a 2-week period by e-mail and providing a telephone helpline. Our guidance document for research partners to complete resource logs is in Appendix 2 . Our contact and ongoing dialogue with the academics and research partners who used our guidance and completed our resource logs enabled us to become familiar with how involvement activities were working within each case study from the point of view of both academics and their nominated research partners. These exchanges helped us gain a rounded understanding of the nature and diversity of involvement activity and the relationships and issues within each case study.

Economic valuation/costing of involvement activities

We translated the knowledge we had accrued of each case study into some working assumptions about each one. These assumptions are significant but complex, so we have detailed them in Appendices 3 – 5 .

We then used the completed 2-week resource logs to estimate involvement costs for a projected 12-month period. From there we scaled up the 12-month projected costs to the length of each case study. This enabled us to compare the actual budgeted costs from each grant with the projected costs on a like-for-like basis.

We followed a standard economic approach to treat resource use and prices separately to arrive at a cost.

For example:

Ideally the price applied should come from a published source or the next best alternative, a recognised or established source. There are illustrative examples within INVOLVE guidelines of a range of prices for different research activities connected with public involvement. In our own project we had previously paid research partners at a ‘meeting rate’ of £19.77 per hour, but early in this project it became obvious that most work was being done outside meetings, so a lower ‘research associate’ rate of £14.02 per hour was agreed. Research partners kept records of all their work for the project (including e-mails, collecting and analysing data, and writing) and submitted claim forms regularly. Our project did not have a means of costing researcher time for public involvement activities, as working alongside research partners was a continuous process during our project.

A new set of guidelines from INVOLVE to budget for involvement was incomplete at the time of our analysis, but we saw the draft document, which again gave the example of the flat rate payment of £19.40 per hour for public involvement participation, so we used this price when costing research partners’ activities for our case studies. 23

Reflective practice

Data were captured on our reflective learning on the impact of public involvement in our own study. This was done by facilitating and audio-recording short reflective sessions during team meetings on our own experiences as a project team of academic researchers and research partners working together.

Consensus events

Two consensus workshops were organised as part of our plans to develop and test a theory of public involvement in research. Initially we aimed to hold the first event prior to the first round of data collection to inform the interview schedules for this round. As the project developed, however, we realised that this would not be practical in terms of the length of time research governance approval was taking from some NHS trusts and, more importantly, that an event after the first round would be more fruitful in terms of theory development. Thus, the decision was taken to hold the first consensus event between the first and second rounds of data collection.

At the first workshop we presented an overview of our initial findings from our first round of interviews and visits in the eight case studies. The overview was in the form of 12 statements drawn from our initial mapping of the case studies. The statements identify key contextual factors and mechanisms for public involvement in research that we hypothesised were regularly linked to positive impacts on research design and delivery.

The aim of the workshop was to test these statements with case study participants and steering group members, drawing on their experiences and insights regarding public involvement in research, in order to refine or replace the statements, to inform the next phase of data collection and analysis. The workshop was limited to one afternoon in the hope that this relatively short time commitment would make it more feasible for case study participants to attend.

Nineteen participants took part in the first consensus workshop. Six of the eight case studies were represented. The intention had been that all case studies would be represented by both research staff and research partners in their projects, but it was not possible to achieve this because of participants’ other commitments and some last-minute illness.

Participants first voted electronically on the 12 statements with the choices ‘agree’, ‘disagree’ or ‘abstain’. Participants were then divided into three groups, with each group asked to look in depth at four of the statements, discuss and revise them as necessary and identify any omissions, connections or other comments. The groups then fed back to a plenary session and participated in a final discussion.

A second half-day consensus workshop was held at the end of the third round of data collection. On this occasion all eight case studies were represented with a total of 29 participants. Our emerging theory of public involvement was presented in graphic form in a set of four slides covering different aspects of CMO regularities (field of research, leadership and culture, relationships and structures of involvement). Participants were asked to discuss, amend and comment on A1 printed versions of the slides. The output of the workshop was amended slides with marginal commentary, which were further analysed by the project team and used to form the basis of the analysis of findings presented in Chapter 5 and the development of our theory of public involvement as described in Chapter 8 , Our revised theory of public involvement in research .

Case study data analysis

All interview data were transcribed and entered into an NVivo 10 database (QSR International, Warrington, Cheshire, UK). A key team discussion was how to most fully involve our research partners in the analysis of these data given that only one of them had experience of using any version of the NVivo software. The decision was made to offer NVivo 10 training to research partners but not to require this, as some did not feel confident of learning and using the programme effectively in the time available. A manual coding alternative was therefore made available. In order to make this practical, we limited the number of codes we identified to a minimum necessary to allow meaningful analysis. Those team members coding in NVivo 10 were supplied with this coding framework. Those coding manually were given a numerical code to use with transcripts and the coding was entered into the NVivo 10 database by the project research associate. For each case study, at least one transcript was coded independently by a researcher and research partner, and any divergence discussed and a joint approach agreed.

Data analysis focused on identifying CMO regularities across our case studies. From the initial CMO configuration identified in the proposal, with amendments from the first consensus workshop, a coding framework was devised with 38 codes (see Appendix 6 ) organised into six broad themes: relationships, leadership and culture, field of research, structures of involvement, resources and outcomes. We agreed as a team that the codes were the primary unit of analysis and the themes were provisional. Following coding of data, team discussion lead to the codes being reordered in terms of hypothesised CMO regularities presented in Chapter 5 . This coding framework was then validated by one academic team member not involved in the case studies, who independently undertook a framework analysis 24 of a sample of transcripts and compared her emerging framework with that drawn from the CMO configuration.

Verification of coding

Initial data were analysed by team members identifying codes within interviews. NVivo 10 software was used for data storage, retrieval, coding, analysis, memo writing and theme building across the CMO approach. This was useful in that data coding and development of findings was a collective team activity but an overall verification process was also established. One senior team member, who had not been party to the initial coding discussions, undertook a second verification to ensure consistency and rigor. The coding verification consisted of five transcripts randomly chosen across the case studies and involved two activities: naive reading and structured coding review analysis.

First, transcripts were repeatedly read, blindly from assigned codes, by the independent reviewer, with memo writing with regard to potential codes. Next, data were coded line by line, and each sentence or group of sentences was given a code using the direct meaning of the text. The second reviewer then read the transcripts with the allocated codes assigned by the initial coder. Similarities and differences were recorded. Comparing and contrasting meanings across and within transcripts through the use of memos was used. There was very high agreement found between the coder and second reviewer, which was a very positive result.

Narrative review

There were many issues of agreement in the broader level of understanding. For example, leadership emerged in all five transcripts, as did common terms such as culture (team and organisational), PI beliefs or senior lead issues. Feeling valued, trust and interpersonal relationships and other ‘emotional’-type codes were allocated by coders in all five transcripts. The second reviewer found similar patterns and this showed good overall broad agreement of coders. Power emerged in three transcripts more clearly and repeatedly but was in all five transcripts in some form.

There were minor issues of differences in coding where coders had consistently coded information in a similar way in terms of the value of public involvement. There was only one research partner who coded public involvement not just in terms of value but in terms of impact .

The thematic analysis of each code across the case studies was then used as the basis for the thematic analysis used to test our theory of public involvement in research as presented in Chapter 5 .

Research ethics and governance

The study team took the importance of ethical practice extremely seriously and considered whether it raised any substantive ethical issues. As the study was primarily qualitative and did not involve questions around particularly personal health status or behaviours, we came to the view that it was relatively low risk. However, we recognised that, in asking researchers and research partners from the same studies about what was working and not working in terms of public involvement, we could potentially be raising some sensitive interpersonal relationship issues. We therefore sought to address these issues in our study design, participant information sheets and processes for ensuring confidentiality and anonymity. Following the screening questions on the Integrated Research Application System form, our study was identified as eligible for proportionate review. Ethical approval for the study was therefore sought from the County Durham & Tees Valley Research Ethics Committee prior to the commencement of the study and approval was given with minor conditions in August 2011. An application for a substantive amendment was made in December 2011 to include observation of case study meetings, which had not been included in the original application. Approval was given in February 2012.

Research governance approval, which was sought from the three NHS trusts hosting the four NHS-based case studies, proved much more time-consuming and problematic to obtain than expected. This was particularly because of our desire to enable research partners to participate fully in data collection, which required taking them through the NHS research passport system, something that neither the university nor the NHS trust human resources departments appeared familiar with. Final research governance approval for all three NHS trusts was not obtained until late March 2012, thus delaying our planned date for data collection in some case studies by around 3 months.

Throughout the study we sought to adhere to our ethical and research governance approvals by ensuring informed consent for all participants and fully complying with all conditions of our approvals. All case study participants were sent copies of the report in draft form and invited to comment on how their data had been used and any inaccuracies or other comments on their case studies.

Public involvement in our team

Our aim throughout this project has been to model good practice in our own research while studying the impact of public involvement in our case studies. The project was developed by the SUCIR group at UWE, which had strong service user representation. One research partner co-applicant was the cochair of SUCIR. Three other research partner co-applicants had previously worked with the PI and other academic co-applicants on developing the SUCIR scheme and/or on other research projects.

The four research partner co-applicants were involved in all aspects of the project including design, data collection, analysis and dissemination. The case studies were designed to be undertaken by four subteams, each consisting of one academic researcher and one research partner working together on two case studies. The research partners also formed a separate research partner reference group meeting bimonthly.

