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Scope of the Research – Writing Guide and Examples

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Scope of the Research

Scope of the Research

Scope of research refers to the range of topics, areas, and subjects that a research project intends to cover. It is the extent and limitations of the study, defining what is included and excluded in the research.

The scope of a research project depends on various factors, such as the research questions , objectives , methodology, and available resources. It is essential to define the scope of the research project clearly to avoid confusion and ensure that the study addresses the intended research questions.

How to Write Scope of the Research

Writing the scope of the research involves identifying the specific boundaries and limitations of the study. Here are some steps you can follow to write a clear and concise scope of the research:

  • Identify the research question: Start by identifying the specific question that you want to answer through your research . This will help you focus your research and define the scope more clearly.
  • Define the objectives: Once you have identified the research question, define the objectives of your study. What specific goals do you want to achieve through your research?
  • Determine the population and sample: Identify the population or group of people that you will be studying, as well as the sample size and selection criteria. This will help you narrow down the scope of your research and ensure that your findings are applicable to the intended audience.
  • Identify the variables: Determine the variables that will be measured or analyzed in your research. This could include demographic variables, independent variables , dependent variables , or any other relevant factors.
  • Define the timeframe: Determine the timeframe for your study, including the start and end date, as well as any specific time intervals that will be measured.
  • Determine the geographical scope: If your research is location-specific, define the geographical scope of your study. This could include specific regions, cities, or neighborhoods that you will be focusing on.
  • Outline the limitations: Finally, outline any limitations or constraints of your research, such as time, resources, or access to data. This will help readers understand the scope and applicability of your research findings.

Examples of the Scope of the Research

Some Examples of the Scope of the Research are as follows:

Title : “Investigating the impact of artificial intelligence on job automation in the IT industry”

Scope of Research:

This study aims to explore the impact of artificial intelligence on job automation in the IT industry. The research will involve a qualitative analysis of job postings, identifying tasks that can be automated using AI. The study will also assess the potential implications of job automation on the workforce, including job displacement, job creation, and changes in job requirements.

Title : “Developing a machine learning model for predicting cyberattacks on corporate networks”

This study will develop a machine learning model for predicting cyberattacks on corporate networks. The research will involve collecting and analyzing network traffic data, identifying patterns and trends that are indicative of cyberattacks. The study aims to build an accurate and reliable predictive model that can help organizations identify and prevent cyberattacks before they occur.

Title: “Assessing the usability of a mobile app for managing personal finances”

This study will assess the usability of a mobile app for managing personal finances. The research will involve conducting a usability test with a group of participants, evaluating the app’s ease of use, efficiency, and user satisfaction. The study aims to identify areas of the app that need improvement, and to provide recommendations for enhancing its usability and user experience.

Title : “Exploring the effects of mindfulness meditation on stress reduction among college students”

This study aims to investigate the impact of mindfulness meditation on reducing stress levels among college students. The research will involve a randomized controlled trial with two groups: a treatment group that receives mindfulness meditation training and a control group that receives no intervention. The study will examine changes in stress levels, as measured by self-report questionnaires, before and after the intervention.

Title: “Investigating the impact of social media on body image dissatisfaction among young adults”

This study will explore the relationship between social media use and body image dissatisfaction among young adults. The research will involve a cross-sectional survey of participants aged 18-25, assessing their social media use, body image perceptions, and self-esteem. The study aims to identify any correlations between social media use and body image dissatisfaction, and to determine if certain social media platforms or types of content are particularly harmful.

When to Write Scope of the Research

Here is a guide on When to Write the Scope of the Research:

  • Before starting your research project, it’s important to clearly define the scope of your study. This will help you stay focused on your research question and avoid getting sidetracked by irrelevant information.
  • The scope of the research should be determined by the research question or problem statement. It should outline what you intend to investigate and what you will not be investigating.
  • The scope should also take into consideration any limitations of the study, such as time, resources, or access to data. This will help you realistically plan and execute your research.
  • Writing the scope of the research early in the research process can also help you refine your research question and identify any gaps in the existing literature that your study can address.
  • It’s important to revisit the scope of the research throughout the research process to ensure that you stay on track and make any necessary adjustments.
  • The scope of the research should be clearly communicated in the research proposal or study protocol to ensure that all stakeholders are aware of the research objectives and limitations.
  • The scope of the research should also be reflected in the research design, methods, and analysis plan. This will ensure that the research is conducted in a systematic and rigorous manner that is aligned with the research objectives.
  • The scope of the research should be written in a clear and concise manner, using language that is accessible to all stakeholders, including those who may not be familiar with the research topic or methodology.
  • When writing the scope of the research, it’s important to be transparent about any assumptions or biases that may influence the research findings. This will help ensure that the research is conducted in an ethical and responsible manner.
  • The scope of the research should be reviewed and approved by the research supervisor, committee members, or other relevant stakeholders. This will ensure that the research is feasible, relevant, and contributes to the field of study.
  • Finally, the scope of the research should be clearly stated in the research report or dissertation to provide context for the research findings and conclusions. This will help readers understand the significance of the research and its contribution to the field of study.

Purpose of Scope of the Research

Purposes of Scope of the Research are as follows:

  • Defines the boundaries and extent of the study.
  • Determines the specific objectives and research questions to be addressed.
  • Provides direction and focus for the research.
  • Helps to identify the relevant theories, concepts, and variables to be studied.
  • Enables the researcher to select the appropriate research methodology and techniques.
  • Allows for the allocation of resources (time, money, personnel) to the research.
  • Establishes the criteria for the selection of the sample and data collection methods.
  • Facilitates the interpretation and generalization of the results.
  • Ensures the ethical considerations and constraints are addressed.
  • Provides a framework for the presentation and dissemination of the research findings.

Advantages of Scope of the Research

Here are some advantages of having a well-defined scope of research:

  • Provides clarity and focus: Defining the scope of research helps to provide clarity and focus to the study. This ensures that the research stays on track and does not deviate from its intended purpose.
  • Helps to manage resources: Knowing the scope of research allows researchers to allocate resources effectively. This includes managing time, budget, and personnel required to conduct the study.
  • Improves the quality of research: A well-defined scope of research helps to ensure that the study is designed to achieve specific objectives. This helps to improve the quality of the research by reducing the likelihood of errors or bias.
  • Facilitates communication: A clear scope of research enables researchers to communicate the goals and objectives of the study to stakeholders, such as funding agencies or participants. This facilitates understanding and enhances cooperation.
  • Enables replication : A well-defined scope of research makes it easier to replicate the study in the future. This allows other researchers to validate the findings and build upon them, leading to the advancement of knowledge in the field.
  • Increases the relevance of research: Defining the scope of research helps to ensure that the study is relevant to the problem or issue being investigated. This increases the likelihood that the findings will be useful and applicable to real-world situations.
  • Reduces the risk of scope creep : Scope creep occurs when the research expands beyond the original scope, leading to an increase in the time, cost, and resources required to complete the study. A clear definition of the scope of research helps to reduce the risk of scope creep by establishing boundaries and limitations.
  • Enhances the credibility of research: A well-defined scope of research helps to enhance the credibility of the study by ensuring that it is designed to achieve specific objectives and answer specific research questions. This makes it easier for others to assess the validity and reliability of the study.
  • Provides a framework for decision-making : A clear scope of research provides a framework for decision-making throughout the research process. This includes decisions related to data collection, analysis, and interpretation.

Scope of the Research Vs Scope of the Project

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Scope and Delimitations – Explained & Example

DiscoverPhDs

  • By DiscoverPhDs
  • October 2, 2020

Scope and Delimitation

What Is Scope and Delimitation in Research?

The scope and delimitations of a thesis, dissertation or research paper define the topic and boundaries of the research problem to be investigated.

The scope details how in-depth your study is to explore the research question and the parameters in which it will operate in relation to the population and timeframe.

The delimitations of a study are the factors and variables not to be included in the investigation. In other words, they are the boundaries the researcher sets in terms of study duration, population size and type of participants, etc.

Difference Between Delimitations and Limitations

Delimitations refer to the boundaries of the research study, based on the researcher’s decision of what to include and what to exclude. They narrow your study to make it more manageable and relevant to what you are trying to prove.

Limitations relate to the validity and reliability of the study. They are characteristics of the research design or methodology that are out of your control but influence your research findings. Because of this, they determine the internal and external validity of your study and are considered potential weaknesses.

In other words, limitations are what the researcher cannot do (elements outside of their control) and delimitations are what the researcher will not do (elements outside of the boundaries they have set). Both are important because they help to put the research findings into context, and although they explain how the study is limited, they increase the credibility and validity of a research project.

Guidelines on How to Write a Scope

A good scope statement will answer the following six questions:

Delimitation Scope for Thesis Statement

  • Why – the general aims and objectives (purpose) of the research.
  • What – the subject to be investigated, and the included variables.
  • Where – the location or setting of the study, i.e. where the data will be gathered and to which entity the data will belong.
  • When – the timeframe within which the data is to be collected.
  • Who – the subject matter of the study and the population from which they will be selected. This population needs to be large enough to be able to make generalisations.
  • How – how the research is to be conducted, including a description of the research design (e.g. whether it is experimental research, qualitative research or a case study), methodology, research tools and analysis techniques.

To make things as clear as possible, you should also state why specific variables were omitted from the research scope, and whether this was because it was a delimitation or a limitation. You should also explain why they could not be overcome with standard research methods backed up by scientific evidence.

How to Start Writing Your Study Scope

Use the below prompts as an effective way to start writing your scope:

  • This study is to focus on…
  • This study covers the…
  • This study aims to…

Guidelines on How to Write Delimitations

Since the delimitation parameters are within the researcher’s control, readers need to know why they were set, what alternative options were available, and why these alternatives were rejected. For example, if you are collecting data that can be derived from three different but similar experiments, the reader needs to understand how and why you decided to select the one you have.

Your reasons should always be linked back to your research question, as all delimitations should result from trying to make your study more relevant to your scope. Therefore, the scope and delimitations are usually considered together when writing a paper.

How to Start Writing Your Study Delimitations

Use the below prompts as an effective way to start writing your study delimitations:

  • This study does not cover…
  • This study is limited to…
  • The following has been excluded from this study…

Examples of Delimitation in Research

Examples of delimitations include:

  • research objectives,
  • research questions,
  • research variables,
  • target populations,
  • statistical analysis techniques .

Examples of Limitations in Research

Examples of limitations include:

  • Issues with sample and selection,
  • Insufficient sample size, population traits or specific participants for statistical significance,
  • Lack of previous research studies on the topic which has allowed for further analysis,
  • Limitations in the technology/instruments used to collect your data,
  • Limited financial resources and/or funding constraints.

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Scope and Delimitations in Research

Delimitations are the boundaries that the researcher sets in a research study, deciding what to include and what to exclude. They help to narrow down the study and make it more manageable and relevant to the research goal.

Updated on October 19, 2022

Scope and Delimitations in Research

All scientific research has boundaries, whether or not the authors clearly explain them. Your study's scope and delimitations are the sections where you define the broader parameters and boundaries of your research.

The scope details what your study will explore, such as the target population, extent, or study duration. Delimitations are factors and variables not included in the study.

Scope and delimitations are not methodological shortcomings; they're always under your control. Discussing these is essential because doing so shows that your project is manageable and scientifically sound.

This article covers:

  • What's meant by “scope” and “delimitations”
  • Why these are integral components of every study
  • How and where to actually write about scope and delimitations in your manuscript
  • Examples of scope and delimitations from published studies

What is the scope in a research paper?

Simply put, the scope is the domain of your research. It describes the extent to which the research question will be explored in your study.

Articulating your study's scope early on helps you make your research question focused and realistic.

It also helps decide what data you need to collect (and, therefore, what data collection tools you need to design). Getting this right is vital for both academic articles and funding applications.

What are delimitations in a research paper?

Delimitations are those factors or aspects of the research area that you'll exclude from your research. The scope and delimitations of the study are intimately linked.

Essentially, delimitations form a more detailed and narrowed-down formulation of the scope in terms of exclusion. The delimitations explain what was (intentionally) not considered within the given piece of research.

Scope and delimitations examples

Use the following examples provided by our expert PhD editors as a reference when coming up with your own scope and delimitations.

Scope example

Your research question is, “What is the impact of bullying on the mental health of adolescents?” This topic, on its own, doesn't say much about what's being investigated.

The scope, for example, could encompass:

  • Variables: “bullying” (dependent variable), “mental health” (independent variable), and ways of defining or measuring them
  • Bullying type: Both face-to-face and cyberbullying
  • Target population: Adolescents aged 12–17
  • Geographical coverage: France or only one specific town in France

Delimitations example

Look back at the previous example.

Exploring the adverse effects of bullying on adolescents' mental health is a preliminary delimitation. This one was chosen from among many possible research questions (e.g., the impact of bullying on suicide rates, or children or adults).

Delimiting factors could include:

  • Research design : Mixed-methods research, including thematic analysis of semi-structured interviews and statistical analysis of a survey
  • Timeframe : Data collection to run for 3 months
  • Population size : 100 survey participants; 15 interviewees
  • Recruitment of participants : Quota sampling (aiming for specific portions of men, women, ethnic minority students etc.)

We can see that every choice you make in planning and conducting your research inevitably excludes other possible options.

What's the difference between limitations and delimitations?

Delimitations and limitations are entirely different, although they often get mixed up. These are the main differences:

scope of study in research

This chart explains the difference between delimitations and limitations. Delimitations are the boundaries of the study while the limitations are the characteristics of the research design or methodology.

Delimitations encompass the elements outside of the boundaries you've set and depends on your decision of what yo include and exclude. On the flip side, limitations are the elements outside of your control, such as:

  • limited financial resources
  • unplanned work or expenses
  • unexpected events (for example, the COVID-19 pandemic)
  • time constraints
  • lack of technology/instruments
  • unavailable evidence or previous research on the topic

Delimitations involve narrowing your study to make it more manageable and relevant to what you're trying to prove. Limitations influence the validity and reliability of your research findings. Limitations are seen as potential weaknesses in your research.

Example of the differences

To clarify these differences, go back to the limitations of the earlier example.

Limitations could comprise:

  • Sample size : Not large enough to provide generalizable conclusions.
  • Sampling approach : Non-probability sampling has increased bias risk. For instance, the researchers might not manage to capture the experiences of ethnic minority students.
  • Methodological pitfalls : Research participants from an urban area (Paris) are likely to be more advantaged than students in rural areas. A study exploring the latter's experiences will probably yield very different findings.

Where do you write the scope and delimitations, and why?

It can be surprisingly empowering to realize you're restricted when conducting scholarly research. But this realization also makes writing up your research easier to grasp and makes it easier to see its limits and the expectations placed on it. Properly revealing this information serves your field and the greater scientific community.

Openly (but briefly) acknowledge the scope and delimitations of your study early on. The Abstract and Introduction sections are good places to set the parameters of your paper.

Next, discuss the scope and delimitations in greater detail in the Methods section. You'll need to do this to justify your methodological approach and data collection instruments, as well as analyses

At this point, spell out why these delimitations were set. What alternative options did you consider? Why did you reject alternatives? What could your study not address?

Let's say you're gathering data that can be derived from different but related experiments. You must convince the reader that the one you selected best suits your research question.

Finally, a solid paper will return to the scope and delimitations in the Findings or Discussion section. Doing so helps readers contextualize and interpret findings because the study's scope and methods influence the results.

For instance, agricultural field experiments carried out under irrigated conditions yield different results from experiments carried out without irrigation.

Being transparent about the scope and any outstanding issues increases your research's credibility and objectivity. It helps other researchers replicate your study and advance scientific understanding of the same topic (e.g., by adopting a different approach).

How do you write the scope and delimitations?

Define the scope and delimitations of your study before collecting data. This is critical. This step should be part of your research project planning.

Answering the following questions will help you address your scope and delimitations clearly and convincingly.

  • What are your study's aims and objectives?
  • Why did you carry out the study?
  • What was the exact topic under investigation?
  • Which factors and variables were included? And state why specific variables were omitted from the research scope.
  • Who or what did the study explore? What was the target population?
  • What was the study's location (geographical area) or setting (e.g., laboratory)?
  • What was the timeframe within which you collected your data ?
  • Consider a study exploring the differences between identical twins who were raised together versus identical twins who weren't. The data collection might span 5, 10, or more years.
  • A study exploring a new immigration policy will cover the period since the policy came into effect and the present moment.
  • How was the research conducted (research design)?
  • Experimental research, qualitative, quantitative, or mixed-methods research, literature review, etc.
  • What data collection tools and analysis techniques were used? e.g., If you chose quantitative methods, which statistical analysis techniques and software did you use?
  • What did you find?
  • What did you conclude?

Useful vocabulary for scope and delimitations

scope of study in research

When explaining both the scope and delimitations, it's important to use the proper language to clearly state each.

For the scope , use the following language:

  • This study focuses on/considers/investigates/covers the following:
  • This study aims to . . . / Here, we aim to show . . . / In this study, we . . .
  • The overall objective of the research is . . . / Our objective is to . . .

When stating the delimitations, use the following language:

  • This [ . . . ] will not be the focus, for it has been frequently and exhaustively discusses in earlier studies.
  • To review the [ . . . ] is a task that lies outside the scope of this study.
  • The following [ . . . ] has been excluded from this study . . .
  • This study does not provide a complete literature review of [ . . . ]. Instead, it draws on selected pertinent studies [ . . . ]

Analysis of a published scope

In one example, Simione and Gnagnarella (2020) compared the psychological and behavioral impact of COVID-19 on Italy's health workers and general population.

Here's a breakdown of the study's scope into smaller chunks and discussion of what works and why.

Also notable is that this study's delimitations include references to:

  • Recruitment of participants: Convenience sampling
  • Demographic characteristics of study participants: Age, sex, etc.
  • Measurements methods: E.g., the death anxiety scale of the Existential Concerns Questionnaire (ECQ; van Bruggen et al., 2017) etc.
  • Data analysis tool: The statistical software R

Analysis of published scope and delimitations

Scope of the study : Johnsson et al. (2019) explored the effect of in-hospital physiotherapy on postoperative physical capacity, physical activity, and lung function in patients who underwent lung cancer surgery.

