research design and methodology difference

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Research Methods Guide: Research Design & Method

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Research Methods (sociology-focused)

Qualitative vs. Quantitative Methods (intro)

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FAQ: Research Design & Method

What is the difference between Research Design and Research Method?

Research design is a plan to answer your research question.  A research method is a strategy used to implement that plan.  Research design and methods are different but closely related, because good research design ensures that the data you obtain will help you answer your research question more effectively.

Which research method should I choose ?

It depends on your research goal.  It depends on what subjects (and who) you want to study.  Let's say you are interested in studying what makes people happy, or why some students are more conscious about recycling on campus.  To answer these questions, you need to make a decision about how to collect your data.  Most frequently used methods include:

• Observation / Participant Observation
• Focus Groups
• Experiments
• Secondary Data Analysis / Archival Study
• Mixed Methods (combination of some of the above)

One particular method could be better suited to your research goal than others, because the data you collect from different methods will be different in quality and quantity.   For instance, surveys are usually designed to produce relatively short answers, rather than the extensive responses expected in qualitative interviews.

What other factors should I consider when choosing one method over another?

Time for data collection and analysis is something you want to consider.  An observation or interview method, so-called qualitative approach, helps you collect richer information, but it takes time.  Using a survey helps you collect more data quickly, yet it may lack details.  So, you will need to consider the time you have for research and the balance between strengths and weaknesses associated with each method (e.g., qualitative vs. quantitative).

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Home » Education » Difference Between Research Methods and Research Design

Difference Between Research Methods and Research Design

Main difference – research methods vs research design.

Research methods and research design are terms you must know before starting a research project. Both these elements are essential to the success of a research project. However, many new researchers assume research methods and research design to be the same. Research design is the overall structure of a research project. For example, if you are building a house, you need to have a good idea about what kind of house you are going to build; you cannot do anything without knowing this. A research design is the same – you cannot proceed with the research study without having a proper research design. Research methods are the procedures that are used to collect and analyze data. Thus, the main difference between research methods and research design is that research design is the overall structure of the research study whereas research methods are the various processes, procedures, and tools used to collect and analyze data.

1. What are Research Methods?      – Definition, Features, Characteristics

2. What is Research Design?      – Definition, Features, Characteristics

What are Research Methods

Research methods are concerned with the various research processes, procedures, and tools – techniques of gathering information, various ways of analyzing them. Research problems can be categorized into two basic sections: qualitative research and quantitative research . Researchers may use one or both of these methods (mixed method) in their research studies. The type of research method you choose would depend on your research questions or problem and research design.

The main aim of a research study is to produce new knowledge or deepen the existing understanding of a field. This can be done by three forms.

Exploratory research – identifies and outlines a problem or question

Constructive research – tests theories and suggests solutions to a problem or question

Empirical research – tests the viability of a solution using empirical evidence

What is a Research Design

Research design is the overall plan or structure of the research project. It indicates what type of study is planned and what kind of results are expected from this project. It specifically focuses on the final results of the research. It is almost impossible to proceed with a research project without a proper research design. The main function of a research design is to make sure that the information gathered throughout the research answers the initial question unambiguously. In other words, the final outcomes and conclusions of the research must correspond with the research problems chosen at the beginning of the research.

A research design can be,

Descriptive (case study, survey, naturalistic observation, etc.)

Correlational (case-control study, observational study, etc.)

Experimental (experiments)

Semi-experimental (field experiment, quasi-experiment, etc.)

Meta-analytic (meta-analysis)

Review ( literature review , systematic review)

Research Methods : Research methods are the procedures that will be used to collect and analyze data.

Research Design: Research design is the overall structure of the research.

Research Methods: Research methods focus on what type of methods are more suitable to collect and analyze the evidence we need.

Research Design: Research design focuses on what type of study is planned and what kind of results are expected from the research.

Research Methods: Research methods depend on the research design.

Research Design: Research design is based on the research question or problem.

De Vaus, D. A. 2001. Research design in social research. London: SAGE.

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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.

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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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How to write a Literature Review: Research design vs research methodology

• Literature review process
• Purpose of a literature review
• Evaluating sources
• Managing sources
• Request a literature search
• Selecting the approach to use
• Quantitative vs qualitative method
• Summary of different research methodologies
• Research design vs research methodology
• Diagram: importance of research
• Attributes of a good research scholar

Research design and methodology

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Research Methodology: Overview of Research Methodology

• Overview of Research Methodology
• General Encyclopedias on Research Methodology
• General Handbooks on Research Methodology
• Focus Groups
• Case Studies
• Cost Benefit Analysis
• Participatory Action Research
• Archival Research
• Data Analysis

Research Methods Overview

If you are planning to do research - whether you are doing a student research project,  IQP,  MQP, GPS project, thesis, or dissertation, you need to use valid approaches and tools to set up your study, gather your data, and make sense of your findings. This research methods guide will help you choose a methodology and launch into your research project. 

Data collection and data analysis are  research methods  that can be applied to many disciplines. There is Qualitative research and Quantitative Research. The focus of this guide, includes most popular methods including: 

focus groups

case studies

We are happy to answer questions about research methods and assist with choosing a method that is right for your research in person or online. below is a video on how to book a research consultation

"How-To": Booking a Research Consultation

" Research Data Management " by  Peter Neish  is marked with  CC0 1.0 .

Research Design vs Research Method

What is the difference between Research Design and Research Method?

Research design is a plan to answer your research question.  A research method is a strategy used to implement that plan.  Research design and methods are different but closely related, because good research design ensures that the data you obtain will help you answer your research question more effectively.

Which research method should I choose ?

It depends on your research goal.  It depends on what subjects (and who) you want to study.  Let's say you are interested in studying what makes people happy, or why some students are more conscious about recycling on campus.  To answer these questions, you need to make a decision about how to collect your data.  Most frequently used methods include:

• Observation / Participant Observation
• Experiments
• Secondary Data Analysis / Archival Study
• Mixed Methods (combination of some of the above)

One particular method could be better suited to your research goal than others, because the data you collect from different methods will be different in quality and quantity.   For instance, surveys are usually designed to produce relatively short answers, rather than the extensive responses expected in qualitative interviews.

What other factors should I consider when choosing one method over another?

Time for data collection and analysis is something you want to consider.  An observation or interview method, so-called qualitative approach, helps you collect richer information, but it takes time.  Using a survey helps you collect more data quickly, yet it may lack details.  So, you will need to consider the time you have for research and the balance between strengths and weaknesses associated with each method (e.g., qualitative vs. quantitative).

Research Data Management

Research Data Management (RDM) refers to how you are going to keep and share your data over longer time frame - like after you graduate. It is defined as the organization, documentation, storage, and  preservation  of the  data  resulting from the research process, where data can be broadly defined as the outcome of experiments or observations that validate research findings, and can take a variety of forms including numerical output ( quantitative data ),  qualitative data , documentation, images, audio, and video.

"Research Design"  by  George C Gordon Library  is licensed under  CC BY 4.0  / A derivative from the  original work

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• Last Updated: Jul 31, 2023 3:07 PM
• URL: https://libguides.wpi.edu/researchmethod

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• Types of Research Designs Compared | Guide & Examples

Types of Research Designs Compared | Guide & Examples

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

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

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

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

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

Table of contents

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

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

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

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

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

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

Read more about creating a research design

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

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

Research bias

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

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Research Design and Methodology

• First Online: 19 July 2018

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At the heart of research is the question of methodology, which needs to be set out. Well-designed research and clear methodology, as well as the methods to be used in undertaking a scientific inquiry, facilitate the process of generating knowledge. Nonetheless, the multiplicity of definitions and semantic attributions of research components needs to be clarified.

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Kiyala, J.C.K. (2019). Research Design and Methodology. In: Child Soldiers and Restorative Justice. Springer, Cham. https://doi.org/10.1007/978-3-319-90071-1_9

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How To Choose Your Research Methodology

Qualitative vs quantitative vs mixed methods.

By: Derek Jansen (MBA). Expert Reviewed By: Dr Eunice Rautenbach | June 2021

Without a doubt, one of the most common questions we receive at Grad Coach is “ How do I choose the right methodology for my research? ”. It’s easy to see why – with so many options on the research design table, it’s easy to get intimidated, especially with all the complex lingo!

