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Research Methods Guide: Research Design & Method

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Research Methods (sociology-focused)

Qualitative vs. Quantitative Methods (intro)

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FAQ: Research Design & Method

What is the difference between Research Design and Research Method?

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

Which research method should I choose ?

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

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

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

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

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

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How to Write a Research Design – Guide with Examples

Published by Alaxendra Bets at August 14th, 2021 , Revised On October 3, 2023

A research design is a structure that combines different components of research. It involves the use of different data collection and data analysis techniques logically to answer the  research questions .

It would be best to make some decisions about addressing the research questions adequately before starting the research process, which is achieved with the help of the research design.

Below are the key aspects of the decision-making process:

• Data type required for research
• Research resources
• Participants required for research
• Hypothesis based upon research question(s)
• Data analysis  methodologies
• Variables (Independent, dependent, and confounding)
• The location and timescale for conducting the data
• The time period required for research

The research design provides the strategy of investigation for your project. Furthermore, it defines the parameters and criteria to compile the data to evaluate results and conclude.

Your project’s validity depends on the data collection and  interpretation techniques.  A strong research design reflects a strong  dissertation , scientific paper, or research proposal .

Step 1: Establish Priorities for Research Design

Before conducting any research study, you must address an important question: “how to create a research design.”

The research design depends on the researcher’s priorities and choices because every research has different priorities. For a complex research study involving multiple methods, you may choose to have more than one research design.

Multimethodology or multimethod research includes using more than one data collection method or research in a research study or set of related studies.

If one research design is weak in one area, then another research design can cover that weakness. For instance, a  dissertation analyzing different situations or cases will have more than one research design.

For example:

• Experimental research involves experimental investigation and laboratory experience, but it does not accurately investigate the real world.
• Quantitative research is good for the  statistical part of the project, but it may not provide an in-depth understanding of the  topic .
• Also, correlational research will not provide experimental results because it is a technique that assesses the statistical relationship between two variables.

While scientific considerations are a fundamental aspect of the research design, It is equally important that the researcher think practically before deciding on its structure. Here are some questions that you should think of;

• Do you have enough time to gather data and complete the write-up?
• Will you be able to collect the necessary data by interviewing a specific person or visiting a specific location?
• Do you have in-depth knowledge about the  different statistical analysis and data collection techniques to address the research questions  or test the  hypothesis ?

If you think that the chosen research design cannot answer the research questions properly, you can refine your research questions to gain better insight.

Step 2: Data Type you Need for Research

Decide on the type of data you need for your research. The type of data you need to collect depends on your research questions or research hypothesis. Two types of research data can be used to answer the research questions:

Primary Data Vs. Secondary Data

Qualitative vs. quantitative data.

Also, see; Research methods, design, and analysis .

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• Hire an expert from ResearchProspect today!
• Statistical analysis, research methodology, discussion of the results or conclusion – our experts can help you no matter how complex the requirements are.

Step 3: Data Collection Techniques

Once you have selected the type of research to answer your research question, you need to decide where and how to collect the data.

It is time to determine your research method to address the  research problem . Research methods involve procedures, techniques, materials, and tools used for the study.

For instance, a dissertation research design includes the different resources and data collection techniques and helps establish your  dissertation’s structure .

The following table shows the characteristics of the most popularly employed research methods.

Research Methods

Step 4: Procedure of Data Analysis

Use of the  correct data and statistical analysis technique is necessary for the validity of your research. Therefore, you need to be certain about the data type that would best address the research problem. Choosing an appropriate analysis method is the final step for the research design. It can be split into two main categories;

Quantitative Data Analysis

The quantitative data analysis technique involves analyzing the numerical data with the help of different applications such as; SPSS, STATA, Excel, origin lab, etc.

This data analysis strategy tests different variables such as spectrum, frequencies, averages, and more. The research question and the hypothesis must be established to identify the variables for testing.

Qualitative Data Analysis

Qualitative data analysis of figures, themes, and words allows for flexibility and the researcher’s subjective opinions. This means that the researcher’s primary focus will be interpreting patterns, tendencies, and accounts and understanding the implications and social framework.

You should be clear about your research objectives before starting to analyze the data. For example, you should ask yourself whether you need to explain respondents’ experiences and insights or do you also need to evaluate their responses with reference to a certain social framework.

Step 5: Write your Research Proposal

The research design is an important component of a research proposal because it plans the project’s execution. You can share it with the supervisor, who would evaluate the feasibility and capacity of the results  and  conclusion .

Read our guidelines to write a research proposal  if you have already formulated your research design. The research proposal is written in the future tense because you are writing your proposal before conducting research.

The  research methodology  or research design, on the other hand, is generally written in the past tense.

How to Write a Research Design – Conclusion

A research design is the plan, structure, strategy of investigation conceived to answer the research question and test the hypothesis. The dissertation research design can be classified based on the type of data and the type of analysis.

Above mentioned five steps are the answer to how to write a research design. So, follow these steps to  formulate the perfect research design for your dissertation .

ResearchProspect writers have years of experience creating research designs that align with the dissertation’s aim and objectives. If you are struggling with your dissertation methodology chapter, you might want to look at our dissertation part-writing service.

Our dissertation writers can also help you with the full dissertation paper . No matter how urgent or complex your need may be, ResearchProspect can help. We also offer PhD level research paper writing services.

Frequently Asked Questions

What is research design.

Research design is a systematic plan that guides the research process, outlining the methodology and procedures for collecting and analysing data. It determines the structure of the study, ensuring the research question is answered effectively, reliably, and validly. It serves as the blueprint for the entire research project.

How to write a research design?

To write a research design, define your research question, identify the research method (qualitative, quantitative, or mixed), choose data collection techniques (e.g., surveys, interviews), determine the sample size and sampling method, outline data analysis procedures, and highlight potential limitations and ethical considerations for the study.

How to write the design section of a research paper?

In the design section of a research paper, describe the research methodology chosen and justify its selection. Outline the data collection methods, participants or samples, instruments used, and procedures followed. Detail any experimental controls, if applicable. Ensure clarity and precision to enable replication of the study by other researchers.

How to write a research design in methodology?

To write a research design in methodology, clearly outline the research strategy (e.g., experimental, survey, case study). Describe the sampling technique, participants, and data collection methods. Detail the procedures for data collection and analysis. Justify choices by linking them to research objectives, addressing reliability and validity.

You May Also Like

Repository of ten perfect research question examples will provide you a better perspective about how to create research questions.

Make sure that your selected topic is intriguing, manageable, and relevant. Here are some guidelines to help understand how to find a good dissertation topic.

How to write a hypothesis for dissertation,? A hypothesis is a statement that can be tested with the help of experimental or theoretical research.

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Types of Research Designs Compared | Examples

Published on 5 May 2022 by Shona McCombes . Revised on 10 October 2022.

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

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

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

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

Table of contents

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

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

Prevent plagiarism, run a free check.

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

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

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

Read more about creating a research design

Cite this Scribbr article

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

McCombes, S. (2022, October 10). Types of Research Designs Compared | Examples. Scribbr. Retrieved 14 May 2024, from https://www.scribbr.co.uk/research-methods/types-of-research-designs/

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Research Methodology Example

Detailed Walkthrough + Free Methodology Chapter Template

If you’re working on a dissertation or thesis and are looking for an example of a research methodology chapter , you’ve come to the right place.

In this video, we walk you through a research methodology from a dissertation that earned full distinction , step by step. We start off by discussing the core components of a research methodology by unpacking our free methodology chapter template . We then progress to the sample research methodology to show how these concepts are applied in an actual dissertation, thesis or research project.

If you’re currently working on your research methodology chapter, you may also find the following resources useful:

• Research methodology 101 : an introductory video discussing what a methodology is and the role it plays within a dissertation
• Research design 101 : an overview of the most common research designs for both qualitative and quantitative studies
• Variables 101 : an introductory video covering the different types of variables that exist within research.
• Sampling 101 : an overview of the main sampling methods
• Methodology tips : a video discussion covering various tips to help you write a high-quality methodology chapter
• Private coaching : Get hands-on help with your research methodology

PS – If you’re working on a dissertation, be sure to also check out our collection of dissertation and thesis examples here .

FAQ: Research Methodology Example

Research methodology example: frequently asked questions, is the sample research methodology real.

Yes. The chapter example is an extract from a Master’s-level dissertation for an MBA program. A few minor edits have been made to protect the privacy of the sponsoring organisation, but these have no material impact on the research methodology.

Can I replicate this methodology for my dissertation?

As we discuss in the video, every research methodology will be different, depending on the research aims, objectives and research questions. Therefore, you’ll need to tailor your literature review to suit your specific context.

You can learn more about the basics of writing a research methodology chapter here .

Where can I find more examples of research methodologies?

The best place to find more examples of methodology chapters would be within dissertation/thesis databases. These databases include dissertations, theses and research projects that have successfully passed the assessment criteria for the respective university, meaning that you have at least some sort of quality assurance.

The Open Access Thesis Database (OATD) is a good starting point.

How do I get the research methodology chapter template?

You can access our free methodology chapter template here .

Is the methodology template really free?

Yes. There is no cost for the template and you are free to use it as you wish.

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Home » Descriptive Research Design – Types, Methods and Examples

Descriptive Research Design – Types, Methods and Examples

Table of Contents

Descriptive Research Design

Definition:

Descriptive research design is a type of research methodology that aims to describe or document the characteristics, behaviors, attitudes, opinions, or perceptions of a group or population being studied.

Descriptive research design does not attempt to establish cause-and-effect relationships between variables or make predictions about future outcomes. Instead, it focuses on providing a detailed and accurate representation of the data collected, which can be useful for generating hypotheses, exploring trends, and identifying patterns in the data.

Types of Descriptive Research Design

Types of Descriptive Research Design are as follows:

Cross-sectional Study

This involves collecting data at a single point in time from a sample or population to describe their characteristics or behaviors. For example, a researcher may conduct a cross-sectional study to investigate the prevalence of certain health conditions among a population, or to describe the attitudes and beliefs of a particular group.

Longitudinal Study

This involves collecting data over an extended period of time, often through repeated observations or surveys of the same group or population. Longitudinal studies can be used to track changes in attitudes, behaviors, or outcomes over time, or to investigate the effects of interventions or treatments.

This involves an in-depth examination of a single individual, group, or situation to gain a detailed understanding of its characteristics or dynamics. Case studies are often used in psychology, sociology, and business to explore complex phenomena or to generate hypotheses for further research.

Survey Research

This involves collecting data from a sample or population through standardized questionnaires or interviews. Surveys can be used to describe attitudes, opinions, behaviors, or demographic characteristics of a group, and can be conducted in person, by phone, or online.

Observational Research

This involves observing and documenting the behavior or interactions of individuals or groups in a natural or controlled setting. Observational studies can be used to describe social, cultural, or environmental phenomena, or to investigate the effects of interventions or treatments.

Correlational Research

This involves examining the relationships between two or more variables to describe their patterns or associations. Correlational studies can be used to identify potential causal relationships or to explore the strength and direction of relationships between variables.

Data Analysis Methods

Descriptive research design data analysis methods depend on the type of data collected and the research question being addressed. Here are some common methods of data analysis for descriptive research:

Descriptive Statistics

This method involves analyzing data to summarize and describe the key features of a sample or population. Descriptive statistics can include measures of central tendency (e.g., mean, median, mode) and measures of variability (e.g., range, standard deviation).

Cross-tabulation

This method involves analyzing data by creating a table that shows the frequency of two or more variables together. Cross-tabulation can help identify patterns or relationships between variables.

Content Analysis

This method involves analyzing qualitative data (e.g., text, images, audio) to identify themes, patterns, or trends. Content analysis can be used to describe the characteristics of a sample or population, or to identify factors that influence attitudes or behaviors.

Qualitative Coding

This method involves analyzing qualitative data by assigning codes to segments of data based on their meaning or content. Qualitative coding can be used to identify common themes, patterns, or categories within the data.

Visualization

This method involves creating graphs or charts to represent data visually. Visualization can help identify patterns or relationships between variables and make it easier to communicate findings to others.

Comparative Analysis

This method involves comparing data across different groups or time periods to identify similarities and differences. Comparative analysis can help describe changes in attitudes or behaviors over time or differences between subgroups within a population.

Applications of Descriptive Research Design

Descriptive research design has numerous applications in various fields. Some of the common applications of descriptive research design are:

• Market research: Descriptive research design is widely used in market research to understand consumer preferences, behavior, and attitudes. This helps companies to develop new products and services, improve marketing strategies, and increase customer satisfaction.
• Health research: Descriptive research design is used in health research to describe the prevalence and distribution of a disease or health condition in a population. This helps healthcare providers to develop prevention and treatment strategies.
• Educational research: Descriptive research design is used in educational research to describe the performance of students, schools, or educational programs. This helps educators to improve teaching methods and develop effective educational programs.
• Social science research: Descriptive research design is used in social science research to describe social phenomena such as cultural norms, values, and beliefs. This helps researchers to understand social behavior and develop effective policies.
• Public opinion research: Descriptive research design is used in public opinion research to understand the opinions and attitudes of the general public on various issues. This helps policymakers to develop effective policies that are aligned with public opinion.
• Environmental research: Descriptive research design is used in environmental research to describe the environmental conditions of a particular region or ecosystem. This helps policymakers and environmentalists to develop effective conservation and preservation strategies.

Descriptive Research Design Examples

Here are some real-time examples of descriptive research designs:

• A restaurant chain wants to understand the demographics and attitudes of its customers. They conduct a survey asking customers about their age, gender, income, frequency of visits, favorite menu items, and overall satisfaction. The survey data is analyzed using descriptive statistics and cross-tabulation to describe the characteristics of their customer base.
• A medical researcher wants to describe the prevalence and risk factors of a particular disease in a population. They conduct a cross-sectional study in which they collect data from a sample of individuals using a standardized questionnaire. The data is analyzed using descriptive statistics and cross-tabulation to identify patterns in the prevalence and risk factors of the disease.
• An education researcher wants to describe the learning outcomes of students in a particular school district. They collect test scores from a representative sample of students in the district and use descriptive statistics to calculate the mean, median, and standard deviation of the scores. They also create visualizations such as histograms and box plots to show the distribution of scores.
• A marketing team wants to understand the attitudes and behaviors of consumers towards a new product. They conduct a series of focus groups and use qualitative coding to identify common themes and patterns in the data. They also create visualizations such as word clouds to show the most frequently mentioned topics.
• An environmental scientist wants to describe the biodiversity of a particular ecosystem. They conduct an observational study in which they collect data on the species and abundance of plants and animals in the ecosystem. The data is analyzed using descriptive statistics to describe the diversity and richness of the ecosystem.

How to Conduct Descriptive Research Design

To conduct a descriptive research design, you can follow these general steps:

• Define your research question: Clearly define the research question or problem that you want to address. Your research question should be specific and focused to guide your data collection and analysis.
• Choose your research method: Select the most appropriate research method for your research question. As discussed earlier, common research methods for descriptive research include surveys, case studies, observational studies, cross-sectional studies, and longitudinal studies.
• Design your study: Plan the details of your study, including the sampling strategy, data collection methods, and data analysis plan. Determine the sample size and sampling method, decide on the data collection tools (such as questionnaires, interviews, or observations), and outline your data analysis plan.
• Collect data: Collect data from your sample or population using the data collection tools you have chosen. Ensure that you follow ethical guidelines for research and obtain informed consent from participants.
• Analyze data: Use appropriate statistical or qualitative analysis methods to analyze your data. As discussed earlier, common data analysis methods for descriptive research include descriptive statistics, cross-tabulation, content analysis, qualitative coding, visualization, and comparative analysis.
• I nterpret results: Interpret your findings in light of your research question and objectives. Identify patterns, trends, and relationships in the data, and describe the characteristics of your sample or population.
• Draw conclusions and report results: Draw conclusions based on your analysis and interpretation of the data. Report your results in a clear and concise manner, using appropriate tables, graphs, or figures to present your findings. Ensure that your report follows accepted research standards and guidelines.

When to Use Descriptive Research Design

Descriptive research design is used in situations where the researcher wants to describe a population or phenomenon in detail. It is used to gather information about the current status or condition of a group or phenomenon without making any causal inferences. Descriptive research design is useful in the following situations:

• Exploratory research: Descriptive research design is often used in exploratory research to gain an initial understanding of a phenomenon or population.
• Identifying trends: Descriptive research design can be used to identify trends or patterns in a population, such as changes in consumer behavior or attitudes over time.
• Market research: Descriptive research design is commonly used in market research to understand consumer preferences, behavior, and attitudes.
• Health research: Descriptive research design is useful in health research to describe the prevalence and distribution of a disease or health condition in a population.
• Social science research: Descriptive research design is used in social science research to describe social phenomena such as cultural norms, values, and beliefs.
• Educational research: Descriptive research design is used in educational research to describe the performance of students, schools, or educational programs.

Purpose of Descriptive Research Design

The main purpose of descriptive research design is to describe and measure the characteristics of a population or phenomenon in a systematic and objective manner. It involves collecting data that describe the current status or condition of the population or phenomenon of interest, without manipulating or altering any variables.

The purpose of descriptive research design can be summarized as follows:

• To provide an accurate description of a population or phenomenon: Descriptive research design aims to provide a comprehensive and accurate description of a population or phenomenon of interest. This can help researchers to develop a better understanding of the characteristics of the population or phenomenon.
• To identify trends and patterns: Descriptive research design can help researchers to identify trends and patterns in the data, such as changes in behavior or attitudes over time. This can be useful for making predictions and developing strategies.
• To generate hypotheses: Descriptive research design can be used to generate hypotheses or research questions that can be tested in future studies. For example, if a descriptive study finds a correlation between two variables, this could lead to the development of a hypothesis about the causal relationship between the variables.
• To establish a baseline: Descriptive research design can establish a baseline or starting point for future research. This can be useful for comparing data from different time periods or populations.

Characteristics of Descriptive Research Design

Descriptive research design has several key characteristics that distinguish it from other research designs. Some of the main characteristics of descriptive research design are:

• Objective : Descriptive research design is objective in nature, which means that it focuses on collecting factual and accurate data without any personal bias. The researcher aims to report the data objectively without any personal interpretation.
• Non-experimental: Descriptive research design is non-experimental, which means that the researcher does not manipulate any variables. The researcher simply observes and records the behavior or characteristics of the population or phenomenon of interest.
• Quantitative : Descriptive research design is quantitative in nature, which means that it involves collecting numerical data that can be analyzed using statistical techniques. This helps to provide a more precise and accurate description of the population or phenomenon.
• Cross-sectional: Descriptive research design is often cross-sectional, which means that the data is collected at a single point in time. This can be useful for understanding the current state of the population or phenomenon, but it may not provide information about changes over time.
• Large sample size: Descriptive research design typically involves a large sample size, which helps to ensure that the data is representative of the population of interest. A large sample size also helps to increase the reliability and validity of the data.
• Systematic and structured: Descriptive research design involves a systematic and structured approach to data collection, which helps to ensure that the data is accurate and reliable. This involves using standardized procedures for data collection, such as surveys, questionnaires, or observation checklists.