The delimitations narrowed down the scope as follows:

Refine your scope, delimitations, and scientific English

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Defining the Scope of your Project

What is scope.

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Post-Grad Collective [PGC]. (2017, February 13). Thesis Writing-Narrow the Scope   [Video file]. Retrieved from https://www.youtube.com/watch?v=IlCO5yRB9No&feature=youtu.be

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The scope of your project sets clear parameters for your research. 

A scope statement will give basic information about the depth and breadth of the project. It tells your reader exactly what you want to find out , how you will conduct your study, the reports and deliverables  that will be part of the outcome of the study, and the responsibilities of the researchers involved in the study. The extent of the scope will be a part of acknowledging any biases in the research project. 

Defining the scope of a project: 

  • focuses your research goals
  • clarifies the expectations for your research project
  •  helps you determine potential biases in your research methodology by acknowledging the limits of your research study 
  • identifies the limitations of your research 
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  • Research Objectives | Definition & Examples

Research Objectives | Definition & Examples

Published on July 12, 2022 by Eoghan Ryan . Revised on November 20, 2023.

Research objectives describe what your research is trying to achieve and explain why you are pursuing it. They summarize the approach and purpose of your project and help to focus your research.

Your objectives should appear in the introduction of your research paper , at the end of your problem statement . They should:

  • Establish the scope and depth of your project
  • Contribute to your research design
  • Indicate how your project will contribute to existing knowledge

Table of contents

What is a research objective, why are research objectives important, how to write research aims and objectives, smart research objectives, other interesting articles, frequently asked questions about research objectives.

Research objectives describe what your research project intends to accomplish. They should guide every step of the research process , including how you collect data , build your argument , and develop your conclusions .

Your research objectives may evolve slightly as your research progresses, but they should always line up with the research carried out and the actual content of your paper.

Research aims

A distinction is often made between research objectives and research aims.

A research aim typically refers to a broad statement indicating the general purpose of your research project. It should appear at the end of your problem statement, before your research objectives.

Your research objectives are more specific than your research aim and indicate the particular focus and approach of your project. Though you will only have one research aim, you will likely have several research objectives.

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Research objectives are important because they:

  • Establish the scope and depth of your project: This helps you avoid unnecessary research. It also means that your research methods and conclusions can easily be evaluated .
  • Contribute to your research design: When you know what your objectives are, you have a clearer idea of what methods are most appropriate for your research.
  • Indicate how your project will contribute to extant research: They allow you to display your knowledge of up-to-date research, employ or build on current research methods, and attempt to contribute to recent debates.

Once you’ve established a research problem you want to address, you need to decide how you will address it. This is where your research aim and objectives come in.

Step 1: Decide on a general aim

Your research aim should reflect your research problem and should be relatively broad.

Step 2: Decide on specific objectives

Break down your aim into a limited number of steps that will help you resolve your research problem. What specific aspects of the problem do you want to examine or understand?

Step 3: Formulate your aims and objectives

Once you’ve established your research aim and objectives, you need to explain them clearly and concisely to the reader.

You’ll lay out your aims and objectives at the end of your problem statement, which appears in your introduction. Frame them as clear declarative statements, and use appropriate verbs to accurately characterize the work that you will carry out.

The acronym “SMART” is commonly used in relation to research objectives. It states that your objectives should be:

  • Specific: Make sure your objectives aren’t overly vague. Your research needs to be clearly defined in order to get useful results.
  • Measurable: Know how you’ll measure whether your objectives have been achieved.
  • Achievable: Your objectives may be challenging, but they should be feasible. Make sure that relevant groundwork has been done on your topic or that relevant primary or secondary sources exist. Also ensure that you have access to relevant research facilities (labs, library resources , research databases , etc.).
  • Relevant: Make sure that they directly address the research problem you want to work on and that they contribute to the current state of research in your field.
  • Time-based: Set clear deadlines for objectives to ensure that the project stays on track.

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

Methodology

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

 Statistics

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

Research bias

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

Research objectives describe what you intend your research project to accomplish.

They summarize the approach and purpose of the project and help to focus your research.

Your objectives should appear in the introduction of your research paper , at the end of your problem statement .

Your research objectives indicate how you’ll try to address your research problem and should be specific:

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

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

I will compare …

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

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

Scope of research is determined at the beginning of your research process , prior to the data collection stage. Sometimes called “scope of study,” your scope delineates what will and will not be covered in your project. It helps you focus your work and your time, ensuring that you’ll be able to achieve your goals and outcomes.

Defining a scope can be very useful in any research project, from a research proposal to a thesis or dissertation . A scope is needed for all types of research: quantitative , qualitative , and mixed methods .

To define your scope of research, consider the following:

  • Budget constraints or any specifics of grant funding
  • Your proposed timeline and duration
  • Specifics about your population of study, your proposed sample size , and the research methodology you’ll pursue
  • Any inclusion and exclusion criteria
  • Any anticipated control , extraneous , or confounding variables that could bias your research if not accounted for properly.

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How to Write the Scope of the Study

June 12, 2023

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Source: https://www.discoverphds.com/blog/scope-of-the-study

The scope of the study is defined at the start of the research project before data collection begins. It is used by researchers to set the boundaries and limitations within which the study will be performed.

What is the Scope of the Study?

The scope of the study refers to the boundaries within which your research project will be performed; this is sometimes also called the scope of research. To define the scope of the study is to define all aspects that will be considered in your research project. It is also just as important to make clear what aspects will not be covered; i.e. what is outside of the scope of the study.

Why is the Scope of the Study Important?

The scope of the study is always considered and agreed upon in the early stages of the project, before any data collection or experimental work has started. This is important because it focuses the work of the proposed study down to what is practically achievable within a given timeframe.

A well-defined research or study scope enables a researcher to give clarity to the study outcomes that are to be investigated. It makes clear why specific data points have been collected whilst others have been excluded.

Without this, it is difficult to define an end point for a research project since no limits have been defined on the work that could take place. Similarly, it can also make the approach to answering a research question too open ended.

How do you Write the Scope of the Study?

In order to write the scope of the study that you plan to perform, you must be clear on the research parameters that you will and won’t consider. These parameters usually consist of the sample size, the duration, inclusion and exclusion criteria, the methodology and any geographical or monetary constraints.

Each of these parameters will have limits placed on them so that the study can practically be performed, and the results interpreted relative to the limitations that have been defined. These parameters will also help to shape the direction of each research question you consider.

The term limitations’ is often used together with the scope of the study to describe the constraints of any parameters that are considered and also to clarify which parameters have not been considered at all. Make sure you get the balance right here between not making the scope too broad and unachievable, and it not being too restrictive, resulting in a lack of useful data.

The sample size is a commonly used parameter in the definition of the research scope. For example, a research project involving human participants may define at the start of the study that 100 participants will be recruited. This number will be determined based on an understanding of the difficulty in recruiting participants to studies and an agreement of an acceptable period of time in which to recruit this number.

Any results that are obtained by the research group can then be interpreted by others with the knowledge that the study was capped to 100 participants and an acceptance of this as a limitation of the study. In other words, it is acknowledged that recruiting 100 rather than 1,000 participants has limited the amount of data that could be collected, however this is an acceptable limitation due to the known difficulties in recruiting so many participants (e.g. the significant period of time it would take and the costs associated with this).

Example of a Scope of the Study

The follow is a (hypothetical) example of the definition of the scope of the study, with the research question investigating the impact of the COVID-19 pandemic on mental health .

Whilst the immediate negative health problems related to the COVID-19 pandemic have been well documented, the impact of the virus on the mental health (MH) of young adults (age 18-24 years) is poorly understood. The aim of this study is to report on MH changes in population group due to the pandemic.

The scope of the study is limited to recruiting 100 volunteers between the ages of 18 and 24 who will be contacted using their university email accounts. This recruitment period will last for a maximum of 2 months and will end when either 100 volunteers have been recruited or 2 months have passed. Each volunteer to the study will be asked to complete a short questionnaire in order to evaluate any changes in their MH.

From this example we can immediately see that the scope of the study has placed a constraint on the sample size to be used and/or the time frame for recruitment of volunteers. It has also introduced a limitation by only opening recruitment to people that have university emails; i.e. anyone that does not attend university will be excluded from this study.

This may be an important factor when interpreting the results of this study; the comparison of MH during the pandemic between those that do and do not attend university, is therefore outside the scope of the study here. We are also told that the methodology used to assess any changes in MH are via a questionnaire. This is a clear definition of how the outcome measure will be investigated and any other methods are not within the scope of research and their exclusion may be a limitation of the study.

The scope of the study is important to define as it enables a researcher to focus their research to within achievable parameters.

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Setting Limits and Focusing Your Study: Exploring scope and delimitation

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As a researcher, it can be easy to get lost in the vast expanse of information and data available. Thus, when starting a research project, one of the most important things to consider is the scope and delimitation of the study. Setting limits and focusing your study is essential to ensure that the research project is manageable, relevant, and able to produce useful results. In this article, we will explore the importance of setting limits and focusing your study through an in-depth analysis of scope and delimitation.

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Table of Contents

Scope and Delimitation – Definition and difference

Scope refers to the range of the research project and the study limitations set in place to define the boundaries of the project and delimitation refers to the specific aspects of the research project that the study will focus on.

In simpler words, scope is the breadth of your study, while delimitation is the depth of your study.

Scope and delimitation are both essential components of a research project, and they are often confused with one another. The scope defines the parameters of the study, while delimitation sets the boundaries within those parameters. The scope and delimitation of a study are usually established early on in the research process and guide the rest of the project.

Types of Scope and Delimitation

scope of study in research

Significance of Scope and Delimitation

Setting limits and focusing your study through scope and delimitation is crucial for the following reasons:

  • It allows researchers to define the research project’s boundaries, enabling them to focus on specific aspects of the project. This focus makes it easier to gather relevant data and avoid unnecessary information that might complicate the study’s results.
  • Setting limits and focusing your study through scope and delimitation enables the researcher to stay within the parameters of the project’s resources.
  • A well-defined scope and delimitation ensure that the research project can be completed within the available resources, such as time and budget, while still achieving the project’s objectives.

5 Steps to Setting Limits and Defining the Scope and Delimitation of Your Study

scope of study in research

There are a few steps that you can take to set limits and focus your study.

1. Identify your research question or topic

The first step is to identify what you are interested in learning about. The research question should be specific, measurable, achievable, relevant, and time-bound (SMART). Once you have a research question or topic, you can start to narrow your focus.

2. Consider the key terms or concepts related to your topic

What are the important terms or concepts that you need to understand in order to answer your research question? Consider all available resources, such as time, budget, and data availability, when setting scope and delimitation.

The scope and delimitation should be established within the parameters of the available resources. Once you have identified the key terms or concepts, you can start to develop a glossary or list of definitions.

3. Consider the different perspectives on your topic

There are often different perspectives on any given topic. Get feedback on the proposed scope and delimitation. Advisors can provide guidance on the feasibility of the study and offer suggestions for improvement.

It is important to consider all of the different perspectives in order to get a well-rounded understanding of your topic.

4. Narrow your focus

Be specific and concise when setting scope and delimitation. The parameters of the study should be clearly defined to avoid ambiguity and ensure that the study is focused on relevant aspects of the research question.

This means deciding which aspects of your topic you will focus on and which aspects you will eliminate.

5. Develop the final research plan

Revisit and revise the scope and delimitation as needed. As the research project progresses, the scope and delimitation may need to be adjusted to ensure that the study remains focused on the research question and can produce useful results. This plan should include your research goals, methods, and timeline.

Examples of Scope and Delimitation

To better understand scope and delimitation, let us consider two examples of research questions and how scope and delimitation would apply to them.

Research question: What are the effects of social media on mental health?

Scope: The scope of the study will focus on the impact of social media on the mental health of young adults aged 18-24 in the United States.

Delimitation: The study will specifically examine the following aspects of social media: frequency of use, types of social media platforms used, and the impact of social media on self-esteem and body image.

Research question: What are the factors that influence employee job satisfaction in the healthcare industry?

Scope: The scope of the study will focus on employee job satisfaction in the healthcare industry in the United States.

Delimitation: The study will specifically examine the following factors that influence employee job satisfaction: salary, work-life balance, job security, and opportunities for career growth.

Setting limits and defining the scope and delimitation of a research study is essential to conducting effective research. By doing so, researchers can ensure that their study is focused, manageable, and feasible within the given time frame and resources. It can also help to identify areas that require further study, providing a foundation for future research.

So, the next time you embark on a research project, don’t forget to set clear limits and define the scope and delimitation of your study. It may seem like a tedious task, but it can ultimately lead to more meaningful and impactful research. And if you still can’t find a solution, reach out to Enago Academy using #AskEnago and tag @EnagoAcademy on Twitter , Facebook , and Quora .

Frequently Asked Questions

The scope in research refers to the boundaries and extent of a study, defining its specific objectives, target population, variables, methods, and limitations, which helps researchers focus and provide a clear understanding of what will be investigated.

Delimitation in research defines the specific boundaries and limitations of a study, such as geographical, temporal, or conceptual constraints, outlining what will be excluded or not within the scope of investigation, providing clarity and ensuring the study remains focused and manageable.

To write a scope; 1. Clearly define research objectives. 2. Identify specific research questions. 3. Determine the target population for the study. 4. Outline the variables to be investigated. 5. Establish limitations and constraints. 6. Set boundaries and extent of the investigation. 7. Ensure focus, clarity, and manageability. 8. Provide context for the research project.

To write delimitations; 1. Identify geographical boundaries or constraints. 2. Define the specific time period or timeframe of the study. 3. Specify the sample size or selection criteria. 4. Clarify any demographic limitations (e.g., age, gender, occupation). 5. Address any limitations related to data collection methods. 6. Consider limitations regarding the availability of resources or data. 7. Exclude specific variables or factors from the scope of the study. 8. Clearly state any conceptual boundaries or theoretical frameworks. 9. Acknowledge any potential biases or constraints in the research design. 10. Ensure that the delimitations provide a clear focus and scope for the study.

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Scoping studies: advancing the methodology

Danielle levac.

1 School of Rehabilitation Science, McMaster University, 1400 Main Street West, Room 403, Hamilton, Ontario, Canada

Heather Colquhoun

Kelly k o'brien.

2 Department of Physical Therapy, University of Toronto, 160-500 University Avenue, Toronto, Ontario, Canada

Scoping studies are an increasingly popular approach to reviewing health research evidence. In 2005, Arksey and O'Malley published the first methodological framework for conducting scoping studies. While this framework provides an excellent foundation for scoping study methodology, further clarifying and enhancing this framework will help support the consistency with which authors undertake and report scoping studies and may encourage researchers and clinicians to engage in this process.

We build upon our experiences conducting three scoping studies using the Arksey and O'Malley methodology to propose recommendations that clarify and enhance each stage of the framework. Recommendations include: clarifying and linking the purpose and research question (stage one); balancing feasibility with breadth and comprehensiveness of the scoping process (stage two); using an iterative team approach to selecting studies (stage three) and extracting data (stage four); incorporating a numerical summary and qualitative thematic analysis, reporting results, and considering the implications of study findings to policy, practice, or research (stage five); and incorporating consultation with stakeholders as a required knowledge translation component of scoping study methodology (stage six). Lastly, we propose additional considerations for scoping study methodology in order to support the advancement, application and relevance of scoping studies in health research.

Specific recommendations to clarify and enhance this methodology are outlined for each stage of the Arksey and O'Malley framework. Continued debate and development about scoping study methodology will help to maximize the usefulness and rigor of scoping study findings within healthcare research and practice.

Scoping studies (or scoping reviews) represent an increasingly popular approach to reviewing health research evidence [ 1 ]. However, no universal scoping study definition or purpose exists (Table ​ (Table1) 1 ) [ 1 , 2 ]. Definitions commonly refer to 'mapping,' a process of summarizing a range of evidence in order to convey the breadth and depth of a field. Scoping studies differ from systematic reviews because authors do not typically assess the quality of included studies [ 3 - 5 ]. Scoping studies also differ from narrative or literature reviews in that the scoping process requires analytical reinterpretation of the literature [ 1 ].

Definitions and purposes of scoping studies

Researchers can undertake a scoping study to examine the extent, range, and nature of research activity, determine the value of undertaking a full systematic review, summarize and disseminate research findings, or identify gaps in the existing literature [ 6 ]. As such, researchers can use scoping studies to clarify a complex concept and refine subsequent research inquiries [ 1 ]. Scoping studies may be particularly relevant to disciplines with emerging evidence, such as rehabilitation science, in which the paucity of randomized controlled trials makes it difficult for researchers to undertake systematic reviews. In these situations, scoping studies are ideal because researchers can incorporate a range of study designs in both published and grey literature, address questions beyond those related to intervention effectiveness, and generate findings that can complement the findings of clinical trials.

In an effort to provide guidance to authors undertaking scoping studies, Arksey and O'Malley [ 6 ] developed a six-stage methodological framework: identifying the research question, searching for relevant studies, selecting studies, charting the data, collating, summarizing, and reporting the results, and consulting with stakeholders to inform or validate study findings (Table ​ (Table2). 2 ). While this framework provided an excellent methodological foundation, published scoping studies continue to lack sufficient methodological description or detail about the data analysis process, making it challenging for readers to understand how study findings were determined [ 1 ]. Arksey and O'Malley [ 6 ] encouraged other authors to refine their framework in order to enhance the methodology.

Overview of the Arksey and O'Malley methodological framework for conducting a scoping study

In this paper, we apply our experiences using the Arksey and O'Malley framework to build on the existing methodological framework. Specifically, we propose recommendations for each stage of the framework, followed by considerations for the advancement, application, and relevance of scoping studies in health research. Continual refinement of the framework stages may provide greater clarity about scoping study methodology, encourage researchers and clinicians to engage in this process, and help to enhance the methodological rigor with which authors undertake and report scoping studies [ 1 ].