The initial intention was for two academic co-applicants with extensive experience in working with young people to recruit and support a young persons’ advisory group to work on the two case studies where participants were young people. In the end it did not prove feasible to recruit such a group and a decision was made to develop an alternative model of involving young people in the project. Two young people, one of whom who had worked on a previous study, were recruited to join the project as research partners. Over time they came to play a similar role to the original four research partners, attending team meetings, research partner meetings and other events, and participating in data collection and analysis in their two case studies.

Research partners were involved in our team’s reflective process on what worked well and what did not work well in terms of our own processes around public involvement. A period of approximately 15 minutes was set aside at the beginning of each team meeting and research partner meeting to share reflections and learning about public involvement in our own project. Research partners have co-authored and presented our outputs at the INVOLVE conference and elsewhere, and have contributed to ensuring that this final report is as user-friendly as possible, and that our wider dissemination plans include outputs specifically designed to be accessible to a wide public. The plain English summary of this report was drafted by research partners. Chapter 6 of this report includes the synthesis, led by one research partner, of the shared reflections on public involvement in our project by both the academic researchers and the research partners.

Included under terms of UK Non-commercial Government License .

• Cite this Page Evans D, Coad J, Cottrell K, et al. Public involvement in research: assessing impact through a realist evaluation. Southampton (UK): NIHR Journals Library; 2014 Oct. (Health Services and Delivery Research, No. 2.36.) Chapter 2, Project design and methodology.
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• How to Write a Research Proposal | Examples & Templates

How to Write a Research Proposal | Examples & Templates

Published on October 12, 2022 by Shona McCombes and Tegan George. Revised on September 5, 2024.

A research proposal describes what you will investigate, why it’s important, and how you will conduct your research.

The format of a research proposal varies between fields, but most proposals will contain at least these elements:

Introduction

Literature review.

• Research design

Reference list

While the sections may vary, the overall objective is always the same. A research proposal serves as a blueprint and guide for your research plan, helping you get organized and feel confident in the path forward you choose to take.

Table of contents

Research proposal purpose, research proposal examples, research design and methods, contribution to knowledge, research schedule, other interesting articles, frequently asked questions about research proposals.

Academics often have to write research proposals to get funding for their projects. As a student, you might have to write a research proposal as part of a grad school application , or prior to starting your thesis or dissertation .

In addition to helping you figure out what your research can look like, a proposal can also serve to demonstrate why your project is worth pursuing to a funder, educational institution, or supervisor.

Research proposal length

The length of a research proposal can vary quite a bit. A bachelor’s or master’s thesis proposal can be just a few pages, while proposals for PhD dissertations or research funding are usually much longer and more detailed. Your supervisor can help you determine the best length for your work.

One trick to get started is to think of your proposal’s structure as a shorter version of your thesis or dissertation , only without the results , conclusion and discussion sections.

Download our research proposal template

Prevent plagiarism. Run a free check.

Writing a research proposal can be quite challenging, but a good starting point could be to look at some examples. We’ve included a few for you below.

• Example research proposal #1: “A Conceptual Framework for Scheduling Constraint Management”
• Example research proposal #2: “Medical Students as Mediators of Change in Tobacco Use”

Like your dissertation or thesis, the proposal will usually have a title page that includes:

• The proposed title of your project
• Your supervisor’s name
• Your institution and department

The first part of your proposal is the initial pitch for your project. Make sure it succinctly explains what you want to do and why.

Your introduction should:

• Introduce your topic
• Give necessary background and context
• Outline your  problem statement  and research questions

To guide your introduction , include information about:

• Who could have an interest in the topic (e.g., scientists, policymakers)
• How much is already known about the topic
• What is missing from this current knowledge
• What new insights your research will contribute
• Why you believe this research is worth doing

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

• Academic style
• Vague sentences
• Style consistency

See an example

As you get started, it’s important to demonstrate that you’re familiar with the most important research on your topic. A strong literature review  shows your reader that your project has a solid foundation in existing knowledge or theory. It also shows that you’re not simply repeating what other people have already done or said, but rather using existing research as a jumping-off point for your own.

In this section, share exactly how your project will contribute to ongoing conversations in the field by:

• Comparing and contrasting the main theories, methods, and debates
• Examining the strengths and weaknesses of different approaches
• Explaining how will you build on, challenge, or synthesize prior scholarship

Following the literature review, restate your main  objectives . This brings the focus back to your own project. Next, your research design or methodology section will describe your overall approach, and the practical steps you will take to answer your research questions.

To finish your proposal on a strong note, explore the potential implications of your research for your field. Emphasize again what you aim to contribute and why it matters.

For example, your results might have implications for:

• Improving best practices
• Informing policymaking decisions
• Strengthening a theory or model
• Challenging popular or scientific beliefs
• Creating a basis for future research

Last but not least, your research proposal must include correct citations for every source you have used, compiled in a reference list . To create citations quickly and easily, you can use our free APA citation generator .

Some institutions or funders require a detailed timeline of the project, asking you to forecast what you will do at each stage and how long it may take. While not always required, be sure to check the requirements of your project.

Here’s an example schedule to help you get started. You can also download a template at the button below.

Download our research schedule template

If you are applying for research funding, chances are you will have to include a detailed budget. This shows your estimates of how much each part of your project will cost.

Make sure to check what type of costs the funding body will agree to cover. For each item, include:

• Cost : exactly how much money do you need?
• Justification : why is this cost necessary to complete the research?
• Source : how did you calculate the amount?

To determine your budget, think about:

• Travel costs : do you need to go somewhere to collect your data? How will you get there, and how much time will you need? What will you do there (e.g., interviews, archival research)?
• Materials : do you need access to any tools or technologies?
• Help : do you need to hire any research assistants for the project? What will they do, and how much will you pay them?

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

Methodology

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement .

Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.

I will compare …

A research aim is a broad statement indicating the general purpose of your research project. It should appear in your introduction at the end of your problem statement , before your research objectives.

Research objectives are more specific than your research aim. They indicate the specific ways you’ll address the overarching aim.

A PhD, which is short for philosophiae doctor (doctor of philosophy in Latin), is the highest university degree that can be obtained. In a PhD, students spend 3–5 years writing a dissertation , which aims to make a significant, original contribution to current knowledge.

A PhD is intended to prepare students for a career as a researcher, whether that be in academia, the public sector, or the private sector.

A master’s is a 1- or 2-year graduate degree that can prepare you for a variety of careers.

All master’s involve graduate-level coursework. Some are research-intensive and intend to prepare students for further study in a PhD; these usually require their students to write a master’s thesis . Others focus on professional training for a specific career.

Critical thinking refers to the ability to evaluate information and to be aware of biases or assumptions, including your own.

Like information literacy , it involves evaluating arguments, identifying and solving problems in an objective and systematic way, and clearly communicating your ideas.

The best way to remember the difference between a research plan and a research proposal is that they have fundamentally different audiences. A research plan helps you, the researcher, organize your thoughts. On the other hand, a dissertation proposal or research proposal aims to convince others (e.g., a supervisor, a funding body, or a dissertation committee) that your research topic is relevant and worthy of being conducted.

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OPPORTUNITY

Funding opportunity now live: Driver Projects to inform design of cross-council trusted research environments

Elizabeth Waind

Apply for funding from UK Research and Innovation to contribute as a Driver Project to lay the foundations for a coordinated and trustworthy national data research infrastructure. Applications close 14 December 2022.

Please note: this opportunity has now closed.

UK Research and Innovation (UKRI) has now opened applications for Driver Projects to inform the design of cross-council trusted research environments (TREs) as part of the DARE UK (Data and Analytics Research Environments UK) programme. The aim of these short duration driver projects will be to take a leading role in informing the design of specific components of what will be a UK-wide, interoperable network of TREs for sensitive data research at scale for public good.

The driver projects will be integrated with working groups that will be established under DARE UK and our partners to address some of the fundamental challenges identified so far during Phase 1 of the programme. These working groups will act as expert bodies responsible for collaboratively defining the strategy, delivery planning, and execution in each working group’s area of expertise. A project team can be led by or include members of a working group. Successful applicants to this funding call will be required to actively collaborate with relevant working groups.

DARE UK is committed to meaningful public involvement and engagement, and all applications must include plans for embedding public involvement and engagement in the lifecycle of the project. Find out more about methods for involving the public in research.

• Opening date: 09:00 on Friday 28 October 2022
• Mid-call webinar: 13:00-14:00 on Thursday 17 November 2022. If you missed the event, you can view the recording and the slides.
• Applications close: 09:00 on Wednesday 14 December 2022
• Panel meeting: Week beginning 9 January 2023
• Projects start: No later than Monday 23 January 2023
• Projects end: No later than Tuesday 31 October 2023

Areas of focus

Each driver project will be focused on 1 of the following areas:

• Trusted research environment (TRE) reference architecture Applications for a short, targeted project focused on consolidating the existing work on TRE reference architectures, including example implementations, and co-developing with feedback from established stakeholders within the TRE community a composite reference architectures for TREs. The expected output would be a formal open source project to support collaborative longer term development.
• Core federation services Applications to establish an open-source project with the purpose of conceptualising, designing, structuring, and driving early development of a library of API services and micro-services as the beginning of a ‘federation layer’ of a network of trusted research environments in the UK. It is important to note that the focus in Phase 1b for this area is on establishing the development process and framework for the API library to allow for future delivery of the detailed services.
• Federated identity management across TREs Investigate and pilot an identity management service across 2 or more established trusted research environments, this should include:
• identifying and selecting the most suitable platform for such a service
• establishing an identity brokerage service as the integration partner across the different identity providers within each of the trusted research environments
• ensuring that testing and usage of such a service is possible in parallel with existing individual services provided by each involved trusted research environment
• Partial automated risk assessment at data access request Building on existing work in this area, investigate and advance a framework for the partial automation of risk assessment for sensitive data research projects at the data access request stage to pilot and test a consistent, efficient, and trustworthy approach (including tools) to risk assessment that can support existing data governance committee processes.
• Partial automation of output control Building on existing work in this area, investigate and advance a framework for automating components of the disclosure control process within trusted research environments to support a consistent, efficient, and trustworthy approach to the partial automation of output checking and disclosure control. This includes developing the tools necessary to underpin this to support manual review.