Advantages of Descriptive Research Design

Descriptive research design has several advantages that make it a popular choice for researchers. Some of the main advantages of descriptive research design are:

• Provides an accurate description: Descriptive research design is focused on accurately describing the characteristics of a population or phenomenon. This can help researchers to develop a better understanding of the subject of interest.
• Easy to conduct: Descriptive research design is relatively easy to conduct and requires minimal resources compared to other research designs. It can be conducted quickly and efficiently, and data can be collected through surveys, questionnaires, or observations.
• Useful for generating hypotheses: Descriptive research design can be used to generate hypotheses or research questions that can be tested in future studies. For example, if a descriptive study finds a correlation between two variables, this could lead to the development of a hypothesis about the causal relationship between the variables.
• Large sample size : Descriptive research design typically involves a large sample size, which helps to ensure that the data is representative of the population of interest. A large sample size also helps to increase the reliability and validity of the data.
• Can be used to monitor changes : Descriptive research design can be used to monitor changes over time in a population or phenomenon. This can be useful for identifying trends and patterns, and for making predictions about future behavior or attitudes.
• Can be used in a variety of fields : Descriptive research design can be used in a variety of fields, including social sciences, healthcare, business, and education.

Limitation of Descriptive Research Design

Descriptive research design also has some limitations that researchers should consider before using this design. Some of the main limitations of descriptive research design are:

• Cannot establish cause and effect: Descriptive research design cannot establish cause and effect relationships between variables. It only provides a description of the characteristics of the population or phenomenon of interest.
• Limited generalizability: The results of a descriptive study may not be generalizable to other populations or situations. This is because descriptive research design often involves a specific sample or situation, which may not be representative of the broader population.
• Potential for bias: Descriptive research design can be subject to bias, particularly if the researcher is not objective in their data collection or interpretation. This can lead to inaccurate or incomplete descriptions of the population or phenomenon of interest.
• Limited depth: Descriptive research design may provide a superficial description of the population or phenomenon of interest. It does not delve into the underlying causes or mechanisms behind the observed behavior or characteristics.
• Limited utility for theory development: Descriptive research design may not be useful for developing theories about the relationship between variables. It only provides a description of the variables themselves.
• Relies on self-report data: Descriptive research design often relies on self-report data, such as surveys or questionnaires. This type of data may be subject to biases, such as social desirability bias or recall bias.

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What is Research Methodology? Definition, Types, and Examples

Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of the research. Several aspects must be considered before selecting an appropriate research methodology, such as research limitations and ethical concerns that may affect your research.

The research methodology section in a scientific paper describes the different methodological choices made, such as the data collection and analysis methods, and why these choices were selected. The reasons should explain why the methods chosen are the most appropriate to answer the research question. A good research methodology also helps ensure the reliability and validity of the research findings. There are three types of research methodology—quantitative, qualitative, and mixed-method, which can be chosen based on the research objectives.

What is research methodology ?

A research methodology describes the techniques and procedures used to identify and analyze information regarding a specific research topic. It is a process by which researchers design their study so that they can achieve their objectives using the selected research instruments. It includes all the important aspects of research, including research design, data collection methods, data analysis methods, and the overall framework within which the research is conducted. While these points can help you understand what is research methodology, you also need to know why it is important to pick the right methodology.

Why is research methodology important?

Having a good research methodology in place has the following advantages: 3

• Helps other researchers who may want to replicate your research; the explanations will be of benefit to them.
• You can easily answer any questions about your research if they arise at a later stage.
• A research methodology provides a framework and guidelines for researchers to clearly define research questions, hypotheses, and objectives.
• It helps researchers identify the most appropriate research design, sampling technique, and data collection and analysis methods.
• A sound research methodology helps researchers ensure that their findings are valid and reliable and free from biases and errors.
• It also helps ensure that ethical guidelines are followed while conducting research.
• A good research methodology helps researchers in planning their research efficiently, by ensuring optimum usage of their time and resources.

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Types of research methodology.

There are three types of research methodology based on the type of research and the data required. 1

• Quantitative research methodology focuses on measuring and testing numerical data. This approach is good for reaching a large number of people in a short amount of time. This type of research helps in testing the causal relationships between variables, making predictions, and generalizing results to wider populations.
• Qualitative research methodology examines the opinions, behaviors, and experiences of people. It collects and analyzes words and textual data. This research methodology requires fewer participants but is still more time consuming because the time spent per participant is quite large. This method is used in exploratory research where the research problem being investigated is not clearly defined.
• Mixed-method research methodology uses the characteristics of both quantitative and qualitative research methodologies in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method.

What are the types of sampling designs in research methodology?

Sampling 4 is an important part of a research methodology and involves selecting a representative sample of the population to conduct the study, making statistical inferences about them, and estimating the characteristics of the whole population based on these inferences. There are two types of sampling designs in research methodology—probability and nonprobability.

• Probability sampling

In this type of sampling design, a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are:

• Systematic —sample members are chosen at regular intervals. It requires selecting a starting point for the sample and sample size determination that can be repeated at regular intervals. This type of sampling method has a predefined range; hence, it is the least time consuming.
• Stratified —researchers divide the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized, and then a sample can be drawn from each group separately.
• Cluster —the population is divided into clusters based on demographic parameters like age, sex, location, etc.
• Convenience —selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.
• Purposive —participants are selected at the researcher’s discretion. Researchers consider the purpose of the study and the understanding of the target audience.
• Snowball —already selected participants use their social networks to refer the researcher to other potential participants.
• Quota —while designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.

What are data collection methods?

During research, data are collected using various methods depending on the research methodology being followed and the research methods being undertaken. Both qualitative and quantitative research have different data collection methods, as listed below.

Qualitative research 5

• One-on-one interviews: Helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event
• Document study/literature review/record keeping: Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.
• Focus groups: Constructive discussions that usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic.
• Qualitative observation : Researchers collect data using their five senses (sight, smell, touch, taste, and hearing).

Quantitative research 6

• Sampling: The most common type is probability sampling.
• Interviews: Commonly telephonic or done in-person.
• Observations: Structured observations are most commonly used in quantitative research. In this method, researchers make observations about specific behaviors of individuals in a structured setting.
• Document review: Reviewing existing research or documents to collect evidence for supporting the research.
• Surveys and questionnaires. Surveys can be administered both online and offline depending on the requirement and sample size.

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What are data analysis methods.

The data collected using the various methods for qualitative and quantitative research need to be analyzed to generate meaningful conclusions. These data analysis methods 7 also differ between quantitative and qualitative research.

Quantitative research involves a deductive method for data analysis where hypotheses are developed at the beginning of the research and precise measurement is required. The methods include statistical analysis applications to analyze numerical data and are grouped into two categories—descriptive and inferential.

Descriptive analysis is used to describe the basic features of different types of data to present it in a way that ensures the patterns become meaningful. The different types of descriptive analysis methods are:

• Measures of frequency (count, percent, frequency)
• Measures of central tendency (mean, median, mode)
• Measures of dispersion or variation (range, variance, standard deviation)
• Measure of position (percentile ranks, quartile ranks)

Inferential analysis is used to make predictions about a larger population based on the analysis of the data collected from a smaller population. This analysis is used to study the relationships between different variables. Some commonly used inferential data analysis methods are:

• Correlation: To understand the relationship between two or more variables.
• Cross-tabulation: Analyze the relationship between multiple variables.
• Regression analysis: Study the impact of independent variables on the dependent variable.
• Frequency tables: To understand the frequency of data.
• Analysis of variance: To test the degree to which two or more variables differ in an experiment.

Qualitative research involves an inductive method for data analysis where hypotheses are developed after data collection. The methods include:

• Content analysis: For analyzing documented information from text and images by determining the presence of certain words or concepts in texts.
• Narrative analysis: For analyzing content obtained from sources such as interviews, field observations, and surveys. The stories and opinions shared by people are used to answer research questions.
• Discourse analysis: For analyzing interactions with people considering the social context, that is, the lifestyle and environment, under which the interaction occurs.
• Grounded theory: Involves hypothesis creation by data collection and analysis to explain why a phenomenon occurred.
• Thematic analysis: To identify important themes or patterns in data and use these to address an issue.

How to choose a research methodology?

Here are some important factors to consider when choosing a research methodology: 8

• Research objectives, aims, and questions —these would help structure the research design.
• Review existing literature to identify any gaps in knowledge.
• Check the statistical requirements —if data-driven or statistical results are needed then quantitative research is the best. If the research questions can be answered based on people’s opinions and perceptions, then qualitative research is most suitable.
• Sample size —sample size can often determine the feasibility of a research methodology. For a large sample, less effort- and time-intensive methods are appropriate.
• Constraints —constraints of time, geography, and resources can help define the appropriate methodology.

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How to write a research methodology .

A research methodology should include the following components: 3,9

• Research design —should be selected based on the research question and the data required. Common research designs include experimental, quasi-experimental, correlational, descriptive, and exploratory.
• Research method —this can be quantitative, qualitative, or mixed-method.
• Reason for selecting a specific methodology —explain why this methodology is the most suitable to answer your research problem.
• Research instruments —explain the research instruments you plan to use, mainly referring to the data collection methods such as interviews, surveys, etc. Here as well, a reason should be mentioned for selecting the particular instrument.
• Sampling —this involves selecting a representative subset of the population being studied.
• Data collection —involves gathering data using several data collection methods, such as surveys, interviews, etc.
• Data analysis —describe the data analysis methods you will use once you’ve collected the data.
• Research limitations —mention any limitations you foresee while conducting your research.
• Validity and reliability —validity helps identify the accuracy and truthfulness of the findings; reliability refers to the consistency and stability of the results over time and across different conditions.
• Ethical considerations —research should be conducted ethically. The considerations include obtaining consent from participants, maintaining confidentiality, and addressing conflicts of interest.

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Frequently Asked Questions

Q1. What are the key components of research methodology?

A1. A good research methodology has the following key components:

• Research design
• Data collection procedures
• Data analysis methods
• Ethical considerations

Q2. Why is ethical consideration important in research methodology?

A2. Ethical consideration is important in research methodology to ensure the readers of the reliability and validity of the study. Researchers must clearly mention the ethical norms and standards followed during the conduct of the research and also mention if the research has been cleared by any institutional board. The following 10 points are the important principles related to ethical considerations: 10

• Participants should not be subjected to harm.
• Respect for the dignity of participants should be prioritized.
• Full consent should be obtained from participants before the study.
• Participants’ privacy should be ensured.
• Confidentiality of the research data should be ensured.
• Anonymity of individuals and organizations participating in the research should be maintained.
• The aims and objectives of the research should not be exaggerated.
• Affiliations, sources of funding, and any possible conflicts of interest should be declared.
• Communication in relation to the research should be honest and transparent.
• Misleading information and biased representation of primary data findings should be avoided.

Q3. What is the difference between methodology and method?

A3. Research methodology is different from a research method, although both terms are often confused. Research methods are the tools used to gather data, while the research methodology provides a framework for how research is planned, conducted, and analyzed. The latter guides researchers in making decisions about the most appropriate methods for their research. Research methods refer to the specific techniques, procedures, and tools used by researchers to collect, analyze, and interpret data, for instance surveys, questionnaires, interviews, etc.

Research methodology is, thus, an integral part of a research study. It helps ensure that you stay on track to meet your research objectives and answer your research questions using the most appropriate data collection and analysis tools based on your research design.

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• Research methodologies. Pfeiffer Library website. Accessed August 15, 2023. https://library.tiffin.edu/researchmethodologies/whatareresearchmethodologies
• Types of research methodology. Eduvoice website. Accessed August 16, 2023. https://eduvoice.in/types-research-methodology/
• The basics of research methodology: A key to quality research. Voxco. Accessed August 16, 2023. https://www.voxco.com/blog/what-is-research-methodology/
• Sampling methods: Types with examples. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/types-of-sampling-for-social-research/
• What is qualitative research? Methods, types, approaches, examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-qualitative-research-methods-types-examples/
• What is quantitative research? Definition, methods, types, and examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-quantitative-research-types-and-examples/
• Data analysis in research: Types & methods. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/data-analysis-in-research/#Data_analysis_in_qualitative_research
• Factors to consider while choosing the right research methodology. PhD Monster website. Accessed August 17, 2023. https://www.phdmonster.com/factors-to-consider-while-choosing-the-right-research-methodology/
• What is research methodology? Research and writing guides. Accessed August 14, 2023. https://paperpile.com/g/what-is-research-methodology/
• Ethical considerations. Business research methodology website. Accessed August 17, 2023. https://research-methodology.net/research-methodology/ethical-considerations/

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• Open access
• Published: 14 May 2024

Investigating young children’s physical activity through time and place

• T. Remmers 1 ,
• P. Koolwijk 2 ,
• I. Fassaert 1 , 8 ,
• J. Nolles 3 ,
• W. de Groot 3 ,
• S. B. Vos 1 , 4 ,
• S. I. de Vries 2 , 5 ,
• R. Mombarg 3 , 6 &
• D. H. H. Van Kann 1 , 7  

International Journal of Health Geographics volume  23 , Article number:  12 ( 2024 ) Cite this article

58 Accesses

Metrics details

Previous research indicates the start of primary school (4-5-year-old) as an essential period for the development of children’s physical activity (PA) patterns, as from this point, the age-related decline of PA is most often observed. During this period, young children are exposed to a wider variety of environmental- and social contexts and therefore their PA is influenced by more diverse factors. However, in order to understand children’s daily PA patterns and identify relevant opportunities for PA promotion, it is important to further unravel in which (social) contexts throughout the day, PA of young children takes place.

We included a cross-national sample of 21 primary schools from the Startvaardig study. In total, 248 children provided valid accelerometer and global positioning (GPS) data. Geospatial analyses were conducted to quantify PA in (social) environments based on their school and home. Transport-related PA was evaluated using GPS speed-algorithms. PA was analysed at different environments, time-periods and for week- and weekend days separately.

Children accumulated an average of 60 min of moderate-to-vigorous PA (MVPA), both during week- and weekend days. Schools contributed to approximately half of daily MVPA during weekdays. During weekends, environments within 100 m from home were important, as well as locations outside the home-school neighbourhood. Pedestrian trips contributed to almost half of the daily MVPA.

Conclusions

We identified several social contexts relevant for children’s daily MVPA. Schools have the potential to significantly contribute to young children’s PA patterns and are therefore encouraged to systematically evaluate and implement parts of the school-system that stimulate PA and potentially also learning processes. Pedestrian trips also have substantial contribution to daily MVPA of young children, which highlights the importance of daily active transport in school- and parental routines.

Early childhood (i.e. from birth until five years old) has recently become a prominent health-promotion target group as there is increased recognition that establishing health-supporting environments in early childhood can reduce subsequent population-level risk factors and disease [ 1 ]. Within these health-supporting environments, physical activity (PA) and sedentary behaviours contribute to the development of children’s physical-, psychosocial and cognitive abilities [ 2 , 3 , 4 ]. The consistency, quality and timing of these interconnected behaviours are formed in early childhood and the accompanied habits tend to track from childhood through adolescence [ 5 , 6 ].

In early childhood, the role of PA is of particular interest because through PA a child interacts with the surrounding environment and experiences the capabilities of its own body. By doing so, PA acts as an initiator of various learning processes [ 7 ]. In addition, sufficient- and appropriate variation of PA leads to the development of fundamental motor skills [ 8 ] which are important building blocks for more complex motor skills later in life [ 9 , 10 , 11 ]. Research suggests that PA and the development of motor skills may be more intertwined with cognitive development than previously assumed [ 12 , 13 , 14 ]. In addition, more PA in early childhood is associated with a broad range of favourable indicators relating to cardiometabolic-, skeletal- and morphological health [ 15 , 16 , 17 ]. In 2020, the WHO formulated specific international guidelines for early childhood [ 18 ]. For 3-4-year-old children, at least 180 daily minutes of PA (of which 60 min of moderate-to-vigorous intensity) and no more than 60 min of daily sedentary screen time are recommended [ 19 ]. Before five- to six years of age, children seem to be sufficiently active, especially at light intensity [ 20 , 21 ]. However, already around the age of 6 years, children’s PA levels decline while sedentary activities such as screen-related behaviours increase [ 21 ]. To understand the mechanism behind this age-related decline, it is vital to gain more insight in the daily PA patterns of young children [ 22 , 23 , 24 ].

Previous longitudinal studies showed that the onset of primary school is crucial in the development of healthy PA patterns of children, as notable increases in sedentary patterns were observed in this phase [ 25 , 26 ]. In primary school, children are exposed to a wider social- and physical environment (both in- and out of school), extending the potential of barriers and affordances for PA. Also, previous research showed that sedentary time predominantly increased during school hours, suggesting that in-school practices are probably responsible for decreasing PA [ 27 , 28 , 29 ]. Other studies have reported that variability between children’s PA was highest out of school [ 28 , 30 , 31 ]. This illustrates that the start of primary school is an interesting phase in which a complex and dynamic system of environmental factors have great influence of children’s emerging PA patterns [ 26 , 32 , 33 ]. In addition, the context in which PA occurs greatly influences the potential of these factors in influencing PA [ 34 ]. For example, children’s PA at school and PA at home are influenced by different environmental factors [ 34 ]. This means that in order to understand children’s PA patterns and how to effectively promote PA, more contextual information about the type of PA is essential [ 35 ]. However, investigating context-specific PA of young children is complex, because they predominantly perform PA in short sporadic bursts, sometimes without clear motives [ 36 ]. This makes the application of subjective assessment (e.g. parental recall) challenging and susceptible for social-desirability bias [ 37 , 38 ]. On the other hand, objective measurements (e.g. accelerometry) fail to capture essential contextual information (e.g. location) about the type of PA performed [ 16 ]. One way of overcoming these issues is by combined accelerometer and GPS methodology, which simultaneously combines information about PA and the geographic context [ 39 ]. Previous studies that have used this methodology in young children are scarce and have either focused on places for PA within childcare centers [ 40 ] or residential neighbourhoods separately [ 41 ]. Results showed that within childcare centers, larger open areas with portable equipment (e.g. balls, toys) were associated with children’s PA-hotspots [ 40 ] and that approximately 60% of the daily moderate-to-vigorous PA (MVPA) of 3-year-old Western-Australian children occurred < 500 m from their home, while 30% of daily MVPA occurred outside their neighbourhood (> 1600 m from their home) [ 41 ]. Although this provides valuable insights in where children’s PA takes place within the childcare and neighbourhood context, integrated information from both contexts is warranted to evaluate the degree to which each of these contexts contribute to children’s daily PA. Therefore, the purpose of this study was to investigate context-specific PA patterns of 4-6-year-old children (i.e. onset of primary school in the Netherlands) to improve our understanding of how to effectively promote these PA patterns.