In this post, we’ll explain the three overarching types of research – qualitative, quantitative and mixed methods – and how you can go about choosing the best methodological approach for your research.

Overview: Choosing Your Methodology

Understanding the options – Qualitative research – Quantitative research – Mixed methods-based research

Choosing a research methodology – Nature of the research – Research area norms – Practicalities

1. Understanding the options

Before we jump into the question of how to choose a research methodology, it’s useful to take a step back to understand the three overarching types of research – qualitative , quantitative and mixed methods -based research. Each of these options takes a different methodological approach.

Qualitative research utilises data that is not numbers-based. In other words, qualitative research focuses on words , descriptions , concepts or ideas – while quantitative research makes use of numbers and statistics. Qualitative research investigates the “softer side” of things to explore and describe, while quantitative research focuses on the “hard numbers”, to measure differences between variables and the relationships between them.

Importantly, qualitative research methods are typically used to explore and gain a deeper understanding of the complexity of a situation – to draw a rich picture . In contrast to this, quantitative methods are usually used to confirm or test hypotheses . In other words, they have distinctly different purposes. The table below highlights a few of the key differences between qualitative and quantitative research – you can learn more about the differences here.

• Uses an inductive approach
• Is used to build theories
• Takes a subjective approach
• Adopts an open and flexible approach
• The researcher is close to the respondents
• Interviews and focus groups are oftentimes used to collect word-based data.
• Generally, draws on small sample sizes
• Uses qualitative data analysis techniques (e.g. content analysis , thematic analysis , etc)
• Uses a deductive approach
• Is used to test theories
• Takes an objective approach
• Adopts a closed, highly planned approach
• The research is disconnected from respondents
• Surveys or laboratory equipment are often used to collect number-based data.
• Generally, requires large sample sizes
• Uses statistical analysis techniques to make sense of the data

Mixed methods -based research, as you’d expect, attempts to bring these two types of research together, drawing on both qualitative and quantitative data. Quite often, mixed methods-based studies will use qualitative research to explore a situation and develop a potential model of understanding (this is called a conceptual framework), and then go on to use quantitative methods to test that model empirically.

In other words, while qualitative and quantitative methods (and the philosophies that underpin them) are completely different, they are not at odds with each other. It’s not a competition of qualitative vs quantitative. On the contrary, they can be used together to develop a high-quality piece of research. Of course, this is easier said than done, so we usually recommend that first-time researchers stick to a single approach , unless the nature of their study truly warrants a mixed-methods approach.

The key takeaway here, and the reason we started by looking at the three options, is that it’s important to understand that each methodological approach has a different purpose – for example, to explore and understand situations (qualitative), to test and measure (quantitative) or to do both. They’re not simply alternative tools for the same job. 

Right – now that we’ve got that out of the way, let’s look at how you can go about choosing the right methodology for your research.

2. How to choose a research methodology

To choose the right research methodology for your dissertation or thesis, you need to consider three important factors . Based on these three factors, you can decide on your overarching approach – qualitative, quantitative or mixed methods. Once you’ve made that decision, you can flesh out the finer details of your methodology, such as the sampling , data collection methods and analysis techniques (we discuss these separately in other posts ).

The three factors you need to consider are:

• The nature of your research aims, objectives and research questions
• The methodological approaches taken in the existing literature
• Practicalities and constraints

Let’s take a look at each of these.

Factor #1: The nature of your research

As I mentioned earlier, each type of research (and therefore, research methodology), whether qualitative, quantitative or mixed, has a different purpose and helps solve a different type of question. So, it’s logical that the key deciding factor in terms of which research methodology you adopt is the nature of your research aims, objectives and research questions .

But, what types of research exist?

Broadly speaking, research can fall into one of three categories:

• Exploratory – getting a better understanding of an issue and potentially developing a theory regarding it
• Confirmatory – confirming a potential theory or hypothesis by testing it empirically
• A mix of both – building a potential theory or hypothesis and then testing it

As a rule of thumb, exploratory research tends to adopt a qualitative approach , whereas confirmatory research tends to use quantitative methods . This isn’t set in stone, but it’s a very useful heuristic. Naturally then, research that combines a mix of both, or is seeking to develop a theory from the ground up and then test that theory, would utilize a mixed-methods approach.

Let’s look at an example in action.

If your research aims were to understand the perspectives of war veterans regarding certain political matters, you’d likely adopt a qualitative methodology, making use of interviews to collect data and one or more qualitative data analysis methods to make sense of the data.

If, on the other hand, your research aims involved testing a set of hypotheses regarding the link between political leaning and income levels, you’d likely adopt a quantitative methodology, using numbers-based data from a survey to measure the links between variables and/or constructs .

So, the first (and most important thing) thing you need to consider when deciding which methodological approach to use for your research project is the nature of your research aims , objectives and research questions. Specifically, you need to assess whether your research leans in an exploratory or confirmatory direction or involves a mix of both.

The importance of achieving solid alignment between these three factors and your methodology can’t be overstated. If they’re misaligned, you’re going to be forcing a square peg into a round hole. In other words, you’ll be using the wrong tool for the job, and your research will become a disjointed mess.

If your research is a mix of both exploratory and confirmatory, but you have a tight word count limit, you may need to consider trimming down the scope a little and focusing on one or the other. One methodology executed well has a far better chance of earning marks than a poorly executed mixed methods approach. So, don’t try to be a hero, unless there is a very strong underpinning logic.

Need a helping hand?

Factor #2: The disciplinary norms

Choosing the right methodology for your research also involves looking at the approaches used by other researchers in the field, and studies with similar research aims and objectives to yours. Oftentimes, within a discipline, there is a common methodological approach (or set of approaches) used in studies. While this doesn’t mean you should follow the herd “just because”, you should at least consider these approaches and evaluate their merit within your context.

A major benefit of reviewing the research methodologies used by similar studies in your field is that you can often piggyback on the data collection techniques that other (more experienced) researchers have developed. For example, if you’re undertaking a quantitative study, you can often find tried and tested survey scales with high Cronbach’s alphas. These are usually included in the appendices of journal articles, so you don’t even have to contact the original authors. By using these, you’ll save a lot of time and ensure that your study stands on the proverbial “shoulders of giants” by using high-quality measurement instruments .

Of course, when reviewing existing literature, keep point #1 front of mind. In other words, your methodology needs to align with your research aims, objectives and questions. Don’t fall into the trap of adopting the methodological “norm” of other studies just because it’s popular. Only adopt that which is relevant to your research.

Factor #3: Practicalities

When choosing a research methodology, there will always be a tension between doing what’s theoretically best (i.e., the most scientifically rigorous research design ) and doing what’s practical , given your constraints . This is the nature of doing research and there are always trade-offs, as with anything else.

But what constraints, you ask?

When you’re evaluating your methodological options, you need to consider the following constraints:

• Data access
• Equipment and software
• Your knowledge and skills

Let’s look at each of these.

Constraint #1: Data access

The first practical constraint you need to consider is your access to data . If you’re going to be undertaking primary research , you need to think critically about the sample of respondents you realistically have access to. For example, if you plan to use in-person interviews , you need to ask yourself how many people you’ll need to interview, whether they’ll be agreeable to being interviewed, where they’re located, and so on.

If you’re wanting to undertake a quantitative approach using surveys to collect data, you’ll need to consider how many responses you’ll require to achieve statistically significant results. For many statistical tests, a sample of a few hundred respondents is typically needed to develop convincing conclusions.

So, think carefully about what data you’ll need access to, how much data you’ll need and how you’ll collect it. The last thing you want is to spend a huge amount of time on your research only to find that you can’t get access to the required data.

Constraint #2: Time

The next constraint is time. If you’re undertaking research as part of a PhD, you may have a fairly open-ended time limit, but this is unlikely to be the case for undergrad and Masters-level projects. So, pay attention to your timeline, as the data collection and analysis components of different methodologies have a major impact on time requirements . Also, keep in mind that these stages of the research often take a lot longer than originally anticipated.