Funding available

The full economic cost of your project can be up to £750,000.

Up to £2.75 million is available to fund the delivery of the projects. The minimum funding level for a project is £100,000. However, all projects will be assessed as described in this specification and will be expected to demonstrate the potential to make a significant contribution to informing the design of future phases of the programme. Requests for extensions, including zero cost extensions, will not be agreed.

Contact details

For help and advice on costings and writing your proposal please contact your research office in the first instance, allowing sufficient time for your organisation’s submission process.

If you have any questions about this funding opportunity: Download the Frequently Asked Questions document (updated weekly on Thursdays).

For other questions that are not covered in the FAQ, please contact: Dr Yan Yip, Programme Manager for Data Science, Medical Research Council: [email protected] . Please include ‘DARE UK’ in the subject line and cc in [email protected] . We aim to respond within three working days.

Full details of this funding opportunity, including application instructions, can be found on the UKRI Funding Finder.

YOU MIGHT ALSO LIKE THESE

Rob Baxter joins DARE UK as Technical Lead

DARE UK Driver Projects unveil shared plans to transform UK-wide sensitive data research

DARE UK Driver Projects final outputs published

Recap: Linking Sensitive Data: Insights from the DARE UK Driver Projects Webinar; Wednesday, 17 January 2024; 12 – 1:30 pm

Get in touch.

If you’re interested in learning more about our work, how it can benefit you, or how to get involved, click the button to get in touch with us using our contact form.

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Open Access

Peer-reviewed

Research Article

How Etuaptmumk /Two-Eyed Seeing is used in indigenous health research: A scoping review

Roles Formal analysis, Investigation, Project administration, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Institute for Circumpolar Health Research, Yellowknife, Northwest Territories, Canada, Department of Anthropology, University of Toronto Mississauga, Toronto, Ontario, Canada

Roles Formal analysis, Funding acquisition, Project administration, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

¶ ‡ DHM and ACB are joint senior authors and contributed equally to this work.

Affiliation Faculty of Health, Health Promotion Division, Dalhousie University, Halifax, Nova Scotia, Canada

Roles Data curation, Resources, Software

Affiliation Pediatric ICU, BC Children’s Hospital, Vancouver, British Columbia, Canada

Roles Investigation, Validation, Writing – review & editing

Affiliation Faculty of Health Sciences, School of Occupational Therapy, Westerns3 University, London, Ontario, Canada

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliations Department of Health and Society, University of Toronto Scarborough, Toronto, Ontario, Canada, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada, Women’s College Research Institute-Women’s College Hospital, University of Toronto, Toronto, Ontario, Canada

• Sophie I. G. Roher, 
• Debbie H. Martin, 
• Ziwa Yu, 
• Tara Pride, 
• Marni Amirault, 
• Jenny R. Rand, 
• Anita C. Benoit

• Published: September 19, 2024
• https://doi.org/10.1371/journal.pone.0310247
• Reader Comments

Our scoping review sought to describe how Etuaptmumk or Two-Eyed Seeing is used and reported on in Indigenous health research. Using the JBI scoping review methodology, we extracted uses of Etuaptmumk /Two-Eyed Seeing from 83 articles and then categorized the reported uses of Etuaptmumk /Two-Eyed Seeing according to Huria et al.’s eight CONSIDER statement domains (governance, prioritization, relationships, methodologies, participation, capacity, analysis and interpretation, and dissemination). We found that while authors used Etuaptmumk /Two-Eyed Seeing in varied ways and at different stages of their research projects, characterizations of the guiding principle were often insufficiently described or overly simplified. This scoping review intends to contribute to a greater dialogue about how Etuaptmumk /Two-Eyed Seeing is conceptualized and used in Indigenous health research with the goal of encouraging more intentional reporting of the guiding principle.

Citation: Roher SIG, Martin DH, Yu Z, Pride T, Amirault M, Rand JR, et al. (2024) How Etuaptmumk /Two-Eyed Seeing is used in indigenous health research: A scoping review. PLoS ONE 19(9): e0310247. https://doi.org/10.1371/journal.pone.0310247

Editor: Julia Morgan, University of Greenwich, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND

Received: March 6, 2024; Accepted: August 23, 2024; Published: September 19, 2024

Copyright: © 2024 Roher et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: Author SIGR is supported by a Canadian Institutes of Health Research (CIHR)’s Patient-Oriented Research Fellowship Award (grant # CIHR/170664; https://cihr-irsc.gc.ca/e …) and was previously supported by a CIHR Doctoral Research Award through the CIHR Institute of Aboriginal People’s Health (grant # CIHR/152258; https://cihr-irsc.gc.ca/e/8668.html ). DHM is supported by a Tier II Canada Research Chair in Indigenous Peoples’ Health and Well-Being through the Canada Research Chairs Program (grant # CRC-2021-00436; https://www.chairs-chaires.gc.ca/home -accueil-eng.aspx). ACB was previously supported by an OHTN-CIHR New Investigator Award through CIHR (grant #APP268899; https://cihr-irsc.gc.ca/e/ 44181.html). TP was supported by a SSRHC Doctoral Fellowship and the Atlantic Indigenous Mentorship Kausattumi Grants Program Doctoral Award. JRR is supported through DHM’s Canada Research Chair Program (grant # CRC-2021-00436; https://www.chairs-chaires.gc.ca/home -accueil-eng.aspx). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Etuaptmumk (E) is the Mi’kmaw word for Two-Eyed Seeing (TES), a guiding principle that has been increasingly taken up in Indigenous health research [ 1 ]. E/TES was first introduced to the academic community by Mi’kmaq Elders Drs. Albert and Murdena Marshall from Eskasoni First Nation and Dr. Cheryl Bartlett to guide the Integrative Science program at Unama’ki College [ 2 , 3 ]. Elders Drs. Albert and Murdena Marshall and Dr. Cheryl Bartlett (i.e., the original authors) described E/TES as: “learning to see from one eye with the strengths of Indigenous knowledges and ways of knowing, and from the other eye with the strengths of Western knowledges and ways of knowing… and learning to use both these eyes together, for the benefit of all” [ 4 ]. While E/TES has been used in academic research, Elder Dr. Albert Marshall explains that E/TES cannot be easily classified in academic terms. According to Elder Dr. Albert Marshall, E/TES is a broader and more dynamic guiding principle for how to live one’s life. It is a way of thinking and living that is deeply connected to spirit [ 5 ].

Since E/TES cannot be easily labeled using academic terms, it is fitting that there is no checkbox of things one needs to do to enact E/TES and little practical guidance is given to researchers for how to use E/TES in research. Indeed, we would argue that one of the strengths of E/TES is that it is fluid and dependent on contextual factors such as time, place, and people(s) involved. When E/TES is communicated by its original authors, it is often communicated orally [ 6 ]. Nevertheless, given that there is no practical guidance for how to use the guiding principle in research, and as E/TES is increasingly used in Indigenous health scholarship, it is also at greater risk of being misused or misrepresented [ 1 , 7 , 8 ]. Elder Dr. Albert Marshall noted: “The work can all too easily slip into a lazy, tokenistic approach in which E/TES and similar efforts quickly become mere jargon, trivialized, romanticized, co-opted, or used as a ‘mechanism’” [ 7 ]. Since future academic work builds on previous academic work, it is important for researchers to clearly articulate how they are conceptualizing and using E/TES in their research projects so that we can develop a rich and nuanced understanding of the guiding principle.

Huria et al. developed the CONS ol ID ated crit ER ria (CONSIDER) statement for strengthening reporting of health research involving Indigenous Peoples and knowledges [ 9 ]. The CONSIDER statement consists of eight research domains that researchers should be attentive to when reporting about Indigenous engagement and the use of Indigenous knowledges in health research: governance, prioritization, relationships, methodologies, participation, capacity, analysis and interpretation, and dissemination.

To encourage more thoughtful engagement with E/TES, we carried out a scoping review to better understand how E/TES is used in Indigenous health research literature. Our review is intended to build on a previous scoping review, which found that E/TES is characterized and described in Indigenous health research in a variety of ways [ 1 ]. Our previous review identified seven ways that E/TES was described by the original authors and new authors. E/TES was characterized as a guide for life; co-learning journey; responsibility for future generations; numerous or diverse perspectives; spirit; decolonization and self-determination; and humans as part of the environment [ 1 ]. Since our goal is to strengthen the way that researchers are reporting their use of E/TES, in this scoping review we sought to examine how E/TES is used in Indigenous health research and to assess researchers’ reported usage of E/TES through the CONSIDER statement’s eight domains. Our intention is not to claim that there is ‘one’ ‘right’ way to use E/TES, nor are we claiming that we hold some sort of authority about how E/TES ‘should’ be used. Rather, our aim is to encourage all of us to be more thoughtful in the ways that we engage with and describe E/TES.