Design and participants

In this cross-sectional study, a convenience sample of 21 primary schools in medium- to large scale cities of the Netherlands (i.e. 5 schools located in Eindhoven, 7 schools in the vicinity of The Hague, 9 schools in the vicinity of Groningen) were selected from the cross-national ‘Start Vaardig’ project (Dutch for ‘Skilful Start’). The three cities lie relatively close to each other (i.e. 370 km of driving distance to visit all three cities), with comparable climate during the period of measurement. Participating schools represented a wide variation of predominantly suburban areas in the north, middle, and south of the Netherlands (Fig.  1 ). In terms of PA- or transport related geography (e.g. percentage greenness, flat land, degree of urbanization) the suburban areas of the participating schools were comparable. The Dutch primary school system ranges from grade 1 (for 4-year-old children) till grade 8 (for 12-year-old children), and in our study children from grades 1 and 2 were eligible for participation. Schools provided detailed information about schedules and break times.

Geographical distribution of participating schools

All participating schools were visited four times by a team of two trained researchers. At the first visit, children and teachers were informed about the project and shown how to wear the accelerometer (Actigraph GT3X+, Pensacola, FL, USA) and GPS devices (Qstarz BT1000XT, Tapei, Taiwan). Children were provided with a written information letter and informed consent form. Parents were given the possibility to sign and return the written informed consent form to their child’s teacher or to sign online. Teachers were provided with additional written instruction about the purpose of the project and how to collect the informed consent forms. At the second visit, consent forms were collected, and reminders were handed out to the children. At the third visit, children received the devices with verbal instruction and parents were provided with written instructions. We instructed children to wear the devices at the right hip using an elastic belt during waking hours, for six consecutive days (containing two weekend days). We instructed to only remove the devices during sleep or water-related activities (e.g. swimming, showering) and to recharge the GPS logger every day just before going to bed. Additionally, parents of all participating children received a paper questionnaire, as well as an online version of the questionnaire. At the fourth and last visit, devices were returned, and paper questionnaires were collected.

Data collection took place between the 26th of May and the 15th of July 2021, in-between restrictions caused by the COVID-19 pandemic. Daily average temperature was 18.1 degrees Celsius (SD = 3.1) with average precipitation of 3.7 mm per day (69% of days with < 1 mm). Sunset times during this period were between 21:38 and 21:48 h ( www.timeanddate.com ). Ethical approval was obtained by the Ethical Research Committee of the VU Medical Centre in Amsterdam, the Netherlands (VCWE-2020-137).

Measurements

Parents provided socio-demographic information in the questionnaire, such as their child’s date of birth and gender, postal code and number of spouses. In addition, questions were asked about the frequency and reason that the accelerometer- and GPS devices were taken off (e.g. swimming, showering, discomfort) as well as the days on which their child did not sleep at home during the night.

Numerous studies have supported validity and accuracy of the accelerometer and GPS devices [ 42 , 43 , 44 , 45 ]. We used the manufacturer’s software to initialize devices and export data to CSV-files, for the accelerometer (Actilife version 6.13.4) and GPS logger (QTravel version 1.54) separately. Devices were set to record data every 10 s epochs. GPS loggers were initialized to record data between 6 AM and 10 PM to optimize battery life and storage capacity and to stop logging when storage capacity was full. We processed accelerometer data using R-package GGIR (version 3.0–1) [ 46 ], which included algorithms regarding autocalibration of accelerometers [ 47 ] and standard weartime detection algorithms. Namely, non-wear time was investigated per 15-minute time blocks, while the definition of non-wear time was based on the standard deviation (i.e. <13 milli gravity (mg)) and range (i.e. <50 mg) of the 60-minute time window that centered each 15-minute time block. Intensity-classification of PA was based on the vertical-axis classification of Evenson et al. (2008) [ 48 ] and were adjusted for the 10 s epoch by linear interpolation. We processed combined GPS and accelerometer output using the HABITUS (hbGPS) software [ 49 , 50 ], inspired by functionality from the earlier PALMS system [ 44 , 51 ]. GPS data was cleaned by removing outliers based on (1) missing values in speed estimates, (2) speed greater than 130 km/h with a speed-difference > 30 km/h, and (3) elevation change between successive values > 1000 m [ 50 ]. Trips were identified by a consistent speed of at least 1 kmph for any sequence of three successive datapoints (i.e. 30 s). We furthermore identified trip pause points with insufficient speed (see sentence above) for a maximum of 2 min. When the pause time exceeded 2 min, we classified this as a trip end point. Alternatively, we treated this as one common trip. We subsequently removed trips with (1) distance < 100 m, (2) duration < 60 s, (3) no available GPS data (time gaps) of > 30 s between each datapoint and the preceding datapoint. GPS data were exported as latitude, longitude, and trip-characteristics. Finally, accelerometer- and GPS data were matched based on timestamp of the accelerometer. Trip mode was based on the 90th percentile speed-thresholds of 1, 10- and 35 kmph for walking, cycling and vehicle respectively [ 52 ].

Data analyses

In total, 358 parents (26.2% from total potential sample) provided written informed consent for their child to participate in combined accelerometer and GPS measurements. After accounting for participant refusal and device malfunctioning, our sample of analysis consisted of 311 4-6-year-old children (84.5% from the sample of parents with informed consent, see Fig.  2 ). Next, a total of 281 parents filled in the questionnaire at the start of the study and 248 children provided valid combined accelerometer- and GPS data (i.e. sensor-data), defined as weekdays with 8 h- and weekend days with 6 h of combined accelerometer and GPS data. We defined these criteria because during weekend days, we observed less weartime due to a delayed start of weartime in the morning. From the 281 children with questionnaire-data, 85 children had insufficient sensor-data. From the 248 children with valid sensor-data, questionnaire-data were missing for 52 children. Consequently, for 196 children we had both valid sensor-data and questionnaire-data. Slight differences between the drop-out percentage between the cities were caused by the fact that in Eindhoven, accelerometers were handed out to the classroom teacher for individual children from parents that provided informed consent but were absent during the day of measurement (e.g. often due to COVID-19 restrictions). This led to an increased number of participants not meeting the 3-day valid data criteria, whereas in Groningen and The Hague, these children were considered missing a-priori and not treated as drop-out.

We imported combined accelerometer and GPS datasets for each school into ArcGIS Pro version 3.1.0 (ESRI, Redlands, CA, USA) for additional geospatial analyses. We geocoded the location of schools based on the school’s registry and extracted polygons of the school building and surrounding parcel. For the residential location of children, parents provided their six-digit postal code (i.e. identifies street-level area of 15- to 20 addresses without house number). In addition, we extracted the average centroid point of GPS data on week- and weekend days between 6- and 8 AM, during days that the child slept at home. These locations were validated by calculating Euclidean distances between the centroid point and the six-digit postal codes that parents provided in the questionnaire (median distance was 52.2 m for weekdays and 54.1 for weekend days). Next, for each datapoint, we calculated Euclidean- (i.e. < 10 m) and network distances (i.e. remaining distance categories) between children’s home and school. To investigate distances of children’s datapoints based on the combined home-school environment (not based on home and school separately), we integrated these distance-categories from both home and school (see Fig.  3 ). In addition, based on the Dutch national registry of large-scale topography (i.e. BGT), polygons identified as parks, sports terrains and public playgrounds were extracted and we subsequently performed ‘spatial join’ analyses to identify the datapoints that were within 10-meters from these parks, sports terrains, or playground parcels.

Example of distance-categories integrating both home and school locations

Parents indicated that children were awake for an average of 12 h per day and that water activities such as swimming were the primary reason for non-weartime during waking hours, while 11 parents (8.0%) reported their child experiencing discomfort when wearing the devices. Finally, only data points containing both valid accelerometer- and GPS data were retained, which resulted in a final sample of 248 children (1017 days of measurement; with 762 weekdays and 255 weekend days). We used days as the unit of analysis as this allows variation between days within children. We presented PA as minutes and percentage in light (LPA) and moderate-to-vigorous (MVPA) intensities.

Slightly more boys (54.3%) than girls participated in the study. The mean age of children was 5.56-year-old (SD = 0.75). Almost all children had either one- (57.8%) or two or more siblings (34.5%), and 61 children (40.0%) had at least one older sibling. Parents reported that 82.3% of the children slept home for all days during measurement. In total, 49.8% reported that the child had visited afterschool childcare at school for at least one day during measurement and 15.7% had visited afterschool childcare outside the school’s parcel (e.g. childcare at other location or other organization). Regarding the use of bicycles, 45.2% indicated that their child was able to cycle without supervision. In terms of organized sports, 55.6% of the children was a member of a sports club, while 30.6%- and 49.5% participated in organized sports and swimming lessons during the measurement period, respectively (see Table  1 ).

School start times were 8.30 am (19 schools) and 8.40 am (2 schools), while school bell times ranged from 2.00 pm to 3.15 pm. In total, 15 schools used a shortened schedule on Wednesdays (i.e. bell times ranging from 12.00 am to 12.35 pm) and 5 schools used a shortened schedule on Fridays (i.e. bell times ranging from 12.00 am to 12.30 pm). All schools provided breaks at the school parcel, so children were not allowed to leave school before school bell time. On average children lived at 2.76 km (SD = 0.33 km) pedestrian network-distance from their school (median = 604 m). Alternatively, when categorized in distance-categories, 30.8% lived within 400 m, 29.1% lived between 400- and 800 m (i.e., approximately 8 min walking time) and 40.1% lived more than 800 m from their school.

When looking at the temporal distribution of PA, average daily weartime of combined sensor-data was 713.26 min (SD = 116.07) during weekdays and 670.34 min (SD = 117.38) during weekend days, while children performed an average of 63.00 min (8.9%) and 65.37 min (9.8%) of MVPA during week- and weekend days, respectively. On weekdays, children spent an average of 294.88 min (SD = 78.90) in the temporal school-schedule, which makes the average distribution of time during weekdays approximately 50% for combined before- and in school and 50% for afterschool till sleep (data not shown). Within weekdays, schooltime contributed to almost half of the daily MVPA (i.e. 29 min), while after school time periods approximately contributed to the other half (Fig.  4 ). The minutes of MVPA after school, as well as its relative percentage, gradually declined during the day. During weekends, the absolute and relative contribution of MVPA slightly increased across the day, with the most active part in the early afternoon. After 16:00 h, intensity of MVPA dropped to 7.2% on average.

Temporal distribution of mean daily minutes of MVPA in week- and weekend days

When looking at the geographical distribution of PA during weekdays, percentages of LPA and MVPA were about twice as high at school versus at home (Table  2 ). At school, children spent on average 21.99 min in MVPA, which is 10.7% from the total daily weartime at school. Very little time was spent in the overlapping home-school neighbourhood and in the home neighbourhood outside the school neighbourhood. During weekdays, the vast majority of weartime was spent at- or close to home and school parcels. Children reported most daily minutes of MVPA at their school-parcel (i.e. approximately 22 min). Another 5.8 min of MVPA occurred within 100 m from their school, summing up to approximately 28 min. Also, compared to all other environments, the absolute- and relative contribution of LPA was highest at school, meaning that children were least sedentary at- and around their school (data not shown). At home, absolute- and relative contributions of LPA, as well as MVPA, were lower. Children spent more LPA and MVPA outside their home (but within 100 m from home) compared to their direct home location. In addition, children spent on average 70 min outside the home-school neighbourhood, with a relatively high amount of 7.5 min in MVPA (i.e. 10.6% of time spent outside home-school neighbourhood). Obviously, during weekend days the influence of school on PA disappeared, but this resulted in higher absolute- and slightly higher relative contribution of the home location in children’s LPA and MVPA (Table  2 ). Children spent especially more time at the ‘close to home’ location, resulting in approximately 23 min of MVPA. The percentage of MVPA that occurred at home remained relatively stable (i.e. 4.5% during weekdays versus 5.8% during weekend days). During weekends children also spent more time outside the home-school neighbourhood, while the percentage MVPA remained stable compared to weekdays. This resulted in another 23 min of MVPA performed outside the home-school neighbourhood (i.e. 12.0% of time spent at this location).

Transport-related pedestrian trips were responsible for approximately 45% (i.e. 26 min) and 38% (i.e. 22 min) of children’s average daily MVPA during weekdays and weekend days respectively (Table  3 ). Higher daily mean minutes of pedestrian trips were found during weekdays compared to weekends. During weekdays, additional analyses revealed that slightly more minutes of daily pedestrian trips were observed during in-school time zones (82.25, SD = 80.22 min) compared to afterschool time zones (66.29, SD = 61.36 min). The influence of bicycle- and motorized trips to MVPA was substantially lower. In general, this also means that approximately 30 min of MVPA during weekdays- and 34 min during weekend days was spent relatively stationary (i.e. not identified by GPS-based algorithm as a transport trip). The percentage MVPA was higher in pedestrian trips compared to stationary activities (e.g. 12.3% versus 6.8%, respectively).

Public open spaces equipped for PA (i.e. parks, sports terrains, and playgrounds) played a minor role in young children’s daily PA patterns. Although playgrounds showed a relatively high percentage of time spent in MVPA, absolute time spent at playgrounds was relatively low (2.8 and 5.1 daily minutes during week- and weekend days, respectively).

This study demonstrated context-specific PA patterns of young children by investigating their PA through space and time. More specifically, we showed that at the onset of primary school, half of children’s daily amount of MVPA during weekdays occurred at school or within 100 m from school, while the other half was divided between home or within 100 m from home and environments outside children’s home-school neighbourhood. During weekend days, from the daily amount of MVPA (i.e., approximately 65 min), slightly over half was performed at home or within 100 m from home. Only a marginal part of total daily MVPA occurred outside the home-school neighbourhood. These findings are in line with the study of Bai and colleagues, who showed that about 60% of 3-year-old children’s daily weekday MVPA of approximately 76 min occurred within 500 m from their home [ 41 ]. Furthermore, this shows that although the school-context was responsible for over 50% of MVPA during weekdays, these children seem to be able to reallocate this with PA around home and outside the home-school neighbourhood during weekend days. This is not in line with the Structured Days Hypothesis [ 53 ], stating that the presence of structure and routine of pre-scheduled activities (e.g. physical education, active travel, limited screen time) may positively influence children’s PA. Future studies are encouraged to further unravel within-person mechanisms (both between-day and within-day) in order to tailor future PA interventions [ 54 , 55 ].

Our study demonstrated the importance of pedestrian-trips in daily MVPA of young children. Urban planners, school boards, policy-makers and health scientists are encouraged to co-develop initiatives that persuade parents and children to use active mobility instead of passive forms while exploiting the potential of supportive social- and physical environments [ 56 ]. Sensitivity analyses revealed that during weekdays most of time spent in pedestrian trips were during school time. However, we also showed that in our sample, cycling played a minor role in daily MVPA, which is in contrast with studies in older Dutch children [ 57 ] showing that cycling being one of the major contributors to daily PA in Dutch children [ 58 ]. This is in accordance with the long history of normalization of daily cycling mobility in the Netherlands [ 59 , 60 ]. Children usually learn to cycle around the age of 5–7 years [ 61 ]. According to our questionnaire-data, parents reported that most of the children in our study was technically already able to ride a bike with- (32%) or without supervision (45%), but 98.5% reported supervision of parents- or siblings in home-school trips. An alternative explanation for this finding may be the use of the uniaxial signal of our hip-worn accelerometer in our study, as this underestimates PA during cycling [ 62 ]. Future studies, especially in older populations, are encouraged to improve measurement of cycling (e.g. using alternative placement, tri-axial signals, or multiple measurements). In addition, future studies may continue to distinguish between transport trips and relative stationary PA (i.e. not identified as a trip), potentially also leading to associations with motor development of young children.

The present study contributed to the understanding of how children’s integrated school- and home environments contribute to their daily PA, in both week- and weekend days. Previous studies have investigated PA from either one of these environments [ 63 , 64 ], but to our knowledge, this is the first study that applied this combination of contexts. In particular, this study showed that especially during weekends, a considerable proportion of MVPA was performed > 800 m from both home- and school locations. This is again in line with preschool-data from Bai and colleagues, who showed that almost 30% of daily MVPA occurred at residential locations outside children’s neighbourhoods [ 41 ]. Our data showed that young children’s daily exposure during both week- and weekend days in parks, sports terrains, and playgrounds was very low but the percentage of MVPA at these locations was relatively high. This may require specific interventions focusing on increasing young children’s exposure at these environments, potentially as a multi-component involving both the home/family- and the school setting [ 65 ]. In addition, based on the same findings regarding the low daily minutes of PA that occurred in parks, sports terrains, and playgrounds, it seems unlikely that MVPA outside home-school neighbourhood would relate to these specific locations. Furthermore, it seems also unlikely that afterschool childcare or care by grandparents outside the neighbourhood may be responsible for this, since our questionnaire-data showed that only 15% of the parents reported a visit to non-school childcare for at least one day during measurement. Another suggestion may be that these children often participated in pre-arranged play sessions at a friend’s house outside their own neighbourhood or more informal play-spaces around their residential neighbourhood, but future research should provide additional insight in this type of affordance [ 41 ].

One of the strengths of this study is the inclusion of multiple study-sites surrounding three cities in the Netherlands, which allowed us to study children’s PA patterns in diverse settings, increasing the variability in environmental exposure [ 34 ]. In addition, the use of the combined accelerometer GPS methodology allowed us to objectively monitor context-specific PA patterns throughout multiple days, minimizing potential recall bias. The additional use of geospatial analyses yielded further understanding of where young children are active. Although efforts were made to include a diverse and representative sample of young children by recruiting schools from multiple Dutch cities and the fact that daily PA of our sample was relatively comparable to international literature, it still may be that wearing accelerometer- and GPS devices was most interesting for active children or parents that perceive their child as relatively active. Future technological advancements such as smaller wrist-worn devices may have potential to be suitable and interesting for all children. Another potential weakness of this study was the use of a descriptive approach that elaborated on mean daily patterns for all children in multiple contexts, while future studies may implement a more evaluative approach to investigate differences between subgroups of children or evaluate determinants of specific behaviours (e.g. active transport to- and from school) or environments. For example, the relative contribution of school times to children’s daily PA may vary between types of children and environments where they live, allowing increased tailoring of PA intervention to the target group. We showed that MVPA at- and around children’s home was low. As previous research indicated that there is a lack of knowledge about facilitators and barriers in the home-based family environment (e.g. related to practices of both active and sedentary behaviours) [ 66 ] Previous studies showed that parents act as key gatekeepers for children’s spatial freedom [ 67 , 68 ], while this study demonstrated the importance of the environment within 100 m from home. Hence, it seems essential to get a better understanding of how parental rearing-constructs such as perception of traffic safety or ‘stranger danger’, but also social- and environmental factors influence parent-practices regarding independent mobility and, in turn, influences children’s PA [ 69 ]. Indications from our questionnaire data show that approximately 50% of the parents allowed their child to independently play in their neighbourhood, while 27% allowed their child to independently travel to visit family or friends. Supervision of siblings or peers increased the percentages above to approximately 68% and 42%, respectively. Future studies are encouraged to progress this field by combining data from parents (e.g. child-rearing constructs) and objective PA- and location data from children, with specific interest for home and school environments.