We each completed a scoping study in separate areas of rehabilitation using the Arksey and O'Malley framework [ 6 ]. Goals of these studies included: identifying research priorities within HIV and rehabilitation [ 7 ], applying motor learning strategies within pediatric physical and occupational therapy intervention approaches [ 8 ], and exploring the use of theory within studies of knowledge translation [ 9 ]. The amount of literature reviewed in our studies ranged from 31 (DL) to 146 (KO) publications. Upon discovering that we had similar challenges implementing the scoping study methodology, we decided to use our experiences to further develop the existing framework. We conducted an informal literature search on scoping study methodology. We searched CINAHL, MEDLINE, PubMed, ERIC, PsycInfo, and Web of Science databases using the search terms 'scoping,' 'scoping study,' 'scoping review,' and 'scoping methodology' for papers published in English between January 1990 and May 2010. Reference lists of pertinent papers were also searched. This search yielded seven citations that reflected on scoping study methodology, which were reviewed by one author (DL). After independently considering our own experiences utilizing the Arskey and O'Malley [ 6 ] framework, we met on seven occasions to discuss the challenges and develop recommendations for each stage of the methodological framework.

Recommendations to enhance scoping study methodology

We outline the challenges and recommendations associated with each stage of the methodological framework (Table ​ (Table3 3 ).

Summary of challenges and recommendations for scoping studies

Framework stage one: Identifying the research question

Scoping study research questions are broad in nature as the focus is on summarizing breadth of evidence. Arksey and O'Malley [ 6 ] acknowledge the need to maintain a broad scope to research questions, however we found our research questions lacked the direction, clarity, and focus needed to inform subsequent stages of the research process, such as identifying studies and making decisions about study inclusion. To clarify this stage, we recommend that researchers combine a broad research question with a clearly articulated scope of inquiry. This includes defining the concept, target population, and health outcomes of interest to clarify the focus of the scoping study and establish an effective search strategy. For example, in one author's (KO) scoping study, the research question was broadly 'what is known about HIV and rehabilitation?' Defining the concept of 'rehabilitation' was essential in order to establish a clear scope to the study, guide the search strategy, and establish parameters around study selection in subsequent stages of the process [ 7 ].

Although Arskey and O'Malley [ 6 ] outline four main purposes for undertaking a scoping study, they do not articulate that purpose be specified within a specific framework stage. We recommend researchers simultaneously consider the purpose of the scoping study when articulating the research question. Linking a clear purpose for undertaking a scoping study to a well-defined research question at the first stage of the framework will help to provide a clear rationale for completing the study and facilitate decision making about study selection and data extraction later in the methodological process. A helpful strategy may be to envision the content and format of the intended outcome that may assist researchers to clearly determine the purpose at the beginning of a study. In the abovementioned HIV study, authors linked the broadly stated research question with a more specific purpose 'to identify the key research priorities in HIV and rehabilitation to advance policy and practice for people living with HIV in Canada' [ 7 ]. The envisioned outcome was a thematic framework that represented strengths and opportunities in HIV rehabilitation research, followed by a list of the key research priorities to pursue in future work.

Finally, the purposes put forth by Arksey and O'Malley [ 6 ] require more debate. We concur with Anderson et al. [ 2 ] and Davis et al. [ 1 ], who state that researchers may benefit from further clarification of the purposes for undertaking a scoping study. The first purpose, as articulated by Arksey and O'Malley [ 6 ], is to summarize the extent, range, and nature of research activity; however, researchers are not required to reflect on their underlying motivation for doing so. We recommend that researchers consider the rationale for why they should summarize the activity in a field and the implications that this will have on research, practice, or policy. The second purpose is to assess the need for a full systematic review. However, it is difficult to determine whether a systematic review is advantageous when a scoping study does not involve methodological quality assessment of included studies. Furthermore, it is unclear how this purpose differs from existing methods of determining feasibility for a systematic review. The third purpose is to summarize and disseminate research findings, but we question how this differs from other narrative or systematic literature reviews. Lastly, the fourth purpose of undertaking a scoping study -- to identify gaps in the existing literature -- may yield false conclusions about the nature and extent of those gaps if the quality of the evidence is not assessed. The purpose 'to identify the key research priorities in HIV and rehabilitation to advance policy and practice for people living with HIV in Canada' does not explicitly align with one of the four Arskey and O'Malley purposes [ 7 ]. However, it appears authors inherently first summarized the extent, range, and nature of research (purpose one) and identified gaps in the existing literature (purpose four) in order to subsequently identify the key research priorities in HIV and rehabilitation (author purpose). This suggests authors might have an overall study purpose with multiple objectives articulated by Arksey and O'Malley that are required in order to help achieve their overall purpose.

Framework stage two: Identifying relevant studies

A strength of scoping studies includes the breadth and depth, or comprehensiveness, of evidence covered in a given field [ 1 ]. However, practical issues related to time, funding, and access to resources often require researchers to consider the balance between feasibility, breadth, and comprehensiveness. Brien et al. [ 5 ] reported that their search strategy yielded a vast amount of literature, making it difficult to determine how in depth to carry out the information synthesis. Although Arksey and O'Malley [ 6 ] identify these concerns and provide some suggestions to support these decisions, we also struggled with the trade-off between breadth and comprehensiveness and feasibility in our scoping studies. As such, we recommend that researchers ensure decisions surrounding feasibility do not compromise their ability to answer the research question or achieve the study purpose. Second, we recommend that a scoping study team be assembled whose members provide the methodological and context expertise needed for decisions regarding breadth and comprehensiveness. When limiting scope is unavoidable, researchers should justify their decisions and acknowledge the potential limitations of their study.

Framework stage three: Study selection

Arksey and O'Malley [ 6 ] provide suggestions to manage the time-consuming process of determining which studies to include in a scoping study. We experienced this stage as more iterative and requiring additional steps than implied in the original framework. While Arksey and O'Malley [ 6 ] do not indicate a team approach is imperative, we agree with others and suggest scoping studies involve multidisciplinary teams using a transparent and replicable process [ 2 , 10 ]. In two of our studies (HC and DL) where decision making was primarily completed by a single author, we faced several challenges, including uncertainty about which studies to include, variables to extract on the data-charting form, and the nature and extent of detail to conduct the data extraction process. This raised questions related to rigor and led to our recommendations for undertaking a systematic team approach to conducting a scoping study.

Specifically, we recommend that the team meet to discuss decisions surrounding study inclusion and exclusion at the beginning of the scoping process. Refining the search strategy based on abstracts retrieved from the search and reviewing full articles for study inclusion is also a critical step. We recommend that at least two researchers each independently review abstracts yielded from the search strategy for study selection. Reviewers should meet at the beginning, midpoint, and final stages of the abstract review process to discuss any challenges or uncertainties related to study selection and to go back and refine the search strategy if needed. This can help to alleviate potential ambiguity with a broad research question and to ensure that abstracts selected are relevant for full article review. Next, two reviewers should independently review the full articles for inclusion. When disagreements occur, a third reviewer can be consulted to determine final inclusion.

Framework stage four: Charting the data

This stage involves extracting data from included studies. Based on our experiences, we were uncertain about the nature and extent of information to extract from the included studies. To clarify this stage, we recommend that the research team collectively develop the data-charting form to determine which variables to extract that will help to answer the research question. Secondly, we recommend that charting be considered an iterative process in which researchers continually update the data-charting form. This is particularly true for process-oriented data, such as understanding how a theory or model has been used within a study. Uncertainty about the nature and extent of data that should be extracted may be resolved by researchers beginning the charting process and becoming familiar with study data, and then meeting again to refine the form. We recommend an additional step to charting the data in which two researchers independently extract data from the first five to ten studies using the data-charting form and meet to determine whether their approach to data extraction is consistent with the research question and purpose. Researchers may review one study several times within this stage. The number of researchers involved in the data extraction process will likely depend upon the number of included studies. For example, in one study, authors had difficulty developing one data-charting form that could apply to all included studies representing a range study designs, reviews, reports, and commentaries [ 7 ]. As a preliminary step, authors decided to classify the included studies into three areas --HIV disability, interventions, and roles of rehabilitation professionals in HIV care -- to help determine the nature and extent of information to extract from each of the types of studies [ 7 ].

Arksey and O'Malley [ 6 ] refer to a 'descriptive analytical method' that involves summarizing process information, such as the use of a theory or model in a meaningful format. Our experiences indicated that this is a highly valuable, though challenging aspect of scoping studies, as we struggled to chart and summarize complex concepts in a meaningful way. Arksey and O'Malley [ 6 ] indicate that synthesis of material is critical as scoping studies are not a short summary of many articles. We agree, and feel that additional direction in the framework might help to navigate this crucial but challenging stage. Perhaps synthesizing process information may benefit from utilization of qualitative content analysis approaches to make sense of the wealth of extracted data [ 11 ]. This issue also highlights the overlap with the next analytical stage. The role and relevance of analyzing process data and using qualitative content analysis within scoping study methodology requires further discussion.

Framework stage five: Collating, summarizing, and reporting the results

Stage five is the most extensive in the scoping process, yet it lacks detail in the Arksey and O'Malley framework. Scoping studies have been criticized for rarely providing methodological detail about how results were achieved [ 1 ]. We appreciate the importance of breaking the analysis phase into meaningful and systematic steps so that researchers can provide this undertake scoping studies and report on findings in a rigorous manner. As a result, we recommend three distinct steps in framework stage five to increase the consistency with which researchers undertake and report scoping study methodology: analyzing the data, reporting results, and applying meaning to the results. As described in the existing framework, analysis (otherwise referred to as collating and summarizing) should involve a descriptive numerical summary and a thematic analysis. Arksey and O'Malley [ 6 ] describe the need to provide a descriptive numerical summary, stating that researchers should describe the characteristics of included studies, such as the overall number of studies included, types of study design, years of publication, types of interventions, characteristics of the study populations, and countries where studies were conducted. However, the description of thematic analysis requires additional detail to assist authors in understanding and completing this step. In our experience, this analytical stage resembled qualitative data analytical techniques, and researchers may consider using qualitative content analytical techniques [ 10 ] and qualitative software to facilitate this process.

Second, when reporting results, we recommend that researchers consider the best approach to stating the outcome or end product of the study and how the scoping study findings will be articulated to readers ( e.g ., through themes, a framework, or a table of strengths and gaps in the evidence). This product should be tied to the purpose of the scoping study as recommended in framework stage one.

Finally, in order to advance the legitimacy of scoping study methodology, we must consider the implications of findings within the broader context. As a result, we recommend that researchers consider the meaning of their scoping study results and the broader implications for research, policy, and practice. For example, for the question 'how are motor-learning strategies used within contemporary physical and occupational therapy intervention approaches for children with neuromotor conditions?,' the author (DL) presented themes that described strategy use. Results yielded insights into how researchers should better describe interventions in their publications and provided further considerations for clinicians to make informed decisions about which therapeutic approach might best fit their clients' needs. Considering the overall implications of the results as an explicit framework stage will help to ensure that scoping study results have practical implications for future clinical practice, research, and policy. This recommendation leads to the final stage of the framework.

Optional stage six: Consultation

Arksey and O'Malley [ 6 ] suggest that consultation is an optional stage in conducting a scoping study. Although only one of our three scoping studies incorporated this stage, we argue that it adds methodological rigor and should be considered a required component. Arksey and O'Malley [ 6 ] suggest that the purposes of consulting with stakeholders are to offer additional sources of information, perspectives, meaning, and applicability to the scoping study. However, it is unclear when, how, and why to consult with stakeholders, and how to analyze and integrate these data with the findings. We recommend researchers clearly establish a purpose for the consultation, which may include sharing preliminary findings with stakeholders, validating the findings, or informing future research. We suggest researchers use preliminary findings from stage five (either in the form of a framework, themes, or list of findings) as a foundation from which to inform the consultation. This will enable stakeholders to build on the evidence and offer a higher level of meaning, content expertise, and perspective to the preliminary findings. We also recommend that researchers clearly articulate the type of stakeholders with whom they wish to consult, how they will collect the data ( e.g ., focus groups, interviews, surveys), and how these data will be analyzed, reported, and integrated within the overall study outcome.

Finally, given that consultation requires researchers to orient stakeholders on the scoping study purpose, research question, preliminary findings, and plans for dissemination, we recommend that this stage additionally be considered a knowledge transfer mechanism. This may address Brien et al .'s [ 5 ] concern about the usefulness of scoping studies for stakeholders and how to translate knowledge about scoping studies. Given the importance of knowledge transfer and exchange in the uptake of research evidence [ 12 , 13 ], the consultation stage can be used to specifically translate the preliminary scoping study findings and develop effective dissemination strategies with stakeholders in the field, offering additional value to a scoping study.

One scoping study included a consultation phase comprised of focus groups and interviews with 28 stakeholders including people living with HIV, researchers, educators, clinicians, and policy makers [ 7 ]. Authors shared preliminary findings from the literature review phase of the scoping study with stakeholders and asked whether they may be able to identify any additional emerging issues related to HIV and rehabilitation not yet published in the evidence. The team proceeded to conduct a second consultation with 17 new and returning stakeholders whereby the team presented a preliminary framework of HIV and rehabilitation research and stakeholders refined the framework to further identify six key research priorities on HIV and rehabilitation. This series of consultations engaged community members in the development of the study outcome and provided opportunities for knowledge transfer about HIV and rehabilitation research. This process offered an ideal mechanism to enhance the validity of the study outcome while translating findings with the community. Nevertheless, further development of steps for undertaking knowledge translation as a part of the scoping study framework is required.

Additional considerations for scoping studies to support the advancement, application, and relevance of scoping studies in health research

Scoping study terminology.

Discrepancies in nomenclature between 'scoping reviews,' 'scoping studies,' 'scoping literature reviews,' and 'scoping exercises' lead to confusion. Despite our collective use of the Arksey and O'Malley framework, two authors (DL, HC) titled their studies as 'scoping reviews' while the other used 'scoping study.' In this paper, we use 'scoping studies' for consistency with Arksey and O'Malley's original framework. Nevertheless, the potential differences (if any) among the terms merit clarification. Lack of a universal definition for scoping studies is also problematic to researchers trying to clearly articulate their reasons for undertaking a scoping study. Finally, we advocate for labeling the methodology as the 'Arksey and O'Malley framework' to provide consistency for future use.

Quality assessment

Another consideration for scoping study methodology is the potential need to assess included studies for methodological quality. Brien et al. [ 5 ] state that this lack of quality assessment makes the results of scoping studies more challenging to interpret. Grant and Booth [ 4 ] imply that a lack of quality assessment limits the uptake of scoping study findings into policy and practice. While our research questions did not directly relate to any quality assessment debate, we recognize the challenges in assessing quality among the vast range of published and grey literature that may be included in scoping studies. This also raises the question of whether and how evidence from stakeholder consultation is evaluated in the scoping study process. It remains unclear whether the lack of quality assessment impacts the uptake and relevance of scoping study findings.

A final consideration for legitimization of scoping study methodology includes the development of a critical appraisal tool for scoping study quality [ 5 ]. Anderson et al. [ 2 ] offer criteria for assessing the value and utility of a commissioned scoping study in health policy contexts, but these criteria are not necessarily applicable to scoping studies in other areas of health research. Developing a critical appraisal tool would require the elements of a methodologically rigorous scoping study to be defined. This could include, but would not be limited to, the minimum level of analysis required and the requirements for reporting results. Overall, the issues surrounding quality assessment of included studies and subsequent scoping studies require further discussion.

Limitations

This paper responds to Arksey and O'Malley's [ 6 ] request for feedback to their proposed methodological framework. However, the recommendations that we propose are derived from our subjective experiences undertaking scoping studies of varying sizes in the rehabilitation field, and we recognize that they may not represent the opinions of all scoping study authors. Other than our individual experiences with our own studies, we have not yet implemented the full framework recommendations. Hence, readers can determine how strongly to interpret and implement these recommendations in their scoping study research. We invite others to trial our recommendations and continue the process of refining and improving this methodology.

Scoping studies present an increasingly popular option for synthesizing health evidence. Brien et al. [ 5 ] argue that guidelines are required to facilitate scoping review reporting and transparency. In this paper, we build on the existing methodological framework for scoping studies outlined by Arksey and O'Malley [ 6 ] and provide recommendations to clarify and enhance each stage, which may increase the consistency with which researchers undertake and report scoping studies. Recommendations include: clarifying and linking the purpose and research question; balancing feasibility with breadth and comprehensiveness of the scoping process; using an iterative team approach to selecting studies and extracting data; incorporating a numerical summary and qualitative thematic analysis; identifying the implications of the study findings for policy, practice, or research; and adopting consultation as a required component of scoping study methodology. Ongoing considerations include: establishing a common accepted definition and purpose(s) of scoping studies; defining methodological rigor for the assessment of scoping study quality; debating the need for quality assessment of included studies; and formalizing knowledge translation as a required element of scoping methodology. Continued debate and development about scoping study methodology will help to maximize the usefulness of scoping study findings within healthcare research and practice.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

DL and HC conceived of this paper. DL undertook the literature review process. DL, HC and KO developed challenges and recommendations. All authors drafted the manuscript. All authors read and approved the final manuscript.

Authors' information

DL is a physical therapist and doctoral candidate in the School of Rehabilitation Science at McMaster University. HC is an occupational therapist and doctoral candidate in the School of Rehabilitation Science at McMaster University. KO is a clinical epidemiologist, physical therapist, and postdoctoral fellow in the School of Rehabilitation Science at McMaster University. She is also a Lecturer in the Department of Physical Therapy at the University of Toronto.

Acknowledgements

DL is supported by a Doctoral Award from the Canadian Child Health Clinician Scientist Program, a strategic training initiative of the Canadian Institutes of Health Research (CIHR), and the McMaster Child Health Research Institute. HC is supported by a Doctoral Award from the CIHR, the CIHR Quality of Life Strategic Training Program in Rehabilitation Research and the Canadian Occupational Therapy Foundation. KO is supported by a Fellowship from the CIHR, HIV/AIDS Research Program and a Michael DeGroote Postdoctoral Fellowship (McMaster University). The authors acknowledge the helpful feedback of Dr. Cheryl Missiuna on an earlier draft of this manuscript.

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  • Canadian Institutes of Health Research. Knowledge Translation. http://www.cihr-irsc.gc.ca/e/29418.html
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Exploring Scope and Delimitation in Academic Research

David Costello

Academic research is a meticulous process that requires precise planning and clear boundaries. Two pivotal components in this process are the scope and delimitations of the study. The definitions and establishment of these parameters are instrumental in ensuring that the research is effective, manageable, and yields relevant results.