Our scoping review followed the methods outlined in the JBI Manual for Evidence Synthesis [ 10 ] (See S1 Protocol ). We worked with the five stages of the York Framework, including having a team approach of regular and consistent meetings throughout the entire review process such as data extraction, analysis, and presentation [ 11 ] with clarifications as described by Levac et al. 2010 [ 12 ]. As recommended by the JBI scoping review guidelines, we used open coding, which included allocating the use of E/TES into overall categories, and we used a deductive approach, which involved mapping our data to the CONSIDER statement domains, which was our coding framework (we describe our process in greater detail below).

Our research question was: How is Etuaptmumk/Two-Eyed Seeing reportedly being used in Indigenous health research? The Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews (PRISMA-ScR) [ 13 ] guided the conduct and reporting of this scoping review, which is congruent with the JBI approach.

Eligibility criteria

The key concept underpinning our scoping review is ‘Two-Eyed Seeing’ known in the Mi’kmaw language as ‘Etuaptmumk’. The main populations of interest were First Nations, Inuit, and Métis in Canada, though we also considered international scholarship using E/TES. Literature that involved non-Indigenous populations (e.g., non-Indigenous health professionals, educators, policy makers, and researchers) were included so long as the research aim aligned with CIHR’s definition of Indigenous health research, which can be defined by “any field or discipline related to health and/or wellness that is conducted by, grounded in, or engaged with, First Nations, Inuit or Métis communities, societies or individuals and their wisdom, cultures, experiences or knowledge systems, as expressed in their dynamic forms, past and present” [ 14 ]. We considered scholarship across a variety of academic disciplines including health sciences, education, and biology, among others.

We included English-language literature published from Jan 1, 2004 (i.e., the year when E/TES was introduced to academia through the Integrative Science research program by Elders Drs. Albert and Murdena Marshall and Dr. Cheryl Bartlett [ 15 ]) until August 31, 2023. In terms of types of literature, we considered primary research of all study designs and reviews such as scoping or systematic reviews. Only abstracts that have a corresponding full-text publication were included.

Data sources

The following databases were searched by a JBI-trained health sciences librarian: Medline (PubMed) and Medline (Ovid), Academic Search Premier (EBSCOhost), PsycINFO (EBSCOhost), CINAHL (EBSCOhost), Bibliography of Indigenous Peoples in North America (EBSCOhost), and EMBASE (Ovid). We also searched for our key terms in the grey literature: the Indigenous Studies Portal (iPortal) and the Institute for Integrative Science & Health (IISH) website. Four key journals (International Journal of Indigenous Health, International Journal of Circumpolar Health, International Indigenous Policy Journal, and Pimatisiwin: A Journal of Aboriginal and Indigenous Community Health) were also searched. The search end date was August 31, 2023 with a search start date of January 1, 2004, aligning with our inclusion criteria.

Search strategy

Two key terms, ‘Two-Eyed Seeing’ or ‘Etuaptmumk’, were used to search the title, abstracts, and keywords for our databases with limits to English language sources. We searched our key terms one at a time using them as keywords as there are no synonyms or MeSH terms and then combining our individual searches using the Boolean operator “OR”. The grey literature and four key journals were hand searched for relevancy using our two key terms. Reference lists of included literature were scanned for additional records. Finally, we contacted authors of conference abstracts to request potential full-text publications.

Citation management and screening process

Search results were imported into the online systematic review platform Covidence (Veritas, Melbourne, Australia) for screening. First, each title and abstract were independently assessed by two reviewers against pre-defined eligibility criteria. Potentially relevant citations were then retrieved in full-text and assessed again by two reviewers independently. To exclude a full-text article, reviewers needed to provide a rationale, which we summarized in Fig 1 . Any disagreements that arose between reviewers were settled through discussion or by a third reviewer.

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Study selection process.

https://doi.org/10.1371/journal.pone.0310247.g001

Data charting and synthesis

We extracted the data in two parts. First, a charting table in Microsoft Excel was created by authors to extract the following details from included literature: author(s), year of publication, research design, study objectives, research participants, and study location. The charting table was first trialed independently by each member of the review team on four full-text articles to ensure all relevant information was captured and that there was a mutual understanding of all data extraction terms. The remaining data extraction was completed with two members of the review team independently reviewing each article. Any disagreements were resolved through discussion or with a third reviewer, if required.

Second, we created a chart to extract authors’ explicit descriptions of how E/TES was used to guide their research activities. In the chart, we categorized E/TES usage according to the eight domains from the CONSIDER statement [ 9 ]. To start, two members of the review team independently reviewed each article and extracted quotations that described how authors used E/TES in their research projects. When needed, disagreements were resolved through discussion or with a third reviewer. The quotations were then categorized according to the eight research domains of the CONSIDER statement. The entire review team met multiple times to discuss the categorizations until consensus was reached. Finally, based on the categorizations, the review team worked together to create short summaries for each domain to describe how researchers were reporting their use of E/TES (see ‘Domains describing the reported use of Etuaptmumk /Two-Eyed Seeing’).

The literature screening process is summarized in a PRISMA-ScR diagram ( Fig 1 ). The search of databases resulted in 497 records. An additional 20 articles were included based on searching key websites, journals, and reviewing relevant articles’ reference lists. After removing duplicates, 297 remained for title and abstract screening of our key terms, of which 136 progressed to full text review. Ultimately, 83 articles met the eligibility criteria and were included in our review.

Characteristics of included articles

An overall description of the included literature is presented in S1. All 83 articles were published after 2009 with 80 articles published since 2015. The included literature were journal articles (n = 82) and book chapters (n = 1). In terms of research design, 61 research articles employed an empirical design (i.e., research that is based in observation or measurement of phenomena and uses qualitative or quantitative methods to gather evidence [ 16 ]). Among these, 22 used community-based research design variations, such as community-based participatory research or participatory action research [ 17 – 38 ].

Domains describing the reported use of Etuaptmumk /Two-Eyed Seeing

The descriptions below illustrate how E/TES was used and characterized according to the CONSIDER statement. Some articles used E/TES according to more than one domain. Usage of E/TES was most often categorized in the CONSIDER statement’s domains of methodologies (n = 46); relationships (n = 45); and analysis and interpretation (n = 36); followed by dissemination (n = 12) and capacity (n = 9); and was least often categorized in the domains of prioritization (n = 7); governance (n = 1); and participation (n = 1) ( Fig 2 ).

CONSIDER domains with specific components of the definitions reflected in the articles.

https://doi.org/10.1371/journal.pone.0310247.g002

To better demonstrate how E/TES was used and catalogued, we present Huria et al.’s definition of each CONSIDER statement domain, followed by a summary of how researchers’ reported usage of E/TES aligned with that domain.

Domain 1: Relationships

According to Huria et al. [ 9 ], relationships consist of specified measures that “adhere and honour Indigenous ethical guidelines, processes, and approvals” for all Indigenous individuals or groups who may have different research approaches, reporting Indigenous involvement in the research process from funding to dissemination, and a description of the research team’s expertise in Indigenous health and research.

The use of E/TES in relationships was mentioned in 45 articles. In seven articles, E/TES was described in relationships according to more than one of the characterizations in Huria et al.’s definition [ 29 , 32 , 37 – 41 ]. Fourteen articles described a role for E/TES in specific measures that adhere to and honour Indigenous ethical guidelines, processes, and approvals [ 17 , 27 , 32 , 33 , 37 – 40 , 42 – 47 ]. A role for E/TES in shaping Indigenous involvement in the research process was described in thirteen articles that focused on power dynamics, engagement throughout research phases, and forming the research team [ 29 , 32 , 34 , 37 – 39 , 41 , 48 – 53 ]; nine articles in the selection of methods [ 21 , 22 , 29 , 38 , 40 , 41 , 54 – 56 ]; and three articles for knowledge co-creation [ 23 , 57 , 58 ]. We discuss each of these articulations of E/TES in greater detail below.

Indigenous ethical guidelines , processes , and approvals . A role for E/TES in specific measures that adhere to and honour Indigenous ethical guidelines, processes and approvals was articulated in fourteen articles [ 17 , 27 , 32 , 33 , 37 – 40 , 42 – 47 ]. In five articles, E/TES was part of the more formal aspects of preparing for research to take place–including the establishment of guidelines for how to undertake the work [ 32 , 40 , 42 , 43 , 45 ]. In four articles, E/TES was used to build authentic relationships that facilitated a safe and trusting environment in which to share [ 33 , 38 , 40 , 44 ]. In two articles, E/TES was part of reviewing adaptations of existing programs to ensure cultural appropriateness and sensitivity [ 17 , 27 ]. In one article, E/TES was involved in processes for ensuring that the appropriate approvals were in place ahead of data collection [ 39 ], and in another, E/TES was reflected through ceremonies at the start of community engagement sessions to recognize the people and ancestors whose land the research was conducted upon [ 32 ]. Finally, in one article, an Elder’s involvement in the research process was part of their E/TES approach [ 47 ].

Mitigating power dynamics and the formation of the research team . For some authors, E/TES included consciously considering power dynamics within a team [ 37 , 39 , 48 , 49 ]. For instance, Mantyka-Pringle et al. [ 48 ] indicated that E/TES contributed a means for knowledge co-production that was ‘power neutral’ in the sense that multiple modalities of data capture were included, and that feedback on the process was elicited from various representatives of the research project, including local people, Elders, social and natural scientists, and government workers. Hall [ 49 ] indicated that although the funding was held at an academic institution (therefore creating an uneven power relationship at the outset), this was somewhat mitigated by having data collection led entirely by an Elder.