Our sample of 5.5-year-old children reported approximately 29 min of weekday MVPA during schooltime. Conversely, a previous review suggested that in older children, less than a quarter reached 30 min schooltime MVPA and that adolescents even reported lower levels [ 70 ]. Additionally, a previous study showed that in a sample of 7-11-year-old children with relatively low motor competence, school was the least active time period of their day. compared to before- and after school [ 71 ]. In turn, recent research showed that longer-term integration of PA in curricula, such as active breaks and physically active learning, fosters important pre-requisites of academic learning (e.g. time on task) [ 72 , 73 ]. Therefore, schools are well-suited for addressing important PA-related health inequalities of young children [ 74 ] and are therefore encouraged to implement evidence-based policies and to systematically evaluate which parts of the school-system hamper and stimulate their pupil’s PA as well as academic performance.

Overall, our study demonstrated the importance of schools in supporting PA of young children during weekdays. During weekends, the environment within 100 m from young children’s home was important, as well as locations outside the home-school neighbourhood. During- week and weekend days, walking contributed to almost half of the daily MVPA, emphasizing the importance of active school transportation- but also habitual daily walking and cycling (during week- and weekend days) for sustainable and PA promotion in children.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

Dutch Organization for Scientific Research

Physical Activity

Moderate-to-vigorous Physical Activity

Global Positioning System

Geographic Information System

Personal Activity Location Measurement System

Human Activity Behavior Identification Tool and data Unification System

Software R-package to process raw accelerometer data

Standard Deviation

Mistry KB, Minkovitz CS, Riley AW, Johnson SB, Grason HA, Dubay LC, et al. A new framework for childhood health promotion: the role of policies and programs in building capacity and foundations of early childhood health. Am J Public Health. 2012;102(9):1688–96.

Article   PubMed   PubMed Central   Google Scholar  

Wilhite K, Booker B, Huang B-H, Antczak D, Corbett L, Parker P, et al. Combinations of physical activity, sedentary behavior, and Sleep Duration and their associations with Physical, Psychological, and Educational outcomes in Children and adolescents: a systematic review. Am J Epidemiol. 2023;192(4):665–79.

Article   PubMed   Google Scholar  

Pang JC, Chan EL, Lau H, Reeves KK, Chung TH, Hui HW, et al. The impacts of physical activity on psychological and behavioral problems, and changes in physical activity, sleep and quality of life during the COVID-19 pandemic in preschoolers, children, and adolescents: a systematic review and meta-analysis. Front Pead. 2023;11:1015943.

Article   Google Scholar  

Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020;54(24):1451–62.

Telama R, Yang X, Leskinen E, Kankaanpää A, Hirvensalo M, Tammelin T, et al. Tracking of physical activity from early childhood through youth into adulthood. Med Sci Sports Exerc. 2014;46(5):955–62.

Biddle SJ, Pearson N, Ross GM, Braithwaite R. Tracking of sedentary behaviours of young people: a systematic review. Prev Med. 2010;51(5):345–51.

Erickson KI, Hillman C, Stillman CM, Ballard RM, Bloodgood B, Conroy DE, et al. Physical activity, cognition, and brain outcomes: a review of the 2018 physical activity guidelines. Med Sci Sports Exerc. 2019;51(6):1242.

Zeng N, Ayyub M, Sun H, Wen X, Xiang P, Gao Z. Effects of physical activity on motor skills and cognitive development in early childhood: a systematic review. BioMed research international. 2017;2017.

Clark JE, Metcalfe JS. The mountain of motor development: a metaphor. Motor Development: Res Reviews. 2002;2(163–190):183–202.

Google Scholar  

Barnett LM, Webster EK, Hulteen RM, De Meester A, Valentini NC, Lenoir M et al. Through the looking glass: a systematic review of longitudinal evidence, providing new insight for motor competence and health. Sports Med. 2021:1–46.

Lopes L, Santos R, Coelho-e-Silva M, Draper C, Mota J, Jidovtseff B, et al. A narrative review of motor competence in children and adolescents: what we know and what we need to find out. Int J Environ Res Public Health. 2021;18(1):18.

Diamond A. Close interrelation of motor development and cognitive development and of the cerebellum and prefrontal cortex. Child Dev. 2000;71(1):44–56.

Article   CAS   PubMed   Google Scholar  

Veldman SL, Santos R, Jones RA, Sousa-Sá E, Okely AD. Associations between gross motor skills and cognitive development in toddlers. Early Hum Dev. 2019;132:39–44.

Carson V, Hunter S, Kuzik N, Wiebe SA, Spence JC, Friedman A, et al. Systematic review of physical activity and cognitive development in early childhood. J Sci Med Sport. 2016;19(7):573–8.

Carson V, Lee E-Y, Hewitt L, Jennings C, Hunter S, Kuzik N, et al. Systematic review of the relationships between physical activity and health indicators in the early years (0–4 years). BMC Public Health. 2017;17(5):33–63.

Hinkley T, Teychenne M, Downing KL, Ball K, Salmon J, Hesketh KD. Early childhood physical activity, sedentary behaviors and psychosocial well-being: a systematic review. Prev Med. 2014;62:182–92.

Wiersma R, Haverkamp BF, van Beek JH, Riemersma AM, Boezen HM, Smidt N, et al. Unravelling the association between accelerometer-derived physical activity and adiposity among preschool children: a systematic review and meta‐analyses. Obes Rev. 2020;21(2):e12936.

Willumsen J, Bull F. Development of WHO guidelines on physical activity, sedentary behavior, and sleep for children less than 5 years of age. J Phys Activity Health. 2020;17(1):96–100.

Guidelines on physical. Activity, sedentary behaviour and sleep for children under 5 years of age. World Health Organization; 2019.

Bruijns BA, Truelove S, Johnson AM, Gilliland J, Tucker P. Infants’ and toddlers’ physical activity and sedentary time as measured by accelerometry: a systematic review and meta-analysis. Int J Behav Nutr Phys Activity. 2020;17:1–14.

Steene-Johannessen J, Hansen BH, Dalene KE, Kolle E, Northstone K, Møller NC, et al. Variations in accelerometry measured physical activity and sedentary time across Europe–harmonized analyses of 47,497 children and adolescents. Int J Behav Nutr Phys Activity. 2020;17(1):1–14.

Aubert S, Brazo-Sayavera J, González SA, Janssen I, Manyanga T, Oyeyemi AL, et al. Global prevalence of physical activity for children and adolescents; inconsistencies, research gaps, and recommendations: a narrative review. Int J Behav Nutr Phys Activity. 2021;18(1):1–11.

Cooper AR, Goodman A, Page AS, Sherar LB, Esliger DW, van Sluijs EM, et al. Objectively measured physical activity and sedentary time in youth: the international children’s accelerometry database (ICAD). Int J Behav Nutr Phys Activity. 2015;12(1):1–10.

Reilly JJ. When does it all go wrong? Longitudinal studies of changes in moderate-to-vigorous-intensity physical activity across childhood and adolescence. J Exerc Sci Fit. 2016;14(1):1–6.

Azevedo LB, van Sluijs EM, Moore HJ, Hesketh K. Determinants of change in accelerometer-assessed sedentary behaviour in children 0 to 6 years of age: a systematic review. Obes Rev. 2019;20(10):1441–64.

Gropper H, John JM, Sudeck G, Thiel A. The impact of life events and transitions on physical activity: a scoping review. PLoS ONE. 2020;15(6):e0234794.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Carson V, Salmon J, Crawford D, Hinkley T, Hesketh KD. Longitudinal levels and bouts of objectively measured sedentary time among young Australian children in the HAPPY study. J Sci Med Sport. 2016;19(3):232–6.

Cox M, Schofield G, Greasley N, Kolt GS. Pedometer steps in primary school-aged children: a comparison of school-based and out-of-school activity. J Sci Med Sport. 2006;9(1):91–7.

Sigmund E, Sigmundová D, El Ansari W. Changes in physical activity in pre-schoolers and first-grade children: Longitudinal study in the Czech Republic. Child: care, health and development. 2009;35:376 – 82.

Arundell L, Ridgers ND, Veitch J, Salmon J, Hinkley T, Timperio A. 5-year changes in afterschool physical activity and sedentary behavior. Am J Prev Med. 2013;44(6):605–11.

Vincent SD, Pangrazi RP. An examination of the activity patterns of elementary school children. Pediatr Exerc Sci. 2002;14(4):432–41.

Spence JC, Lee RE. Toward a comprehensive model of physical activity. Psychol Sport Exerc. 2003;4(1):7–24.

Downing KL, Hinkley T, Timperio A, Salmon J, Carver A, Cliff DP, et al. Volume and accumulation patterns of physical activity and sedentary time: longitudinal changes and tracking from early to late childhood. Int J Behav Nutr Phys Activity. 2021;18:1–11.

Giles-Corti B, Timperio A, Bull F, Pikora T. Understanding physical activity environmental correlates: increased specificity for ecological models. Exerc Sport Sci Rev. 2005;33(4):175–81.

Terrón-Pérez M, Molina-García J, Martínez-Bello VE, Queralt A. Relationship between the physical environment and physical activity levels in preschool children: a systematic review. Curr Environ Health Rep. 2021;8(2):177–95.

Cliff DP, Reilly JJ, Okely AD. Methodological considerations in using accelerometers to assess habitual physical activity in children aged 0–5 years. J Sci Med Sport. 2009;12(5):557–67.

Oliver M, Schofield GM, Kolt GS. Physical activity in preschoolers: understanding prevalence and measurement issues. Sports Med. 2007;37:1045–70.

Helmerhorst HHJ, Brage S, Warren J, Besson H, Ekelund U. A systematic review of reliability and objective criterion-related validity of physical activity questionnaires. Int J Behav Nutr Phys Activity. 2012;9(1):1–55.

Klinker CD, Schipperijn J, Kerr J, Ersbøll AK, Troelsen J. Context-specific outdoor time and physical activity among school-children across gender and age: using accelerometers and GPS to advance methods. Front Public Health. 2014;2:20.

Bai P, Schipperijn J, Rosenberg M, Christian H. Where are preschoolers active in childcare centers? A hot-spot analysis using GIS, GPS and accelerometry data. Children’s Geographies. 2023;21(4):660–76.

Bai P, Schipperijn J, Rosenberg M, Christian H. Neighborhood places for Preschool Children’s physical activity: a mixed-methods study using global Positioning System, Geographic Information Systems, and Accelerometry Data. J Phys Activity Health. 2023;1:1–11.

Vorlíček M, Stewart T, Schipperijn J, Burian J, Rubín L, Dygrýn J, et al. Smart Watch Versus Classic receivers: static validity of three GPS devices in different types of built environments. Sensors. 2021;21(21):7232.

Kerr J, Duncan S, Schipperjin J. Using global positioning systems in health research: a practical approach to data collection and processing. Am J Prev Med. 2011;41(5):532–40.

Jankowska MM, Schipperijn J, Kerr J. A framework for using GPS data in physical activity and sedentary behavior studies. Exerc Sport Sci Rev. 2015;43(1):48.

Duncan S, Stewart TI, Oliver M, Mavoa S, MacRae D, Badland HM, et al. Portable global positioning system receivers: static validity and environmental conditions. Am J Prev Med. 2013;44(2):e19–29.

Migueles JH, Rowlands AV, Huber F, Sabia S, van Hees VT. GGIR: a research community–driven open source R package for generating physical activity and sleep outcomes from multi-day raw accelerometer data. J Meas Phys Behav. 2019;2(3):188–96.

Van Hees VT, Fang Z, Langford J, Assah F, Mohammad A, Da Silva IC, et al. Autocalibration of accelerometer data for free-living physical activity assessment using local gravity and temperature: an evaluation on four continents. J Appl Physiol. 2014;117(7):738–44.

Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG. Calibration of two objective measures of physical activity for children. J Sports Sci. 2008;26(14):1557–65.

Denmark UoS. Human activity behavior identifi- cation Tool and Data Unification System. Odense, Denmark: University of Southern Denmark; 2019.

van Hees VT. Description of R package hbGPS [internet] 2024 [ https://github.com/habitus-eu/hbGPS/blob/main/documentation.md .

Patrick K, Kerr J, Norman G, Ryan S, Sallis J, Krueger I, et al. Geospatial measurement & analysis of physical activity: physical activity location measurement system (PALMS). Epidemiology. 2008;19(6):S63.

Carlson JA, Jankowska MM, Meseck K, Godbole S, Natarajan L, Raab F, et al. Validity of PALMS GPS scoring of active and passive travel compared to SenseCam. Med Sci Sports Exerc. 2015;47(3):662.

Brazendale K, Beets MW, Armstrong B, Weaver RG, Hunt ET, Pate RR, et al. Children’s moderate-to-vigorous physical activity on weekdays versus weekend days: a multi-country analysis. Int J Behav Nutr Phys Activity. 2021;18:1–13.

Beck F, Engel FA, Reimers AK. Compensation or displacement of physical activity in children and adolescents: a systematic review of empirical studies. Children. 2022;9(3):351.

Swelam BA, Verswijveren SJ, Salmon J, Arundell L, Ridgers ND. Exploring activity compensation amongst youth and adults: a systematic review. Int J Behav Nutr Phys Activity. 2022;19(1):1–25.

Schönbach DM, Altenburg TM, Marques A, Chinapaw MJ, Demetriou Y. Strategies and effects of school-based interventions to promote active school transportation by bicycle among children and adolescents: a systematic review. Int J Behav Nutr Phys Activity. 2020;17(1):1–17.

Remmers T, Van Kann D, Kremers S, Ettema D, De Vries SI, Vos S, et al. Investigating longitudinal context-specific physical activity patterns in transition from primary to secondary school using accelerometers, GPS, and GIS. Int J Behav Nutr Phys Activity. 2020;17:1–14.

Burghard M, Knitel K, van Oost I, Tremblay MS, Takken T. Is our youth cycling to health? Results from the Netherlands’ 2016 report card on physical activity for children and youth. J Phys Activity Health. 2016;13(s2):S218–24.

den Hoed W, Jarvis H. Normalising cycling mobilities: an age-friendly approach to cycling in the Netherlands. Appl Mobilities. 2022;7(3):298–318.

Stoffers M. Cycling as heritage: representing the history of cycling in the Netherlands. J Transp History. 2012;33(1):92–114.

McDonald NC. Children and cycling. City Cycl. 2012;487:211–34.

Harrison F, Atkin AJ, van Sluijs EM, Jones AP. Seasonality in swimming and cycling: exploring a limitation of accelerometer based studies. Prev Med Rep. 2017;7:16–9.

Davison KK, Lawson CT. Do attributes in the physical environment influence children’s physical activity? A review of the literature. Int J Behav Nutr Phys Activity. 2006;3(1):1–17.

McCrorie PR, Fenton C, Ellaway A, Combining GPS. GIS, and accelerometry to explore the physical activity and environment relationship in children and young people-a review. Int J Behav Nutr Phys Activity. 2014;11(1):1–14.

Bernal CMM, Lhuisset L, Fabre N, Bois J. School-based multicomponent intervention to promote physical activity and reduce sedentary time of disadvantaged children aged 6–10 years: protocol for a randomized controlled trial. JMIR Res Protocols. 2020;9(9):e17815.

Hesketh KR, Lakshman R, van Sluijs EM. Barriers and facilitators to young children’s physical activity and sedentary behaviour: a systematic review and synthesis of qualitative literature. Obes Rev. 2017;18(9):987–1017.

Bassett-Gunter R, Rhodes R, Sweet S, Tristani L, Soltani Y. Parent support for children’s physical activity: a qualitative investigation of barriers and strategies. Res Q Exerc Sport. 2017;88(3):282–92.

Arts J, Drotos E, Singh AS, Chinapaw MJ, Altenburg TM, Gubbels JS. Correlates of physical activity in 0-to 5-year-olds: a systematic umbrella review and consultation of international researchers. Sports Med. 2023;53(1):215–40.

Larouche R, Barnes JD, Blanchette S, Faulkner G, Riazi NA, Trudeau F, et al. Relationships among children’s independent mobility, active transportation, and physical activity: a multisite cross-sectional study. Pediatr Exerc Sci. 2020;32(4):189–96.

Grao-Cruces A, Velázquez-Romero MJ, Rodríguez-Rodríguez F. Levels of physical activity during school hours in children and adolescents: a systematic review. Int J Environ Res Public Health. 2020;17(13):4773.

Van Kann DH, Adank AM, van Dijk ML, Remmers T, Vos SB. Disentangling physical activity and sedentary behavior patterns in children with low motor competence. Int J Environ Res Public Health. 2019;16(20):3804.

Daly-Smith AJ, Zwolinsky S, McKenna J, Tomporowski PD, Defeyter MA, Manley A. Systematic review of acute physically active learning and classroom movement breaks on children’s physical activity, cognition, academic performance and classroom behaviour: understanding critical design features. BMJ Open Sport—Exercise Med. 2018;4(1).

Ruhland S, Lange KW. Effect of classroom-based physical activity interventions on attention and on-task behavior in schoolchildren: a systematic review. Sports Med Health Sci. 2021;3(3):125–33.

Vander Ploeg KA, Maximova K, McGavock J, Davis W, Veugelers P. Do school-based physical activity interventions increase or reduce inequalities in health? Soc Sci Med. 2014;112:80–7.

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Acknowledgements

We are grateful to all schools and children participating in the Start Vaardig study.

The Start Vaardig study was funded by the Dutch Organization for Scientific Research (NWO) (RAAKPRO03.123).

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TR analyzed and interpreted the data and drafted the original manuscript. PK assisted in the ethical approval and managed data collection. IF managed data collection and assisted in analyses. JN managed data collection and assisted in drafting the manuscript. WdG assisted in data collection and assisted in ethical approval. SV supervised the project and assisted in funding. SdV managed the project and supervised the funding. RM supervised the project and assisted in funding. DVK supervised the project, assisted in funding, and assisted in drafting the manuscript. All authors read and approved the final manuscript.