Another practical implication of time limits is that it will directly impact which time horizon you can use – i.e. longitudinal vs cross-sectional . For example, if you’ve got a 6-month limit for your entire research project, it’s quite unlikely that you’ll be able to adopt a longitudinal time horizon. 

Constraint #3: Money

As with so many things, money is another important constraint you’ll need to consider when deciding on your research methodology. While some research designs will cost near zero to execute, others may require a substantial budget .

Some of the costs that may arise include:

• Software costs – e.g. survey hosting services, analysis software, etc.
• Promotion costs – e.g. advertising a survey to attract respondents
• Incentive costs – e.g. providing a prize or cash payment incentive to attract respondents
• Equipment rental costs – e.g. recording equipment, lab equipment, etc.
• Travel costs
• Food & beverages

These are just a handful of costs that can creep into your research budget. Like most projects, the actual costs tend to be higher than the estimates, so be sure to err on the conservative side and expect the unexpected. It’s critically important that you’re honest with yourself about these costs, or you could end up getting stuck midway through your project because you’ve run out of money.

Constraint #4: Equipment & software

Another practical consideration is the hardware and/or software you’ll need in order to undertake your research. Of course, this variable will depend on the type of data you’re collecting and analysing. For example, you may need lab equipment to analyse substances, or you may need specific analysis software to analyse statistical data. So, be sure to think about what hardware and/or software you’ll need for each potential methodological approach, and whether you have access to these.

Constraint #5: Your knowledge and skillset

The final practical constraint is a big one. Naturally, the research process involves a lot of learning and development along the way, so you will accrue knowledge and skills as you progress. However, when considering your methodological options, you should still consider your current position on the ladder.

Some of the questions you should ask yourself are:

• Am I more of a “numbers person” or a “words person”?
• How much do I know about the analysis methods I’ll potentially use (e.g. statistical analysis)?
• How much do I know about the software and/or hardware that I’ll potentially use?
• How excited am I to learn new research skills and gain new knowledge?
• How much time do I have to learn the things I need to learn?

Answering these questions honestly will provide you with another set of criteria against which you can evaluate the research methodology options you’ve shortlisted.

So, as you can see, there is a wide range of practicalities and constraints that you need to take into account when you’re deciding on a research methodology. These practicalities create a tension between the “ideal” methodology and the methodology that you can realistically pull off. This is perfectly normal, and it’s your job to find the option that presents the best set of trade-offs.

Recap: Choosing a methodology

In this post, we’ve discussed how to go about choosing a research methodology. The three major deciding factors we looked at were:

• Exploratory
• Confirmatory
• Combination
• Research area norms
• Hardware and software
• Your knowledge and skillset

If you have any questions, feel free to leave a comment below. If you’d like a helping hand with your research methodology, check out our 1-on-1 research coaching service , or book a free consultation with a friendly Grad Coach.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

Very useful and informative especially for beginners

Nice article! I’m a beginner in the field of cybersecurity research. I am a Telecom and Network Engineer and Also aiming for PhD scholarship.

I find the article very informative especially for my decitation it has been helpful and an eye opener.

Hi I am Anna ,

I am a PHD candidate in the area of cyber security, maybe we can link up

The Examples shows by you, for sure they are really direct me and others to knows and practices the Research Design and prepration.

I found the post very informative and practical.

I struggle so much with designs of the research for sure!

I’m the process of constructing my research design and I want to know if the data analysis I plan to present in my thesis defense proposal possibly change especially after I gathered the data already.

Thank you so much this site is such a life saver. How I wish 1-1 coaching is available in our country but sadly it’s not.

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Research Design Considerations

Associated data.

Editor's Note: The online version of this article contains references and resources for further reading and the authors' professional information.

The Challenge

“I'd really like to do a survey” or “Let's conduct some interviews” might sound like reasonable starting points for a research project. However, it is crucial that researchers examine their philosophical assumptions and those underpinning their research questions before selecting data collection methods. Philosophical assumptions relate to ontology, or the nature of reality, and epistemology, the nature of knowledge. Alignment of the researcher's worldview (ie, ontology and epistemology) with methodology (research approach) and methods (specific data collection, analysis, and interpretation tools) is key to quality research design. This Rip Out will explain philosophical differences between quantitative and qualitative research designs and how they affect definitions of rigorous research.

What Is Known

Worldviews offer different beliefs about what can be known and how it can be known, thereby shaping the types of research questions that are asked, the research approach taken, and ultimately, the data collection and analytic methods used. Ontology refers to the question of “What can we know?” Ontological viewpoints can be placed on a continuum: researchers at one end believe that an observable reality exists independent of our knowledge of it, while at the other end, researchers believe that reality is subjective and constructed, with no universal “truth” to be discovered. 1,2 Epistemology refers to the question of “How can we know?” 3 Epistemological positions also can be placed on a continuum, influenced by the researcher's ontological viewpoint. For example, the positivist worldview is based on belief in an objective reality and a truth to be discovered. Therefore, knowledge is produced through objective measurements and the quantitative relationships between variables. 4 This might include measuring the difference in examination scores between groups of learners who have been exposed to 2 different teaching formats, in order to determine whether a particular teaching format influenced the resulting examination scores.

In contrast, subjectivists (also referred to as constructionists or constructivists ) are at the opposite end of the continuum, and believe there are multiple or situated realities that are constructed in particular social, cultural, institutional, and historical contexts. According to this view, knowledge is created through the exploration of beliefs, perceptions, and experiences of the world, often captured and interpreted through observation, interviews, and focus groups. A researcher with this worldview might be interested in exploring the perceptions of students exposed to the 2 teaching formats, to better understand how learning is experienced in the 2 settings. It is crucial that there is alignment between ontology (what can we know?), epistemology (how can we know it?), methodology (what approach should be used?), and data collection and analysis methods (what specific tools should be used?). 5

Key Differences in Qualitative and Quantitative Approaches

Use of theory.

Quantitative approaches generally test theory, while qualitative approaches either use theory as a lens that shapes the research design or generate new theories inductively from their data. 4

Use of Logic

Quantitative approaches often involve deductive logic, starting off with general arguments of theories and concepts that result in data points. 4 Qualitative approaches often use inductive logic or both inductive and deductive logic, start with the data, and build up to a description, theory, or explanatory model. 4

Purpose of Results

Quantitative approaches attempt to generalize findings; qualitative approaches pay specific attention to particular individuals, groups, contexts, or cultures to provide a deep understanding of a phenomenon in local context. 4

Establishing Rigor

Quantitative researchers must collect evidence of validity and reliability. Some qualitative researchers also aim to establish validity and reliability. They seek to be as objective as possible through techniques, including cross-checking and cross-validating sources during observations. 6 Other qualitative researchers have developed specific frameworks, terminology, and criteria on which qualitative research should be evaluated. 6,7 For example, the use of credibility, transferability, dependability, and confirmability as criteria for rigor seek to establish the accuracy, trustworthiness, and believability of the research, rather than its validity and reliability. 8 Thus, the framework of rigor you choose will depend on your chosen methodology (see “Choosing a Qualitative Research Approach” Rip Out).

View of Objectivity

A goal of quantitative research is to maintain objectivity, in other words, to reduce the influence of the researcher on data collection as much as possible. Some qualitative researchers also attempt to reduce their own influence on the research. However, others suggest that these approaches subscribe to positivistic ideals, which are inappropriate for qualitative research, 6,9,10 as researchers should not seek to eliminate the effects of their influence on the study but to understand them through reflexivity . 11 Reflexivity is an acknowledgement that, to make sense of the social world, a researcher will inevitably draw on his or her own values, norms, and concepts, which prevent a totally objective view of the social world. 12

Sampling Strategies

Quantitative research favors using large, randomly generated samples, especially if the intent of the research is to generalize to other populations. 6 Instead, qualitative research often focuses on participants who are likely to provide rich information about the study questions, known as purposive sampling . 6

How You Can Start TODAY

• Consider how you can best address your research problem and what philosophical assumptions you are making.
• Consider your ontological and epistemological stance by asking yourself: What can I know about the phenomenon of interest? How can I know what I want to know? W hat approach should I use and why? Answers to these questions might be relatively fixed but should be flexible enough to guide methodological choices that best suit different research problems under study. 5
• Select an appropriate sampling strategy. Purposive sampling is often used in qualitative research, with a goal of finding information-rich cases, not to generalize. 6
• Be reflexive: Examine the ways in which your history, education, experiences, and worldviews have affected the research questions you have selected and your data collection methods, analyses, and writing. 13

How You Can Start TODAY—An Example

Let's assume that you want to know about resident learning on a particular clinical rotation. Your initial thought is to use end-of-rotation assessment scores as a way to measure learning. However, these assessments cannot tell you how or why residents are learning. While you cannot know for sure that residents are learning, consider what you can know—resident perceptions of their learning experiences on this rotation.