The "scope" of a research project refers to the areas that the study will cover. It is the breadth and depth of the investigation. It defines the subject matter, the geographical location, the time frame, and the issues that the study will explore. Essentially, the scope delineates what the researcher aims to cover in the study.

On the other hand, "delimitations" are the boundaries or limitations set by the researcher. They define what the study will not include. Delimitations could involve the choice of research methodology , the selection of respondents, the duration of the study, and more. They help in confining the study to a manageable size while excluding peripheral elements.

Understanding and correctly implementing scope and delimitations are vital to ensuring your research is well-defined and focused, facilitating higher accuracy and relevancy in your findings.

Importance of scope in research

"Scope" in research refers to the comprehensive extent of study—it outlines the parameters of what will be explored and addressed. It defines the topic of the research , the geographical region under study, the timeframe considered, and the issues that the study will address. The scope of a research project is vital because it determines the depth and breadth of your investigation.

Defining the scope of research is a fundamental step in the research process for several reasons. First, it provides a roadmap for the study, giving the researcher clear guidelines about what to include and exclude. Without a well-defined scope, research can become unmanageably vast or lose its focus.

Second, the scope ensures the research's relevance and applicability. It helps the researcher maintain a tight focus on the study's central question , ensuring that all aspects of the research contribute to answering this question. This focus aids in avoiding irrelevant diversions that could dilute the final conclusions.

Finally, a well-defined scope can help ensure the efficient use of resources. Research involves considerable time, effort, and often financial resources. By providing clear boundaries, the scope ensures these resources are utilized effectively without wasted effort on peripheral issues.

Suppose a research study is looking at the impacts of social media usage on mental health. If the scope is too broad—like examining all social media platforms' effects on all demographic groups worldwide—then the research can quickly become unwieldy and hard to manage. It would involve vast amounts of data, requiring considerable time, resources, and computational power to analyze effectively.

However, if the scope is narrowed down—such as investigating the impact of Instagram usage on the mental health of teenagers in a specific city over the past five years—the research becomes far more manageable. This specific focus allows for a more in-depth analysis and likely will provide more meaningful, actionable results. This example illustrates the importance of appropriately defining the scope of research for its successful execution.

Determining the scope of your research

Setting the scope of your research project is a critical and delicate task. Below are steps, tips, and common mistakes to avoid when determining the scope of your research:

Steps to define the scope

  • Identify Your Topic: The first step involves identifying and understanding your research topic. This knowledge will serve as a basis for determining the breadth and depth of your study.
  • Define Your Research Questions: The research questions are the heart of your study. They will help you determine the specific areas your research should cover.
  • Establish Boundaries: Clearly establish the geographical, temporal, and topical boundaries of your research. These boundaries will guide the range of your study.
  • Choose Your Methodology: Decide on the research methods you will use as these will directly impact the scope of your study.

Tips for a manageable scope

  • Stay Focused: Stay concentrated on your research questions. Do not stray into areas that aren't directly relevant.
  • Be Realistic: Consider the resources (time, money, manpower) available. Ensure your scope is feasible given these resources.
  • Seek Guidance: Consult with your academic advisor or peers for feedback on your proposed scope.

Common mistakes to avoid

  • Overly Broad Scope: Avoid setting an overly broad scope which could result in an unmanageable and unfocused study.
  • Too Narrow Scope: Conversely, a scope that is too narrow may miss important aspects of the research topic.
  • Ignoring Resources: Not taking into account available resources when setting the scope can lead to a project that is impossible to complete.

Defining the scope of your research is a delicate balance, requiring careful consideration of your research questions, resources, and the depth and breadth of investigation needed to answer these questions effectively.

Importance of delimitations in research

In the context of academic research, "delimitations" refers to the choices made by the researcher which define the boundaries of the study. These are the variables that lead the researcher to narrow the scope of the study from its potential vastness to a manageable size.

Delimitations might include the geographic area where the study is confined, the participants involved in the study, the methodology used, the time period considered, or the specific incidents or aspects the study will focus on. Essentially, delimitations are the self-imposed limitations on the scope of the study.

Defining the delimitations of a research project is crucial for several reasons. Firstly, they establish the context or setting in which the study occurs. This, in turn, allows for the work to be reproduced in a similar context for verification or refutation in future studies.

Secondly, delimitations provide a way to narrow the scope of the research to a manageable size, thus avoiding the pitfall of an overly ambitious project. They help researchers to stay focused on the main research questions and prevent diversion into irrelevant aspects.

Finally, clearly defined delimitations enhance the credibility of the research. They offer transparency about the research design and methodology, which adds to the validity of the results.

For instance, in a research study examining the impact of technology on student achievement in a certain district, examples of delimitations might include focusing only on public schools, considering only high school students, and confining the study to a particular school year. These choices help to focus the research and ensure its manageability. Therefore, delimitations play a pivotal role in structuring and guiding an effective and efficient research study.

Setting delimitations for your research

Establishing appropriate delimitations for your research project is an important part of research design. Here are some steps, guidelines, and common mistakes to consider when setting your research delimitations:

Steps to establish delimitations

  • Identify the boundaries: Begin by deciding the geographical region, time period, and subject matter your research will cover.
  • Determine Your Research Population: Identify the specific population your study will focus on. This could be based on age, profession, geographical location, etc.
  • Choose Your Research Methods: Decide the specific methods you will use to collect and analyze data, as these decisions will also set limitations on your study.

Guidelines for choosing delimitations

  • Align with Your Research Objectives: The delimitations should be in line with your research questions and objectives. They should help focus your study without detracting from its goals.
  • Be Practical: Consider the resources available, including time, funds, and access to data. Your delimitations should be feasible given these constraints.
  • Seek Input: Consult with your research advisor or peers. Their feedback can help ensure your delimitations are appropriate and well thought out.

Common errors to avoid:

  • Unrealistic Delimitations: Be wary of setting delimitations that are too stringent or ambitious to be feasible given your resources and timeframe.
  • Undefined Delimitations: Avoid leaving your delimitations vague or undefined. This can lead to scope creep, where your project expands beyond its initial plan, making it unmanageable.
  • Ignoring Delimitations: Once set, stick to your delimitations. Deviating from them can lead to a loss of focus and can compromise the integrity of your results.

Setting delimitations is a crucial step in research planning. Properly defined delimitations can make your research project more manageable, maintain your focus, and ensure the effective use of your resources.

The interplay between scope and delimitations

The relationship between scope and delimitations in academic research is a dynamic and interdependent one. Each aspect serves to shape and refine the other, ultimately leading to a focused, feasible, and effective research design.

The scope of a research project describes the breadth and depth of the investigation—what it aims to cover and how far it intends to delve into the subject matter. The delimitations, on the other hand, identify the boundaries and constraints of the study—what it will not cover.

As such, the scope and delimitations of a research study are intimately connected. When the scope of a study is broad, the delimitations must be carefully considered to ensure the project remains manageable and focused. Conversely, when the scope is narrow, the delimitations might be less constraining, but they still play a critical role in defining the specificity of the research.

Balancing the scope and delimitations is crucial for an efficient research design. Too broad a scope without carefully defined delimitations can lead to a study that is unwieldy and lacks depth. On the other hand, a very narrow scope with overly rigid delimitations might result in a study that overlooks important aspects of the research topic.

Thus, researchers must strive to maintain a balance—establishing a scope that is wide enough to fully explore the research topic, but also setting appropriate delimitations to ensure the study remains feasible and focused. In doing so, the research will be well-structured and yield meaningful, relevant findings.

Role of scope and delimitations in research validity

Scope and delimitations are fundamental aspects of research design that directly influence the validity, reliability, and replicability of a study.

Research validity refers to the degree to which a study accurately reflects or measures the concept that the researcher intends to investigate. A well-defined scope is critical to research validity because it clearly delineates what the study will cover. This clear definition ensures that the research focuses on relevant aspects of the topic and that the findings accurately reflect the concept under investigation.

Similarly, carefully thought-out delimitations contribute to research validity by identifying what the study will not cover. This clarity helps to prevent the study from straying into irrelevant areas, ensuring that the research stays focused and relevant.

In addition to contributing to research validity, scope and delimitations also influence the reliability and replicability of a study. Reliability refers to the consistency of a study's results, while replicability refers to the ability of other researchers to repeat the study and obtain similar results.

A clearly defined scope makes a study more reliable by providing a detailed outline of the areas covered by the research. This clarity makes it more likely that the study will produce consistent results. Moreover, clearly defined delimitations enhance the replicability of a study by providing explicit boundaries for the research, which makes it easier for other researchers to repeat the study in a similar context.

In summary, a well-defined scope and carefully thought-out delimitations contribute significantly to the validity, reliability, and replicability of academic research. They ensure that the research is focused, that the findings are relevant and accurate, and that the study can be reliably repeated by other researchers.

Examples of scope and delimitation in well-known research

  • The Milgram Experiment: Stanley Milgram's famous psychology experiment sought to understand obedience to authority figures. The scope of this study was clearly defined—it focused on how far individuals would go in obeying an instruction if it involved harming another person. However, delimitations were set to ensure manageability. Participants were delimited to male individuals, and the experiment was confined to a controlled laboratory setting. These delimitations allowed Milgram to manage the research effectively while maintaining the depth of his study on human behavior.
  • The Framingham Heart Study: This ongoing cardiovascular study began in 1948 and is aimed at identifying common factors that contribute to cardiovascular disease. The scope of the research is broad, covering many aspects of lifestyle, medical history, and physical characteristics. However, the study set clear delimitations: it initially only involved adult residents of Framingham, Massachusetts. This geographical delimitation made this broad-scope study manageable and eventually yielded influential results that shaped our understanding of heart disease.
  • The Marshmallow Test: This well-known study by Walter Mischel explored delayed gratification in children. The scope was clearly defined: the study aimed to understand the ability of children to delay gratification and how it related to future success. The delimitations of the study included the age of the participants (preschool children), the setting (a controlled experiment with a treat), and the measure of future success (academic achievement, ability to cope with stress, etc.). These delimitations helped keep the study focused and manageable.

In all these examples, the researchers set a clear scope to outline the focus of their studies and used delimitations to restrict the boundaries. This balance between scope and delimitation was key in conducting successful and influential research.

In academic research, defining the scope and delimitations is a pivotal step in designing a robust and effective study. The scope outlines the breadth and depth of the investigation, offering a clear direction for the research. Meanwhile, delimitations set the boundaries of the study, ensuring that the research remains focused and manageable. Together, they play a crucial role in enhancing the validity, reliability, and replicability of a study.

Understanding the interplay between scope and delimitations is key to conducting efficient research. A well-defined scope paired with thoughtfully set delimitations contribute to a study's feasibility and its potential to yield meaningful and applicable results. Mistakes in setting the scope and delimitations can lead to unwieldy, unfocused research or a study that overlooks important aspects of a research question.

Reviewing famous studies, like the Milgram Experiment, the Framingham Heart Study, and the Marshmallow Test, we observe how a balanced approach to setting scope and delimitations can result in influential and valuable findings. Therefore, researchers should give careful thought to defining the scope and delimitations of their studies, keeping in mind their research questions, available resources, and the need for balance between breadth and focus. By doing so, they pave the way for successful and impactful research outcomes.

Header image by Kübra Arslaner .

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Good review practice: a researcher guide to systematic review methodology in the sciences of food and health

  • About this guide
  • Part A: Systematic review method
  • What are Good Practice points?
  • Part C: The core steps of the SR process
  • 1.1 Setting eligibility criteria
  • 1.2 Identifying search terms
  • 1.3 Protocol development
  • 2. Searching for studies
  • 3. Screening the results
  • 4. Evaluation of included studies: quality assessment
  • 5. Data extraction
  • 6. Data synthesis and summary
  • 7. Presenting results
  • Links to current versions of the reference guidelines
  • Download templates
  • Food science databases
  • Process management tools
  • Screening tools
  • Reference management tools
  • Grey literature sources
  • Links for access to protocol repository and platforms for registration
  • Links for access to PRISMA frameworks
  • Links for access to 'Risk of Bias' assessment tools for quantitative and qualitative studies
  • Links for access to grading checklists
  • Links for access to reporting checklists
  • What questions are suitable for the systematic review methodology?
  • How to assess feasibility of using the method?
  • What is a scoping study and how to construct one?
  • How to construct a systematic review protocol?
  • How to construct a comprehensive search?
  • Study designs and levels of evidence
  • Download a pdf version This link opens in a new window

Scoping Study

Do you need a scoping study.

A scoping study is usually carried out before a full systematic review, to assess the breath of the research around the topic of interest. It may be used to determine how well the subject is researched and whether there is enough evidence or a real need to conduct a full systematic review. They are also planned to map keywords to relevant concepts and put the research topics in context. Scoping exercises are  not  mandatory and are only planned if there is a need to overview the state of the art for the topic of interest. 

In relevance to systematic reviews, they are widely used to:

  • investigate the volume and state of available literature, 
  • map concepts, keywords, and policies,
  • to narrow down the scope of broad questions and make them suitable for the use of the SR methodology. 

The method of scoping research topics was first developed by the EPPI-Centre to pilot systematic reviews of environmental questions. They were then extended to clinical and social science topics and are gradually being adopted in other scientific disciplines.

How to conduct a scoping study

Scoping studies are descriptive and often not comprehensive, but they provide a roadmap of literature. They follow similar steps to a systematic review process to summarise the state of current research on a topic  without  the need for data extraction, quality assessment or sensitivity analysis. 

A standard framework proposed by Arksey, and O’Malley  [2] is commonly used in clinical and healthcare research. This framework can be adapted and applied in other fields as well.  

It consists of the following 5 steps:     Step 1: Identifying the research question,    Step 2: Identifying relevant studies,     Step 3: Study selection,     Step 4: Charting the data,     Step 5: Collating, summarising, and reporting results.

Identifying the research question : the objective of the review question and the purpose of the scoping study determine which aspects of the study are important and what details are needed to provide an appropriate description. For example, to assess different applications of an intervention, a map of relevant literature to find all subpopulation might be planned.

Identifying relevant studies : regardless of the topic, at least 2 key elements of the research question set the foundation for a scoping study: the population and the outcome of interest. But unlike systematic review questions scoping questions seek to describe important aspects of relevant research. For instance, an intervention question can be centered around “what kind” of interventions have been applied to a particular subject for an outcome of interest.

Study selection : the search strategies of scoping studies are often designed to capture a broader spectrum of literature. As a result, the study selection process often is done at two different levels to manage the volume. First, all irrelevant and out of focus literature are removed by screening through citations or titles and abstracts. Then the screening procedure is followed for the full texts of relevant literature. 

Charting the data : this stage of the scoping method can differ considerably based on the purpose. These details can include study characteristics, details of the populations, type and volume of relevant primary studies, details of various concepts and topics, etc. 

Collating, summarising, and reporting results : The presentation formats are also guided by the purpose of the scoping review and often consist of tabulated forms that are used to organise and chart the data accordingly. When inputs or agreements from different field experts are needed, an optional consultation step is sometimes carried out in the end.

Good practice point : For the purpose of good practice this stage should be managed by at least 2 reviewers to make sure all relevant literatures are included.  If the scoping review is intended for publication, a  protocol  should be developed before undertaking it, to outline the methods and objectives. 

Links to access examples of scoping studies

  • << Previous: How to assess feasibility of using the method?
  • Next: How to construct a systematic review protocol? >>
  • Last Updated: Sep 18, 2023 1:16 PM
  • URL: https://ifis.libguides.com/systematic_reviews

Systematic Reviews and Meta-Analyses: Define Scope

  • Get Started
  • Exploratory Search
  • Where to Search
  • How to Search
  • Grey Literature
  • What about errata and retractions?
  • Eligibility Screening
  • Critical Appraisal
  • Data Extraction
  • Synthesis & Discussion
  • Assess Certainty
  • Share & Archive

The scope of a systematic review is defined through the A.   research question  and B.   eligibility criteria .

The scope will inform every aspect of your systematic review.

scope of study in research

The  exploratory search  is also relevant to scope development and discussed in more detail in the subtab of this page.

A. Research Question

Research question.

As with any project, the first step is to define the goal - in research, the goal is usually defined as a research question . 

A systematic review must have a  well-defined and specific research question(s) . To support development, your team may run exploratory searches , (2) speak with others in your field , and/or (3) gather input from stakeholders such as policy makers and community members who may be interested in the findings of your review. 

Research Question Development Tools (e.g., PICO )

Research question development tools, also called 'research question formulation frameworks' or 'concept developers' are simply acronyms that help you consider the details behind your research question. 

The intervention-focused tool PICO,  which stands for Population, Intervention, Comparator, and Outcome, is a common example used in systematic reviews. However, you have many more options  including the 5W's and H, SPIDER, and CIMO.  More about choosing a concept developer !

B. Eligibility Criteria

Eligibility criteria.

Decorative

Inclusion Criteria or the set of characteristics that a reference must have to be included in the final synthesis

Exclusion Criteria  or the set of characteristics that, if present, would make the reference outside of your scope

Eligibility criteria must be defined  before   starting the review. By reducing the likelihood of having to make ad hoc decisions  during  the review, eligibility criteria defined ahead of contributes directly to the cornerstone of reducing likelihood of bias .

Tips for Developing Eligibility Criteria

Having clear , unambiguous , and easy to apply criteria is vital for the review, as all reviewers will need to apply the same criteria in the same way during the eligibility screening .

Try looking at your criteria from the perspective of someone who is unfamiliar with your topic; would these criteria still be clear? Is your criteria relying on assumptions based on your personal background (e.g., discipline, culture, education, age)? Does the criteria make sense given the context of your problem?

Also consider more nuanced  decisions that the reviewers  might need to make when applying the criteria during the  eligibility screening .

Note about Language Limits

It is common to find eligibility criteria in systematic reviews that exclude articles outside of the languages of those in the team. In the US, this often means "English only" articles are included. However, this exclusion poses a serious risk of bias toward research produced by countries where English is a dominant language. Therefore, it is best to avoid excluding based on language when you can. Check out our resources at the bottom of the "Find Full Text" box on the Eligibility Screening tab.