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Remmers, T., Koolwijk, P., Fassaert, I. et al. Investigating young children’s physical activity through time and place. Int J Health Geogr 23 , 12 (2024). https://doi.org/10.1186/s12942-024-00373-8

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Developing a survey to measure nursing students’ knowledge, attitudes and beliefs, influences, and willingness to be involved in Medical Assistance in Dying (MAiD): a mixed method modified e-Delphi study

• Jocelyn Schroeder 1 ,
• Barbara Pesut 1 , 2 ,
• Lise Olsen 2 ,
• Nelly D. Oelke 2 &
• Helen Sharp 2  

BMC Nursing volume  23 , Article number:  326 ( 2024 ) Cite this article

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Medical Assistance in Dying (MAiD) was legalized in Canada in 2016. Canada’s legislation is the first to permit Nurse Practitioners (NP) to serve as independent MAiD assessors and providers. Registered Nurses’ (RN) also have important roles in MAiD that include MAiD care coordination; client and family teaching and support, MAiD procedural quality; healthcare provider and public education; and bereavement care for family. Nurses have a right under the law to conscientious objection to participating in MAiD. Therefore, it is essential to prepare nurses in their entry-level education for the practice implications and moral complexities inherent in this practice. Knowing what nursing students think about MAiD is a critical first step. Therefore, the purpose of this study was to develop a survey to measure nursing students’ knowledge, attitudes and beliefs, influences, and willingness to be involved in MAiD in the Canadian context.

The design was a mixed-method, modified e-Delphi method that entailed item generation from the literature, item refinement through a 2 round survey of an expert faculty panel, and item validation through a cognitive focus group interview with nursing students. The settings were a University located in an urban area and a College located in a rural area in Western Canada.

During phase 1, a 56-item survey was developed from existing literature that included demographic items and items designed to measure experience with death and dying (including MAiD), education and preparation, attitudes and beliefs, influences on those beliefs, and anticipated future involvement. During phase 2, an expert faculty panel reviewed, modified, and prioritized the items yielding 51 items. During phase 3, a sample of nursing students further evaluated and modified the language in the survey to aid readability and comprehension. The final survey consists of 45 items including 4 case studies.

Systematic evaluation of knowledge-to-date coupled with stakeholder perspectives supports robust survey design. This study yielded a survey to assess nursing students’ attitudes toward MAiD in a Canadian context.

The survey is appropriate for use in education and research to measure knowledge and attitudes about MAiD among nurse trainees and can be a helpful step in preparing nursing students for entry-level practice.

Peer Review reports

Medical Assistance in Dying (MAiD) is permitted under an amendment to Canada’s Criminal Code which was passed in 2016 [ 1 ]. MAiD is defined in the legislation as both self-administered and clinician-administered medication for the purpose of causing death. In the 2016 Bill C-14 legislation one of the eligibility criteria was that an applicant for MAiD must have a reasonably foreseeable natural death although this term was not defined. It was left to the clinical judgement of MAiD assessors and providers to determine the time frame that constitutes reasonably foreseeable [ 2 ]. However, in 2021 under Bill C-7, the eligibility criteria for MAiD were changed to allow individuals with irreversible medical conditions, declining health, and suffering, but whose natural death was not reasonably foreseeable, to receive MAiD [ 3 ]. This population of MAiD applicants are referred to as Track 2 MAiD (those whose natural death is foreseeable are referred to as Track 1). Track 2 applicants are subject to additional safeguards under the 2021 C-7 legislation.

Three additional proposed changes to the legislation have been extensively studied by Canadian Expert Panels (Council of Canadian Academics [CCA]) [ 4 , 5 , 6 ] First, under the legislation that defines Track 2, individuals with mental disease as their sole underlying medical condition may apply for MAiD, but implementation of this practice is embargoed until March 2027 [ 4 ]. Second, there is consideration of allowing MAiD to be implemented through advanced consent. This would make it possible for persons living with dementia to receive MAID after they have lost the capacity to consent to the procedure [ 5 ]. Third, there is consideration of extending MAiD to mature minors. A mature minor is defined as “a person under the age of majority…and who has the capacity to understand and appreciate the nature and consequences of a decision” ([ 6 ] p. 5). In summary, since the legalization of MAiD in 2016 the eligibility criteria and safeguards have evolved significantly with consequent implications for nurses and nursing care. Further, the number of Canadians who access MAiD shows steady increases since 2016 [ 7 ] and it is expected that these increases will continue in the foreseeable future.

Nurses have been integral to MAiD care in the Canadian context. While other countries such as Belgium and the Netherlands also permit euthanasia, Canada is the first country to allow Nurse Practitioners (Registered Nurses with additional preparation typically achieved at the graduate level) to act independently as assessors and providers of MAiD [ 1 ]. Although the role of Registered Nurses (RNs) in MAiD is not defined in federal legislation, it has been addressed at the provincial/territorial-level with variability in scope of practice by region [ 8 , 9 ]. For example, there are differences with respect to the obligation of the nurse to provide information to patients about MAiD, and to the degree that nurses are expected to ensure that patient eligibility criteria and safeguards are met prior to their participation [ 10 ]. Studies conducted in the Canadian context indicate that RNs perform essential roles in MAiD care coordination; client and family teaching and support; MAiD procedural quality; healthcare provider and public education; and bereavement care for family [ 9 , 11 ]. Nurse practitioners and RNs are integral to a robust MAiD care system in Canada and hence need to be well-prepared for their role [ 12 ].

Previous studies have found that end of life care, and MAiD specifically, raise complex moral and ethical issues for nurses [ 13 , 14 , 15 , 16 ]. The knowledge, attitudes, and beliefs of nurses are important across practice settings because nurses have consistent, ongoing, and direct contact with patients who experience chronic or life-limiting health conditions. Canadian studies exploring nurses’ moral and ethical decision-making in relation to MAiD reveal that although some nurses are clear in their support for, or opposition to, MAiD, others are unclear on what they believe to be good and right [ 14 ]. Empirical findings suggest that nurses go through a period of moral sense-making that is often informed by their family, peers, and initial experiences with MAID [ 17 , 18 ]. Canadian legislation and policy specifies that nurses are not required to participate in MAiD and may recuse themselves as conscientious objectors with appropriate steps to ensure ongoing and safe care of patients [ 1 , 19 ]. However, with so many nurses having to reflect on and make sense of their moral position, it is essential that they are given adequate time and preparation to make an informed and thoughtful decision before they participate in a MAID death [ 20 , 21 ].

It is well established that nursing students receive inconsistent exposure to end of life care issues [ 22 ] and little or no training related to MAiD [ 23 ]. Without such education and reflection time in pre-entry nursing preparation, nurses are at significant risk for moral harm. An important first step in providing this preparation is to be able to assess the knowledge, values, and beliefs of nursing students regarding MAID and end of life care. As demand for MAiD increases along with the complexities of MAiD, it is critical to understand the knowledge, attitudes, and likelihood of engagement with MAiD among nursing students as a baseline upon which to build curriculum and as a means to track these variables over time.

Aim, design, and setting

The aim of this study was to develop a survey to measure nursing students’ knowledge, attitudes and beliefs, influences, and willingness to be involved in MAiD in the Canadian context. We sought to explore both their willingness to be involved in the registered nursing role and in the nurse practitioner role should they chose to prepare themselves to that level of education. The design was a mixed-method, modified e-Delphi method that entailed item generation, item refinement through an expert faculty panel [ 24 , 25 , 26 ], and initial item validation through a cognitive focus group interview with nursing students [ 27 ]. The settings were a University located in an urban area and a College located in a rural area in Western Canada.

Participants

A panel of 10 faculty from the two nursing education programs were recruited for Phase 2 of the e-Delphi. To be included, faculty were required to have a minimum of three years of experience in nurse education, be employed as nursing faculty, and self-identify as having experience with MAiD. A convenience sample of 5 fourth-year nursing students were recruited to participate in Phase 3. Students had to be in good standing in the nursing program and be willing to share their experiences of the survey in an online group interview format.

The modified e-Delphi was conducted in 3 phases: Phase 1 entailed item generation through literature and existing survey review. Phase 2 entailed item refinement through a faculty expert panel review with focus on content validity, prioritization, and revision of item wording [ 25 ]. Phase 3 entailed an assessment of face validity through focus group-based cognitive interview with nursing students.

Phase I. Item generation through literature review

The goal of phase 1 was to develop a bank of survey items that would represent the variables of interest and which could be provided to expert faculty in Phase 2. Initial survey items were generated through a literature review of similar surveys designed to assess knowledge and attitudes toward MAiD/euthanasia in healthcare providers; Canadian empirical studies on nurses’ roles and/or experiences with MAiD; and legislative and expert panel documents that outlined proposed changes to the legislative eligibility criteria and safeguards. The literature review was conducted in three online databases: CINAHL, PsycINFO, and Medline. Key words for the search included nurses , nursing students , medical students , NPs, MAiD , euthanasia , assisted death , and end-of-life care . Only articles written in English were reviewed. The legalization and legislation of MAiD is new in many countries; therefore, studies that were greater than twenty years old were excluded, no further exclusion criteria set for country.

Items from surveys designed to measure similar variables in other health care providers and geographic contexts were placed in a table and similar items were collated and revised into a single item. Then key variables were identified from the empirical literature on nurses and MAiD in Canada and checked against the items derived from the surveys to ensure that each of the key variables were represented. For example, conscientious objection has figured prominently in the Canadian literature, but there were few items that assessed knowledge of conscientious objection in other surveys and so items were added [ 15 , 21 , 28 , 29 ]. Finally, four case studies were added to the survey to address the anticipated changes to the Canadian legislation. The case studies were based upon the inclusion of mature minors, advanced consent, and mental disorder as the sole underlying medical condition. The intention was to assess nurses’ beliefs and comfort with these potential legislative changes.

Phase 2. Item refinement through expert panel review

The goal of phase 2 was to refine and prioritize the proposed survey items identified in phase 1 using a modified e-Delphi approach to achieve consensus among an expert panel [ 26 ]. Items from phase 1 were presented to an expert faculty panel using a Qualtrics (Provo, UT) online survey. Panel members were asked to review each item to determine if it should be: included, excluded or adapted for the survey. When adapted was selected faculty experts were asked to provide rationale and suggestions for adaptation through the use of an open text box. Items that reached a level of 75% consensus for either inclusion or adaptation were retained [ 25 , 26 ]. New items were categorized and added, and a revised survey was presented to the panel of experts in round 2. Panel members were again asked to review items, including new items, to determine if it should be: included, excluded, or adapted for the survey. Round 2 of the modified e-Delphi approach also included an item prioritization activity, where participants were then asked to rate the importance of each item, based on a 5-point Likert scale (low to high importance), which De Vaus [ 30 ] states is helpful for increasing the reliability of responses. Items that reached a 75% consensus on inclusion were then considered in relation to the importance it was given by the expert panel. Quantitative data were managed using SPSS (IBM Corp).

Phase 3. Face validity through cognitive interviews with nursing students

The goal of phase 3 was to obtain initial face validity of the proposed survey using a sample of nursing student informants. More specifically, student participants were asked to discuss how items were interpreted, to identify confusing wording or other problematic construction of items, and to provide feedback about the survey as a whole including readability and organization [ 31 , 32 , 33 ]. The focus group was held online and audio recorded. A semi-structured interview guide was developed for this study that focused on clarity, meaning, order and wording of questions; emotions evoked by the questions; and overall survey cohesion and length was used to obtain data (see Supplementary Material 2  for the interview guide). A prompt to “think aloud” was used to limit interviewer-imposed bias and encourage participants to describe their thoughts and response to a given item as they reviewed survey items [ 27 ]. Where needed, verbal probes such as “could you expand on that” were used to encourage participants to expand on their responses [ 27 ]. Student participants’ feedback was collated verbatim and presented to the research team where potential survey modifications were negotiated and finalized among team members. Conventional content analysis [ 34 ] of focus group data was conducted to identify key themes that emerged through discussion with students. Themes were derived from the data by grouping common responses and then using those common responses to modify survey items.

Ten nursing faculty participated in the expert panel. Eight of the 10 faculty self-identified as female. No faculty panel members reported conscientious objector status and ninety percent reported general agreement with MAiD with one respondent who indicated their view as “unsure.” Six of the 10 faculty experts had 16 years of experience or more working as a nurse educator.

Five nursing students participated in the cognitive interview focus group. The duration of the focus group was 2.5 h. All participants identified that they were born in Canada, self-identified as female (one preferred not to say) and reported having received some instruction about MAiD as part of their nursing curriculum. See Tables  1 and 2 for the demographic descriptors of the study sample. Study results will be reported in accordance with the study phases. See Fig.  1 for an overview of the results from each phase.

Fig. 1  Overview of survey development findings

Phase 1: survey item generation

Review of the literature identified that no existing survey was available for use with nursing students in the Canadian context. However, an analysis of themes across qualitative and quantitative studies of physicians, medical students, nurses, and nursing students provided sufficient data to develop a preliminary set of items suitable for adaptation to a population of nursing students.

Four major themes and factors that influence knowledge, attitudes, and beliefs about MAiD were evident from the literature: (i) endogenous or individual factors such as age, gender, personally held values, religion, religiosity, and/or spirituality [ 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ], (ii) experience with death and dying in personal and/or professional life [ 35 , 40 , 41 , 43 , 44 , 45 ], (iii) training including curricular instruction about clinical role, scope of practice, or the law [ 23 , 36 , 39 ], and (iv) exogenous or social factors such as the influence of key leaders, colleagues, friends and/or family, professional and licensure organizations, support within professional settings, and/or engagement in MAiD in an interdisciplinary team context [ 9 , 35 , 46 ].

Studies of nursing students also suggest overlap across these categories. For example, value for patient autonomy [ 23 ] and the moral complexity of decision-making [ 37 ] are important factors that contribute to attitudes about MAiD and may stem from a blend of personally held values coupled with curricular content, professional training and norms, and clinical exposure. For example, students report that participation in end of life care allows for personal growth, shifts in perception, and opportunities to build therapeutic relationships with their clients [ 44 , 47 , 48 ].

Preliminary items generated from the literature resulted in 56 questions from 11 published sources (See Table  3 ). These items were constructed across four main categories: (i) socio-demographic questions; (ii) end of life care questions; (iii) knowledge about MAiD; or (iv) comfort and willingness to participate in MAiD. Knowledge questions were refined to reflect current MAiD legislation, policies, and regulatory frameworks. Falconer [ 39 ] and Freeman [ 45 ] studies were foundational sources for item selection. Additionally, four case studies were written to reflect the most recent anticipated changes to MAiD legislation and all used the same open-ended core questions to address respondents’ perspectives about the patient’s right to make the decision, comfort in assisting a physician or NP to administer MAiD in that scenario, and hypothesized comfort about serving as a primary provider if qualified as an NP in future. Response options for the survey were also constructed during this stage and included: open text, categorical, yes/no , and Likert scales.

Phase 2: faculty expert panel review

Of the 56 items presented to the faculty panel, 54 questions reached 75% consensus. However, based upon the qualitative responses 9 items were removed largely because they were felt to be repetitive. Items that generated the most controversy were related to measuring religion and spirituality in the Canadian context, defining end of life care when there is no agreed upon time frames (e.g., last days, months, or years), and predicting willingness to be involved in a future events – thus predicting their future selves. Phase 2, round 1 resulted in an initial set of 47 items which were then presented back to the faculty panel in round 2.

Of the 47 initial questions presented to the panel in round 2, 45 reached a level of consensus of 75% or greater, and 34 of these questions reached a level of 100% consensus [ 27 ] of which all participants chose to include without any adaptations) For each question, level of importance was determined based on a 5-point Likert scale (1 = very unimportant, 2 = somewhat unimportant, 3 = neutral, 4 = somewhat important, and 5 = very important). Figure  2 provides an overview of the level of importance assigned to each item.

Ranking level of importance for survey items

After round 2, a careful analysis of participant comments and level of importance was completed by the research team. While the main method of survey item development came from participants’ response to the first round of Delphi consensus ratings, level of importance was used to assist in the decision of whether to keep or modify questions that created controversy, or that rated lower in the include/exclude/adapt portion of the Delphi. Survey items that rated low in level of importance included questions about future roles, sex and gender, and religion/spirituality. After deliberation by the research committee, these questions were retained in the survey based upon the importance of these variables in the scientific literature.

Of the 47 questions remaining from Phase 2, round 2, four were revised. In addition, the two questions that did not meet the 75% cut off level for consensus were reviewed by the research team. The first question reviewed was What is your comfort level with providing a MAiD death in the future if you were a qualified NP ? Based on a review of participant comments, it was decided to retain this question for the cognitive interviews with students in the final phase of testing. The second question asked about impacts on respondents’ views of MAiD and was changed from one item with 4 subcategories into 4 separate items, resulting in a final total of 51 items for phase 3. The revised survey was then brought forward to the cognitive interviews with student participants in Phase 3. (see Supplementary Material 1 for a complete description of item modification during round 2).

Phase 3. Outcomes of cognitive interview focus group

Of the 51 items reviewed by student participants, 29 were identified as clear with little or no discussion. Participant comments for the remaining 22 questions were noted and verified against the audio recording. Following content analysis of the comments, four key themes emerged through the student discussion: unclear or ambiguous wording; difficult to answer questions; need for additional response options; and emotional response evoked by questions. An example of unclear or ambiguous wording was a request for clarity in the use of the word “sufficient” in the context of assessing an item that read “My nursing education has provided sufficient content about the nursing role in MAiD.” “Sufficient” was viewed as subjective and “laden with…complexity that distracted me from the question.” The group recommended rewording the item to read “My nursing education has provided enough content for me to care for a patient considering or requesting MAiD.”

An example of having difficulty answering questions related to limited knowledge related to terms used in the legislation such as such as safeguards , mature minor , eligibility criteria , and conscientious objection. Students were unclear about what these words meant relative to the legislation and indicated that this lack of clarity would hamper appropriate responses to the survey. To ensure that respondents are able to answer relevant questions, student participants recommended that the final survey include explanation of key terms such as mature minor and conscientious objection and an overview of current legislation.

Response options were also a point of discussion. Participants noted a lack of distinction between response options of unsure and unable to say . Additionally, scaling of attitudes was noted as important since perspectives about MAiD are dynamic and not dichotomous “agree or disagree” responses. Although the faculty expert panel recommended the integration of the demographic variables of religious and/or spiritual remain as a single item, the student group stated a preference to have religion and spirituality appear as separate items. The student focus group also took issue with separate items for the variables of sex and gender, specifically that non-binary respondents might feel othered or “outed” particularly when asked to identify their sex. These variables had been created based upon best practices in health research but students did not feel they were appropriate in this context [ 49 ]. Finally, students agreed with the faculty expert panel in terms of the complexity of projecting their future involvement as a Nurse Practitioner. One participant stated: “I certainly had to like, whoa, whoa, whoa. Now let me finish this degree first, please.” Another stated, “I'm still imagining myself, my future career as an RN.”

Finally, student participants acknowledged the array of emotions that some of the items produced for them. For example, one student described positive feelings when interacting with the survey. “Brought me a little bit of feeling of joy. Like it reminded me that this is the last piece of independence that people grab on to.” Another participant, described the freedom that the idea of an advance request gave her. “The advance request gives the most comfort for me, just with early onset Alzheimer’s and knowing what it can do.” But other participants described less positive feelings. For example, the mature minor case study yielded a comment: “This whole scenario just made my heart hurt with the idea of a child requesting that.”