Next, you consider how to go about collecting this data—you could ask residents about their experiences in interviews or watch them in their natural settings. Since you would like to develop a theory of resident learning in clinical settings, you decide to use grounded theory as a methodology, as you believe asking residents about their experience using in-depth interviews is the best way for you to elicit the information you are seeking. You should also do more research on grounded theory by consulting related resources, and you will discover that grounded theory requires theoretical sampling. 14,15 You also decide to use the end-of-rotation assessment scores to help select your sample.

Since you want to know how and why students learn, you decide to sample extreme cases of students who have performed well and poorly on the end-of-rotation assessments. You think about how your background influences your standpoint about the research question: Were you ever a resident? How did you score on your end-of-rotation assessments? Did you feel this was an accurate representation of your learning? Are you a clinical faculty member now? Did your rotations prepare you well for this role? How does your history shape the way you view the problem? Seek to challenge, elaborate, and refine your assumptions throughout the research.

As you proceed with the interviews, they trigger further questions, and you then decide to conduct interviews with faculty members to get a more complete picture of the process of learning in this particular resident clinical rotation.

What You Can Do LONG TERM

• Familiarize yourself with published guides on conducting and evaluating qualitative research. 5,16–18 There is no one-size-fits-all formula for qualitative research. However, there are techniques for conducting your research in a way that stays true to the traditions of qualitative research.
• Consider the reporting style of your results. For some research approaches, it would be inappropriate to quantify results through frequency or numerical counts. 19 In this case, instead of saying “5 respondents reported X,” you might consider “respondents who reported X described Y.”
• Review the conventions and writing styles of articles published with a methodological approach similar to the one you are considering. If appropriate, consider using a reflexive writing style to demonstrate understanding of your own role in shaping the research. 6

Supplementary Material

Research Methodology vs. Research Methods

What's the difference.

Research methodology and research methods are two closely related concepts in the field of research. Research methodology refers to the overall approach or strategy used to conduct research, while research methods are the specific techniques or tools employed within that approach. In other words, research methodology is the framework that guides the entire research process, including the selection of research methods. It involves making decisions about the research design, data collection methods, data analysis techniques, and interpretation of findings. On the other hand, research methods are the practical steps taken to gather and analyze data, such as surveys, interviews, experiments, or observations. Therefore, research methodology provides the overarching structure, while research methods are the specific actions taken to carry out the research.

Further Detail

Introduction.

Research plays a crucial role in advancing knowledge and understanding in various fields. It provides a systematic approach to investigate and explore different phenomena. However, it is essential to distinguish between research methodology and research methods. While they are closely related, they have distinct attributes that contribute to the overall research process. In this article, we will compare and contrast the characteristics of research methodology and research methods, highlighting their significance in conducting effective research.

Research Methodology

Research methodology refers to the overall framework and strategy employed to conduct research. It encompasses the theoretical underpinnings, principles, and guidelines that guide the entire research process. Research methodology provides a roadmap for researchers to design, plan, and execute their studies effectively. It involves making decisions about the research design, data collection methods, data analysis techniques, and interpretation of findings.

One of the key attributes of research methodology is its focus on the overall research approach. It involves selecting the appropriate research design, such as experimental, correlational, or qualitative, based on the research objectives and nature of the research problem. Research methodology also emphasizes the importance of formulating research questions or hypotheses that align with the research objectives and can be effectively addressed through the chosen research design.

Furthermore, research methodology involves determining the appropriate data collection methods. This includes selecting between primary and secondary data sources, deciding on the sample size and sampling technique, and choosing the data collection instruments, such as surveys, interviews, or observations. Research methodology also emphasizes the need for ethical considerations, ensuring that the research is conducted in an ethical and responsible manner.

Another crucial aspect of research methodology is data analysis. It involves selecting the appropriate statistical or qualitative analysis techniques to analyze the collected data. Researchers need to consider the nature of the data and the research objectives to determine the most suitable analysis methods. Additionally, research methodology emphasizes the importance of interpreting the findings and drawing valid conclusions based on the analysis results.

Overall, research methodology provides a comprehensive framework that guides the entire research process. It ensures that the research is conducted systematically, adhering to established principles and guidelines. Research methodology plays a vital role in ensuring the validity, reliability, and generalizability of research findings.

Research Methods

Research methods, on the other hand, refer to the specific techniques and tools used to collect and analyze data within the chosen research methodology. Research methods are the practical steps taken by researchers to gather information and generate empirical evidence. They are the tangible actions that researchers undertake to answer their research questions or test their hypotheses.

One of the key attributes of research methods is their focus on data collection. Researchers employ various methods to collect data, such as surveys, interviews, observations, experiments, or document analysis. Each method has its strengths and limitations, and researchers need to carefully select the most appropriate method based on the research objectives, research design, and available resources.

Research methods also involve determining the sample size and sampling technique. Researchers need to decide on the number of participants or cases to include in their study and the method of selecting those participants. The choice of sample size and sampling technique can significantly impact the generalizability and representativeness of the research findings.

Furthermore, research methods encompass the process of data analysis. Depending on the nature of the data collected, researchers employ various statistical or qualitative analysis techniques. Statistical methods may include descriptive statistics, inferential statistics, or regression analysis, while qualitative methods may involve thematic analysis, content analysis, or grounded theory. The choice of analysis method depends on the research questions, data type, and research design.

Research methods also involve the interpretation of findings. Researchers need to analyze the results of their data analysis and draw meaningful conclusions. They need to critically evaluate the findings in the context of the research objectives and existing literature. The interpretation of findings should be unbiased, logical, and supported by evidence.

In summary, research methods are the practical tools and techniques used to collect and analyze data within the chosen research methodology. They provide the means to gather empirical evidence and answer research questions. Research methods are essential for the successful execution of research projects and contribute to the overall validity and reliability of the research findings.

Research methodology and research methods are two interconnected yet distinct components of the research process. Research methodology provides the overall framework and strategy for conducting research, guiding researchers in making decisions about research design, data collection methods, data analysis techniques, and interpretation of findings. On the other hand, research methods are the specific techniques and tools used to collect and analyze data within the chosen research methodology. They involve practical steps such as data collection, sample size determination, data analysis, and interpretation of findings.

Both research methodology and research methods are crucial for conducting effective research. They ensure that the research is conducted systematically, adhering to established principles and guidelines. By employing appropriate research methodology and selecting suitable research methods, researchers can enhance the validity, reliability, and generalizability of their research findings. Understanding the attributes and distinctions between research methodology and research methods is essential for researchers to design and execute high-quality research studies.

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Home » Research Design – Types, Methods and Examples

Research Design – Types, Methods and Examples

Table of Contents

Research Design

Definition:

Research design refers to the overall strategy or plan for conducting a research study. It outlines the methods and procedures that will be used to collect and analyze data, as well as the goals and objectives of the study. Research design is important because it guides the entire research process and ensures that the study is conducted in a systematic and rigorous manner.

Types of Research Design

Types of Research Design are as follows:

Descriptive Research Design

This type of research design is used to describe a phenomenon or situation. It involves collecting data through surveys, questionnaires, interviews, and observations. The aim of descriptive research is to provide an accurate and detailed portrayal of a particular group, event, or situation. It can be useful in identifying patterns, trends, and relationships in the data.