Methodological Guidance

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  • Environmental Sciences

Cochrane Handbook  -  Part 2: Core Methods

Chapter 2:  Determining Scope and Questions  provides guidance for scope development

  • 2.1 Rationale for well-formulated questions
  • 2.2 Aims of reviews of interventions
  • 2.3 Defining the scope of a review question
  • 2.4 Ensuring the review addresses the right questions
  • 2.5 Methods and tools for structuring the review

Chapter 3:  Defining the criteria for including studies and how they will be grouped for the synthesis  

  • 3.2 Articulating the review and comparison PICO
  • 3.3 Determining which study designs to include
  • 3.4 Eligibility based on publication status and language

SYREAF Tutorials

Step 1:  developing a protocol.

Conducting systematic reviews of intervention questions I: Writing the review protocol, formulating the question and searching the literature.  O’Connor AM, Anderson KM, Goodell CK, Sargeant JM. Zoonoses Public Health. 2014 Jun;61 Suppl 1:28-38. doi: 10.1111/zph.12125. PMID: 24905994

Campbell -  MECCIR

C1. Formulating review questions  ( title registration & protocol )

C2. Predefining objectives ( title registration & protocol )

C3. Considering potential adverse effects ( protocol )

C4. Considering equity and specific populations ( protocol )

C5. Predefining unambiguous criteria for participants ( protocol )

C6. Predefining a strategy for studies with a subset of eligible participants ( protocol )

C7. Predefining unambiguous criteria for interventions and comparators ( protocol )

C8. Clarifying role of outcomes  ( protocol & review / final manuscript )

C9. Predefining study designs   (protocol )

C10. Including randomized trials ( protocol - effectiveness reviews only )

C11. Justifying choice of study design ( protocol )

C12. Including studies regardless of publication status ( protocol & review / final manuscript )

C13. Changing eligibility criteria ( review / final manuscript ) 

C14. Predefining [primary and secondary ] outcomes ( protocol )

C15. Choosing outcomes ( protocol )

C16. Predefining outcome details ( protocol )

C17. Predefining choices from multiple outcome measures ( protocol )

C18. Predefining time points of interest ( protocol )

CEE -  Guidelines and Standards for Evidence synthesis in Environmental Management

Section 2.  identifying the need for evidence, determining the evidence synthesis type, and establishing a review team.

2.3 From a problem to a reviewable question : Question generation and formulation

Reporting in Protocol and Final Manuscript

  • Final Manuscript

In the Protocol |  PRISMA-P

Objectives (item 7).

Provide an explicit statement of the question(s)the review will address with reference to participants, interventions, comparators, and outcomes (PICO)

Eligibility Criteria (Item 8)

Specify the study characteristics (such as PICO, study design, setting, time frame) and report characteristics (such as years considered, language, publication status) to be used as criteria for eligibility for the review

In the Final Manuscript |  PRISMA

Objectives (item 4), essential items.

  • Provide an explicit statement of all objective(s) or question(s) the review addresses, expressed in terms of a relevant question formulation framework (see Booth et al and Munn et al for various frameworks).
  • If the purpose is to evaluate the effects of interventions, use the Population, Intervention, Comparator, Outcome (PICO) framework or one of its variants to state the comparisons that will be made.

Eligibility Criteria (Item 5)

  • Specify all study characteristics used to decide whether a study was eligible for inclusion in the review, that is, components described in the PICO framework or one of its variants, and other characteristics, such as eligible study design(s) and setting(s) and minimum duration of follow-up.
  • Specify eligibility criteria with regard to report characteristics , such as year of dissemination, language, and report status (for example, whether reports such as unpublished manuscripts and conference abstracts were eligible for inclusion).
  • Clearly indicate if studies were i neligible because the outcomes of interest were not measured , or ineligible because the results for the outcome of interest were not reported. Reporting that studies were excluded because they had “no relevant outcome data” is ambiguous and should be avoided.
  • Specify any groups used in the synthesis (such as intervention, outcome, and population groups) and link these to the comparisons specified in the objectives (item #4)

Additional Items

Consider providing rationales for any notable restrictions to study eligibility. For example, authors might explain that the review was restricted to studies published from 2000 onward because that was the year the device was first available.

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How to write the scope of the study?

The scope of the study refers to the elements that will be covered in a research project. It defines the boundaries of the research. The scope is always decided in the preliminary stages of a study. Deciding it in the later stages creates a lot of ambiguity regarding the research goals. The main purpose of the scope of the study is that explains the extent to which the research area will be explored and thus specifies the parameters that will be observed within the study. In other words, it enables the researcher to define what the study will cover and the elements that it will not. Defining the scope helps the researcher acquire a high level of research and writing capability.

Goals of establishing the scope of the study

The following steps can help the researcher to effectively define the goals of establishing a scope of the study.

Identification of the project or research needs

The first step is to identify the research needs. This helps them set a benchmark from the first step. Identification of the ‘what’ and ‘why’ enables the researcher to clearly set the research goals and objectives and the manner in which they will be performed.

Confirmation of the goals and objectives of the research

The goals and objectives defined in the project scope should be aligned with the SMART (Specific, Measurable, Achievable, Realistic and Timeframe) guidelines, which are:

  • Specific- this involves a clear specification of what the researcher wants to achieve. It involves specifying what, why and how things will be done. This reduces the chances of ambiguities and any misunderstanding in the future.
  • Measurable- Goals should be measurable and dynamic so that constant feedback can be generated for improvement.
  • Achievable- Research goals should be achievable with the resources that are available.
  • Realistic- Goals should be easier to deliver so that complications that can hamper the quality of the research can be avoided. Other considerations to be kept in mind are the budget and timeline.  
  • Time frame- lastly, the researcher should estimate whether the set goals can be achieved within the given time frame or not.

Expectations and Acceptance

The researcher should take into account the expectations of the research and how well the findings of the researcher will be accepted by the reader. For instance, will the findings of your study help in policymaking or not?

Identification of the constraints

there are always certain roadblocks in conducting research, such as environmental conditions, technological inefficiency and lack of resources. Identifying these limitations and their possible solutions in advance help achieve goals better.

Identifying the necessary changes

After the preliminary goals are set, the researcher must carry out some part of the research so that necessary changes that lead to waste of time and resources at later stages are reduced. For example, while conducting an interview, if the researcher believes that the sample size decided is too large or too small according to the scope of the study, then the researcher can make the necessary changes in that order to avoid wastage of time and resources.

Guidelines for writing the scope of the study

The major things that the researcher should keep in mind while writing the scope of the study are as follows.

  • Time period: While writing the scope of the study the researcher should first mention or state categorically the time periods the study will cover. Generally, the researchers combine the scope of the study with the limitation of the study. These things are quite interwoven. The main difference between the two is that limitations further cover the points like monetary constraints or non-cooperation from the side of the target audience.
  • Geography: In addition to this another major point that the researcher should keep in mind is that the scope of the study should state the specific aspect of the data that needs to be collected like the geographic locations and the variables.
  • Research population: Another major aspect that should be involved while writing the scope of the study is the sample size or the population that the researcher has selected for the study. The sampling plan must clearly indicate the sample universe, target population, profile and sample size with justification.
  • Theories: The researcher should state the academic theories that are being applied to the data collected so that the reader better knows the lens of the analysis. This is presented in the ‘theoretical framework’ section.
  • Purpose: The scope of the study must indicate the purpose behind it. It must briefly define the larger picture, i.e. the overall goal the researcher is trying to achieve.  
  • Limitations: It is impossible to avoid roadblocks in research. Every research is restricted in scope and is subjected to certain limitations. By acknowledging these limitations and how they are restricting the study makes its findings even more credible.

Elements of the scope of the study

Consider the topic ‘Analysis of the role of social media on the educational development in India from 2000-2015’. The scope of the study for this research topic should include several roles within the mentioned time period. Further, it should also cover the mass media types that have been used in the analysis of the study also including the location and the sample size as well.

Scope of the study

With the increase in the number of social media users and its use in everyday communication at the individual and organizational levels, there has been a corresponding increase in its incorporation in educational development and especially in a country like India. In view of this situation, the present study analyzes the role of social media on the educational development of students. To this end, the study will also cover the changes in the usage of social media in the educational field over the time period ranging from 2000-2015. The scope of the study is restricted to select social media platforms, specifically Facebook, Twitter and YouTube. The empirical study in this research is restricted to five universities located across India, wherein the opinions of 30 teachers were studied in interview sessions. Further, the study also involves an analysis of students’ perspectives on the role of social media in education from the same university. Therefore the scope of this study is limited to India, and more specifically to those offering Arts and Science-related courses.

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What is the Scope of the Study in Research?

What is the Scope of the Study in Research?

The scope of the study explains the extent to which your research area will be explored, and the parameters the study will operate. It gives the reader and the writer an insight into what the study is aimed at and what should be anticipated.

This implies that the scope of the study should define the purpose of your study, the sample size and qualities, geographical location, the timeframe at which the study will be executed, theories the study will focus on, etc.

The scope of the study is just an aspect of research writing, and great attention needs to be taken not to go beyond what is expected. Therefore, the scope of the study sheds light on areas your study will cover and what it focuses on. What your study area is not going to focus on is of no relevance to your research study, and the scope of the study eliminates that.

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  • Published: 07 March 2024

Quantitative analysis of mass mortality events in salmon aquaculture shows increasing scale of fish loss events around the world

  • Gerald G. Singh 1 ,
  • Zaman Sajid 2 &
  • Charles Mather 3  

Scientific Reports volume  14 , Article number:  3763 ( 2024 ) Cite this article

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  • Environmental impact
  • Ocean sciences
  • Sustainability

Globally, salmon aquaculture promises to contribute to sustainable sources of animal protein for a growing human population. However, the growth of the industry also includes increased reports of mass mortality events—disaster events where large numbers of fish die in short periods of time. As salmon production increases in scale and more technology is used to grow salmon in contexts otherwise not suited for them, there is a possibility for more frequent and more severe mortality events. Despite investigations into specific cases of mass mortality events—no global study has been conducted to see if large scale mortality is increasing in frequency and scale. Using a global dataset of publicly available and government-collated data on salmon mortality events including nations responsible for the majority of salmon aquaculture, we document trends in mortality events, showing that in some of the major salmon producing nations of the world (in particular Norway, Canada, and the UK), mass mortality events have increased in frequency from 2012 to 2022. We also show that the scope of mass mortality events has increased over time—that is, the upper bound of how many fish were killed in a specific mortality event has increased over time. Finally, the expected maximum size of a mass mortality event differs from country to country, but is likely much larger than site and jurisdictional thresholds of concern for animal welfare, early warning thresholds, and capacity to respond to mortality events. The consequences of the increased scale and scope of mass mortality events extend past aquaculture production to include severe consequences to aquaculture companies and to coastal communities who depend on aquaculture. Our results agree with predictions of the concept of “manufactured risk”, which suggests that risk emerges from the aggressive use of technology to optimize production in variable environments, and we argue that there is a need for more fine-scale and standard data collection on salmon mortality events, and that future investigations into salmon aquaculture should increase focus on disaster potential and realization.

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Introduction

The global salmon aquaculture industry is seen as a sector that has the potential to produce a sustainable animal protein for the planet’s growing population 1 , 2 . Indeed, representative organizations of the aquaculture industry claim that farmed salmon is a ‘climate friendly’ protein based on its carbon footprint and low greenhouse gas emissions relative to other animal proteins 3 . At the same time, the sector is facing the problem of mass mortality events (MMEs)—events where large numbers of farmed fish die in a short period of time. While fish mortality has always been a concern for farmed salmon production 4 , 5 , 6 , 7 , 8 , 9 , MMEs are of particular concern because of the scale and rapidity of loss, and associated effects to communities dependent on aquaculture. MMEs have been recorded in most of the major salmon producing countries including Norway 11 , Canada 12 , 13 , Scotland 14 , Ireland 15 , Chile 16 , 17 , the United States 18 , and Australasia 19 . Analysis of MMEs, often led by national regulatory authorities, tend to focus on the causes of single events that involve one or several production sites with a view to mitigating future MMEs 11 , 15 . These studies are useful in providing in-depth analysis of the magnitude and possible causes of single mass die off events and report changes in mortality over time, but few if any studies have attempted to quantitatively assess trends in extreme loss events—MMEs—at multinational to global scales. Here we ask: is the scale and magnitude of MMEs in salmon aquaculture increasing in scope and over time?

The salmon aquaculture sector has grown very rapidly since it was first established in Norway in the 1960s 20 . Production has spread from Norway to other European countries as well as to Chile, Canada, the United States and Tasmania making it one of the fastest growing food production systems in the world. While production has increased dramatically in the last 60 years on the basis of a highly successful and standardized production model involving cages located in near shore ocean sites 21 , the industry faces considerable environmental challenges, including that environmental stressors (some amplified by climate change) affect aquaculture production and salmon health and that production affects the wider environment and wild salmon 11 . Warming oceans have posed a significant challenge to salmon aquaculture and this warming has exacerbated problems of rise in water temperature and hypoxia (low oxygen levels) contributing to MMEs 22 . Additional environmental problems include existing and new diseases, sea lice, water quality problems, and harmful algae blooms 23 . Living fish expel their wastes into water as a result of their bodily function while the decomposition of dead fish releases nutrients in the water, which causes algae blooms—making survival difficult for the remaining fish. In MMEs, these challenges often appear to work in tandem: higher temperatures may lead to hypoxia, which in turn can be fatal for fish that are immune compromised due to disease 22 .

The risks associated with salmon production that lead to MMEs are, however, rarely only environmental. Mortalities including those that result in MMEs are often caused by a combination of natural events and human decisions. For example, salmon mortality within aquaculture production facilities can often be the result of production practices such as mechanical and thermal delousing that coincide with other environmental and physiological conditions compromising fish health 6 . Similarly, overuse of antibiotics and antiparasitics can cause bacteria and parasites to develop resistance to them, and these treatments can become ineffective, which leads to an increased risk of MMEs 23 . Aquaculture operations manufacture systems where high densities of salmon allow for large populations to face mortality-inducing conditions simultaneously. The consequences of these MMEs are not limited to the stock of salmon but can have significant impacts to the surrounding environment (through nutrient release and the creation of anoxic “dead zones”) and the people working in the aquaculture production facilities 24 , and the consequences tend to worsen with increased magnitude of MMEs. For example, MMEs can be met with regulation that strips a company’s permit to raise fish, which can devastate local economies, e.g. 11 . The process of collecting and disposing of large volumes of dead fish may also have potential occupational health and safety consequences for workers involved in these labour-intensive and potentially risky tasks 24 , 25 .

The research in science and technology studies refers to risks that come about from human development and from human infrastructure, rather than external impacts to human communities alone, as “manufactured risk” 26 . Manufactured risk occurs when human decisions and infrastructure create or enhance contexts for consequential events. Manufactured risks are frequently the outcome of industrialization and modernization, in which technology and procedures are developed to boost efficiency and output but can also represent dangers if not managed appropriately or increase vulnerability to disasters by exposing a system to greater environmental variation that serve as hazards 27 . To our understanding, manufactured risk has yet to be quantitatively explored in aquatic food systems. Aquaculture, as an engineered system set up to optimize food production within an increasingly uncertain and variable environment, raises questions on whether risk is being manufactured in this food system. New efforts to expand aquaculture production under climate change and to gain maximum benefits from introducing salmon aquaculture to new environments (such as growing interest to grow salmon aquaculture offshore) present new potentials for manufactured risk, cf. 28 . Our research explores whether the frequency and scale of MMEs in salmon aquaculture is increasing, which is the first step in understanding if trends in salmon aquaculture are increasingly introducing manufactured risk—an important concern in a food system we may come to rely on more in the future.

We found salmon mortality records for the top 4 salmon aquaculture producing nations of the world (Norway, Chile, United Kingdom, and Canada) which in 2021 cumulatively produced approximately 90% of global salmon aquaculture output 29 . We also found MME records for Australia (the sixth largest producer) and New Zealand (the tenth largest producer), and cumulatively these six nations produced over 92% of the world’s salmon (by live weight) in 2021 27 . Our database records mortality of 865,000,000 fish in these six nations over the last decade (Fig.  1 , Supplementary Fig.  1 shows the records of loss events over time per country in a dynamic map).

figure 1

The scales of fish lost in salmon aquaculture around the world during the period 2012–2022 from collected data (see “ Methods ” and Supplement). The map was created by the authors using Adobe Illustrator—Version 24.2.2 (adobe.com).

We found that the frequency of the highest mortality events (as defined by the top 10% of highest mortality events from 2012–2022 within each country) increased over time for Norway, Canada, and the United Kingdom (Fig.  2 ). Trend analysis showed significant monotonic trends over time for Norway (Kendall’s tau = 0.961, p = 0.0248), Canada (Kendall’s tau = 0.3, p = 0.0177), and the United Kingdom (Kendall’s tau = 0.457, p = 0.000854). For Chile, Australia, and New Zealand, no clear trends in the frequency of the top 50% highest mortality events were observed, though we note that there was considerably less data to analyze due to aggregated data reporting in these countries.

figure 2

Trends in the counts of MMEs across countries. For ( A – C ), events are counted as the top 10% of events as measured by the number of fish lost, within each country. For ( D – F ), events are counted as measured by the top 50% events, since there are too few observations to track the top 10%. ( D – F ) should be considered illustrative and not conclusive given the aggregation of data and low samples. Trend lines represent monthly (black) and yearly (red) lowess regression across the counts of events.

Trends in the sizes of the largest magnitude mortality events shows that the scale of MMEs have grown over time for Norway, Canada, and the United Kingdom, reflected in an increasing scope of loss for individual MMEs (Fig.  3 ). Trend analysis show significant monotonic trends over time for Norway (Kendall’s tau = 0.432, p = 4.77 × 10 –7 ), Canada (Kendall’s tau = 0.766, p = 2.22 × 10 –16 ), and the United Kingdom (Kendall’s tau = 0.606, p = 2.22 × 10 –16 ). In Norway, where data was collected at county levels instead of production site levels, the increasing trends in frequency of highest mortality events and magnitude of upper limit of loss did not co-occur with a trend in the increase in the number of production sites within Norwegian counties. That is, the number of production sites across Norway remained relatively constant, with no statistically significant trend in production sites (Supplementary Fig.  2 ). Trend analysis for Chile, Australia and New Zealand showed no clear trend, but data collection for these three countries is not per mortality event but for individual production facilities aggregated each year, meaning, with the available data, we cannot estimate the scale of losses of individual MMEs for these countries.

figure 3

Trends in the scale of salmon mortality events over time. The continuous red line represents a local polynomial regression (lowess regression) line following the maximum of monthly events in ( A – C ), and follows the maximum of yearly reportings in ( D – F ). Note the break in the y-axis for ( C ).