Based on the data gathered from the cognitive interview focus group of nursing students, revisions were made to 11 closed-ended questions (see Table  4 ) and 3 items were excluded. In the four case studies, the open-ended question related to a respondents’ hypothesized actions in a future role as NP were removed. The final survey consists of 45 items including 4 case studies (see Supplementary Material 3 ).

The aim of this study was to develop and validate a survey that can be used to track the growth of knowledge about MAiD among nursing students over time, inform training programs about curricular needs, and evaluate attitudes and willingness to participate in MAiD at time-points during training or across nursing programs over time.

The faculty expert panel and student participants in the cognitive interview focus group identified a need to establish core knowledge of the terminology and legislative rules related to MAiD. For example, within the cognitive interview group of student participants, several acknowledged lack of clear understanding of specific terms such as “conscientious objector” and “safeguards.” Participants acknowledged discomfort with the uncertainty of not knowing and their inclination to look up these terms to assist with answering the questions. This survey can be administered to nursing or pre-nursing students at any phase of their training within a program or across training programs. However, in doing so it is important to acknowledge that their baseline knowledge of MAiD will vary. A response option of “not sure” is important and provides a means for respondents to convey uncertainty. If this survey is used to inform curricular needs, respondents should be given explicit instructions not to conduct online searches to inform their responses, but rather to provide an honest appraisal of their current knowledge and these instructions are included in the survey (see Supplementary Material 3 ).

Some provincial regulatory bodies have established core competencies for entry-level nurses that include MAiD. For example, the BC College of Nurses and Midwives (BCCNM) requires “knowledge about ethical, legal, and regulatory implications of medical assistance in dying (MAiD) when providing nursing care.” (10 p. 6) However, across Canada curricular content and coverage related to end of life care and MAiD is variable [ 23 ]. Given the dynamic nature of the legislation that includes portions of the law that are embargoed until 2024, it is important to ensure that respondents are guided by current and accurate information. As the law changes, nursing curricula, and public attitudes continue to evolve, inclusion of core knowledge and content is essential and relevant for investigators to be able to interpret the portions of the survey focused on attitudes and beliefs about MAiD. Content knowledge portions of the survey may need to be modified over time as legislation and training change and to meet the specific purposes of the investigator.

Given the sensitive nature of the topic, it is strongly recommended that surveys be conducted anonymously and that students be provided with an opportunity to discuss their responses to the survey. A majority of feedback from both the expert panel of faculty and from student participants related to the wording and inclusion of demographic variables, in particular religion, religiosity, gender identity, and sex assigned at birth. These and other demographic variables have the potential to be highly identifying in small samples. In any instance in which the survey could be expected to yield demographic group sizes less than 5, users should eliminate the demographic variables from the survey. For example, the profession of nursing is highly dominated by females with over 90% of nurses who identify as female [ 50 ]. Thus, a survey within a single class of students or even across classes in a single institution is likely to yield a small number of male respondents and/or respondents who report a difference between sex assigned at birth and gender identity. When variables that serve to identify respondents are included, respondents are less likely to complete or submit the survey, to obscure their responses so as not to be identifiable, or to be influenced by social desirability bias in their responses rather than to convey their attitudes accurately [ 51 ]. Further, small samples do not allow for conclusive analyses or interpretation of apparent group differences. Although these variables are often included in surveys, such demographics should be included only when anonymity can be sustained. In small and/or known samples, highly identifying variables should be omitted.

There are several limitations associated with the development of this survey. The expert panel was comprised of faculty who teach nursing students and are knowledgeable about MAiD and curricular content, however none identified as a conscientious objector to MAiD. Ideally, our expert panel would have included one or more conscientious objectors to MAiD to provide a broader perspective. Review by practitioners who participate in MAiD, those who are neutral or undecided, and practitioners who are conscientious objectors would ensure broad applicability of the survey. This study included one student cognitive interview focus group with 5 self-selected participants. All student participants had held discussions about end of life care with at least one patient, 4 of 5 participants had worked with a patient who requested MAiD, and one had been present for a MAiD death. It is not clear that these participants are representative of nursing students demographically or by experience with end of life care. It is possible that the students who elected to participate hold perspectives and reflections on patient care and MAiD that differ from students with little or no exposure to end of life care and/or MAiD. However, previous studies find that most nursing students have been involved with end of life care including meaningful discussions about patients’ preferences and care needs during their education [ 40 , 44 , 47 , 48 , 52 ]. Data collection with additional student focus groups with students early in their training and drawn from other training contexts would contribute to further validation of survey items.

Future studies should incorporate pilot testing with small sample of nursing students followed by a larger cross-program sample to allow evaluation of the psychometric properties of specific items and further refinement of the survey tool. Consistent with literature about the importance of leadership in the context of MAiD [ 12 , 53 , 54 ], a study of faculty knowledge, beliefs, and attitudes toward MAiD would provide context for understanding student perspectives within and across programs. Additional research is also needed to understand the timing and content coverage of MAiD across Canadian nurse training programs’ curricula.

The implementation of MAiD is complex and requires understanding of the perspectives of multiple stakeholders. Within the field of nursing this includes clinical providers, educators, and students who will deliver clinical care. A survey to assess nursing students’ attitudes toward and willingness to participate in MAiD in the Canadian context is timely, due to the legislation enacted in 2016 and subsequent modifications to the law in 2021 with portions of the law to be enacted in 2027. Further development of this survey could be undertaken to allow for use in settings with practicing nurses or to allow longitudinal follow up with students as they enter practice. As the Canadian landscape changes, ongoing assessment of the perspectives and needs of health professionals and students in the health professions is needed to inform policy makers, leaders in practice, curricular needs, and to monitor changes in attitudes and practice patterns over time.

Availability of data and materials

The datasets used and/or analysed during the current study are not publicly available due to small sample sizes, but are available from the corresponding author on reasonable request.

Abbreviations

British Columbia College of Nurses and Midwives

Medical assistance in dying

Nurse practitioner

Registered nurse

University of British Columbia Okanagan

Nicol J, Tiedemann M. Legislative Summary: Bill C-14: An Act to amend the Criminal Code and to make related amendments to other Acts (medical assistance in dying). Available from: https://lop.parl.ca/staticfiles/PublicWebsite/Home/ResearchPublications/LegislativeSummaries/PDF/42-1/c14-e.pdf .

Downie J, Scallion K. Foreseeably unclear. The meaning of the “reasonably foreseeable” criterion for access to medical assistance in dying in Canada. Dalhousie Law J. 2018;41(1):23–57.

Nicol J, Tiedeman M. Legislative summary of Bill C-7: an act to amend the criminal code (medical assistance in dying). Ottawa: Government of Canada; 2021.

Google Scholar  

Council of Canadian Academies. The state of knowledge on medical assistance in dying where a mental disorder is the sole underlying medical condition. Ottawa; 2018. Available from: https://cca-reports.ca/wp-content/uploads/2018/12/The-State-of-Knowledge-on-Medical-Assistance-in-Dying-Where-a-Mental-Disorder-is-the-Sole-Underlying-Medical-Condition.pdf .

Council of Canadian Academies. The state of knowledge on advance requests for medical assistance in dying. Ottawa; 2018. Available from: https://cca-reports.ca/wp-content/uploads/2019/02/The-State-of-Knowledge-on-Advance-Requests-for-Medical-Assistance-in-Dying.pdf .

Council of Canadian Academies. The state of knowledge on medical assistance in dying for mature minors. Ottawa; 2018. Available from: https://cca-reports.ca/wp-content/uploads/2018/12/The-State-of-Knowledge-on-Medical-Assistance-in-Dying-for-Mature-Minors.pdf .

Health Canada. Third annual report on medical assistance in dying in Canada 2021. Ottawa; 2022. [cited 2023 Oct 23]. Available from: https://www.canada.ca/en/health-canada/services/medical-assistance-dying/annual-report-2021.html .

Banner D, Schiller CJ, Freeman S. Medical assistance in dying: a political issue for nurses and nursing in Canada. Nurs Philos. 2019;20(4): e12281.

Article   PubMed   Google Scholar  

Pesut B, Thorne S, Stager ML, Schiller CJ, Penney C, Hoffman C, et al. Medical assistance in dying: a review of Canadian nursing regulatory documents. Policy Polit Nurs Pract. 2019;20(3):113–30.

Article   PubMed   PubMed Central   Google Scholar  

College of Registered Nurses of British Columbia. Scope of practice for registered nurses [Internet]. Vancouver; 2018. Available from: https://www.bccnm.ca/Documents/standards_practice/rn/RN_ScopeofPractice.pdf .

Pesut B, Thorne S, Schiller C, Greig M, Roussel J, Tishelman C. Constructing good nursing practice for medical assistance in dying in Canada: an interpretive descriptive study. Global Qual Nurs Res. 2020;7:2333393620938686. https://doi.org/10.1177/2333393620938686 .

Article   Google Scholar  

Pesut B, Thorne S, Schiller CJ, Greig M, Roussel J. The rocks and hard places of MAiD: a qualitative study of nursing practice in the context of legislated assisted death. BMC Nurs. 2020;19:12. https://doi.org/10.1186/s12912-020-0404-5 .

Pesut B, Greig M, Thorne S, Burgess M, Storch JL, Tishelman C, et al. Nursing and euthanasia: a narrative review of the nursing ethics literature. Nurs Ethics. 2020;27(1):152–67.

Pesut B, Thorne S, Storch J, Chambaere K, Greig M, Burgess M. Riding an elephant: a qualitative study of nurses’ moral journeys in the context of Medical Assistance in Dying (MAiD). Journal Clin Nurs. 2020;29(19–20):3870–81.

Lamb C, Babenko-Mould Y, Evans M, Wong CA, Kirkwood KW. Conscientious objection and nurses: results of an interpretive phenomenological study. Nurs Ethics. 2018;26(5):1337–49.

Wright DK, Chan LS, Fishman JR, Macdonald ME. “Reflection and soul searching:” Negotiating nursing identity at the fault lines of palliative care and medical assistance in dying. Social Sci & Med. 2021;289: 114366.

Beuthin R, Bruce A, Scaia M. Medical assistance in dying (MAiD): Canadian nurses’ experiences. Nurs Forum. 2018;54(4):511–20.

Bruce A, Beuthin R. Medically assisted dying in Canada: "Beautiful Death" is transforming nurses' experiences of suffering. The Canadian J Nurs Res | Revue Canadienne de Recherche en Sci Infirmieres. 2020;52(4):268–77. https://doi.org/10.1177/0844562119856234 .

Canadian Nurses Association. Code of ethics for registered nurses. Ottawa; 2017. Available from: https://www.cna-aiic.ca/en/nursing/regulated-nursing-in-canada/nursing-ethics .

Canadian Nurses Association. National nursing framework on Medical Assistance in Dying in Canada. Ottawa: 2017. Available from: https://www.virtualhospice.ca/Assets/cna-national-nursing-framework-on-maidEng_20170216155827.pdf .

Pesut B, Thorne S, Greig M. Shades of gray: conscientious objection in medical assistance in dying. Nursing Inq. 2020;27(1): e12308.

Durojaiye A, Ryan R, Doody O. Student nurse education and preparation for palliative care: a scoping review. PLoS ONE. 2023. https://doi.org/10.1371/journal.pone.0286678 .

McMechan C, Bruce A, Beuthin R. Canadian nursing students’ experiences with medical assistance in dying | Les expériences d’étudiantes en sciences infirmières au regard de l’aide médicale à mourir. Qual Adv Nurs Educ - Avancées en Formation Infirmière. 2019;5(1). https://doi.org/10.17483/2368-6669.1179 .

Adler M, Ziglio E. Gazing into the oracle. The Delphi method and its application to social policy and public health. London: Jessica Kingsley Publishers; 1996

Keeney S, Hasson F, McKenna H. Consulting the oracle: ten lessons from using the Delphi technique in nursing research. J Adv Nurs. 2006;53(2):205–12.

Keeney S, Hasson F, McKenna H. The Delphi technique in nursing and health research. 1st ed. City: Wiley; 2011.

Willis GB. Cognitive interviewing: a tool for improving questionnaire design. 1st ed. Thousand Oaks, Calif: Sage; 2005. ISBN: 9780761928041

Lamb C, Evans M, Babenko-Mould Y, Wong CA, Kirkwood EW. Conscience, conscientious objection, and nursing: a concept analysis. Nurs Ethics. 2017;26(1):37–49.

Lamb C, Evans M, Babenko-Mould Y, Wong CA, Kirkwood K. Nurses’ use of conscientious objection and the implications of conscience. J Adv Nurs. 2018;75(3):594–602.

de Vaus D. Surveys in social research. 6th ed. Abingdon, Oxon: Routledge; 2014.

Boateng GO, Neilands TB, Frongillo EA, Melgar-Quiñonez HR, Young SL. Best practices for developing and validating scales for health, social, and behavioral research: A primer. Front Public Health. 2018;6:149. https://doi.org/10.3389/fpubh.2018.00149 .

Puchta C, Potter J. Focus group practice. 1st ed. London: Sage; 2004.

Book   Google Scholar  

Streiner DL, Norman GR, Cairney J. Health measurement scales: a practical guide to their development and use. 5th ed. Oxford: Oxford University Press; 2015.

Hsieh H-F, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005;15(9):1277–88.

Adesina O, DeBellis A, Zannettino L. Third-year Australian nursing students’ attitudes, experiences, knowledge, and education concerning end-of-life care. Int J of Palliative Nurs. 2014;20(8):395–401.

Bator EX, Philpott B, Costa AP. This moral coil: a cross-sectional survey of Canadian medical student attitudes toward medical assistance in dying. BMC Med Ethics. 2017;18(1):58.

Beuthin R, Bruce A, Scaia M. Medical assistance in dying (MAiD): Canadian nurses’ experiences. Nurs Forum. 2018;53(4):511–20.

Brown J, Goodridge D, Thorpe L, Crizzle A. What is right for me, is not necessarily right for you: the endogenous factors influencing nonparticipation in medical assistance in dying. Qual Health Res. 2021;31(10):1786–1800.

Falconer J, Couture F, Demir KK, Lang M, Shefman Z, Woo M. Perceptions and intentions toward medical assistance in dying among Canadian medical students. BMC Med Ethics. 2019;20(1):22.

Green G, Reicher S, Herman M, Raspaolo A, Spero T, Blau A. Attitudes toward euthanasia—dual view: Nursing students and nurses. Death Stud. 2022;46(1):124–31.

Hosseinzadeh K, Rafiei H. Nursing student attitudes toward euthanasia: a cross-sectional study. Nurs Ethics. 2019;26(2):496–503.

Ozcelik H, Tekir O, Samancioglu S, Fadiloglu C, Ozkara E. Nursing students’ approaches toward euthanasia. Omega (Westport). 2014;69(1):93–103.

Canning SE, Drew C. Canadian nursing students’ understanding, and comfort levels related to medical assistance in dying. Qual Adv Nurs Educ - Avancées en Formation Infirmière. 2022;8(2). https://doi.org/10.17483/2368-6669.1326 .

Edo-Gual M, Tomás-Sábado J, Bardallo-Porras D, Monforte-Royo C. The impact of death and dying on nursing students: an explanatory model. J Clin Nurs. 2014;23(23–24):3501–12.

Freeman LA, Pfaff KA, Kopchek L, Liebman J. Investigating palliative care nurse attitudes towards medical assistance in dying: an exploratory cross-sectional study. J Adv Nurs. 2020;76(2):535–45.

Brown J, Goodridge D, Thorpe L, Crizzle A. “I am okay with it, but I am not going to do it:” the exogenous factors influencing non-participation in medical assistance in dying. Qual Health Res. 2021;31(12):2274–89.

Dimoula M, Kotronoulas G, Katsaragakis S, Christou M, Sgourou S, Patiraki E. Undergraduate nursing students’ knowledge about palliative care and attitudes towards end-of-life care: A three-cohort, cross-sectional survey. Nurs Educ Today. 2019;74:7–14.

Matchim Y, Raetong P. Thai nursing students’ experiences of caring for patients at the end of life: a phenomenological study. Int J Palliative Nurs. 2018;24(5):220–9.

Canadian Institute for Health Research. Sex and gender in health research [Internet]. Ottawa: CIHR; 2021 [cited 2023 Oct 23]. Available from: https://cihr-irsc.gc.ca/e/50833.html .

Canadian Nurses’ Association. Nursing statistics. Ottawa: CNA; 2023 [cited 2023 Oct 23]. Available from: https://www.cna-aiic.ca/en/nursing/regulated-nursing-in-canada/nursing-statistics .

Krumpal I. Determinants of social desirability bias in sensitive surveys: a literature review. Qual Quant. 2013;47(4):2025–47. https://doi.org/10.1007/s11135-011-9640-9 .

Ferri P, Di Lorenzo R, Stifani S, Morotti E, Vagnini M, Jiménez Herrera MF, et al. Nursing student attitudes toward dying patient care: a European multicenter cross-sectional study. Acta Bio Medica Atenei Parmensis. 2021;92(S2): e2021018.

PubMed   PubMed Central   Google Scholar  

Beuthin R, Bruce A. Medical assistance in dying (MAiD): Ten things leaders need to know. Nurs Leadership. 2018;31(4):74–81.

Thiele T, Dunsford J. Nurse leaders’ role in medical assistance in dying: a relational ethics approach. Nurs Ethics. 2019;26(4):993–9.

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We would like to acknowledge the faculty and students who generously contributed their time to this work.

JS received a student traineeship through the Principal Research Chairs program at the University of British Columbia Okanagan.

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JS made substantial contributions to the conception of the work; data acquisition, analysis, and interpretation; and drafting and substantively revising the work. JS has approved the submitted version and agreed to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. BP made substantial contributions to the conception of the work; data acquisition, analysis, and interpretation; and drafting and substantively revising the work. BP has approved the submitted version and agreed to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. LO made substantial contributions to the conception of the work; data acquisition, analysis, and interpretation; and substantively revising the work. LO has approved the submitted version and agreed to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. NDO made substantial contributions to the conception of the work; data acquisition, analysis, and interpretation; and substantively revising the work. NDO has approved the submitted version and agreed to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. HS made substantial contributions to drafting and substantively revising the work. HS has approved the submitted version and agreed to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature.

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Schroeder, J., Pesut, B., Olsen, L. et al. Developing a survey to measure nursing students’ knowledge, attitudes and beliefs, influences, and willingness to be involved in Medical Assistance in Dying (MAiD): a mixed method modified e-Delphi study. BMC Nurs 23 , 326 (2024). https://doi.org/10.1186/s12912-024-01984-z

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• Medical assistance in dying (MAiD)
• End of life care
• Student nurses
• Nursing education

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• Study Protocol
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• Published: 10 May 2024

Evaluation of serological assays for the diagnosis of childhood tuberculosis disease: a study protocol

• Daniela Neudecker 1 ,
• Nora Fritisch 1 , 2 ,
• Thomas Sutter 3 ,
• Lenette Lu 4 , 5 , 6 ,
• Marc Tebruegge 7 , 8 , 9 ,
• Begoña Santiago-Garcia 10 , 11 , 12 , 13 &
• Nicole Ritz 1 , 7 , 14  

BMC Infectious Diseases volume  24 , Article number:  481 ( 2024 ) Cite this article

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Tuberculosis (TB) poses a major public health challenge, particularly in children. A substantial proportion of children with TB disease remain undetected and unconfirmed. Therefore, there is an urgent need for a highly sensitive point-of-care test. This study aims to assess the performance of serological assays based on various antigen targets and antibody properties in distinguishing children (0–18 years) with TB disease (1) from healthy TB-exposed children, (2) children with non-TB lower respiratory tract infections, and (3) from children with TB infection.