In other examples, authors described how E/TES was considered in relationships throughout different stages of the research process. In terms of data analysis, some authors indicated that this was undertaken specifically by both Indigenous and non-Indigenous peoples (i.e., a non-Indigenous researcher and Indigenous research assistant) [ 41 ], whereas in cases where the analysis was done by a team of non-Indigenous peoples, authors described re-engaging with the governing circle (which consisted of Indigenous peoples) to present the results for their feedback and comments [ 39 ].

For some researchers, E/TES shaped the composition of the research team [ 29 , 32 , 34 , 38 , 50 – 53 ]. For example, Wright et al. explained that in keeping with their E/TES approach, the study was collaboratively designed by a non-Indigenous nurse practitioner, a First Nations nurse and PhD student, a Métis scholar, and members of the Indigenous community in Hamilton [ 51 ]. Similarly, Rowan et al. [ 50 ] described how E/TES shaped the make-up of the study team in their scoping review process and they outlined the types of expertise brought to bear on the process by the various people involved. Both western and Indigenous thinkers were brought together in a shared space to exchange knowledge. These gatherings were important throughout the scoping review process, but particularly at the outset in shaping the research question.

Selection of methods . Some authors described involving Indigenous advisory committees, research participants, and research team members in decisions about the methods selected for the study [ 21 , 22 , 29 , 38 , 40 , 41 , 54 – 56 ]. Marsh [ 40 ] described that the involvement of an Indigenous advisory group, Elders, and the research committee ensured that the research process itself was culturally safe.

In one instance, authors specifically mentioned that relationships with the Indigenous community provided a means to verify the results of the research. “In Mi’kma’ki Two-Eyed Seeing collaborations are helping to create better and broader understandings of netukulimk within communities. The integrative approach is conducive to gathering Indigenous fisheries knowledge from active fishers and Elders participate in evidence verification” [ 56 ].

Knowledge co-creation . Another way that authors described their research relationships was through knowledge co-creation, whereby research teams indicated that Indigenous peoples were instrumental in forming a part of the research process itself [ 23 , 57 , 58 ]. Crooks et al. described this as both a collaborative and community-driven process that opened space to co-create research questions, identify appropriate methods, and ensure that data was being interpreted appropriately [ 23 ]. Similarly, Castleden et al. described the involvement of an advisory committee that consisted of Indigenous and non-Indigenous water experts that informed the research process from design to dissemination [ 57 ]. For Marsh et al. [ 58 ], co-creation involved the presence of an Elder during storytelling sessions which was intended to allow research participants to develop a connection to the spirit world through traditional teachings, and to offer a space for healing as they shared their own stories.

Insufficiently described . Notably, of the 45 articles, there were 19 articles whose usage of E/TES aligned generally with Huria et al.’s definition of ‘relationships’ but did not clearly describe what Indigenous involvement looked like in their projects and how this aligned with E/TES [ 20 , 41 , 45 , 50 , 55 , 56 , 59 – 71 ]. For example, McKivett [ 62 ] stated that they carried out E/TES by bringing together the Indigenous community, healthcare practitioners, medical educators, and medical students as key research stakeholders in a way that centers Indigenous worldviews; nevertheless, it was unclear what this looked like in their study and how it aligned with their conceptualization of E/TES. Notably, of the 19 articles, we categorized five articles as both clearly and not clearly describing relationships because, in some sections of their articles they clearly described E/TES, while in other places they did not [ 41 , 45 , 50 , 55 , 56 ].

Domain 2: Methodologies

Methodologies consist of describing the methodological approach including the rationale for the methods used and implication of Indigenous people involved in the research, describing Indigenous worldviews as well as how the methodology considers the physical, social, economic and cultural environment of study participants [ 9 ].

The use of E/TES in methodologies was described in 46 articles. 17 articles reported using E/TES in their descriptions of Indigenous worldviews [ 22 , 24 , 28 , 32 , 36 , 37 , 43 , 46 , 55 , 67 , 69 , 72 – 77 ], and 35 articles reported using E/TES in the methodological approach including the rationale for the methods [ 21 , 23 , 25 , 27 , 29 – 31 , 33 , 34 , 38 , 40 , 42 – 45 , 47 , 48 , 50 , 53 , 55 , 58 , 60 , 64 , 69 , 72 – 75 , 78 – 84 ]. Five of the articles reported E/TES both as a rationale for the methods and in their descriptions of Indigenous worldviews [ 55 , 69 , 72 , 73 , 75 ]. The implication of Indigenous peoples involved in the research was not clearly described in relation to E/TES, nor were considerations for the physical, social, economic, and cultural environment of study participants.

Use of E/TES as theoretical approach . Some authors reported using E/TES as an overarching theory or approach for bringing together Indigenous and Western knowledges [ 22 , 24 , 28 , 32 , 36 , 37 , 43 , 46 , 55 , 67 , 69 , 72 – 77 ]. For example, Rand employed E/TES as a theoretical framework to bridge Inuit Quajimajatuqangit (IQ) and postcolonial theory [ 24 ]. Similarly, Snooks et al. used E/TES by “blending together…feminist, Indigenous, decolonial, and participatory action frameworks” [ 32 ]. Other authors used E/TES as a theoretical approach along with Indigenous or decolonizing methodologies. For instance, Quinn used E/TES with a Relational Worldview Model and decolonizing Indigenous research epistemologies to guide their study questions [ 46 ]. Similarly, Ward et al. used E/TES conceptually to recognize the partiality of Western knowledge and the fact that Western knowledges need to be located within Indigenous histories and worldviews [ 36 ]. Ward et al. described that E/TES encouraged them to reflect on and actively work to address power imbalances in the research process by collaborating with Indigenous peoples throughout and ensuring that the study benefits Indigenous peoples and communities who are taking part [ 36 , 37 ].

Rationale for methods . Some researchers conceptualized and used E/TES by including both Indigenous and Western methodologies, methods, or perspectives in their research [ 21 , 23 , 25 , 27 , 29 – 31 , 33 , 34 , 38 , 40 , 42 – 45 , 47 , 48 , 50 , 53 , 55 , 58 , 60 , 64 , 69 , 72 – 75 , 78 – 84 ]. This was referred to by some authors as a ‘mixed methods’ approach [ 75 ]. One example of this can be found in Rowan et al.’s scoping review which brought together Indigenous and Western perspectives in different ways at different points in the study [ 50 ]. According to Rowan et al., E/TES encouraged the researchers to form a balanced team of Western and Indigenous thinkers; to create a research question that recognized Indigenous knowledge and Western understandings of evidence; to use search term parameters that came from Indigenous perspectives; and to employ both Western and Indigenous criteria to label and extract data. Similarly, Poirier and Tait Neufeld used E/TES by employing both Indigenous sharing circles and Western reflexive thematic analysis in their research design [ 31 ].

While some researchers understood E/TES as a theory or approach for bringing together Indigenous and non-Indigenous knowledges, others conceptualized and used E/TES by centering Indigenous knowledges and methodologies [ 43 , 55 , 69 , 73 ]. For example, some researchers employed E/TES by taking up methods that honour the oral tradition, such as interviews [ 43 , 55 ] and discussion groups [ 55 ]. Similarly, in Hall et al.’s study, E/TES enabled the researchers to use Indigenous methodologies such as storytelling and knowledge gardening [ 73 ]. According to Hall et al., E/TES enabled them to prioritize Indigenous governance and cultural guidance and ensured that Western timeframes did not dictate their research timelines. Additionally, E/TES meant that they used culturally-rooted analyses to validate their findings when Western research methods were used.

For some researchers, E/TES prompted them to ‘Indigenize’ western methodologies. For example, Carter et al. asserted that they conceptualized E/TES as a theory “for [how] Indigenous theory and non-Indigenous methods [could] be harmonized” [ 74 ] and used E/TES by Indigenizing their narrative methodology. For the authors, this meant that the non-Indigenous researcher “acknowledged with curiosity and respect the ways the participants interpreted experiences, which were outside of her worldview” and, in return, “participants helped [the researcher] understand by explaining the context and their beliefs” [ 74 ].

Insufficiently described . It is important to note that although some researchers reported that they used E/TES as a theoretical approach, methodology, or method, they did not always articulate how E/TES was used in their study [ 85 ]. For example, in Crook et al.’s article about a mental health first aid course, they described using E/TES as an approach to data collection and they outlined the ways they saw E/TES aligning with other Indigenous frameworks; however, they did not provide specific examples of what E/TES looked like in their study [ 23 ]. Similarly, Blangy et al. simply wrote that they adopted a ‘Two-Eyed Seeing’ framework without a greater explanation of how this looked in practice [ 80 ]. Stelkia et al. asserted that they embodied a E/TES approach, respecting distinct perspectives of diverse Nations in the region, however, they did not provide further detail [ 83 ].

Domain 3: Analysis and interpretation

Analysis and interpretation refers to specifying “how the research analysis and reporting supported critical inquiry and a strength-based approach inclusive of Indigenous values” [ 9 ].

E/TES was used in the analysis and interpretation sections of 36 articles. Among the 36 articles, 31 articles included E/TES in data analysis [ 20 , 29 , 34 , 35 , 38 – 41 , 43 , 47 , 48 , 50 , 52 , 53 , 55 , 56 , 58 , 63 , 64 , 70 , 73 , 74 , 81 , 82 , 86 – 92 ], and nine articles focused on using E/TES in the interpretation of findings [ 19 , 22 , 29 , 48 , 50 , 73 , 77 , 93 , 94 ]. Three articles were included in both analysis and interpretation [ 29 , 48 , 73 ].