In estimating the largest potential mass die off event within Norway, Canada, and the UK (where loss data is reported per month or more frequently), we found that all countries have potentials for a single mass mortality event much higher than the average company-defined threshold. Norway has the potential for the largest loss (with an expected loss of the worst 0.1% of cases equalling 5.14 million fish), however Norway’s data is aggregated to the county scale. Among countries with data at the site scale, Canada has the largest potential for a single mass mortality event (with an expected loss of the worst 0.1% cases equalling 5.05 million fish, Fig.  4 A). For estimating the potential annual loss within Chile, Australia, and New Zealand (where loss data is reported per year), we again found that all countries have potentials for loss over a single year to greatly surpass the average company-defined threshold. Chile has the highest potential loss (at 8.19 million fish), followed by New Zealand (4.39 million fish) and then Australia (1.55 million fish, Fig.  4 B).

figure 4

The expected maximum loss per event for Norway, Canada, and the UK ( A ) and expected maximum yearly loss per year for New Zealand, Australia, and Chile ( B ). For reference, these figures are compared against an average threshold, which reflects an average of what production sites define as MMEs. Estimates of maximum loss show the Expected Shortfall values, with error bars representing the number of fish estimated to be lost in a 1/1000 event (lower bound) and a 1/10,000 event (upper bound).

Over the past decade, salmon aquaculture has generally increased in terms of geographic scope, frequency, and in the scope of magnitude of individual MMEs (as documented by a growing upper bound of magnitude of mortality). While we find growth in the frequency and scope of magnitude of MMEs in Canada and the United Kingdom because they report at per-site levels, we also document a greater frequency of high mortality at county scales in Norway, and suggest that this adds an important dimension to the broad problem of fish mortality in Norway’s farmed salmon sector 10 . Simultaneously, we suggest that increasing trends of the scope of high mortality at county scales in Norway may reflect increased sizes in individual events at production sites. To justify these conclusions, we point to the findings that the increased frequency of high loss and scope of high-loss observed at county levels do not correspond with similar increases in the number of production sites. That is, higher levels of mortality were observed over time while the number of production sites remained relatively constant.

The increased frequency of high mortality events in many parts of the world may track the growth of aquaculture in terms of the number of sites and geographic spread of aquaculture production. However, the increased scope of MMEs may not be attributed to the growth of aquaculture production around the world. Instead, the growing scope of loss may be a consequence of the technologies and practices intended to increase productivity at production sites, such as technology to optimize production conditions and a greater tendency to move production sites offshore 28 .

The increase in distribution, frequency, and scope of the magnitude of MMEs adds to the growing concerns about global aquaculture’s ability to feed the future. Globally, salmon aquaculture has grown in some regions more than others, with FAO data showing that the most growth in production between 2016 and 2020 occurred in Norway and Chile, and more modest to stagnant growth in the UK, Australia, New Zealand, and Canada (Supplementary Fig.  3 ). There is also concern that future growth in aquaculture is optimistic, with recent research suggesting that global aquaculture has peaked and may be on the verge of decline 30 . While it is too early to suggest that MMEs may offset global production, it may add to the list of factors pointing away from aquaculture production growth.

Within each country, the expected loss of the worst 0.1% of events indicates that every major salmon producing country faces the possibility of having events that severely surpass thresholds. The thresholds may reflect an individual company or county’s ability to contain and respond to the adverse impacts of MMEs, may reflect early warning thresholds indicating a potential disease/mortality problem, or may reflect thresholds reflecting animal welfare. If the country specific thresholds represent the general capacity of companies and agencies in each country to address mortality events when they occur, then all countries have the potential to be overwhelmed by MMEs. Canada and the UK may face greater single-event consequences for MMEs compared to Norway despite Norway having greater estimated maximum loss since losses are estimated per production site within a month in Canada and the UK, and per county in a month in Norway.

If the thresholds do not reflect capacity restrictions but early-warning systems, then the expected loss of the worst 0.1% of events indicate that the worst case events often far surpass these early indicators. In many countries there are requirements for companies to have contingency plans to address dead fish, however some recent literature questions the efficacy of these plans to address the health, environmental, and social consequences of MMEs, and in some cases they were inadequate or lacking 24 , 25 . While we acknowledge that because of data limitations our estimates of thresholds may not account for all production sites (and therefore estimates of average thresholds may be off), in most cases we estimate threshold exceedances in the millions of fish which we suggest is alarming enough to warrant further investigation into management and contingency plans and their capacity to contain and respond to MMEs. Ignoring the thresholds, we still suggest that the potential loss of millions of fish is alarming, especially in countries where the data is reported per production site (Norway reports loss per county).

Our data collection revealed inconsistent data reporting across the world. Some countries report at site level, while others at regional (county). Some report at relatively precise temporal scales (months or less) while others at yearly. In continuing to build a database on MMEs, we recommend that countries and jurisdictions around the world standardize data collection and reporting so that the risks of production can be traced in standardized formats along with metrics that track the food production benefits.

MMEs pose risks and adverse consequences for salmon production, but the consequences of MMEs are also significant for aquaculture companies and the communities that depend on aquaculture production for employment. A recent report by a Non-Governmental Organization (NGO) has estimated the cost of salmon mortalities in four of the largest producing countries (Norway, Chile, Canada, and the UK) since 2013 to be more than 15 billion dollars 31 . In some cases, our findings of expected extreme losses show greater expected maximum losses in countries with lower production than others (e.g. New Zealand vs. Chile). Contexts where lower production countries face greater extreme losses may face greater individual impact on local economies and ecologies since they will have a greater effect on total production. The impact of MMEs in communities dependent on salmon aquaculture can be particularly devastating. In Chile in 2016 an MME at a production site in the Chiloe region caused by red tide resulted in the death of over 6 million fish, representing more than 12 per cent of annual production 32 . The economic and social costs to the Chiloe region were significant: 4,500 people directly employed by the industry lost their jobs and the livelihoods of 6,000 inshore fisherman were affected, and even the tourism sector was affected because of the environmental impact associated with disposing of dead fish 32 . The resulting economic devastation to the Chiloe region was such that it required government cash supports for affected households.

There is a significant reputational—or social licence—impact of MMEs on companies involved with aquaculture production and to the industry as a whole 24 . For example, in Scotland where recent significant challenges with mass mortalities have led to calls by environmental NGOs, groups concerned with animal welfare, and politicians to restrict the growth of the sector in Scotland in light of these challenges 33 . MMEs may also result in responses by regulators: in Canada, for example, the death of 2.5 million fish on the south coast of Newfoundland resulted in provincial regulators withdrawing the licence for the company involved 11 .

Part of the community and health impacts of MMEs have to do with the post-event clean up. An emerging area of inquiry examines the relationship between MMEs and occupational health and safety 24 . In most (if not all) jurisdictions where salmon aquaculture is regulated, MMEs require the rapid mobilization of workers to remove dead salmon from net pens and to transport them to where they can be disposed of or, in some cases, processed for human or animal consumption 24 . There is very little research on the occupational health and safety implications of these events in an industry that has relatively high rates of injury 25 .

Ironically, some of the methods employed to reduce fish loss and maximize fish production may increase the rate and scale of MMEs. For example, adopting new technologies and early warning systems as well as programs aimed at reducing the vulnerability of salmon to warming events, diseases and pest infestations through improved feeds or selective breeding, can lead to an increased sense of security and justify the growth of salmon in increasingly risky contexts 28 . New technologies, improved feed, and early warning systems are aimed at addressing some of these risks that are a consequence of operating in increasingly variable environments 34 , 35 , 36 , 37 . These include devices that measure temperature, water velocity, oxygen and salinity within the cage environment to remote sensing technology at larger scales that provide data on weather, currents and ocean temperatures. The more advanced systems use artificial intelligence to monitor fish behaviour using underwater cameras during feeding and to warn of potential disease outbreaks 34 . Overall these systems aim to improve decision support in a context of a rapidly changing environment for fish farming in the ocean, but since they often attempt to promote productivity and create justifications for increased production capacity into riskier locations such as offshore and high energy sites, they have the potential to expose greater amounts of fish to hazards that can generate larger MMEs.

Fish farming technologies are geared to managing and controlling production in ocean systems that are changing in trend and variation that are difficult to predict and comprehend at short time-scales, which can lead to aquaculture disasters in the form of MMEs. Scholars in the field of science, technology and society have examined a wide range of disasters and have raised a number of problems with how these events are understood and how industry and regulators respond to them 27 . First, disasters are often seen as a natural event associated with the natural environment (such as climate change or pathogens) that impact human designed production system. However, all disasters are the intersection of environmental hazards and human infrastructure and decisions 38 . In the case of aquaculture, while MMEs in salmon aquaculture are often blamed on climate change or other environmental variables, close analysis of the events always reveals some form of human cause coupled with an environmental stress 6 . Attributing cause to environmental variables ignores the important human dimension to disaster and can deflect responsibility and accountability 38 . Second, these disaster risks are often introduced and can increase in frequency and scale when dependent on technology and infrastructure to produce in environments not naturally conducive to the scale of production 26 . There is, then, a paradox where the increasing sophistication of systems of production can lead to greater risk of disasters, a concept termed the manufacturing of risk 39 . The third and final point is that disasters are often a consequence of economic systems that are shaped by intense competition, financialization of industry, and a lack of regulatory oversight, since these processes can rush development while reducing emphasis on risk assessment 39 . The attribution to natural factors, increased reliance on technology, and increasingly competitive industry are characteristics of global salmon aquaculture.

While we propose that global salmon aquaculture may be an industry prone to these disasters because of the above points, our analyses cannot confirm this. We instead wish to raise these questions and open new inquiry into salmon aquaculture through the lens of MME risks, their causes, how they are responded to, and the extent to which they are becoming normalized in this important sector of the marine economy. Our analysis suggests that MMEs have grown and therefore we propose greater attention to the implication of these events. In particular, we suggest that salmon aquaculture should face questions raised in other sectors about the risks of optimizing production in systems of environmental and biology variability, and the risks of relying on these production systems.

Data collection

To explore the global scope of MMEs, we collected data on salmon mortality from the world’s major salmon aquaculture nations (Norway, Canada, the UK, Chile, Australia, New Zealand). First, we mapped the events spatially to determine the geography of MMEs. Next, we examine whether the frequency and scope of MME loss has changed over time (in particular, we look to see if the scope of loss of individual MMEs has changed over time). Finally, we use extreme value theory (EVT) to explore the estimated maximum potential loss of an event per country, comparing it to known estimates of specific company (or county) thresholds of loss.

Salmon mass mortality data were collected using an extensive literature search (through Web of Science, Scopus, Google Scholar, Google Books, SciFinder, Engineering Village, ResearchGate, Semantic Scholar, JSTOR, and Aquatic Sciences and Fisheries Abstracts), as well as aquaculture companies’ websites and annual production reports, data published in newspapers and magazines, and government websites. In cases where data was not accessible using these resources, and to vet our data in cases where it was available, we established contacts with relevant government departments. We requested them to share salmon mass mortality data (see Appendix for data sources associated with each recorded MME event).

Our literature search used diverse search terms about MMEs. Definitions of “mass mortality” vary by each jurisdiction. Some regions use the term “fish die-off” instead of MME, and some use “fish kill”. Some countries have a defined MME term, with many definitions focused on the rate of loss in a production site, but sometimes focused on rates of absolute loss (that is, kg of fish loss over a given time period 24 ). For example, in British Columbia, Canada, MMEs are defined either by an absolute loss of 4000 kg over a day or a loss of 10,000 kg over 5 days. They can also be defined by relative rate measures, such as if 2% of current stock inventory lost over a day or 5% lost over 5 days. In Norway, MMEs are defined by daily relative rates of loss per fish cage rather than total production site inventory. In Scotland, MMEs are defined either by daily or monthly rates of loss per site. Individual companies and production regions (such as counties in Norway) can also develop their own definitions of MMEs, and the definition of MME can vary from company to company. For example, in Chile, most companies consider MME if the combined annual loss surpasses a certain threshold. In many countries, companies only report their loss events as MME if their annual loss exceeds a specific threshold, which is often some percentage of fish harvested and varies from company to company.

Because of the different definitions around the world and at different scales, and the different reporting standards from each country (see below), we did not analyze mortality against a common standard. Instead, within each country we analyzed the trends in mortality for each country, which allows us to track trends specific to each country’s reporting standards. Within each country, we focus on tracking the most severe loss events (as recorded by each country’s reporting standards) over time and explore if these are increasing in frequency and magnitude. For example, in Canada most events are reported at monthly or lower intervals at the production site scale, while in New Zealand mortality is reported at the scale of production site, but mortality is reported yearly. In isolating the most severe cases we can remain agnostic on a precise global definition of MME while simultaneously tracking the most severe loss events at a country level, therefore providing some quantitative evidence behind potential trends in MMEs around the world.

To explore mortality data relevant to country-specific metrics of concern for MMEs, we collected data of reported threshold values within individual companies in individual countries. In Norway, where data on loss is reported at county scales and not at scales of the production site, we collected data on county-defined scales of thresholds. We assumed that the reported thresholds from companies (or counties, for Norway) represent either a capacity to manage and respond to MMEs and/or a level of concern for animal welfare and disease spread, which allowed us to compare potential loss against capacity to manage MMEs. The available data on these thresholds is not a random sample nor a comprehensive sample (not all companies or counties publish this), so we use these measures in an illustrative rather than a conclusive study (see Supplemental data for threshold values by country).

We found that Canada and the UK report MMEs on a scale of production site per month or less (indicating limited aggregation and even per-event scale), Norway reports monthly mortality per county, while Chile, Australia, and New Zealand report losses at yearly intervals. The data for these latter three countries are therefore highly aggregated and difficult to analyze for trends. Yearly statistics leads to an order of magnitude less data to analyze for trends compared to monthly data, considerably decreasing the statistical power of the analyses conducted. We therefore analyze the data differently for the countries (described below). For Norway, we also collected data on the number of production sites during the time we have mortality data in each county and across the country (2012–2022). By analyzing trends in production sites we can determine whether trends in MMEs (if they exist) follow trends in production sites (if they exist) or not.

Data analysis

From the data collection, we were first able to map out the frequency and magnitude of mortality. Using georeferenced data, we developed a spatial map of mortality around the world over time. We used the Flourish® software to develop a dynamic map showing where MMEs have occurred over time (using the Flourish® software— https://flourish.studio/ ).

To explore the temporal trends in MMEs we explore both the frequency and the magnitude of events over time. First, to analyze if the trend of MMEs is increasing in frequency, we isolated the top 10% of recorded events as measured by the size of the loss per recorded event within each country. These events were reflected to track the most severe loss events recorded within each country (Supplementary Table 1 ). We then tracked when these events occurred and if the frequency of occurrence had grown over time. In isolating the top 10% of cases we can remain agnostic on the precise definition of MME while simultaneously tracking the most severe loss events, at a country level according to the standards of reporting mortality within each country. Because some countries only record loss at yearly intervals, this leads to significant aggregations of data and loss in statistical power. In some cases (e.g. New Zealand and Australia), there are only 10 recorded events each, meaning that choosing the top 10% would not allow for any consideration of trends. Therefore, for countries where data is recorded on a yearly time-step, we chose to track the frequency of the top 50% of cases. We explore these countries for illustrative purposes and note that because of their data aggregation, conclusive statements on trends of MMEs cannot be made.

Because data collection ended during 2022, we did not capture all recorded MMEs for 2022 and in some nations, even MMEs for 2021 because of lags in data recording. For example, our database includes details of only three MMEs from Canada in 2021, but a recent search of the public database in Canada shows 85 events in 2021 in British Columbia alone ( https://www.pac.dfo-mpo.gc.ca/aquaculture/reporting-rapports/episodes-mort-events/index-eng.html ). However, the number of fish killed in each of these 85 events is not available. Therefore, for our analysis of frequency of the top 10% largest mortality events, we only use data for years we are confident in our database being comprehensive, which is from 2012–2021 for Norway, 2013–2020 for Canada, 2015–2021 for the UK, 2013–2021 for Chile, 2013–2021 for Australia, and 2013–2021 for New Zealand.

Second, we explored the magnitude of events over time. While the data is highly variable and the processes that generate the data (human decisions combined with technological innovation and environmental variation) make precise future prediction difficult or even impossible, we focus on analyzing trends within the time period of the database. In doing so we are not interested in developing inferential or predictive models but rather describing how change has occurred in the scope of mass mortalities over the database of events. We are interested in how the scale of the largest losses have changed over time, and so track the upper limit of magnitude of loss events. We analyzed the change in the upper bound of loss over time by calculating the maximum value of MMEs (as measured by magnitude of loss in numbers of fish) in each time period (monthly or yearly, depending on the country).

For tracking trends in both frequency and upper bound magnitude of loss events over time, we conducted a non-parametric Mann–Kendall tests to see if there are monotonic trends and used local polynomial regressions (lowess regression) to visualize the trends over time 40 . Though some evidence suggests that mortality in salmon aquaculture can follow seasonal patterns 5 , and so conducting a seasonal Mann–Kendall test may more accurately account for seasonal trends 41 , we chose to not to conduct a seasonal test, in order to utilize a more conservative test in the face of potential seasonal patterns. That is, should seasonal patterns be present in the data, a non-seasonal Mann–Kendall test would face more unexplained variation than a seasonal test and therefore be less likely to find significant trends. So, our decision for the type of test employed does not presuppose patterns and also is conservative against potentially finding patterns that are not real should random variation resemble seasonal shifts (i.e. we are less likely to commit type I errors). We only conducted these tests on countries with monthly or shorter intervals of data reporting, because of the issues of data aggregation and low sample sizes addressed above. With lowess regression we explored frequency at monthly and yearly intervals. While monthly scale analysis can provide finer resolution, it can also add noise to trends, especially if there are seasonal or other sub-annual patterns in the data, so a yearly trend of frequency was also considered to provide a more general indication of trends in the frequency of MMEs.