The study will use biobanked plasma samples collected from three prospective multicentric diagnostic observational studies: the Childhood TB in Switzerland (CITRUS) study, the Pediatric TB Research Network in Spain (pTBred), and the Procalcitonin guidance to reduce antibiotic treatment of lower respiratory tract infections in children and adolescents (ProPAED) study. Included are children diagnosed with TB disease or infection, healthy TB-exposed children, and sick children with non-TB lower respiratory tract infection. Serological multiplex assays will be performed to identify M. tuberculosis antigen-specific antibody features, including isotypes, subclasses, Fc receptor (FcR) binding, and IgG glycosylation.

The findings from this study will help to design serological assays for diagnosing TB disease in children. Importantly, those assays could easily be developed as low-cost point-of-care tests, thereby offering a potential solution for resource-constrained settings.

ClinicalTrials.gov Identifier

NCT03044509.

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Diagnosing tuberculosis (TB) in children presents several challenges [ 1 ]. TB disease in children is confirmed only in about 50% of patients due to the paucibacillary nature [ 2 , 3 ]. In the absence of a reliable and easily accessible diagnostic test for screening and confirming TB disease in children, diagnosis typically relies on clinical findings, TB contact history, chest radiography findings, and the results of immune-based TB tests, the Tuberculin skin test (TST) and interferon-γ release assays (IGRA) [ 4 ]. However, both immunodiagnostic tests have suboptimal performance and are not well-suited for screening for TB disease [ 5 , 6 ].

Serological assays have the potential to serve as a screening tool for TB infection and disease in children, especially in resource-limited settings where advanced diagnostic methods are limited. This potential stems from their blood-based nature, thus not requiring sputum collection, and their feasibility to be used as point-of-care tests [ 7 ]. However, currently available commercial serological assays are not recommended for clinical use due to their insufficient and variable diagnostic performance, characterised by limited sensitivity, specificity, and susceptibility to cross-reactivity [ 8 , 9 ]. In a recent narrative review focusing on the diagnostic performance of non-commercial serological assays for TB in children, we found that studies which measured antibodies against only one antigen generally reported relatively high specificity but only achieved limited sensitivity [ 10 ]. Higher sensitivity can be achieved when antibodies against multiple targets are measured, and results are interpreted in combination. In addition, emerging evidence suggests that certain antibody properties, such as antibody Fc receptor (FcR) binding profiles [ 11 , 12 ] and antibody glycosylation patterns [ 13 ], can potentially be used to differentiate between TB infection and disease. However, most of those studies have been done in adults, and the evidence in children remains extremely limited.

The aim of this study is to evaluate the diagnostic performance of serological assays in detecting children with TB disease, and in distinguishing those subjects from (1) healthy TB-exposed children, (2) children with non-TB lower respiratory tract infection, and (3) children with TB infection.

Study setting and population

This study will utilise plasma samples obtained from three different prospective multicentric observational studies: the Childhood Tuberculosis in Switzerland (CITRUS) study (NCT03044509), the Pediatric TB Research Network in Spain (pTBred), and the Procalcitonin guidance to reduce antibiotic treatment of lower respiratory tract infections in children and adolescents (ProPAED) study (ISRCTN 17,057,980) (Table  1 ).

CITRUS is a multicentric prospective diagnostic study done at nine centres across Switzerland (Bern, Basel, Zurich, Lausanne, Geneva, Aarau, St. Gallen, Lucerne, Bellinzona). Its primary objective is to evaluate and validate novel immunodiagnostic assays for childhood TB [ 14 , 15 ]. The study includes children under the age of 18 years, with or without a history of Bacillus Calmette-Guérin (BCG) vaccination, who are undergoing evaluation for TB disease, infection, and exposure. Children who have received any anti-mycobacterial treatment for five days or more before inclusion or who have been previously treated for TB disease or infection are excluded. Recruitment for the CITRUS study began in May 2017 and is currently ongoing.

PTBred is a multidisciplinary collaborative network established in 2014 in Spain, recruiting children < 18 years with TB. Since 2017, different types of samples have been stored in the Biobank of the Gregorio Marañon Hospital or in the individual collection registered as C.0006631 in the National Biobank Collections Registry. For this study, a common protocol for sample processing was implemented in October 2019, including children with children with TB disease, infection, and exposure irrespective of their BCG-vaccination status. The pTBred and CITRUS study follow the same inclusion and exclusion criteria [ 16 ].

The ProPAED study collected samples from children and adolescents presenting with fever and cough at two emergency departments in Switzerland (Basel and Aarau), from January 2009 to February 2010. For the ProPAED study, children with severe immunocompromise or known HIV infection, those undergoing immunosuppressive treatment, children with M. tuberculosis infection, neutropenia, cystic fibrosis, viral laryngotracheitis, hospital stay within the preceding 14 days, or other severe infections (e.g., osteomyelitis, endocarditis, or deep tissue abscesses) were excluded [ 17 ].

Case definitions

In this study, we will use the published criteria of compound TB case definitions proposed by Graham et al. [ 18 ]. Briefly, confirmed TB disease is defined as the presence of bacteriologically confirmed TB disease through culture or nucleic acid amplification tests (NAAT). Unconfirmed TB disease is defined as the absence of bacteriological confirmation in the presence of at least two of the following criteria: symptoms or signs suggestive of TB disease, chest radiograph consistent with TB disease, close TB exposure or immunologic evidence of M. tuberculosis infection, positive response to TB treatment. TB infection is defined as the presence of immunologic evidence of M. tuberculosis infection, including a positive TST of ≥ 5 mm (in accordance with the Swiss and Spanish guidelines [ 19 , 20 ]) or a positive IGRA without meeting the criteria for confirmed or unconfirmed TB disease. Healthy TB-exposed children are defined as asymptomatic individuals with negative results on IGRA or TST test (single or repeat testing according to age, time since exposure as defined by national guidelines), making them unlikely to have TB. Children with non-TB lower respiratory tract infection will be the sick control group and are defined as presenting with fever (core body temperature ≥ 38.0° C) and at least one symptom (cough, sputum production, pleuritic pain, poor feeding) and at least one sign (tachypnea, dyspnoea, wheezing, late inspiratory crackles, bronchial breathing, pleural rub) lasting for fewer than 14 days.

Age stratification

The study will analyse antibody concentrations and properties in children stratified into distinct age groups: 0 to < 2, 2 to < 5, 5 to < 10, and ≥ 10 years, as proposed by Cuevas et al. [ 21 ]. This stratification is crucial due to the differences and dynamics of the nature of TB disease across age. In the youngest age range (infants and children < 2 years old), disseminated diseases and heightened susceptibility to progression from TB infection to TB disease is well-documented [ 22 ]. The risks for progression from infection to disease, as well as the subsequent mortality risk following development of disease, consistently declines during childhood, reaching its lowest point between 5 and 10 years of age [ 23 ]. Transitioning into adolescence and the onset of puberty, typically beyond the age of 10 years, the phenotype of TB disease becomes more adult-like. Pulmonary TB becomes more prevalent during this phase, contributing to an upsurge in TB-related mortality rates [ 24 , 25 ].

Selected antigen targets and antibody properties for serological assay

Some previous studies in children have demonstrated improved specificities achieved by combining both protein and glycolipid antigens within serological assays [ 26 , 27 , 28 , 29 ]. Furthermore, several studies have illuminated the potential for heightened sensitivity through the combined analysis of multiple antigen targets, effectively overcoming the interindividual heterogeneity of the human humoral immune response to M. tuberculosis [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ].

We will analyse antibodies concentrations and properties against single protein antigens, single glycolipid antigens [ 12 , 34 , 35 , 36 , 37 , 38 , 39 , 40 ], as well as multiple antigens in combination (Table  2 ). The types of antigens include cell wall fractions, whole cell lysates, and total lipids of M. tuberculosis . The selection of protein antigens is based on results from large protein microarray studies in adults [ 41 , 42 , 43 , 44 , 45 , 46 ], one large multiplex bead-based study in children [ 31 ], and published and unpublished data from an adult study performed in the U.K (MIMIC study; personal communication M. Tebruegge) [ 47 ]. In order to enhance specificity, the overlap of the antigen targets for M. tuberculosis with Bacillus Calmette-Guérin (BCG) and other non-tuberculous mycobacteria will be reduced.

Together with targeted M. tuberculosis antigens, this study will evaluate the following distinct properties of the antibodies: isotypes and their subclasses, FcR binding profiles, and antibody glycosylation patterns (refer to Fig.  1 ). The rational for this is to obtain further information about the immune response to the antigen. TB disease results from a combination of the mycobacteria infecting and the resulting pathologic immune response. Therefore, antibody concentrations may only reflect on exposure, timepoint, and burden of mycobacteria, whereas additional properties such as FcR may reflect on the fact if the immune response producing tissue damage and pathology or not. This is shown in studies in children with TB disease that have demonstrated the potential enhancement of serological assay sensitivity through the integration of diverse antibody isotypes [ 48 , 49 , 50 ]. Recent advancements in adult research have indicated that an evaluation of certain antibody properties, such as FcRs binding profiles and glycosylation patterns, could potentially enable the differentiation between TB disease and infection [ 12 , 13 ].

Overview of the antibody properties

Interaction between the surface of M. tuberculosis, binding of the antibody and the recognition of the antibody by an immune cell. Sections A , B , and C detail the different antibody properties: A ) antibody isotypes and IgG subclasses B ) glycosylation patterns of antibodies, including a core glycan and potential additional sugar residues (1–4) C ) activating and inhibiting FcRs with varying affinities for antibody binding

Abbreviations: Mtb -Mycobacterium tuberculosis; FcR -fragmented crystallizable region (Fc) receptor; IgM - immunoglobulin M; IgD - immunoglobulin D, IgG 1 − 4 - immunoglobulin G 1 − 4 ; IgA - immunoglobulin A, N - N-acetylglucosamine; M - mannose; G - galactose; S - sialic acid; F - fucose

As a quality control and potential normalisation variable, we will measure the total antibody concentration of each isotype and the total antibody concentration binding to distinct FcRs.

Sample preparation

Upon plasma sample collection, preservation is ensured through storage in a − 80 °C freezer until the initiation of laboratory assays. Customised multiplex antigen-coupled beads will be produced to evaluate antigen-specific antibodies concentrations and properties in plasma samples. The protein antigens will be coupled to carboxylated beads through covalent NHS-ester linkages, using 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride and Sulfo-NHS (Thermo Scientific), following the manufacturer’s recommendations [ 51 , 52 ]. Glycan antigen LAM, single lipid antigens (e.g., TDM and TMM), and multiple lipid antigen from Mycobacterium tuberculosis total lipids will be modified using 4-(4,6-dimethoxy [ 1 , 3 , 5 ] triazin-2-yl)-4-methyl-morpholinium (DMTMM) dissolved in ethanol and conjugated beads following the COOH-DMTMM method [ 53 ].

The antigen-specific antibodies concentrations and properties will be measured using different PE-labelled detection antibodies as follows: for the isotypes and subclasses, PE-coupled detection antibodies (anti-IgG, anti-IgA, anti-IgM, anti-IgG 1 , anti-IgG 2 , anti-IgG 3 and anti-IgG 4 ) at a concentration of 1 µg/mL; [ 52 ] for the FcR binding profiles, FcRs (FcγRIIIa/CD16a, FcγRIIIb/CD16b, FcγRIIa/CD32a H167, FcγRIIb/CD32b, FcγRI/CD64 from R&D Systems) will be labelled with PE and added to the samples at a concentration of 1 µg/mL; and for the glycosylation profiles, PE-labelled lectins (SNA for sialic acid, ECL for galactose, LCA for fucose and PHA-E for N-acetylglucosamine) will be used at a concentration of 20 µg/mL. After 2 h of incubation at room temperature, the beads will be washed with PBS-0.05% Tween20, and PE signal will be measured using xMAP technology. (refer to Fig.  2 )

Multiplex bead-based serological assay

For the multiplex bead-base serological assay (1) specific antigens are coupled to beads, (2) plasma samples are incubated with the antigen-coupled beads, allowing specific antibodies to bind to corresponding antigens, (3) fluorescently labelled detection antibodies are added, binding to antigen-specific antibodies or their properties, (4) fluorescence is measured by using a coloured laser, and concentrations are then calculated based on a standard curve

Data management

All data will be securely entered and shared through password-protected and encrypted systems to uphold the confidentiality of health-related personal information. Adhering to Swiss legal requirements for data protection (Ordinance HRO Art. 5), our procedures for storing biological samples and handling health data are meticulously governed. Coding mechanisms and personalised logins are implemented to grant exclusive access to the study database and source documents for authorised personnel, thereby preventing third-party disclosure. Unique identification numbers are assigned to the biological samples and health-related personal data.

Data analysis

Descriptive statistics, including mean, median, standard deviation, and interquartile range, will be used to summarise antibody concentrations stratified by diagnostic group (TB disease, TB infection, healthy TB-exposed controls, and non-TB lower respiratory tract infections) and age groups (< 2 years, 2 to < 5 years, 5 to < 10 years, and ≥ 10 years). Antigen-specific antibody concentrations will be analysed in relation to the total (nonspecific) antibody concentrations. Comparisons between groups will be made using t-tests or Mann-Whitney U tests if normality assumptions are not met. Children with TB disease and infection will be compared with the following groups: all other remaining children combined, healthy TB-exposed children, and children with non-TB lower respiratory tract infections.

To assess the performance of each individual antigen specific antibody feature as a diagnostic assay, sensitivity and specificity will be calculated based on cut-off values determined by the highest Youden’s index. Receiver operating characteristic (ROC) analysis will be performed, and area under the curve (AUC) will be calculated (confidence interval will be determined using the DeLong method).

In subsequent analyses, we aim to evaluate the combined interpretation of antigen-specific antibodies concentrations and properties using different strategies:

Strategy one involves defining cut-off values based on a specificity of ≥ 98%, in accordance with the minimal WHO’s TPP requirement for a biomarker-based detection test. We will calculate the corresponding sensitivity. Similarly, we will determine cut-off values based on a sensitivity of ≥ 66% and calculate the corresponding specificity. To assess the combined interpretation of multiple antigen targets, the test for a specific antibody or antibody property will be scored positive if at least one antibody level against a specific antigen exceeds the cut-off value in an individual’s plasma sample, and negative if all antibody levels against all antigens in a plasma sample are below the cut-off values.

Another strategy for the combined interpretation of multiple antibody concentrations and properties will involve feature selection using the least absolute shrinkage and selection operator (LASSO). This approach will help identifying the most informative features that could be used in diagnostic assays. To validate the predictive power of the selected features (k features), we will train and evaluate an additional model using only those k features. In a further step, we will include the selection of antibody concentrations and properties in the training of the model. By performing feature selection using LASSO, we aim to maximize prediction performance using all features and select the k most informative features after the training stage. This procedure is based on the concept that selecting the most informative features from a well-performing prediction model will also yield a well-performing prediction model when one only has access to the selected subset of features. Recent advances in machine learning research will enable us to incorporate feature subset selection directly into the training step of a model [ 54 , 55 ]. Therefore, we optimise not only the prediction performance but also the subset selection of k features during training. The choice of subset size, k, should be based on external constraints. The diverse sensitivities and specificities observed in paediatric TB serological tests make a precise sample size determination challenging. To estimate the sample size for our experiments, we used data generated from a cohort of adults with latent infection ( n  = 20) and active pulmonary disease ( n  = 22) from South Africa [ 56 ]. For the analysis of 75 antibody features, linear regression was conducted to assess the association between diagnosis and antibody feature, while controlling for age and gender. For the thirteen features exceeding a false discovery rate threshold of 10%, the partial correlation coefficient of 0.50 or higher was observed between diagnosis and antibody feature. Using this estimate as the effect size of biologically active antibody features, 68 individuals in an independent cohort (34 LTB, 34 ATB) would provide a statistical power of 80% to observe significant differences in top antibody features between tuberculosis infection and disease at an alpha level of 0.0005. This alpha level represents the threshold for significance required by the Bonferroni-Holm correction method, set at 0.0005 to accommodate the testing of 100 antibody features.

Publication and dissemination policy

Findings of this study will be disseminated through peer-reviewed journals, scientific conferences, and other relevant platforms. Participants will receive a summary of the results. All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The data and related metadata underlying reported findings will be deposited in a public data repository. A data access committee will support third parties who wish to perform further research with the data. Data will be curated in the repository following accepted standards and a persistent identifier, a DOI, is created for each data set published. If intellectual property is developed, dissemination of data will occur after appropriate protections for intellectual property are put in place.

The development of reliable point-of-care tests for detecting TB infection and disease in children is crucial. Serological assays offer a promising approach, as they may be used in a point-of-care test format, making them suitable for widespread implementation in diverse settings [ 7 ]. However, there are several hurdles that need to be addressed to advance the development of TB serological assays. One challenge is the incomplete understanding of the immunogenic properties of the numerous potential antigens of M. tuberculosis , including proteins and glycolipids [ 57 ]. Our study has four main strengths. First, our study will evaluate antibodies against a broad range of protein antigens [ 41 , 45 , 46 , 58 ], as well as glycolipids that are believed to play a crucial role int the pathogenesis of M. tuberculosis [ 59 , 60 ].

Second, to overcome the challenge of potential cross-reactivity of antibodies detected in a serological assay for TB with BCG- and non-tuberculous mycobacteria-antigens [ 25 ], we will include a large range of antibodies and reduced the overlap between M. tuberculosis and BCG/non-tuberculous mycobacteria-antigens selected. Third, there exists substantial interindividual heterogeneity in the antibody response to M. tuberculosis [ 61 , 62 ]. Different individuals may react to different antigens, resulting in relatively low sensitivity but good specificity for each individual antigen serological assays [ 30 , 31 , 49 ]. To account for this heterogeneity, our analysis includes multiple antigen targets, such as cell wall fractions and total lipids, and aims at a combined interpretation of these parameters.

Finally, we will evaluate specific antibody properties, such as antibody isotypes, glycosylation patterns, and FcR binding profiles [ 12 ]. So far, IgG is the most extensively studied isotype and has shown the most promising results for use in diagnostic assays to detect TB disease in children. Other isotypes, such as IgA, have gained attention more recently, as these have a protective role in human and animal studies in preventing TB infection [ 63 , 64 ]. Glycosylation of the Fc region affects the binding affinity of the antibody to the FcRs. Notably, distinct glycosylation patterns have been associated with various stages of TB disease and infection [ 11 ]. Lastly, our data analysis is stratified across distinct age groups to accommodate the dynamic nature of TB disease during various developmental stages of children.