Data analysis . Thirty-one articles included E/TES in data analysis [ 20 , 29 , 34 , 35 , 38 – 41 , 43 , 47 , 48 , 50 , 52 , 53 , 55 , 56 , 58 , 63 , 64 , 70 , 73 , 74 , 81 , 82 , 86 – 92 ]. E/TES often involved having Indigenous and non-Indigenous people involved in data analysis–either as a collaborative process with independent handling of the data [ 20 , 39 , 40 , 55 , 87 ], with the Indigenous perspective following the primary analysis to contextualize the data [ 41 , 70 ], or stating the inclusion of multiple perspectives in data analysis [ 29 , 34 , 35 , 38 , 43 , 50 , 52 , 53 , 56 , 63 , 64 , 74 , 81 , 82 , 86 , 88 – 92 ]. For example, Wright et al. [ 55 , 87 , 88 ] discussed engaging in a collaborative data analysis process by having an Indigenous research assistant work with a non-Indigenous researcher whereby the data was analyzed independently, then coming together to compare and contrast their analyses. This process required self-reflection and that both individuals carry with them their respective epistemologies and ontologies to the data analysis process with a particular focus on the non-Indigenous researcher taking note of the differences [ 55 ]. Another study involved a more iterative data analysis process with independent handling of the data by two Indigenous research team members who would then come to a consensus on the final coding which was reviewed by a non-Indigenous senior research team member to ensure consistency and accuracy in the coding [ 39 ]. In this study, a team approach involving both Indigenous and non-Indigenous members was implemented to review the final codes [ 39 ]. In another study, Wright et al. discussed what is typically considered member-checking in qualitative research as an additional process to include Indigenous perspectives which would follow a primary analysis [ 41 ]. Data analysis was described as including multiple perspectives with limited details on how data analysis was practiced or explicitly stating where Indigenous perspectives were included [ 20 , 43 , 48 , 50 , 58 , 64 , 86 ]. Some articles reported that the inclusion of E/TES in data analysis allowed them to view the data through a strength-based or Indigenous lens [ 43 , 70 , 87 ], to capture cultural nuances or the impact of colonization on the topic of interest [ 43 , 86 ], or to enhance rigour of the findings [ 43 , 81 ]. The more detailed and iterative analyses often explicitly stated the importance of Indigenous epistemologies and ontologies [ 39 , 55 ].

Additionally, there were some articles that used E/TES by employing Indigenous and Western approaches to data analysis. For example, Roburn described utilizing both a Western social media analysis and Indigenous worldviews to analyze social media expressions [ 90 ]. Similarly, Sam et al. used E/TES by contextualizing data analysis as Indigenous storytelling to make sense of participants’ experiences [ 82 ]. And finally, Vorobyova et al. used E/TES by analyzing perspectives of cultural safety amongst Indigenous and White older adults living with HIV [ 35 ].

Data interpretation . Nine articles focused on using E/TES in the interpretation of findings [ 19 , 22 , 29 , 48 , 50 , 73 , 77 , 93 , 94 ]. Some articles focused on bringing different perspectives together without explaining the influence of these perspectives on the data. For instance, one article simply stated that it allowed the authors to use Indigenous perspectives to explain findings [ 22 ]. Similarly, others used E/TES in a very broad sense to interpret or explain the relevance of the authors’ work with regards to health, illness, healing, or treatment. E/TES was used to explain and understand illnesses and treatments characterized in a biomedical model and reflecting on the Indigenous perspectives or visualizations of illnesses and healing [ 19 , 50 , 77 , 94 ]. These articles did not give specific descriptions of what E/TES looked like in their analysis and interpretation.

In contrast, there were two articles that more specifically described their use of E/TES [ 48 , 93 ]. For example, one author described a role for E/TES in interpreting participants’ responses about the ways they adapt to changes brought on by colonialism and their appreciation of aspects of contemporary life [ 93 ], which aligns with E/TES’s understanding that perspectives are always changing. Another author reflected on the tensions of trying to reconcile diverse knowledge systems [ 48 ].

Domain 4: Capacity

Capacity involves explaining “how the research supported the development and maintenance of Indigenous research capacity” and “how the research team undertook professional development opportunities to develop the capacity to partner with Indigenous stakeholders” [ 9 ].

The use of E/TES was consistent with Huria et al.’s definition of capacity in nine papers [ 21 , 26 , 40 , 49 , 64 , 72 , 74 , 95 , 96 ]. Some authors described their use of E/TES in their research in relation to building physical and human resource capacity (i.e., training Indigenous facilitators [ 40 ] and delivering a baccalaureate-level program in and for the community [ 95 ]), while others (n = 6) explained their use of E/TES in terms of psychological development and self-reflection. That is, authors saw E/TES as enabling researcher(s) to engage in greater reflection about their personal beliefs and values [ 96 ], consider different worldviews and understand the importance of Indigenous culture [ 21 , 26 , 64 ], build capacity to do culturally-rooted research [ 49 ], and promote dialogue and discussion between people of different worldviews [ 72 ]. Additionally, some understood E/TES as encouraging self-reflection by the non-Indigenous researchers and ensuring that the non-Indigenous researchers were cognizant of Indigenous perspectives [ 74 ].

As with articles in other domains, some authors did not sufficiently detail how E/TES was used in relation to capacity building. Whiting described distinct worlds coming together through Indigenous and mainstream service providers as gateways to bring the best aspects of these worlds to meet client and community needs [ 64 ]. We classified this example under ‘capacity’ because we understood this as aligning with the concept of co-learning between cultural and mainstream healthcare providers. However, details were not provided on how coming together was done or how the best of both worlds was chosen.

Domain 5: Dissemination

Dissemination involves a description of “the dissemination of the research findings to relevant Indigenous governing bodies and peoples” and of “the process for knowledge translation and implementation to support Indigenous advancement” [ 9 ].

The use of E/TES was described in dissemination activities in 12 articles [ 27 , 38 , 42 , 43 , 50 , 54 – 56 , 61 , 64 , 79 , 97 ]. All but one article [ 42 ] failed to explicitly acknowledge to whom the findings were being shared. The procedural aspects of dissemination and how the knowledge could be used to support Indigenous advancement was also absent. Among the 12 articles, there were two areas of focus on the use of Indigenous and non-Indigenous perspectives which were to create knowledge translation materials [ 27 , 42 , 43 , 50 , 54 – 56 , 61 , 97 ], and health or wellness approaches [ 64 , 79 ]. One article described knowledge sharing more generally as meaningfully sharing and applying the research to address community health disparities [ 38 ].

Indigenous and non-Indigenous perspectives were brought together in 9 articles to inform the type of knowledge translation materials created (e.g., short stories, academic publications, teaching tools, instrument development, fact sheets, communication and management strategies, consensus statement) [ 27 , 42 , 50 , 61 , 97 ] or to establish the purpose of the materials (e.g., health promotion, health literacy, and awareness messages; greater knowledge on research topics and Indigenous roles; explain how Indigenous worldviews inform the research process; inform policymaking and programming) [ 27 , 42 , 43 , 54 , 56 ]. Two articles focused on co-learning as part of dissemination [ 42 , 56 ]. Three articles stated the role of E/TES in knowledge exchange and influencing future knowledge translation efforts [ 43 , 55 , 56 ].

The use of Indigenous and non-Indigenous perspectives to create health or wellness approaches was described in two articles [ 64 , 79 ]. However, details were not provided on how this was done or how aspects of each perspective were chosen.

Also, all articles described a role for E/TES in advancing Indigenous health or knowledge, but they did not describe how E/TES “support[ed] Indigenous advancement” [ 9 ] with regard to research capacity, policy, and investment specifically within the context of dissemination.

Domain 6: Prioritization

Prioritization refers to how the research aims stem from the identified priorities of Indigenous individuals or groups and empirical evidence [ 9 ].

The use of E/TES in prioritization was characterized in seven papers [ 34 , 42 , 56 , 68 , 82 , 94 , 98 ]. These papers describe “shared priorities” between research partners [ 94 ], how the research team came together [ 82 ], for example “through a shared topic of interest” [ 68 ], or how research can be a means to assert worldviews that are more congruent, representative, and therefore meaningful to Indigenous peoples [ 42 ]. VanEvery et al. described that in keeping with a E/TES approach, they carried out a pre-study community engagement session with researchers, healthcare providers Elders, youth, a nurse research coordinator, and a privacy officer to ensure the study goals reflected community priorities [ 34 ]. Though not specific to research per se, Clark emphasized the importance of using E/TES in health records for Manitoba Inuit by incorporating Inuit perspectives and traditional knowledge [ 98 ]. One clear example is evidenced from a paper by McMillan and Prosper. They report on how the Atlantic Policy Congress of First Nations Chiefs were ascertaining how fisheries scientists can best engage with Indigenous communities. Their policy analysis team worked in collaboration with Fisheries and Oceans Canada, particularly the Aboriginal Aquatic Resource and Oceans Management program, to embark on a co-learning journey with fisheries scientists to generate sustainable interface with Indigenous fishers, foster reciprocal relations, and create a management plan that reflects values that are important to the Mi’kmaw Nation [ 56 ].

Domain 7: Governance

Governance is characterized by “partnership agreements between research institutions with Indigenous-governing organizations”, having accountability and review mechanisms within agreements that also addresses how to minimize harms, and the specification on how agreements protect Indigenous intellectual property and knowledge stemming from research including financial and intellectual benefits [ 9 ].