Because the Mann–Kendall test assumes independence, we tested for autocorrelation in our data by testing for correlations between each time period against subsequent lag time MMEs. Where autocorrelation was found, we first averaged our data across the time period where data is autocorrelated, ensured that autocorrelation was no longer present, then ran our analysis on the resulting averaged data. We found little to no evidence for autocorrelation in our data on maximum MMEs per time-period, globally and within countries, though we did find evidence for autocorrelation in determining a trend in the number of MMEs over time and adjusted accordingly before conducting statistical analyses of trends. For all Mann–Kendall tests we relied on 2-tail tests with a significance threshold α = 0.05.

Finally, we focused on understanding the extent of losses from individual MMEs. First, we describe the distribution of known MMEs per country, then generate estimates of the maximum loss of salmon that could occur. Here again we differentiate between Norway, Canada, and the UK on one hand (where loss at monthly or lower resolutions is available) and Chile, Australia, and New Zealand on the other hand (where loss per year is available). In this way we estimate the maximum potential loss per event in the former set of countries and the maximum potential loss per year in the latter set of countries.

To estimate the maximum potential loss of salmon within each country and to compare against what each country defines as an MME, we relied on EVT. EVT focussed on understanding the behavior of maxima or minima 42 , 43 . Therefore, we used EVT to compute the maximum loss at the distribution tail. EVT employs two main strands of models: Peak Over Threshold (POT) and Block Maxima (BM) 43 . The block maxima method only considers the maximum observations for each non-overlapping, equal-sized interval of the observation period. The POT method is thought to be more data efficient because it makes better use of all available information and is thus mostly used for practical applications, and is frequently used in risk management 43 . In applying EVT, we use the POT approach and fit the resulting data to the generalized Pareto distribution (GPD) distribution. As a threshold, we assessed loss of the top 10% of events as measured by the number of fish lost for Norway, Canada, and the UK. For Chile, Australia, and New Zealand we used the top 50% of cases as the threshold. In this way, we treated MMEs consistently in estimating the maximum size of events within each country and in tracking MME frequency and scale over time (see previous methods on time series).

We used Value at Risk (VaR) and Expected Shortfall (ES) analysis to assess the maximum expected salmon loss in an MME in a country. VaR calculates the worst loss possibly occurring in the given time frame and at a given confidence level 43 . In other words, VaR shows the maximum loss that one can expect with a given confidence level. Here, we focused on a 99.9% confidence level for illustration purposes. While VaR is suitable for assessing the maximum salmon loss, VaR cannot estimate the quantity of loss above the given confidence level.

On the other hand, ES (sometimes called conditional VaR) assesses the quantity of loss above this confidence level and is calculated from VaR 44 . ES is often a preferred risk assessment tool when facing highly variable data (such as the case of salmon mass mortalities) 43 . So, if VaR can be used to estimate the maximum number of fish that can be expected to be lost at the 99.9 percentile worst case, ES can estimate the expected potential loss within the worst 0.1% cases. For Norway, Canada, and the UK, we compare these estimates against the average mortality event threshold to compare an estimated worst case event against the capacity to address mortality events. For Chile, Australia, and New Zealand, we compare the estimated yearly potential maximum loss against the yearly threshold. We therefore calculated the ES as the expected loss within the worst 0.1% of cases, and when plotting the results included error bars representing the point estimate of the worst 0.1% event (as the lower bound) and the worst 0.01% event (as the upper bound).

Data availability

All data generated or analysed during this study are included in this published article (and its Supplementary Information files).

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Acknowledgements

The authors acknowledge support from the Department of Industry, Energy, and Technology in the Government of Newfoundland and Labrador, Canada (grant number 20210487), in addition to support from the Ocean Frontier Institute through an award from the Canada First Research Excellence Fund. GGS would like to acknowledge support from the Nippon Foundation Ocean Nexus Center at EarthLab, University of Washington.

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G.G.S., Z.S., and C.M. conceptualized the project. Z.S. collected the data and conducted the extreme value analysis. G.G.S. conducted the time series analysis. G.G.S. and C.M. led the writing of the paper, to which Z.S. contributed. All authors edited the manuscript.

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Singh, G.G., Sajid, Z. & Mather, C. Quantitative analysis of mass mortality events in salmon aquaculture shows increasing scale of fish loss events around the world. Sci Rep 14 , 3763 (2024). https://doi.org/10.1038/s41598-024-54033-9

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Experimental and numerical simulation study on forced ventilation and dust removal of coal mine heading surface

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  • Haotian Zheng 1 , 2 , 3 ,
  • Bingyou Jiang 1 , 2 , 3 ,
  • Haoyu Wang 1 , 2 , 3 &
  • Yuannan Zheng 1 , 2 , 3  

In order to study the problems of unreasonable airflow distribution and serious dust pollution in a heading surface, an experimental platform for forced ventilation and dust removal was built based on the similar principles. Through the similar experiment and numerical simulation, the distribution of airflow field in the roadway and the spatial and temporal evolution of dust pollution under the conditions of forced ventilation were determined. The airflow field in the roadway can be divided into three zones: jet zone, vortex zone and reflux zone. The dust concentration gradually decreases from the head to the rear of the roadway. Under the forced ventilation conditions, there is a unilateral accumulation of dust, with higher dust concentrations away from the ducts. The position of the equipment has an interception effect on the dust. The maximum error between the test value and the simulation result is 12.9%, which verifies the accuracy of the experimental results. The research results can provide theoretical guidance for the application of dust removal technology in coal mine.

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Avoid common mistakes on your manuscript.

1 Introduction

In recent years, the mechanization level of coal mining has been greatly improved, and the safe and efficient coal mining is becoming mature (Ji et al. 2023 ; Wang et al. 2020 ; Yu et al. 2023 ). However, high concentration dust, which affects the safety of coal mine production and threatens the occupational health of coal mine employees for a long time, is still very serious (Jiang et al. 2023 ; Moreno et al. 2019 ; Zheng et al. 2023b ).

At present, in addition to individual protection measures, coal dust control measures are commonly used at home and abroad: coal seam water injection to reduce dust, spray dust removal, ventilation dust removal and so on (Nie et al. 2017 ; Yu et al. 2017 ; Ashish et al. 2022 ; Han et al. 2023 ; Zhou et al. 2023 ; Zhu et al. 2023 ). Coal seam water injection reduces dust from the source, but there are problems such as water injection difficulty and low dust reduction efficiency (Geng et al. 2017 ; Wang et al. 2023 ; zhang et al. 2022a , b , 2023 ; Zhou et al. 2022 ). Spray dust removal requires a large amount of water and is not suitable for mines where water is scarce, and is prone to environmental pollution and nozzle blockage (Hou et al. 2022 ; Peng et al. 2022 ; Xiong et al. 2021 ). Ventilation is currently one of the more effective ways to remove dust, and a lot of research has been carried out at home and abroad. Zhou et al. found that the ventilation method of long pressure short extraction with the outlet of pressure duct 5 m away from the working face had the best dust removal effect, and the dust concentration could be rapidly reduced to less than 6 mg/m 3 (Zhou et al. 2020 ). Chen et al. used fluent software to numerically simulate the ventilation and dust removal system of the excavation face of rock roadway, and concluded that the average dust removal rates under the conditions of installing the wall duct, installing the dust collector and installing both at the same time were 49.4%, 67.1% and 86.2%, respectively (Chen 2018 ). Kurnia used computational fluid dynamics to evaluate a variety of strategies to improve dust dispersion generated at the coal face and to ensure a safe level of dust concentration in mine tunnels to ensure operator safety (Kurnia et al. 2014 ). Toraño used CFD model to study the dust characteristics of the two auxiliary ventilation systems and found that the model accurately predicted the airflow and dust characteristics of the working face and different roadway sections (Toraño et al. 2011 ).

To sum up, most scholars have used numerical simulations to study the ventilation and dust removal at a particular site coal and rock excavation workface, and relatively few studies have carried out experimental research to explore the laws. Most of the coal mine heading faces use forced ventilation. However, the wind speed of the outlet and the distance from the outlet to the excavation face have great influence on the dust removal effect of the forced ventilation, so it is very important to study the forced ventilation dust removal. In this paper, we take the 25212 heading surface of Hongliulin Mine as a prototype and conduct an experiment by building a simulation test platform for ventilation and dust removal of coal mine heading surface, while combining numerical simulation technology to study the laws of airflow field changes and the spatial and temporal evolution of dust pollution. The study can provide guidance for the determination of the optimal wind speed of the roadway and the optimal distance from the pressure duct to the heading face. It can also provide theoretical basis for the installation position and opening time of the cyclone ventilation device attached to the wall on the mine duct, the air curtain device on the tunneling machine, and the automatic purification water curtain.

2 Experimental and simulation method

2.1 establishment of similar experimental platform, 2.1.1 design of experimental platform.

The 25212 roadhead in the Hongliulin coal mine in Shaanxi Province is used as a prototype, the roadhead is approximately 4 m wide and high, and the roadhead is ventilated by a press-in type ventilation method. There are 2 sets of FBD No. 8.0/2 × 55 local ventilation fans (1 of which is standby), with motor power of 2 × 55 kW, air volume of 680–880 m 3 /min, and noise of ≤ 85 dB. The press-in local ventilation fan is placed in the 25213 exiting frame lane, 30 m west of 25212 bypass. The maximum air supply distance is 3200 m. The press-in ducts are extended to the face of the working face through the 25213 outframe lane and the 25212 outframe lane. The anti-static soft wind pipe with a diameter of 1000 mm is used. The press-in ducts are arranged at the top of the right gang of the roadway, and are laid and hung according to the regulations. The maximum air volume of the working face is 412 m 3 /min and the air volume of the roadway at the fan is 975 m 3 /min. The site of heading face 25212 is shown in Fig.  1 . The ventilation schematic diagram of the working face is shown in Fig.  2 .

figure 1

Site of heading face 25212

figure 2

Ventilation diagram of working face 25212

To ensure the feasibility of the test, the original dimensions were scaled using the similarity criterion to build the experimental platform, using the 25212 heading surface of the Hongliulin coal mine in Shaanxi Province as the prototype. The model was designed according to the reality: model = 2: 1, section height of the model was 2 m, width was 2 m, and length was 9 m. As the dust generated by the heading face tends to stabilize its distribution with the increase of movement distance, the length of the model roadway is not designed according to the actual type length. The distance from the outlet of the air duct to the working face is calculated according to the formula ( 1 ) of the effective range. The cross-sectional area of the roadway head is 4 m 2 , so the distance from the outlet to the working face should be less than 3 m.

where S is the cross-sectional area and L s is the distance from the air outlet to the head.

The roadway adopts the pressure-in ventilation mode, and the turbine fan with the power of 15 kW provides variable frequency air supply. The pressure air duct is composed of an acrylic fixed air duct with a diameter of 0.4 m and a movable flexible air duct. The outlet is equipped with a bidirectional wind speed sensor for mining. The adjustable distance between the air outlet and the driving face is 1–3 m. The dust generation system of the device is composed of an aerosol generator, an air pump, a gas pipe and a moving mode group. The aerosol generator is located at the front end of the roadway and can move on the end face with a moving range of 0–1 m and a precision of 1 mm. Airflow speed, dust height, air duct distance from the head position and other parameters can be adjusted in real-time visual control console. Taking the central position of the end face where the aerosol generator is located as the coordinate origin, X direction indicates that the tunnel head points to the end of the tunnel, Y direction indicates that the tunnel pressure side points to the roadheader, and Z direction indicates that the tunnel floor points to the roof. The experimental model roadway is shown in Fig.  3 .

figure 3

Simulation test platform for ventilation and dust removal of heading surface

2.1.2 Experimental method

2.1.2.1 preparation of experimental materials.

The coal sample used in the experiment was taken from Hongliulin Mine in Shaanxi Province, and the fresh lumps of coal were taken out from under the mine, sealed with cling film and brought to the laboratory. The coal briquettes were put into a planetary ball mill for grinding, which was operated at a frequency of 50 Hz and the running time is 1 h. To ensure uniform dust emission from the dust collector, the coal powder was put into a drying box at 40 °C for 24 h before the experiment. Finally, 0.2 g of coal powder was taken and the dust particle size was determined by Malvern particle size analyser. The particle size of the dust can be set as a CFD parameter, with a minimum dust diameter of 1 μm and a maximum dust diameter of 200 μm. The characteristic particle size of coal dust sample is shown in Table  1 . The particle size distribution curve is shown in Fig.  4 . The fitting result of Rosin–Rammler function is shown in Fig.  5 .

figure 4

Particle size distribution curve of dust

figure 5

Fitting result of Rosin–Rammler function

The instrument for measuring dust mass concentration is CCZ-20A dust sampler (Jiangsu Changshu Yushan Company), with sampling flow of 20 L/min and working noise ≤ 75 dB(A). Polypropylene fiber filter membrane (Shandong Weifang Jukai electronic technology company) is selected for dust collection, with specifications of 40 mm and aperture of 0.8 μm.

2.1.2.2 Pressure ventilation parameters setting

There are many factors affecting dust concentration of roadway under forced ventilation, among which the most important ones are wind speed of outlet and distance from outlet to driving face (Hua et al. 2018 ). In this paper, the control variable method was used to study the changes of dust mass concentration with different wind speed and different distance from the pressure duct to the head. Firstly, the distance from the pressure air outlet to the head is kept at 2 m, and the air speed is set at 0.5, 1.0, 2.0, 3.0 and 4.0 m/s respectively for the dust mass concentration, and the optimal air speed is selected. Then, under the optimal wind speed, the dust mass concentration of 1.0, 1.5, 2.0 and 2.5 m from the pressure duct to the driving face was studied. The measuring points were arranged at 1, 2, 3, 4 and 5 m from the head, and the height of the measuring points was kept at 0.75 m above the human breathing zone.

2.1.2.3 Measurement of dust mass concentration

The experimental installation uses a TOPAS brand dust generator (SAG410) manufactured in Germany. To ensure the uniform and stable dust generation from the aerosol generator, the coal dust is dried before each experiment. The operating power of the dust generator is controlled by the air flow. The power of the dust generator is maintained at 20% and the dust generation rate is maintained at 1000 mg/s. The pressure air duct of the roadway is kept ventilated, and the operating platform is used to control the wind speed, the height of the aerosol generator and the distance between the outlet and the driving face. The dust mass concentration at each measuring point was measured by CCZ-20A dust sampler. In order to reduce the random error of the test, the filter film was put into a drying box at 100 ℃ for 30 min before and after weighing. The filter film before and after the test was weighed by an electronic balance, and the dust mass concentration at each measuring point was calculated by Eq. ( 2 ). Each weighing was repeated 3 times and averaged. Figure  6 shows the specific procedure.

where, C is the dust concentration at measuring point, mg/m 3 ; m 2 is the mass of the sampled membrane, mg; m 1 is the mass of the filter membrane before sampling, mg; Q is the sampling flow, L/min; t is the sampling time, min.

figure 6

Diagram of the experimental process. a Pulverized coal preparation b Drying of pulverised coal and filter membranes c Dust sampler selection d Alleyway testing e Collection of filter membranes f Measurement of dust concentration

2.2 Building of CFD model

The diffusion and diffusion process of dust in heading face under the action of air flow belongs to the category of gas–solid two-phase flow. Eulerian-Lagrange method was used to calculate and solve the process. Euler method focuses on the physical quantity change of particles at every point and moment in space, regardless of the motion of individual particles. Therefore, the flow is regarded and described as a continuous phase in the Euler coordinate system. Lagrange method focuses on the study of each particle, describing the motion process of particles at any time and the change of physical quantity over time. Thus, dust particles are treated as discrete phases and described in Lagrangian coordinates (Jin et al. 2022 ; Liu et al. 2019 ; Nie et al. 2022b ). The following assumptions are made for the model:

Air flow is an incompressible fluid.

The interaction between particles and the influence of particles on the continuous phase are ignored.

All dust is seen as a sphere.

Energy exchange is not considered.

Dust is subjected to multiple forces during its movement (Chhabra 2019 ). According to Newton's second law, the force balance equation of dust is

where \(\frac{{\vec{g}\left( {\rho_{\text{p}} - \rho } \right)}}{{\rho_{\text{p}} }}\) is gravity, \(\overrightarrow {F}\) is the additional force, \(\frac{{\vec{u} - \vec{u}_{\text{p}} }}{{\tau_{r} }}\) is the drag force of the unit particle, and

where \(\tau_{r}\) is the particle relaxation time, \(u\) is the airflow velocity, \(u_{\text{p}}\) is the dust particle velocity, \(\mu\) is the airflow viscosity, ρ is the airflow density, \(\rho_{\text{p}}\) is the dust particle density, and \(d_{\text{p}}^{{}}\) is the dust particle diameter. \({\text{Re}}\) is the relative Reynolds number, defined as

The additional forces \(\overrightarrow {F}\) include the “virtual mass” force, pressure gradient force, thermophoretic force, etc. Based on previously published research on dust particles (V.K. Kollipara 2015 ), this paper does not consider the existence of additional forces.