Correlational Research Design

Correlational research design is used to determine if there is a relationship between two or more variables. This type of research design involves collecting data from participants and analyzing the relationship between the variables using statistical methods. The aim of correlational research is to identify the strength and direction of the relationship between the variables.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This type of research design involves manipulating one variable and measuring the effect on another variable. It usually involves randomly assigning participants to groups and manipulating an independent variable to determine its effect on a dependent variable. The aim of experimental research is to establish causality.

Quasi-experimental Research Design

Quasi-experimental research design is similar to experimental research design, but it lacks one or more of the features of a true experiment. For example, there may not be random assignment to groups or a control group. This type of research design is used when it is not feasible or ethical to conduct a true experiment.

Case Study Research Design

Case study research design is used to investigate a single case or a small number of cases in depth. It involves collecting data through various methods, such as interviews, observations, and document analysis. The aim of case study research is to provide an in-depth understanding of a particular case or situation.

Longitudinal Research Design

Longitudinal research design is used to study changes in a particular phenomenon over time. It involves collecting data at multiple time points and analyzing the changes that occur. The aim of longitudinal research is to provide insights into the development, growth, or decline of a particular phenomenon over time.

Structure of Research Design

The format of a research design typically includes the following sections:

• Introduction : This section provides an overview of the research problem, the research questions, and the importance of the study. It also includes a brief literature review that summarizes previous research on the topic and identifies gaps in the existing knowledge.
• Research Questions or Hypotheses: This section identifies the specific research questions or hypotheses that the study will address. These questions should be clear, specific, and testable.
• Research Methods : This section describes the methods that will be used to collect and analyze data. It includes details about the study design, the sampling strategy, the data collection instruments, and the data analysis techniques.
• Data Collection: This section describes how the data will be collected, including the sample size, data collection procedures, and any ethical considerations.
• Data Analysis: This section describes how the data will be analyzed, including the statistical techniques that will be used to test the research questions or hypotheses.
• Results : This section presents the findings of the study, including descriptive statistics and statistical tests.
• Discussion and Conclusion : This section summarizes the key findings of the study, interprets the results, and discusses the implications of the findings. It also includes recommendations for future research.
• References : This section lists the sources cited in the research design.

Example of Research Design

An Example of Research Design could be:

Research question: Does the use of social media affect the academic performance of high school students?

Research design:

• Research approach : The research approach will be quantitative as it involves collecting numerical data to test the hypothesis.
• Research design : The research design will be a quasi-experimental design, with a pretest-posttest control group design.
• Sample : The sample will be 200 high school students from two schools, with 100 students in the experimental group and 100 students in the control group.
• Data collection : The data will be collected through surveys administered to the students at the beginning and end of the academic year. The surveys will include questions about their social media usage and academic performance.
• Data analysis : The data collected will be analyzed using statistical software. The mean scores of the experimental and control groups will be compared to determine whether there is a significant difference in academic performance between the two groups.
• Limitations : The limitations of the study will be acknowledged, including the fact that social media usage can vary greatly among individuals, and the study only focuses on two schools, which may not be representative of the entire population.
• Ethical considerations: Ethical considerations will be taken into account, such as obtaining informed consent from the participants and ensuring their anonymity and confidentiality.

How to Write Research Design

Writing a research design involves planning and outlining the methodology and approach that will be used to answer a research question or hypothesis. Here are some steps to help you write a research design:

• Define the research question or hypothesis : Before beginning your research design, you should clearly define your research question or hypothesis. This will guide your research design and help you select appropriate methods.
• Select a research design: There are many different research designs to choose from, including experimental, survey, case study, and qualitative designs. Choose a design that best fits your research question and objectives.
• Develop a sampling plan : If your research involves collecting data from a sample, you will need to develop a sampling plan. This should outline how you will select participants and how many participants you will include.
• Define variables: Clearly define the variables you will be measuring or manipulating in your study. This will help ensure that your results are meaningful and relevant to your research question.
• Choose data collection methods : Decide on the data collection methods you will use to gather information. This may include surveys, interviews, observations, experiments, or secondary data sources.
• Create a data analysis plan: Develop a plan for analyzing your data, including the statistical or qualitative techniques you will use.
• Consider ethical concerns : Finally, be sure to consider any ethical concerns related to your research, such as participant confidentiality or potential harm.

When to Write Research Design

Research design should be written before conducting any research study. It is an important planning phase that outlines the research methodology, data collection methods, and data analysis techniques that will be used to investigate a research question or problem. The research design helps to ensure that the research is conducted in a systematic and logical manner, and that the data collected is relevant and reliable.

Ideally, the research design should be developed as early as possible in the research process, before any data is collected. This allows the researcher to carefully consider the research question, identify the most appropriate research methodology, and plan the data collection and analysis procedures in advance. By doing so, the research can be conducted in a more efficient and effective manner, and the results are more likely to be valid and reliable.

Purpose of Research Design

The purpose of research design is to plan and structure a research study in a way that enables the researcher to achieve the desired research goals with accuracy, validity, and reliability. Research design is the blueprint or the framework for conducting a study that outlines the methods, procedures, techniques, and tools for data collection and analysis.

Some of the key purposes of research design include:

• Providing a clear and concise plan of action for the research study.
• Ensuring that the research is conducted ethically and with rigor.
• Maximizing the accuracy and reliability of the research findings.
• Minimizing the possibility of errors, biases, or confounding variables.
• Ensuring that the research is feasible, practical, and cost-effective.
• Determining the appropriate research methodology to answer the research question(s).
• Identifying the sample size, sampling method, and data collection techniques.
• Determining the data analysis method and statistical tests to be used.
• Facilitating the replication of the study by other researchers.
• Enhancing the validity and generalizability of the research findings.

Applications of Research Design

There are numerous applications of research design in various fields, some of which are:

• Social sciences: In fields such as psychology, sociology, and anthropology, research design is used to investigate human behavior and social phenomena. Researchers use various research designs, such as experimental, quasi-experimental, and correlational designs, to study different aspects of social behavior.
• Education : Research design is essential in the field of education to investigate the effectiveness of different teaching methods and learning strategies. Researchers use various designs such as experimental, quasi-experimental, and case study designs to understand how students learn and how to improve teaching practices.
• Health sciences : In the health sciences, research design is used to investigate the causes, prevention, and treatment of diseases. Researchers use various designs, such as randomized controlled trials, cohort studies, and case-control studies, to study different aspects of health and healthcare.
• Business : Research design is used in the field of business to investigate consumer behavior, marketing strategies, and the impact of different business practices. Researchers use various designs, such as survey research, experimental research, and case studies, to study different aspects of the business world.
• Engineering : In the field of engineering, research design is used to investigate the development and implementation of new technologies. Researchers use various designs, such as experimental research and case studies, to study the effectiveness of new technologies and to identify areas for improvement.

Advantages of Research Design

Here are some advantages of research design:

• Systematic and organized approach : A well-designed research plan ensures that the research is conducted in a systematic and organized manner, which makes it easier to manage and analyze the data.
• Clear objectives: The research design helps to clarify the objectives of the study, which makes it easier to identify the variables that need to be measured, and the methods that need to be used to collect and analyze data.
• Minimizes bias: A well-designed research plan minimizes the chances of bias, by ensuring that the data is collected and analyzed objectively, and that the results are not influenced by the researcher’s personal biases or preferences.
• Efficient use of resources: A well-designed research plan helps to ensure that the resources (time, money, and personnel) are used efficiently and effectively, by focusing on the most important variables and methods.
• Replicability: A well-designed research plan makes it easier for other researchers to replicate the study, which enhances the credibility and reliability of the findings.
• Validity: A well-designed research plan helps to ensure that the findings are valid, by ensuring that the methods used to collect and analyze data are appropriate for the research question.
• Generalizability : A well-designed research plan helps to ensure that the findings can be generalized to other populations, settings, or situations, which increases the external validity of the study.