Usage of E/TES in governance (e.g., research agreements, memorandums of understandings) as described by Huria et al. was reflected in one article. Although several papers mention the importance of governance, or in some cases, describe governing bodies that oversaw the research, the definition as it is conceived by Huria et al. requires more specificity than this. The definition asks for evidence that there are partnership agreements in place, and for a description of how those agreements aim to protect the interests of Indigenous Peoples. In the single example that we identified, Denny and Fanning noted that "given the parties involved, any co-management approach being discussed must acknowledge and recognize the value of multiple realities. Pluralism in this case refers to the multiple realities related to views on allocation and access, provincial and customary laws, traditional knowledge and science, values and economics, and natural and legal relationships to salmon, all of which can offer depth and insight in the design of co-management" [ 67 ]. Although this example does not specifically identify research governance, we felt it was important to include as it strives to articulate principles and mechanisms through which co-management can take place–which, although focused in this case on salmon, could apply to research more generally.

Domain 8: Participation

According to Huria et al., participation consists of specifying how individual and collective consent was obtained for future research on data or samples collected, how data and biological samples were stored, explaining the processes of removal from traditional lands, if done, and of disposal; how resource demands on Indigenous participants and communities were identified and agreed upon including any resourcing for participation, knowledge, and expertise [ 9 ].

Although 83 articles were eligible for our review, only one article met the criteria within the participation domain which was related to how resource demands on Indigenous participants and communities were identified and agreed upon including any resourcing for participation, knowledge, and expertise [ 9 ]. Hatala et al. described providing ceremonial and western-based honorariums during data collection as well as research meetings to demonstrate respect and acknowledge the contributions of their study participants [ 45 ].

The motivation for this scoping review came from Elder Dr. Albert Marshall’s concern that as E/TES is increasingly used in research, it is at greater risk of being tokenized [ 7 ]. Our goal was to push ourselves and others to do better. We thought that if we could gain a greater understanding of how E/TES is used in Indigenous health research, then we could help to support ourselves and others to use E/TES in more nuanced and thoughtful ways. Additionally, since the CONSIDER statement offers clear and specific reporting standards for research with Indigenous Peoples, we decided to evaluate the use of E/TES according to the CONSIDER statement’s eight research domains. It is important to note that the goal of this article is not to criticize individual authors for their descriptions, but rather to strive for more conscientious and intentional collective reporting of E/TES. Additionally, we are not trying to provide a prescriptive way of how to use or report on E/TES. Instead, we are hoping to encourage researchers to think critically and intentionally about the ways they are using E/TES in their respective studies and to clearly articulate this in their reports, publications, and presentations.

With these objectives in mind, rather than go through each CONSIDER domain one-by-one, in this discussion, we instead reflect on cross-cutting themes to provoke critical thinking about the ways that E/TES is used in Indigenous health research. The discussion is made up of two parts. First, we reflect on overarching themes from our scoping review and second, we consider the strengths and limitations of using the CONSIDER statement.

Part 1: Reflections on key themes

E/tes was used in varied ways..

One central theme in our scoping review was that E/TES was used in a variety of innovative and unique ways and that its use depended on each study’s specific context. In some articles, E/TES informed the topic under study, the people(s) involved, and the way(s) the project was governed. In other studies, E/TES shaped how data was collected, analyzed, and/or shared. The diversity of uses of E/TES demonstrate the adaptability and resonance of the guiding principle. As we mentioned in the introduction, one of the strengths of E/TES is that it can be used in multi-dimensional ways.

While the studies in this scoping review collectively covered all eight domains of the CONSIDER statement, no single article captured all eight of the domains as they were articulated by Huria et al. There remains much room for expansion on the use of E/TES, particularly since its use was less frequently reported on in research activities that might contribute to greater Indigenous research sovereignty and governance (i.e., the domains of governance, participation, etc.). Indeed, it is possible that E/TES is less commonly used in these domains because they are predicated on the creation of authentic and meaningful research relationships and necessitate a level of specificity, commitment, and institutional support, which require more time and resources and take longer to establish.

While E/TES was minimally used in the domains of governance and participation, it was perhaps unsurprising that E/TES was used most in the domains of ‘methodologies’ (n = 46), and ‘relationships’ (n = 45), ‘analysis and interpretation’ (n = 36) because there has been quite a bit of scholarship written about Indigenous engagement, community-based research, and Indigenous methodologies [ 99 – 101 ]. E/TES may align with the CONSIDER statement’s definition of ‘relationships’ because the guiding principle is relational; it honours the interconnectedness of human beings and the environment and encourages co-learning between different people and perspectives [ 1 , 4 , 7 ]. Similarly, E/TES may more frequently align with Huria et al.’s definitions of ‘methodologies’ and ‘analysis and interpretation’ because E/TES is often articulated as a way of thinking about knowledge and knowledge creation–and particularly, as a way of thinking about how to bring Indigenous and non-Indigenous knowledges together. Since researchers often try to define what knowledge is and how it is generated when they are deciding which methodologies and strategies for analysis and interpretation they are going to use in their projects, there is great alignment between E/TES and these domains.

Nonetheless, even though many researchers used E/TES to inform their methods, Elder Dr. Albert Marshall and Dr. Cheryl Bartlett have been clear that E/TES is not a methodology or method [ 1 ]; it is a guiding principle for life and much broader than research [ 1 ]. As a result, we must not limit our conceptualizations of E/TES by using it solely as a methodology, method, or framework for analysis and interpretation. Rather, we must continually push the limits of our thinking beyond categorical descriptions and towards, what Elders Drs. Albert and Murdena Marshall and Dr. Bartlett describe as integrative thinking; actively pursuing the unique linkages, connections, and interpretations that emerge when diverse understandings are brought together. It is important to continue to think about and use E/TES broadly, aiming for it to be incorporated into each of the domains identified in the CONSIDER statement, and to also reflect on what synergies emerge across domains when E/TES is used to guide the work.

E/TES was insufficiently described.

Another key theme across the domains was that the use of E/TES was often not well described. Authors commonly reported that they used E/TES or they discussed the general benefits of E/TES; however, they did not clearly articulate how they used E/TES. This made it challenging at times to categorize uses of E/TES according to the CONSIDER statement. The lack of sufficient descriptions of E/TES aligns with a finding from our previous scoping review where we observed that authors extensively used direct quotes from the original authors to define and characterize E/TES and frequently would not use their own words to describe E/TES [ 1 ]. It is possible that researchers are not clearly describing E/TES and how they used it in their studies because they do not feel comfortable with E/TES, or because they are concerned that they are not using E/TES in the ‘right’ way. Alternatively, it may be that researchers believe that E/TES can simply be reduced to using Indigenous perspectives through methods and the inclusion of Indigenous people alongside non-Indigenous perspectives without meaningful consideration to what Indigenous ways of knowing and doing might mean for Indigenous communities or Peoples that goes beyond the research. Simply collecting information or data from Indigenous people does not mean that the wisdom of local or shared cultural understandings pertaining to Indigenous knowledges has been respectfully gathered [ 102 ].

Relatedly, we observed that E/TES seemed to be commonly used by non-Indigenous researchers [ 55 , 66 , 70 , 74 , 87 ]. This may be because E/TES is considered a more ‘comfortable’ principle for non-Indigenous researchers than perhaps some other Indigenous principles. For example, Wright et al. asserted that they used E/TES rather than an Indigenous theory because the researcher was not Indigenous and thus felt that she could not appropriately conduct a study grounded in Indigenous knowledges [ 55 ]. It is possible that descriptions of E/TES usage are insufficiently described because researchers may be hesitant to go deeper with the guiding principle and recognize the multiple facets of E/TES, (i.e., the importance of spirit, co-learning, and the desire to work for seven generations into the future). Non-Indigenous researchers who choose E/TES over what they might consider ‘Indigenous theory(ies)’ for comfort should consider the multiple facets of E/TES. Additionally, they might want to reflect and ask themselves why they are comfortable and whether they are simply being complacent. Using an Indigenous guiding principle means that Indigenous knowledges should be centred and valued; this is not to say that other knowledges should be rejected if valued and requested by those for whom the research is intended to benefit.

The fact that some researchers are insufficiently describing E/TES speaks directly to Elder Dr. Albert Marshall’s concern that E/TES can become tokenized or watered down if individuals are not intentional about the ways that they are using and reporting their usage of the guiding principle. This theme underscores the need for researchers to clearly articulate E/TES and its use in research.

E/TES was oversimplified.

Another theme we noticed across categories was that some uses of E/TES were oversimplified in the ways they were described. For example, in Victor et al.’s article, the authors reported that bringing Indigenous and non-Indigenous peoples together “led organically” to a E/TES practice [ 70 ]. This article seemed to suggest that simply having Indigenous and non-Indigenous people involved in a project meant that E/TES was necessarily taking place. In our previous scoping review, we identified seven descriptions of E/TES that were used by the original authors and new authors. E/TES was described as: a guide for life; co-learning journey; responsibility for future generations; numerous or diverse perspectives; spirit; decolonization and self-determination; and humans as part of the environment [ 1 ]. When authors oversimplify E/TES by suggesting that it can happen passively by simply bringing Indigenous and non-Indigenous peoples together, it misses the expansiveness, richness, and active nature of the guiding principle. E/TES is not a passive outcome; instead, it requires an engaged and deliberate process of co-learning, dialogue, and knowledge gardening. We intentionally bring forward the term ‘knowledge gardening’ here, as it is a term often used within the context of E/TES to describe the process by which we come to understand that we have options and alternatives as to how we participate in the web of life (e.g., the fostering of a new consciousness). Elder Dr. Albert Marshall eloquently explains that “seeds only germinate when environmental conditions are appropriate” [ 103 ], which he further elaborates to mean that sometimes a seed or idea (i.e., knowledge) may be planted, but it will take the right conditions, nourishment, and patience for it to begin to germinate and grow.