2.2.1 Establishment of physical model

In order to realize the numerical simulation to reflect the effect of the test situation, this paper takes the test roadway as the prototype, simplifies the prototype to a certain extent, and uses Solidworks software to establish the physical model of the test roadway at 1: 1, the model size is 2 m × 2 m × 9 m. Since dust is generated from the roadway head in the driving process, the roadway head in the model is set as the dust emission surface. The parameters used are listed in Table  2 , and the physical model and grid of the test roadway are shown in Fig.  7 .

figure 7

Experimental roadway. a Physical model. 1-Heading face; 2-Airflow inlet; 3-Roadheader; 4-Roadway; 5-Air duct; 6-Outlet. b Grid model

2.2.2 Grid independence test

When computational fluid dynamics is used to simulate airflow field and dust diffusion, the quality of the grid will directly affect the efficiency and accuracy of the simulation, so it is necessary to verify the grid independence of the physical model. Air flow is the main factor restricting dust diffusion law and dust pollution effect. Therefore, wind speed distribution along the normal central axis of the roadway at the height of human respiratory tract is selected as the grid independence verification parameter. ICEM software was used to divide the physical model into unstructured grids, and three different numbers of grids (Scheme 1, Scheme 2, Scheme 3) with coarse (324, 185 units), medium (817, 508 units) and fine (3, 044, 823 units) were generated. The quality of the grids was all greater than 0.3. As can be seen from Fig.  8 , the wind speed reaches the maximum at 0.08 m of the heading face, and the wind speed is 0.97 m/s (coarse grid), 0.71 m/s (medium grid), and 0.66 m/s (fine grid) respectively. The wind speed reaches the lowest at 0.315 m from the heading face, and the wind speed is 0.37 m/s (coarse grid), 0.14 m /s (medium grid) and 0.10 m/s (fine grid) respectively. The wind speed at 0.3 m to 1.3 m from the heading face fluctuates constantly, which may be due to the influence of equipment storage in the roadway, where there is eddy current and the wind speed is relatively chaotic. After 2.76 m from the heading face, the wind speed showed a decreasing trend. In contrast, the velocity values of coarse grid and fine grid have the largest deviation, and the trend of wind velocity curves of medium grid and fine grid is roughly the same. For example, compared to a fine grid, at the peak of the velocity curve, the relative error of the coarse grid is 31.9%, while the error of the medium grid is only 7.5%. At the valley of the velocity curve, the relative error of the coarse grid is 31.4%, and the error of the medium grid is only 0.3%. Considering the computer performance and computational efficiency, we selected a medium grids to carry out follow-up research.

figure 8

Changes of wind speed along different grid conditions

2.2.3 Boundary conditions and parameter setting

The grid file was imported into Fluent, and the model boundary and dust parameters in the model tree of the software interface were set according to the specific conditions of the 25212 heading face, as shown in Table  3 .

The calculation flow chart includes preprocessing, solve and post-processing, as shown in Fig.  9 .

figure 9

Flow chart of calculation process

3 Analysis of ventilation and dust removal test and simulation results

3.1 analysis of test results of pressure ventilation dust removal, 3.1.1 variation of dust mass concentration with wind speed.

In this paper, the experimental results are fitted using Origin 2023. The variation law of dust concentration with wind speed is shown in Fig.  10 . The higher the wind speed, the faster the dust concentration decreases. The dust mass concentration in the roadway decreases gradually from the head to the rear side of the roadway. When L  < 1.4 m, the dust mass concentration gradually decreases with the increase of wind speed, indicating that when the wind speed is low, the driving effect of air flow is not enough to effectively discharge dust from the roadway, and the dust concentration may gradually accumulate. When the wind speed increases, the pushing effect of the air flow is strengthened, which can carry away the dust more effectively, so that the dust concentration is gradually reduced. When L  > 1.4 m, when the wind speed in the roadway is too high, the mass concentration of dust at each measuring point increases, indicating that when the pressure duct is a certain distance from the driving face, the greater the wind speed, the dust accumulated on the ground may be raised again, resulting in the phenomenon of rising dust concentration in the roadway. When the distance between the pressure tuyere and the driving face is 1.8 m, the dust mass concentration is the lowest when the wind speed is 2 m/s, about 30 mg/m 3 . When the distance between the air pressure tuyere and the driving face is 2.2 m, the dust mass concentration is the lowest when the wind speed is 3 m/s, and the lowest concentration is 130 mg/m 3 . It shown that the increase of wind speed in the compressed ventilation tunnel is not unlimited, and the high wind speed may bring about some negative effects, such as excessive airflow resistance and increased energy consumption. In order to achieve the best dust removal effect and energy consumption balance, the wind speed of the forced ventilation system should be controlled within a suitable range. Therefore, from the perspective of minimum dust concentration and energy saving, when the wind speed is 2 m/s and the distance between the pressure tuyere and the driving face is 1.8 m, the dust concentration in the roadway is minimum, and the parameter setting of the roadway is reasonable.

figure 10

Dust mass concentration at different wind speeds. a L  = 1 m b L  = 1.4 m c L  = 1.8 m d L  = 2.2 m

3.1.2 The variation of dust mass concentration with distance

The measurement results of dust mass concentration with distance were nonlinear fitted, as shown in Fig.  11 . When the distance from the air outlet to the heading surface is 1 m, the dust mass concentration is the highest, up to 510 mg/m 3 , indicating that when the pressure air outlet is too close to the heading face, dust tends to accumulate in the roadway and the ventilation and dust removal effect is poor. First of all, the limited time and space for fresh air to enter the heading face will limit the coverage of the airflow, making it impossible for dust to be effectively carried away from the vicinity of the digging face, thus affecting the dust control effect. Secondly, the close proximity leads to disturbed airflow and the close air supply may result in direct contact between the airflow and the surfaces of equipment and tools on the digging face, thus creating turbulence or backflow prematurely.

figure 11

Dust mass concentration at different distance from pressure duct to heading surface. a V  = 0.5 m/s b V  = 1 m/s c V  = 2 m/s d V  = 3 m/s e V  = 4 m/s

The dust concentration decreases significantly with increasing distance from the pressure air outlet to the digging face, and the further the distance, the lower the dust concentration. However, when the distance between the air outlet and the heading face is 1.8 m, the dust mass concentration is the minimum, and when the distance between the air outlet and the heading face is 2.2 m, the dust mass concentration increases again, because when the distance between the air outlet and the heading face is too far, the fresh air may be subject to some resistance during the transmission process, resulting in a slower airflow, and the reduction of air volume makes it insufficient to dilute the dust mass concentration, resulting in an increase of dust in the air. When the distance between the pressure duct and the driving face is close, the fresh air can reach the driving face quickly and form a strong airflow. In this situation, the air supply effect of the pressure duct is good, and the dust can be effectively taken away from the vicinity of the driving face, thus reducing the dust concentration. Therefore, the reasonable choice of the distance between the outlet and the heading face is very important to the influence of the change of roadway dust concentration. In summary, there are optimal values for both wind speed and distance from the air outlet to the headway. Considering the lowest dust concentration in the roadway and energy saving, when the wind speed is 2 m/s and the distance from the air outlet to the heading surface is 1.8 m, the dust concentration in the roadway is the lowest and the roadway parameter setting is reasonable.

3.2 Analysis of test results of pressure ventilation dust removal

From Sect.  3.1 , it is concluded that the dust mass concentration in the roadway is minimum when the wind speed is 2 m/s and the distance from the air outlet to the headway is 1.8 m. Therefore, the author used ANSYS-Fluent software to simulate the change of wind flow field and the spatial and temporal evolution of dust pollution under this optimal working condition, and compared them with the experimental results. The experimental and numerical simulation results are shown in Fig.  12 , with a minimum error of 6.5% and a maximum error of 12.9% at each measurement point. This shows the correctness and validity of the numerical simulation results, which can be further analysed.

figure 12

Comparison of dust mass concentration between experimental and numerical simulation under optimal working conditions

3.2.1 Variation law of airflow field

The distribution of the wind flow field in the roadway with and without the influence of dust is shown in Fig.  13 . The airflow field in the roadway can be divided into three areas: the jet zone, the vortex zone and the reflux zone (Nie et al. 2022a ). The jet zone is the area where the air flows from the outlet of the duct to the heading face, the air velocity in this area is very high, in the shape of a jet, and has strong characteristics of straight-line movement, which is recorded as zone I. Due to the restriction of the confined space of the roadway and the influence of the continuity of the wind flow, the flow in the opposite direction of the jet soon appears, and the wind flow forms a backflow area in the working area, which is recorded as zone II. At the same time, due to the suction of the jet, there is also a vortex zone at the interface between the jet and the return zone, which usually has a lower flow velocity and a rotational, spiral or cyclonic motion of the air flow, which is recorded as zone III. The interaction between the dust field and the airflow field is due to the fact that when there is a large amount of dust in the air, the dust particles interact with the airflow, slowing it down and changing the direction and distribution of the airflow, thus affecting the flow properties and transfer characteristics of the airflow. Specifically in the wind flow distribution near the location of the wind cylinder is different, with the dust impact of the wind flow field here is a vortex, no dust impact is a backflow.

figure 13

Distribution of airflow field in roadway. a Dust-free air flow field b Air flow field with dust

The formation of the jet, return and vortex zones in the wind flow field takes a certain amount of time and depends on various factors such as air velocity and environmental conditions. The spatial and temporal evolution of the wind flow field in the tunnel is shown in Fig.  14 . When the wind speed is 2 m/s and the distance from the air outlet to the heading face is 1.8 m, the jet zone and the reflux area on the side away from the wind pipe are formed at about 10 s, but at this time the airflow distribution in the roadway is still relatively disorderly, after a period of evolution, the return flow area on the side of the pressure duct is formed at about 40 s, and a more obvious jet zone and return flow area are gradually formed in the tunnel at about 50 s, but the vortex area is not yet obvious, and when it reaches at 60 s the three zones become more obvious and stable. Higher air velocities can facilitate the formation of jet zones, while slower airflows may take longer to form jet zones. The surrounding environment also has an impact on the formation of jet, vortex and reflux zones (Yin et al. 2020 ). Obstructions, flow boundaries or other airflow disturbances in the environment may prevent the formation of jet zones and take longer to achieve stability.

figure 14

The spatial and temporal evolution of the airflow field in the roadway. a t  = 10 s b t  = 20 s c t  = 30 s d t  = 40 s e t  = 50 s f t  = 60 s

As L increases, turbulence effects generally become more significant. The turbulence energy contour is shown in Fig.  15 . The velocity vector diagram at the height of the human breathing zone is shown in Fig.  16 . The contour of dust mass concentration at the height of human breathing zone is shown in Fig.  17 . The contour plot shows the variation of turbulent energy at different locations, with regions with higher energy usually corresponding to regions with stronger turbulence. If dust particles are present in these high-energy regions, they may be affected by turbulence and accumulate, resulting in unusually high dust concentrations. It can be seen from the contour line that there are two eddy currents at the front end of the heading machine, and the dust mass concentration in the roadway basically decreases gradually from the head of the roadway to the back side of the roadway. The dust mass concentration on the side away from the pressure duct is significantly higher than that on the other side.

figure 15

Turbulence contour at the height of human breathing zone

figure 16

Velocity vector diagram at the height of the human breathing zone

figure 17

Contour line of dust mass concentration at the height of human breathing zone

3.2.2 Spatial and temporal model of dust pollution

The diffusion of dust concentration in the roadway over time is shown in Fig.  18 . When the wind speed is low, the dust diffusion is slow and mainly concentrated at the front end. As time passes, the dust gradually diffused to the rear side of the roadheader, and the dust concentration on the rear side of the roadway gradually increased and reached stability at 60 s. This phenomenon shows that the diffusion of the dust field is usually shown as the formation of a concentration gradient, with dust particles spreading from the initial release point to the surrounding area, forming a gradient of decreasing concentration. The reason may be that the size of different particles influences the diffusion behavior. Larger particles usually settling over short distances, while smaller particles can be diffused over longer distances by the airflow. In addition, the air flow can affect the suspension, transportation and settling of dust particles in the roadway. The turbulence effect in the environment can increase the mixing degree between particles and air flow, promote the agglomeration of dust particles and the diffusion of dust particles to the rear of the tunneling machine.

figure 18

Dust diffusion in roadway at different time. a T  = 10 s b T  = 30 s c T  = 60 s

According to the changes of dust concentration at different distances from the head (Fig.  19 ), it can be seen that under the condition of forced ventilation, dust in the roadway has unilateral accumulation, and the dust concentration in the position far from the air duct is relatively high. The reason may be that the tunneling machine and other equipment in the roadway have the blocking effect, which will block the airflow and change its direction. The airflow on the right side of the boring machine (away from the air duct side) produces higher speed and lower pressure, so that dust particles are more likely to accumulate on this side. In addition, the properties of dust particles also affect their behavior in the air flow. Particles with different characteristics will experience different forces in the air flow, resulting in unilateral aggregation. Dust diffusion has self-settling phenomenon. The dust concentration at the lower end is higher than that at the upper end and gradually diffuses pollution to the upper end. The reason is that dust particles themselves will move downward under the influence of gravity (Chen et al. 2022 ).

figure 19

Dust mass concentration at different distances from the heading face. a T  = 10 s b T  = 20 s c T  = 30 s d T  = 40 s e T  = 50 s f T  = 60 s

According to the change of dust concentration at the height of human breathing belt (Fig.  20 ), the dust concentration gradually decreases from the head to the back end of the roadway. The dust concentration is relatively high at the position of the tunneling machine, indicating that the arrangement and location of equipment and tools in the roadway can have an interception effect on the diffusion and propagation of dust particles. Therefore, a partition or barrier is set up in the roadway to block the airflow and the propagation of particulate matter. These obstructions can change the direction and speed of the air stream and cause particulate matter to accumulate or settle in the area behind them. In addition, Fig.  20 also shows that unilateral aggregation usually occurs on the side far from the air duct (air source). When the air duct or air source discharges air in a certain direction, dust particles are deflected in the air due to the difference in the flow direction and speed of the air duct. Driven by the air flow, dust particles move along the direction of the air flow in the return flow area, and the air flow forms a higher speed and lower pressure area near it, which leads to the accumulation of dust concentration in this area, and also forms the phenomenon of unilateral accumulation of dust under the pressurized ventilation condition. From the above analysis, it can be seen that, without considering other factors, the position of the tunneling machine driver near the side of the pressure air duct is less harmful to dust. In addition, the diffusion and propagation of dust particles can be effectively prevented by the reasonable arrangement of obstacles in the roadway.

figure 20

Dust mass concentration at the height of breathing zone. a T  = 10 s b T  = 20 s c T  = 30 s d T  = 40 s e T  = 50 s f T  = 60 s

3.3 Discussion

The experimental and numerical simulation results show that the air flow field in the press-in ventilation roadway can be divided into three areas: jet zone, vortex zone and reflux zone, which is similar to the result in reference (Xiu et al. 2020 ). However, the formation of jet zone, vortex zone, and return zone requires a certain time, which can provide a theoretical basis for the installation position and opening time of the attached wall cyclone ventilation device on the mine duct or the air curtain device on the roadheader. The dust mass concentration on the side away from the air duct is significantly higher than that on the other side, which is similar to the conclusion in reference (Yao et al. 2020 ). Therefore, a dust removal device can be added on the return side of the roadway, especially near the roadheader with large dust collection volume, to reduce the dust concentration (Sun et al. 2019 ). There are two eddies at the front end of the heading machine, so targeted dust removal measures can be implemented for the eddies area. Spraying should be added at the entrance side to effectively capture small particles of dust (Zhang et al. 2020 ). This study helps to improve the understanding of dust distribution in the roadheading face and provides guidance for designing ventilation schemes and zoning to manage dust. On the other hand, this study can provide theoretical guidance for the determination of the optimal air velocity in the roadway and the optimal distance from the pressure duct to the face of the roadheading, and too high an increase in the air velocity does not necessarily lead to a decrease in the dust concentration all the time (Zheng et al. 2023a ). However, this paper only investigated the distribution of dust in the roadway under forced ventilation conditions, which is useful for improving dust management in mines using this ventilation method. The experimental results may be different if a different ventilation method is used, such as the long-pressure, short-extraction ventilation method. Future research should focus on the development of new ventilation methods, such as the development of smart ducts and new wind control devices.

4 Conclusions

In this paper, experiments and numerical simulation are used to study the effects of wind speed and distance from the outlet to the driving face on dust diffusion and propagation. Finally, the following conclusions are drawn:

The similarity criterion number of press-in ventilation dust removal model was deduced by similarity criterion. In order to ensure that the experiment is consistent with the site, the geometric similarity ratio of the experiment is 1: 2, a large pressure ventilation dust removal experimental model is built, and the relevant research on pressure ventilation dust removal is carried out through the similar experiment and numerical simulation. The research results can provide theoretical guidance for the application of the dust removal technology on the integrated mining face of coal mine.

According to similar experimental results, there are optimal values for wind speed and distance from outlet to head. When the wind speed is 2 m/s and the distance from the outlet to the driving face is 1.8 m, the mass concentration of dust in the roadway is the minimum. The maximum error between the test value and the simulation model is 12.9%, which verifies the correctness of the experimental results.

According to the numerical simulation results, the airflow field in the roadway with or without dust disturbance can be divided into three areas: jet zone, vortex zone and reflux zone. Dust concentration gradually decreases from the head to the back end of the roadway. Under the pressure ventilation condition, dust accumulates in one side, and the dust concentration is higher in the position far from the air duct. The arrangement and location of the equipment will have an interception effect on dust particles. Reasonable arrangement of obstacles can effectively prevent the diffusion and propagation of dust particles.

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Acknowledgements

This work was financially supported by the National Key R&D Program of China (2022YFC2503200, 2022YFC2503201), the National Natural Science Foundation of China (52074012, 52204191), the Anhui Provincial Natural Science Foundation (2308085J19), the University Distinguished Youth Foundation of Anhui Province (2022AH020057), the Anhui Province University Discipline (Major) Top Talent Academic Support Project (gxbjZD2022017), the Funding for academic research activities of reserve candidates for academic and technological leaders in Anhui Province (2022H301), the Independent Research fund of Key Laboratory of Industrial Dust Prevention and Control & Occupational Health and Safety, Ministry of Education (Anhui University of Science and Technology) (EK20211004), the Graduate Innovation Fund of Anhui University of Science and Technology (2023CX1003).

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Key Laboratory of Industrial Dust Prevention and Control & Occupational Health and Safety, Ministry of Education, Anhui University of Science and Technology, Huainan, 232001, China

Haotian Zheng, Bingyou Jiang, Haoyu Wang & Yuannan Zheng

Joint National-Local Engineering Research Centre for Safe and Precise Coal Mining, Anhui University of Science and Technology, Huainan, 232001, China

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Zheng, H., Jiang, B., Wang, H. et al. Experimental and numerical simulation study on forced ventilation and dust removal of coal mine heading surface. Int J Coal Sci Technol 11 , 13 (2024). https://doi.org/10.1007/s40789-024-00667-z

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Published : 12 March 2024

DOI : https://doi.org/10.1007/s40789-024-00667-z

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