Research Design Vs Research Methodology

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• Study protocol
• Open access
• Published: 04 September 2024

Evaluating fentanyl test strips as a harm reduction strategy in rural and urban counties: study protocol for a randomized controlled trial

• Ashley Short Mejia 1 ,
• Gary A. Smith 1 , 2 ,
• Soledad A. Fernandez 1 , 3 ,
• Bridget Freisthler 1 , 4 ,
• Christine Grella 5 &
• Nichole L. Michaels   ORCID: orcid.org/0000-0003-2618-6440 1 , 2  

Trials volume  25 , Article number:  587 ( 2024 ) Cite this article

Metrics details

Opioid-related fatalities are a leading cause of death in Ohio and nationally, with an increasing number of overdoses attributable to fentanyl. Rapid fentanyl test strips can identify fentanyl and some fentanyl analogs in urine samples and are increasingly being used to check illicit drugs for fentanyl before they are used. Fentanyl test strips are a promising harm reduction strategy; however, little is known about the real-world acceptability and impact of fentanyl test strip use. This study investigates fentanyl test strip distribution and education as a harm reduction strategy to prevent overdoses among people who use drugs.

The research team will recruit 2400 individuals ≥ 18 years with self-reported use of illicit drugs or drugs purchased on the street within the past 6 months. Recruitment will occur at opioid overdose education and naloxone distribution programs in 16 urban and 12 rural Ohio counties. Participating sites will be randomized at the county level to the intervention or non-intervention study arm. A brief fentanyl test strip educational intervention and fentanyl test strips will be provided to participants recruited from sites in the intervention arm. These participants will be eligible to receive additional fentanyl test strips for 2 years post-enrollment. Participants recruited from sites in the non-intervention arm will not receive fentanyl test strip education or fentanyl test strips. All participants will be followed for 2 years post-enrollment using biweekly, quarterly, and 6-month surveys. Primary outcomes include (1) identification of perceived barriers and facilitating factors associated with incorporating fentanyl test strip education and distribution into opioid overdose education and naloxone distribution programs; (2) differences in knowledge and self-efficacy regarding how to test drugs for fentanyl and strategies for reducing overdose risk between the intervention and non-intervention groups; and (3) differences in non-fatal and fatal overdose rates between the intervention and non-intervention groups.

Findings from this cluster randomized controlled trial will contribute valuable information about the feasibility, acceptability, and impact of integrating fentanyl test strip drug checking in rural and urban communities in Ohio and help guide future overdose prevention interventions.

Trial registration

ClinicalTrials.gov NCT05463341. Registered on July 19, 2022. https://clinicaltrials.gov/study/NCT05463341

Peer Review reports

The United States (US) is experiencing an opioid-related public health crisis. In 2021, Ohio ranked 7th among all states for the highest age-adjusted drug overdose death rate, 48.1 per 100,000 population, which was 48.5% higher than that of the overall US (32.4 per 100,000 population) [ 1 , 2 ]. This drug overdose fatality rate is driven by the use of opioids [ 1 , 2 , 3 ]. An increasing number of opioid-related deaths in the US are attributable to fentanyl, a highly potent synthetic opioid pain medication [ 3 , 4 , 5 ]. Illicit fentanyl and its analogs may be manufactured and sold alone or added to other drugs, such as heroin, cocaine, and counterfeit prescription pills, with or without the user’s knowledge [ 3 , 4 , 5 ].

The increasing pervasiveness of highly lethal fentanyl and fentanyl analogs in the illicit drug supply in the US, including Ohio, has posed a substantial challenge for public health officials looking for strategies to reduce overdoses. While some effective harm reduction strategies, such as opioid overdose education and naloxone distribution (OEND) programs, are becoming more available and widely accepted, they may not be sufficient for preventing overdose deaths due to fentanyl.

Rapid fentanyl test strips (FTS), designed to test for the presence of fentanyl and some fentanyl analogs in urine samples, are increasingly being used off-label to test illicit drugs for fentanyl before they are consumed and are highly sensitive and specific in detecting fentanyl [ 6 , 7 , 8 , 9 ]. Research indicates that when people who use drugs (PWUD) receive a positive result from a fentanyl test strip, they are more likely to perform overdose risk reduction behaviors [ 9 ]. These behaviors (e.g., using less of the drug; using in the presence of someone else) may help to prevent an overdose, or ensure that assistance is nearby, if needed. In the US, access to FTS for home use is variable and is primarily being supported by public health departments and community-based harm reduction organizations. Because access to FTS is limited, little is known about (1) the feasibility and acceptability of this intervention among public health workers, community-based organizations, and PWUD and (2) how outcomes from this intervention compare with OEND-only programs.

This study protocol is designed to test an intervention to prevent drug overdoses among PWUD in rural and urban counties of Ohio. Rural populations are disproportionately burdened by the opioid crisis and face serious health disparities related to their ability to access substance use disorder treatment and emergency care, making them an important population for this research [ 10 , 11 ]. The proposed intervention will incorporate FTS education and distribution into a subset of OEND sites in Ohio. The long-term goal of this research is the reduction of overdose-related morbidity and mortality in Ohio and nationally.

Study objectives and aims

The research objectives of this study are:

Determine the feasibility and acceptability of providing FTS education and testing materials distribution in existing OEND programs.

Determine if adding FTS education and distribution to OEND programs decreases opioid overdose rates among PWUD.

Using a two-arm cluster-randomized trial design, we will answer the research objectives by testing the following specific aims:

Specific aim #1. Determine the perceived barriers and facilitating factors associated with incorporating FTS education and distribution in existing OEND programs in rural and urban counties.

Specific aim #2. Test the hypothesis that PWUD who receive FTS education and testing materials as part of an OEND program will have improved knowledge and self-efficacy regarding how to test drugs for fentanyl and strategies for lowering their risk of an opioid overdose.

Specific aim #3. Test the hypothesis that individuals who receive FTS education and testing materials as part of an OEND program will have a lower opioid overdose rate than individuals who receive OEND only (“usual practice”).

Methods/design

Study setting.

Ohio has an established infrastructure to streamline OEND that can aid in opioid overdose prevention. In an effort to prevent opioid overdose fatalities in the state, the Ohio Department of Health has partnered with local public health departments and community organizations in the state to establish a network of OEND sites. The initiative, called Project DAWN (Deaths Avoided With Naloxone), has more than 200 sites throughout the state, with many counties having multiple sites ( https://odh.ohio.gov/know-our-programs/project-dawn/project-dawn-programs ). Project DAWN sites use trained overdose prevention educators to provide OEND at no cost to clients. Recruitment for this study will occur at Project DAWN sites in Ohio.

Eligibility

Inclusion criteria for the study are (1) age 18 years or older; (2) visitor to a Project DAWN site in Ohio that has agreed to participate in the study; (3) self-reported use of illicit drugs or any drugs purchased on the street within the past 6 months; (4) has a phone number or email address to allow for follow-up contact; and (5) able to participate in study activities in English. Individuals will be excluded from the study if they are unwilling or unable to give informed consent due to altered mental status or other reasons or if they are currently incarcerated.

Study recruitment

Study recruitment will happen on a rolling basis. Periodically throughout the recruitment period, our study partner, Ohio Department of Health, will send recruitment invitations to Project DAWN sites on our behalf. A stratified sampling process will be used to select 12 rural and 16 urban counties from among those with Project DAWN sites that indicate interest in participating in the study and that are not distributing FTS at the time of study enrollment.

Participating counties will then be randomized into the intervention and non-intervention arms of the study, stratified by rural/urban status (Fig.  1 ). Randomization will occur at the county level, and all Project DAWN sites in the same county will be assigned to the same study arm (either intervention or non-intervention). Therefore, all participants enrolled in the same county will be in the same study arm. County randomization will be conducted by the biostatistician on the project (SAF), without influence by study principal investigators (PIs) or staff.

Method of assignment of counties to intervention and non-intervention study arms

To achieve our recruitment goal of 2400 participants, study staff will be on-site to enroll Project DAWN clients who wish to participate in the study. Informed written or e-consent and baseline data, contact information (i.e., locator form), and demographics will be obtained. Project DAWN sites vary in size and operate according to different schedules, but generally provide OEND at least once per week, and frequently see clients more than once. Research study staff will coordinate with each site to ensure rotating coverage of all study counties. Enrollment will begin upon Institutional Review Board (IRB) approval and follow-up will continue with each participant for 2 years. Six-month follow-up questionnaires will be administered to each participating client based on their date of enrollment. Clients who decline to participate will not be included in the study. Individuals who decline to participate but indicate they are interested in obtaining FTS will be offered a printed list of alternate sources of FTS.