Clear description of E/TE.

Finally, we believe that it is important to emphasize that there were some authors who clearly and explicitly articulated how they used E/TES in their studies. These examples illustrate that clear articulations of E/TES are possible. For example, Rowan et al. reported using E/TES differently at different stages in their research project [ 50 ]. At the start of the project, E/TES exposed the researchers to different ways of knowing and encouraged them to include cultural activities and ceremony. E/TES also prompted the research team to have a balance of Western and Indigenous thinkers who were open to different ways of knowing. As the project continued, the researchers’ use of E/TES changed. E/TES informed the research question by bringing together Indigenous knowledges with Western understandings of quality of evidence; it encouraged the team to use both Indigenous-led perspectives and Western-based tools to search and screen the literature; and it prompted the researchers to switch from a systematic review to a scoping review so that the study was more open to Indigenous knowledges and contexts. Rowan et al.’s in-depth and intentional descriptions demonstrate that E/TES can offer different strengths, opportunities, and ways of thinking at different points in a project. This is not to say that there is one right way to use or report E/TES, but rather to say that what is ‘right’ about this description is that the authors were clear and considerate about how they used and reported their usage of E/TES.

Part 2: Strengths and limits of the CONSIDER statement

This was the first study that employed the CONSIDER statement to evaluate uses of E/TES. Ultimately, we found that the CONSIDER statement offered a valuable framework through which to assess how researchers were reportedly using E/TES. One of the strengths of the CONSIDER statement is that the definitions for each domain focus on practical activities and outcomes rather than on theoretical ideas. For example, ‘governance’ does not speak to research governance in general but about specific partnership agreements. Similarly, ‘relationships’ is not about an overarching partnership approach, but instead how Indigenous peoples and communities were involved in all stages of the research. As a result, the CONSIDER statement encourages researchers to move away from buzz words and to instead be clear about the specific ways they enacted E/TES. The clarity demanded in the CONSIDER statement was important because it drew our attention to situations where E/TES was and was not clearly described and thus deepened our understanding of how E/TES is being reported.

While Huria et al.’s CONSIDER domains provided a useful way of analyzing researchers’ reported use of E/TES, there were key pieces that were missing from the CONSIDER statement. For example, our analysis helped to illuminate that spirit and connection to land are not included as part of the domains. For example, Hall et al. wrote that part of their use of E/TES included “recognizing that consciousness exists between human and more-than-human environments, and the need to bring knowledge together in timely, patient, and respectful ways” [ 73 ]. We found that it was hard to categorize this use of E/TES in the CONSIDER statement because spirit and connection to land, which were key elements to their use of E/TES, are not part of the CONSIDER definitions. This finding suggests that there may be an opportunity to expand the CONSIDER statement definitions and domains to include spirit and connection to all beings.

Relatedly, and perhaps connected to this absence of spirit and connection to land, is the fundamental importance of Indigenous worldview as informing elements of all domains. The CONSIDER statement currently includes Indigenous worldviews within the ‘methodologies’ domain, which we would argue is problematic. Many decades of Indigenous scholarship have highlighted Indigenous worldviews as synonymous with Indigenous ways of knowing, which moves far beyond the idea of methodology [ 99 – 101 ].

Study limitations

There were some limitations to our study. We were interested in direct and explicit descriptions of how E/TES was used. As a result, if an article used CBPR and E/TES but discussed Indigenous engagement only in relation to CBPR and not E/TES, then we did not include it in our extraction. Similarly, we found that E/TES was less commonly applied in the domains of governance and prioritization. The absence of these domains does not mean that they were not part of the research process; rather, it means that they were not reported in relation to E/TES.

There was one article that did not fit into the CONSIDER statement’s domains because the authors did not provide sufficient detail about how E/TES was used in their study. Gray et al. wrote: “This study is also an example of how western science and Indigenous knowledge can be merged for the benefit of both knowledge systems in what is known to Indigenous groups as etuaptmumk or ‘two-eyed seeing’” [ 104 ]. Based on this description, it was difficult to determine how this study used or was an example of E/TES despite meeting our inclusion criteria.

Since we only included explicit usage of E/TES when we extracted information from the project, we may have missed some elements about how E/TES was used. This issue speaks to the need for researchers to be attentive to how they are describing their use of E/TES. Additionally, we want to be clear that the responsibility for better reporting of E/TES does not entirely lie with researchers. Since researchers are bound by the reporting requirements and limitations of the journals where they publish (e.g., low word counts and strict reporting structures), it is imperative for journals to also take steps to support better reporting.

In fact, we would argue that it may be increasingly important to publish research protocols related to Indigenous health research because the protocols can give both academic and community researchers the opportunities to expand on the research process and reflect more deeply on the process of doing research. It may also serve as an important mentoring tool for early career Indigenous researchers and shape the approaches undertaken by non-Indigenous researchers. Conducting Indigenous health research frequently requires significant and ongoing relationship building that occurs over an extended period, but is rarely documented to share lessons learned. Also, for many Indigenous and allied researchers, relationship building does not occur only upon receiving funding. A true commitment to community is made prior to asking Indigenous peoples to consult, participate, collaborate, or preferentially co-lead or lead research depending on their needs. As a result, sharing the process of establishing Indigenous governance, sovereignty, and self-determination throughout the research process can support the community in developing sustainable research frameworks as well as obtaining increased independence in pursuing research priorities.

In our paper, E/TES usage was largely found in relation to research conducted in Canada from coast to coast including the Territories with First Nations, Inuit, and Métis Peoples, showing its adaptability to various cultures and research contexts. Nevertheless, an important limitation of our paper would be to consider how and whether Indigenous Peoples from across the globe would be able to conceptualize their research process through E/TES, which may entail sharing some of the same values of the guiding principle [ 1 ] or even agreeing with the notion that bringing Indigenous perspectives and non-Indigenous perspectives together can be beneficial in research with and for Indigenous Peoples. We contend that Indigenous Peoples from regions outside of Canada have thought processes that are similar to E/TES in terms of bringing together diverse perspectives which includes local Indigenous perspectives. These are worth future explorations given the tensions that may exist between Indigenous and non-Indigenous worldviews within academia that sustain power differentials in terms of who teaches and who is taught as well as who researches and who is researched. For example, within education, Strong like Two People stemmed from the words of Tlicho Chief Jimmy Bruneau to accept “…the worldview of the white man but to never lose the skills, teachings and traditions of the Dene” [ 105 ]. Similarly, for educational purposes, the Alaska Rural Systemic Initiative was established to deliver culturally-responsive science curricula reflecting both Indigenous knowledge systems and western science traditions [ 106 ], and the Dual-Learning Environment emerges when scientific and cultural knowledge are held equal to teach Navajo students about stars and planetary system formation, for example [ 107 ]. Other concepts have surfaced to acknowledge diverse knowledge systems and work in the space between the two, such as Cree scholar Willie Ermine’s Ethical Space [ 108 ]. The Negotiated Space , which focuses on Maori and Western scientific knowledges, describes a conceptual space between different worldviews to explore a topic [ 109 ]. The Both Ways philosophy, which applies to education, but could also be used in research, focuses on bringing together two forces where tensions or creativity can occur [ 110 , 111 ]. Both Ways is said to have evolved from metaphors offered by the Yolgnu people of North East Arnhem land and Warlpiri people of Central Australia. This philosophy brings together “Indigenous Australian traditions of knowledge and Western academic disciplinary positions and cultural contexts, and embraces values of respect, tolerance and diversity” [ 110 ].

This scoping review sought to better understand how E/TES is being used in Indigenous health research with the goal of encouraging more thoughtful engagement with and use of the guiding principle. While researchers reported using E/TES in a variety of ways, many did not provide sufficient detail about how they used E/TES in their respective studies. We echo calls made by Elder Dr. Albert Marshall and Dr. Cheryl Bartlett for researchers to intentionally use E/TES in their studies and to clearly articulate this in resulting publications and presentations. We echo these calls not simply to highlight the usefulness of E/TES for research, although we believe that to be the case; we argue that E/TES is needed to bring together epistemic communities (i.e., diverse ways of knowing) to foster a new consciousness that more fulsomely explores human participation in the web of life.

Supporting information

S1 checklist. preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews (prisma-scr) checklist..

https://doi.org/10.1371/journal.pone.0310247.s001

S1 Table. Characteristics of articles that report using Etuaptmumk/Two-Eyed Seeing.

Year of publication, study participants, geographical location, research design and aim of study.

https://doi.org/10.1371/journal.pone.0310247.s002

S1 Protocol. Protocol for two-eyed seeing scoping review.

https://doi.org/10.1371/journal.pone.0310247.s003

https://doi.org/10.1371/journal.pone.0310247.s004

Acknowledgments

We would like to thank Elder Dr. Albert Marshall and Dr. Cheryl Bartlett for their generosity, patience, kindness, and commitment to sharing and teaching about their work about Two-Eyed Seeing with us. Wela’lioq for continually broadening and enriching our understandings of the guiding principle. Wela’lioq to Elder Dr. Albert for sharing Mi’kmaw knowledge to pass on from generation to generation.

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