Intervention

Fentanyl test strip intervention.

A brief 20-min FTS educational intervention will be provided by the study team to participants at Project DAWN sites in the intervention arm of the study following enrollment and collection of baseline data (Table  1 ). The education will be offered one-on-one with participants in the intervention arm using a curriculum developed by the study team. The curriculum contains the following components: education on the purpose, benefits, and limitations of FTS testing; a hands-on demonstration of how to use FTS for drug testing prior to consumption; diagrams explaining how to interpret FTS results; and what to do if the FTS is positive. Education will be provided on how to use FTS for different drug delivery methods (e.g., injection, snorted, pills). A brief video will be developed by the study team to demonstrate how to use and interpret the FTS. The video will be shown during the educational intervention and will also be accessible to participants in the intervention arm following enrollment. Participants will be advised of the possibility of false positive/negative results, as well as the possibility that their drugs could be mixed with other harmful and/or unanticipated substances not detectable with FTS. Participants will be encouraged to practice other harm reduction strategies (e.g., having someone with them when using drugs, keeping naloxone nearby).

Each study participant will be given 10 FTS upon enrollment. The strips will be packaged with instructions on how to use FTS, a QR code link to the video, harm reduction strategies, and contact information for the study team. Replacement FTS will be available to study participants in the intervention arm upon request throughout their 2-year follow-up period and participants will be asked if they need additional FTS during their biweekly surveys. Replacement FTS can be mailed to participants via US Postal Service or obtained from study staff during subsequent visits to the Project DAWN sites.

Non-intervention group

Participants in the non-intervention arm of the study will not receive FTS education or test strips upon enrollment, but will receive OEND from Project DAWN staff according to their usual practice. During the latter half of year 5, after data collection is complete, participants in the non-intervention arm will be offered the FTS educational intervention and a supply of FTS.

Data collection

Questionnaires.

Baseline and 6-month follow-up questionnaires will consist of true/false knowledge questions, 5-point Likert scale attitude and self-efficacy questions, and multiple-choice questions related to participant behaviors and characteristics. Participants will be asked to indicate their degree of interest in using or avoiding drugs containing fentanyl. Baseline questionnaires will be administered to Project DAWN clients who enroll in the study using iPads and the REDCap (Research Electronic Data Capture) data collection platform. Follow-up questionnaires will be administered at 6 months post-enrollment to study participants via email/text, in-person at Project DAWN sites, or via telephone. Data from paper questionnaires will be entered into REDCap by the research team upon completion and double-entry verification will be used.

Qualitative data

In the second quarter of year 5, qualitative data will be collected through interviews with Project DAWN personnel in the intervention arm to examine the feasibility and acceptability of offering FTS at Project DAWN sites. Topics of discussion will include (1) attitudes about the use of FTS; (2) perceptions of the FTS intervention that was offered at their Project DAWN site, including perceived benefits and harms; (3) barriers and enabling/reinforcing factors related to offering FTS at Project DAWN sites; and (4) interest in continuing to offer FTS at Project DAWN sites. Interviews will be conducted by study staff using an interview guide and will be audio recorded and transcribed. Coding and analysis of the transcripts will be conducted by the study team.

Statistical analyses

Study data will be analyzed using an intention-to-treat approach.

Specific aim #1: To determine the feasibility and acceptability of incorporating FTS education and distribution into existing OEND programs, a questionnaire will be administered to Project DAWN personnel, site supervisors, health commissioners, and other key intervention site personnel in year 5. Project DAWN clients in the intervention arm will be asked about the acceptability of the program as part of their 6-month follow-up questionnaire. Process measures will be collected throughout the study as another source of data on the feasibility and acceptability of the intervention. Quantitative data on process measures will include, but is not limited to, number of Project DAWN sites that express interest in participating in the study; number of Project DAWN sites that enroll; number of potential participants who request to enroll in the study; number of participants successfully enrolled; number of replacement FTS requested and distributed; proportion of participants who complete the brief biweekly surveys; and the proportion of participants who complete the 6-month follow-up questionnaire. Descriptive statistics will be calculated, including overall mean estimates with 95% confidence intervals. Analyses will also be performed by subgroups (e.g., rural/urban, Project DAWN site personnel/client, and demographic subgroups).

Specific aim #2: Measures will be taken at two time points (baseline and 6 months) to test specific aim #2. The instrument to test change in knowledge is composed of true/false items. Correct responses for each of the items will be assigned a value of 1, and incorrect responses will be given a value of 0. Total scores will be calculated. There are also items to test changes in attitudes and self-efficacy that use a 5-point Likert scale. We will also compute total scores for these items. We will fit a linear mixed model using total scores for knowledge as the response variable to test change in knowledge and will fit another linear mixed model using total scores for attitudes/self-efficacy as the response variable to test change in self-efficacy.

Random effects for county (rural/urban), Project DAWN site within county, and participant within county will be included, as well as fixed effects for time (baseline or 6 months) and treatment (intervention/non-intervention). A random variable for secular time will also be included to account for changes across time (e.g., new opioid overdose prevention initiatives, changes in drug supply). To test the hypothesis of change differences between the two time points between the two arms, we will include an interaction term “treatment × time (baseline, 6 months)” in the model. This model will include demographic variables (gender, age, and race) and other relevant covariates or confounding factors, such as education level completed, employment, previous receipt of FTS education and testing materials (Y/N), and previously experienced an overdose (Y/N). Other relevant interaction terms, such as “treatment × gender” and “treatment × race,” will be evaluated. Holm’s method will be used to adjust for ad hoc multiple comparisons. In addition, general linear mixed models (GLMM) with a logit link function will be used to study change differences for specific Y/N items or questions.

Specific aim #3: Non-fatal overdose measures will be taken every 2 weeks and fatal overdose measures will be taken quarterly to test specific aim #3. To study the odds of an experienced overdose (Y/N), a GLMM with logit function will be used. This model will include the same random and fixed effects as identified for the model used to test specific aim #2. At the end of the study period, the overall non-fatal overdose rate (with a 95% confidence interval) will be compared between intervention and non-intervention arms. The same comparison will be done separately for the overall fatal overdose rate (with a 95% confidence interval) between the intervention and non-intervention arms.

Missing data

The analyses will be conducted using an intention-to-treat approach. For the primary and secondary outcomes, every effort will be made to minimize missing data; however, in the event that data are missing, we will document the process that resulted in the missing data and consider model-based imputation methods to account for the missing data. Guidelines for handing missing data in clinical trials will be followed [ 12 ].

Sample size

We expect an enrollment rate of 65% of eligible participants and 30% attrition, a conservative estimate based on research with similar populations [ 13 ]. For the power calculations, we conservatively assumed one Project DAWN site per county. We also assumed that non-fatal overdose rates in the non-intervention and intervention groups are 20% and 10%, respectively, and the annual fatal overdose rate in the non-intervention group is 0.65% [ 14 ]. Based on our sample size calculations, we will enroll 1200 participants in each study arm for a total of 2400 participants. Assuming a 30% attrition rate, 840 participants in each arm will complete 2 years of follow-up, for a total of 1680 participants. This will permit detection of an effect size range of 0.3–0.4 for specific aim #2 and rate differences of 0.1 and 0.14, respectively, for non-fatal and fatal rates for specific aim #3, given the assumptions identified above.

Participant retention

Participant retention will be managed in a series of ongoing steps (Table  2 ). First, participants will receive “thank you” messages via email through an automated REDCap system or letter via US mail, if email is not available. Next, participants’ locator form contact information will be verified by the enrolling research assistant (RA) within 2 weeks of enrollment.

After this, participants will receive follow-up communication from the study team if they miss biweekly surveys or their 6-month survey. Participants receive automated reminders via REDCap every 3 days for up to four reminders for each biweekly survey via email or text, depending on the participant’s preference. Within 2 weeks of missing a second consecutive biweekly survey, RAs will send an email, call/voicemail, letter, and/or social media message depending on the participant’s preferences. Within 3 weeks of missing a second consecutive biweekly survey, the RAs will use the participant’s locator form to contact the participant’s friend or family. This process will be completed monthly until the individual has been successfully contacted or begins surveys. Participants also will receive automated reminders for the 6-month survey every 5 days with up to five reminders via their default survey delivery method through REDCap. Within 2 weeks of missing their 6-month survey, RAs will send an email, call/voicemail, letter, and/or message through social media. Within 3 weeks of missing the 6-month survey, RAs will use the participant’s locator form to contact the participant’s friends or family. This process will be completed for up to 2 months. Participants will also receive a participant newsletter and annual “New Year” and birthday cards.

Study timeline

We expect it will take approximately 24 months to enroll all study participants. After enrollment, study participants will complete follow-up activities for 2 years. Participants may choose to withdraw from the study at any time and will not receive further contact from the study team.

Data management

A Certificate of Confidentiality is in place for this study. Confidentiality will be promoted by assigning an identification number to each study participant. We will use only these identification numbers (and not participants' names) in the database used for study analyses. Study materials containing identifiers, including signed consent forms and gift card receipts, will be scanned and then paper copies will be shredded. Research records will be stored in a password protected computer file. Only study team members with a research need to view the data, appropriate research certifications, and IRB approval will have access. Identifiable data will be retained for 6 years after the research is complete. Upon acceptance of all study manuscripts, any electronic files with participant identifiers will be deleted.

The study team consists of two principal investigators who collaborate closely to oversee the day-to-day work of the study team and are responsible for all aspects of this research, as well as 3 co-investigators, a research coordinator, and 4 research associates. Study co-investigators assisted the principal investigators with the development of study protocols and processes in year 1 and contribute their expertise as needed throughout the study. The research coordinator oversees the implementation of participant recruitment, retention, and consent processes as well as data collection procedures conducted by the research associates. A principal investigator meets with the research coordinator at least weekly and meets with the research associates at least biweekly. The study also utilizes a community advisory board that consists of representatives from non-profit organizations active in the harm reduction community, representatives from government agencies, such as health departments and mental health services, and individuals with lived experience of drug use. The advisory committee meets approximately every 6 months.

Data safety and monitoring

A data safety and monitoring board (DSMB) will be used for this study. Collectively, the DSMB has expertise in medicine, harm reduction, behavioral science (including qualitative research expertise), biostatistics, and public health. The DSMB will review study protocols to identify whether appropriate safeguards are in place to prevent adverse events, such as fatal drug overdoses, and to determine whether the observed frequency and type of events exceed those expected in the study population. The DSMB will review the frequency of adverse events reported among intervention and non-intervention participants to identify any unanticipated problems that may increase the risk of harm among study participants or others and will make recommendations for additional safety measures, or in the case of severe unanticipated negative outcomes, stopping the trial. The DSMB will meet twice a year to review study progress and may convene additional meetings as necessary. Further details about the DSMB charter are available upon request.

Dissemination of study findings

Study findings will be shared with study participants and partnering Project DAWN sites. This study is registered on www.ClinicalTrials.gov , and summaries of study findings will be available on the website upon study completion. Study findings will also be shared through publication in peer-reviewed journals and presentation at scientific meetings and conferences. Publication authorship will be determined using International Committee of Medical Journal Editors guidelines.

Because opioid overdose is a tremendous problem in Ohio and nationally, more studies on the primary and secondary prevention of overdose are needed. Collaborating on this research project with public health officials at the state and local levels, as well as community-based harm reduction organizations, will give us insight into the real-world benefits, challenges, and unanswered questions associated with implementing FTS education and distribution programs and guide future studies.

We expect that the findings of this study will be used to inform decisions by public health leaders and policy makers on whether to support the continuation and expansion of fentanyl test strip education and distribution in Ohio. Using improved scientific rigor compared with previous research, the findings of this study will provide missing, fundamental information to our base of knowledge regarding the feasibility, acceptability, and associated benefits and harms of this emerging strategy for preventing opioid overdoses. In addition to Ohio, we believe that this program could serve as a model for other states.

Trial status

Protocol version 5, approved on October 11, 2023. Study recruitment began on September 9, 2022, and is ongoing. We anticipate study recruitment will be complete by December 31, 2024.

Availability of data and materials

The study PIs will oversee the management of all aspects of this research study and will determine access to the final trial dataset. Unique study resources and data will be made available for research purposes to qualified individuals within the scientific community after publication. Upon written request to the study contact PI (NLM), de-identified data used in publications will be made available to users under a data-sharing agreement. Along with the data, we also will make available the data instruments used to collect the data, methods of collection, variable definitions, and potential limitations for use.

Abbreviations

• Fentanyl test strips

Data safety and monitoring board

General linear mixed models

Institutional Review Board

Opioid overdose education and naloxone distribution

Principal investigator

Project Deaths Avoided With Naloxone

People who use drugs

Research assistant

Research Electronic Data Capture

United States

Centers for Disease Control and Prevention. Ohio priority topic investments. Ohio overdose investment snapshot. CDC. https://www.cdc.gov/injury/budget-funding/ohio-aces-and-overdose-prevention-funding.html?CDC_AAref_Val=https://www.cdc.gov/injury/budget/policystatesnapshots/ohio.html . Accessed 27 Jul 2024.

Centers for Disease Control and Prevention. Drug overdose mortality by state. CDC/National Center for Health Statistics. 2021. https://www.cdc.gov/nchs/pressroom/sosmap/drug_poisoning_mortality/drug_poisoning.htm . Accessed 27 Jul 2024.

Centers for Disease Control and Prevention. Preventing opioid overdoses. 2024. https://www.cdc.gov/overdose-prevention/prevention/index.html . Accessed 27 Jul 2024.

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Acknowledgements

We would like to thank our colleagues Alexandra Antonova, Aleah Cumberbatch, Jacob Holycross, and Spencer Long for their contributions to this research.

Research reported in this publication was supported by the National Institute on Drug Abuse of the National Institutes of Health under Award Number R01DA052580. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funders had no role in the design of this study and will not have any role in the collection, management, analysis, and interpretation of data; writing of the report; or decision to submit the report for publication.

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Ashley Short Mejia, Gary A. Smith, Soledad A. Fernandez, Bridget Freisthler & Nichole L. Michaels

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Gary A. Smith & Nichole L. Michaels

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Soledad A. Fernandez

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Bridget Freisthler

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ASM led manuscript preparation. The research was conceptualized and the original study protocol was developed by NLM, GAS, and SAF. All authors provided feedback on the manuscript and approved the final draft of the manuscript for publication.

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Correspondence to Nichole L. Michaels .

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The Nationwide Children’s Hospital Institutional Review Board has given ethical approval for this study (STUDY00001919). Any modifications to the study protocol are subject to approval by the IRB of record. Relevant modifications will be reported to the trial registry and other parties as necessary. Informed consent will be obtained from all study participants according to the IRB-approved study protocol. The consent process will take place on-site at the recruitment location and will be completed prior to any data collection. At the time of enrollment, a member of the research team will review the contents of the informed consent document with the potential participant and answer any questions they may have prior to obtaining written consent via e-signature or paper consent form. Consent will be documented in REDCap and a pdf file of the signed e-consent form will be emailed to the participant. If the participant does not have an email address, a paper copy will be signed and distributed to them. Paper consent forms will be used to obtain written consent in person at the time of enrollment only as necessary (e.g., due to technology failure). Participants will be able to leave the study or stop participating in study activities at any time.

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The authors declare that they have no competing interests.

As the primary organization conducting this study and associated data analysis, Nationwide Children’s Hospital is the sponsor of this research. They can be contacted at 700 Children’s Drive, Columbus, OH 43205, USA; phone number: 614–722-2000.

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Short Mejia, A., Smith, G.A., Fernandez, S.A. et al. Evaluating fentanyl test strips as a harm reduction strategy in rural and urban counties: study protocol for a randomized controlled trial. Trials 25 , 587 (2024). https://doi.org/10.1186/s13063-024-08440-y

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Received : 01 August 2024

Accepted : 28 August 2024

Published : 04 September 2024

DOI : https://doi.org/10.1186/s13063-024-08440-y

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