The findings of our study will improve our understanding of the human humoral immune response to M. tuberculosis infection and disease and holds the potential to pave the way for designing antibody-based assays with high performance characteristic for use in children.

Data availability

Data supporting this study protocol is comprehensively presented within the manuscript. For additional details or inquiries regarding the dataset, kindly reach out to the Corresponding Author, Prof. Nicole Ritz, MD/PhD, [email protected].

Abbreviations

Area under the curve

Bacillus Calmette-Guérin

Childhood tuberculosis in Switzerland study

Fragmented crystallizable region (Fc) receptor

Interferon-γ release assay

Mycobacterium tuberculosis

Nuclear acid amplification testing

least absolute shrinkage operator

Procalcitonin guidance to reduce antibiotic treatment of lower respiratory tract infections in children and adolescents study

The Spanish Pediatric Tuberculosis Research Network

Receiver operating characteristic

Tuberculosis

Tuberculin skin test

World Health Organization

Swaminathan S, Rekha B. Pediatric tuberculosis: global overview and challenges. Clin Infect Diseases: Official Publication Infect Dis Soc Am. 2010;50(Suppl 3):S184–94.

Article   Google Scholar  

Nejat S, Buxbaum C, Eriksson M, Pergert M, Bennet R. Pediatric tuberculosis in Stockholm: a mirror to the world. Pediatr Infect Dis J. 2012;31(3):224–7.

Article   PubMed   Google Scholar  

Oesch Nemeth G, Nemeth J, Altpeter E, Ritz N. Epidemiology of childhood tuberculosis in Switzerland between 1996 and 2011. Eur J Pediatrics. 2014;173(4):457–62.

Oliwa JN, Karumbi JM, Marais BJ, Madhi SA, Graham SM. Tuberculosis as a cause or comorbidity of childhood pneumonia in tuberculosis-endemic areas: a systematic review. Lancet Respir Med. 2015;3(3):235–43.

Steiner P, Rao M, Victoria MS, Jabbar H, Steiner M. Persistently negative tuberculin reactions: their presence among children with culture positive for Mycobacterium tuberculosis (tuberculin-negative tuberculosis). Am J Dis Child. 1980;134(8):747–50.

Article   CAS   PubMed   Google Scholar  

Sun L, Chen Y, Yi P, Yang L, Yan Y, Zhang K, et al. Serological detection of mycobacterium tuberculosis complex infection in multiple hosts by one universal ELISA. PLoS ONE. 2021;16(10):e0257920.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Vaezipour N, Fritschi N, Brasier N, Belard S, Dominguez J, Tebruegge M et al. Towards accurate point-of-care tests for tuberculosis in children. Pathogens. 2022;11(3).

WHO consolidated guidelines on tuberculosis. Geneva: World Health Organization; 2022.

Commercial Serodiagnostic Tests for Diagnosis of Tuberculosis. Policy Statement: World Health Organisation; 2011.

Neudecker Daniela PL, Tebruegge M, Lu L, Ritz N. Fritschi Nora. Serology to Diagnose Tuberculosis in Children - a narrative Review on Advances and current Performance. 2023.

Carpenter SM, Lu LL, Leveraging Antibody B. Cell and Fc receptor interactions to understand heterogeneous immune responses in tuberculosis. Front Immunol. 2022;13:830482.

Nziza N, Cizmeci D, Davies L, Irvine EB, Jung W, Fenderson BA, et al. Defining discriminatory antibody fingerprints in active and latent tuberculosis. Front Immunol. 2022;13:856906.

Lu LL, Das J, Grace PS, Fortune SM, Restrepo BI, Alter G. Antibody fc glycosylation discriminates between latent and active tuberculosis. J Infect Dis. 2020;222(12):2093–102.

Kissling M, Fritschi N, Baumann P, Buettcher M, Bonhoeffer J, Naranbhai V, et al. Monocyte, lymphocyte and neutrophil ratios - easy-to-use biomarkers for the diagnosis of pediatric tuberculosis. Pediatr Infect Dis J. 2023;42(6):520–7.

Article   PubMed   PubMed Central   Google Scholar  

Meier NR, Sutter TM, Jacobsen M, Ottenhoff THM, Vogt JE, Ritz N. Machine learning algorithms evaluate immune response to novel mycobacterium tuberculosis antigens for diagnosis of tuberculosis. Front Cell Infect Microbiol. 2020;10:594030.

Hernanz-Lobo A, Noguera-Julian A, Minguell L, Lopez-Suarez A, Soriano-Arandes A, Espiau M, et al. Prevalence and clinical characteristics of children with nonsevere tuberculosis in Spain. Pediatr Infect Dis J. 2023;42(10):837–43.

Baer G, Baumann P, Buettcher M, Heininger U, Berthet G, Schafer J, et al. Procalcitonin guidance to reduce antibiotic treatment of lower respiratory tract infection in children and adolescents (ProPAED): a randomized controlled trial. PLoS ONE. 2013;8(8):e68419.

Graham SM, Cuevas LE, Jean-Philippe P, Browning R, Casenghi M, Detjen AK, et al. Clinical case definitions for classification of intrathoracic tuberculosis in children: an update. Clin Infect Dis. 2015;61Suppl(3):S179–87.

Tuberculosis. in Switzerland - Guidance for helathycare professionals2121.

Baquero-Artigao F, Del Rosal T, Falcon-Neyra L, Ferreras-Antolin L, Gomez-Pastrana D, Hernanz-Lobo A, et al. Update on the diagnosis and treatment of tuberculosis. Pediatr (Engl Ed). 2023;98(6):460–9.

Google Scholar  

Cuevas LE, Browning R, Bossuyt P, Casenghi M, Cotton MF, Cruz AT, et al. Evaluation of tuberculosis diagnostics in children: 2. Methodological issues for conducting and reporting research evaluations of tuberculosis diagnostics for intrathoracic tuberculosis in children. consensus from an expert panel. J Infect Dis. 2012;205(Suppl 2):S209–15.

Basu Roy R, Whittaker E, Seddon JA, Kampmann B. Tuberculosis susceptibility and protection in children. Lancet Infect Dis. 2019;19(3):e96–108.

Marais BJ, Gie RP, Schaaf HS, Hesseling AC, Obihara CC, Nelson LJ, et al. The clinical epidemiology of childhood pulmonary tuberculosis: a critical review of literature from the pre-chemotherapy era. Int J Tuberc Lung Dis. 2004;8(3):278–85.

CAS   PubMed   Google Scholar  

Seddon JA, Chiang SS, Esmail H, Coussens AK. The wonder years: what can primary school children teach us about immunity to mycobacterium tuberculosis? Front Immunol. 2018;9:2946.

Achkar JM, Ziegenbalg A. Antibody responses to mycobacterial antigens in children with tuberculosis: challenges and potential diagnostic value. Clin Vaccine Immunol. 2012;19(12):1898–906.

Araujo Z, Waard JH, Fernandez de Larrea C, Lopez D, Fandino C, Maldonado A, et al. Study of the antibody response against mycobacterium tuberculosis antigens in Warao Amerindian children in Venezuela. Mem Inst Oswaldo Cruz. 2004;99(5):517–24.

Dayal R, Sirohi G, Singh MK, Mathur PP, Agarwal BM, Katoch VM, et al. Diagnostic value of Elisa serological tests in childhood tuberculosis. J Trop Pediatr. 2006;52(6):433–7.

Narayana Y, Joshi B, Katoch VM, Mishra KC, Balaji KN. Differential B-cell responses are induced by mycobacterium tuberculosis PE antigens Rv1169c, Rv0978c, and Rv1818c. Clin Vaccine Immunol. 2007;14(10):1334–41.

Simonney N, Bourrillon A, Lagrange PH. Analysis of circulating immune complexes (CICs) in childhood tuberculosis: levels of specific antibodies to glycolipid antigens and relationship with serum antibodies. Int J Tuberc Lung Dis. 2000;4(2):152–60.

Kumar G, Dagur PK, Singh M, Yadav VS, Dayal R, Singh HB, et al. Diagnostic potential of Ag85C in comparison to various secretory antigens for childhood tuberculosis. Scand J Immunol. 2008;68(2):177–83.

Nonyane BAS, Nicol MP, Andreas NJ, Rimmele S, Schneiderhan-Marra N, Workman LJ, et al. Serologic responses in childhood pulmonary tuberculosis. Pediatr Infect Dis J. 2018;37(1):1–9.

Kasempimolporn S, Thaveekarn W, Kerdpanich P, Skulpichetrat U, Saekhow O, Boonchang S, et al. Performance of a rapid strip test for the serologic diagnosis of latent tuberculosis in children. J Clin Diagn Res. 2015;9(1):DC11–4.

PubMed   PubMed Central   Google Scholar  

Kasempimolporn S, Thaveekarn W, Promrungreang K, Khow O, Boonchang S, Sitprija V. Improved serodiagnostic sensitivity of strip test for latent tuberculosis. J Clin Diagn Res. 2017;11(6):DC01–3.

CAS   PubMed   PubMed Central   Google Scholar  

Awoniyi DO, Baumann R, Chegou NN, Kriel B, Jacobs R, Kidd M, et al. Detection of a combination of serum IgG and IgA antibodies against selected mycobacterial targets provides promising diagnostic signatures for active TB. Oncotarget. 2017;8(23):37525–37.

Brock M, Hanlon D, Zhao M, Pollock NR. Detection of mycobacterial lipoarabinomannan in serum for diagnosis of active tuberculosis. Diagn Microbiol Infect Dis. 2020;96(2):114937.

He H, Oka S, Han YK, Yamamura Y, Kusunose E, Kusunose M, et al. Rapid serodiagnosis of human mycobacteriosis by ELISA using cord factor (trehalose-6,6’-dimycolate) purified from mycobacterium tuberculosis as antigen. FEMS Microbiol Immunol. 1991;3(4):201–4.

Jones A, Pitts M, Al Dulayymi JR, Gibbons J, Ramsay A, Goletti D, et al. New synthetic lipid antigens for rapid serological diagnosis of tuberculosis. PLoS ONE. 2017;12(8):e0181414.

Maekura R, Okuda Y, Nakagawa M, Hiraga T, Yokota S, Ito M, et al. Clinical evaluation of anti-tuberculous glycolipid immunoglobulin G antibody assay for rapid serodiagnosis of pulmonary tuberculosis. J Clin Microbiol. 2001;39(10):3603–8.

Rens C, Chao JD, Sexton DL, Tocheva EI, Av-Gay Y. Roles for phthiocerol dimycocerosate lipids in mycobacterium tuberculosis pathogenesis. Microbiol (Reading). 2021;167(3).

Yan ZH, Yi L, Wei PJ, Jia HY, Wang J, Wang XJ, et al. Evaluation of panels of mycobacterium tuberculosis antigens for serodiagnosis of tuberculosis. Int J Tuberc Lung Dis. 2018;22(8):959–65.

Deng J, Bi L, Zhou L, Guo SJ, Fleming J, Jiang HW, et al. Mycobacterium tuberculosis proteome microarray for global studies of protein function and immunogenicity. Cell Rep. 2014;9(6):2317–29.

Ireton GC, Greenwald R, Liang H, Esfandiari J, Lyashchenko KP, Reed SG. Identification of mycobacterium tuberculosis antigens of high serodiagnostic value. Clin Vaccine Immunol. 2010;17(10):1539–47.

Kunnath-Velayudhan S, Davidow AL, Wang HY, Molina DM, Huynh VT, Salamon H, et al. Proteome-scale antibody responses and outcome of mycobacterium tuberculosis infection in nonhuman primates and in tuberculosis patients. J Infect Dis. 2012;206(5):697–705.

Kunnath-Velayudhan S, Salamon H, Wang HY, Davidow AL, Molina DM, Huynh VT, et al. Dynamic antibody responses to the mycobacterium tuberculosis proteome. Proc Natl Acad Sci U S A. 2010;107(33):14703–8.

Li J, Wang Y, Yan L, Zhang C, He Y, Zou J, et al. Novel serological biomarker panel using protein microarray can distinguish active TB from latent TB infection. Microbes Infect. 2022;24(8):105002.

Li Z, Hu J, Liu P, Cui D, Di H, Wu S. Microarray-based selection of a serum biomarker panel that can discriminate between latent and active pulmonary TB. Sci Rep. 2021;11(1):14516.

Garay-Baquero DJ, White CH, Walker NF, Tebruegge M, Schiff HF, Ugarte-Gil C et al. Comprehensive plasma proteomic profiling reveals biomarkers for active tuberculosis. JCI Insight. 2020;5(18).

Gupta S, Bhatia R, Datta KK. Serological diagnosis of childhood tuberculosis by estimation of mycobacterial antigen 60-specific immunoglobulins in the serum. Tuber Lung Dis. 1997;78(1):21–7.

Imaz MS, Comini MA, Zerbini E, Sequeira MD, Spoletti MJ, Etchart AA, et al. Evaluation of the diagnostic value of measuring IgG, IgM and IgA antibodies to the recombinant 16-kilodalton antigen of mycobacterium tuberculosis in childhood tuberculosis. Int J Tuberc Lung Dis. 2001;5(11):1036–43.

Raja A, Ranganathan UD, Bethunaickan R, Dharmalingam V. Serologic response to a secreted and a cytosolic antigen of mycobacterium tuberculosis in childhood tuberculosis. Pediatr Infect Dis J. 2001;20(12):1161–4.

Angeloni SDS, Dunbar S, Stone V, Swift S, xMAP. Cookbook: A collection of methods and protocols for developing multiplex assays with xMAP technology. 4th Edition ed: Luminex; 2018.

Lu LL, Smith MT, Yu KKQ, Luedemann C, Suscovich TJ, Grace PS, et al. IFN-gamma-independent immune markers of mycobacterium tuberculosis exposure. Nat Med. 2019;25(6):977–87.

Schlottmann SA, Jain N, Chirmule N, Esser MT. A novel chemistry for conjugating pneumococcal polysaccharides to luminex microspheres. J Immunol Methods. 2006;309(1–2):75–85.

Grover A, Wang E, Zweig A, Ermon S. Stochastic optimization of sorting networks via continuous relaxations. arXiv Preprint arXiv:190308850. 2019.

Xie SM, Ermon S. Reparameterizable Subset Sampling via Continuous Relaxations. Proceedings of the 28th International Joint Conference on Artificial Intelligence; Macao, China: AAAI Press; 2019. pp. 3919–25.

Lu LL, Chung AW, Rosebrock TR, Ghebremichael M, Yu WH, Grace PS, et al. A functional role for antibodies in tuberculosis. Cell. 2016;167(2):433–43. e14.

Cole ST, Brosch R, Parkhill J, Garnier T, Churcher C, Harris D, et al. Deciphering the biology of mycobacterium tuberculosis from the complete genome sequence. Nature. 1998;393(6685):537–44.

Hermann C, King CG. TB or not to be: what specificities and impact do antibodies have during tuberculosis? Oxf Open Immunol. 2021;2(1).

Brennan PJ. Structure of mycobacteria: recent developments in defining cell wall carbohydrates and proteins. Rev Infect Dis. 1989;11(Suppl 2):S420–30.

Garcia-Vilanova A, Chan J, Torrelles JB. Underestimated manipulative roles of mycobacterium tuberculosis cell envelope glycolipids during infection. Front Immunol. 2019;10:2909.

Lyashchenko K, Colangeli R, Houde M, Al Jahdali H, Menzies D, Gennaro ML. Heterogeneous antibody responses in tuberculosis. Infect Immun. 1998;66(8):3936–40.

Wu X, Yang Y, Zhang J, Li B, Liang Y, Zhang C, et al. Humoral immune responses against the mycobacterium tuberculosis 38-kilodalton, MTB48, and CFP-10/ESAT-6 antigens in tuberculosis. Clin Vaccine Immunol. 2010;17(3):372–5.

Zimmermann N, Thormann V, Hu B, Kohler AB, Imai-Matsushima A, Locht C, et al. Human isotype-dependent inhibitory antibody responses against mycobacterium tuberculosis. EMBO Mol Med. 2016;8(11):1325–39.

Balu S, Reljic R, Lewis MJ, Pleass RJ, McIntosh R, van Kooten C, et al. A novel human IgA monoclonal antibody protects against tuberculosis. J Immunol. 2011;186(5):3113–9.

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Acknowledgements

We thank the local Principal Investigators of the CITRUS study: Sara Bernhard, Lisa Kottanattu, Andrea Duppenthaler, Anne Morand, Jürg Barben, Christoph Berger, Christa Relly, Isabelle Rochat, Marie Rohr, as well as of Noemi Meier and Andrea Marten for their contribution to plasma sample collection. Our gratitude extends to the investigators of the ProPAED study: Gurli Baer, Jan Bonhoeffer, Philipp Baumann, Michael Buettcher, Ulrich Heininger, Gerald Berthet, Julia Schäfer, Heiner Bucher, Daniel Trachsel, Jaques Schneider, Muriel Gambon, Diana Reppucci, Jessica Bonhoeffer, Jody Stähelin-Massik, Philipp Schuetz, Beat Mueller, Gabor Szinnai, and Urs Schaad. We also appreciate the efforts of the recruiters of the pTBred network: Mar Santos Sebastián, Marisa Navarro, Elena Rincón, Jesús Saavedra, David Aguilera, and the laboratory and biobank manager Andrea López Suarez. Special thanks go to the children and their parents for their essential participation in this study.

The CITRUS study is supported by grant from: Lunge Zürich, Bangerter Rhyner Stiftung, Swiss Lung Association, Rozalia Foundation, Draksler Foundation, Nora van Meeuwen-Häfliger Foundation. NR was supported by the University of Basel academic mid-level faculty grant. DN, NF and NR were supported by the Thomi Hopf Foundation. TS is supported by the grant #2021 − 911 of the Strategic Focal Area “Personalized Health and Related Technologies (PHRT)” of the ETH Domain (Swiss Federal Institutes of Technology). PTBred received funding to conduct this project by a competitive grant from Instituto de Salud Carlos III through the projects PI17/00711 and PI20/01607, co-financed by the European Regional Development’s funds (FEDER). The Division of Infectious Diseases and Vaccines, University Children’s Hospital, Basel, Switzerland supported the ProPAED study as an investigator-initiated trial. Lenette Lu is supported by NIH (5R01AI158858) and UTSW Disease Oriented Clinical Scholars Award. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Daniela Neudecker, Nora Fritisch & Nicole Ritz

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Thomas Sutter

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This study protocol was designed by DN, NF, LL, PL, TS, BS, MT, and NR; all authors reviewed and revised the protocol and approved the final draft.

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The studies involving human participants were reviewed and approved by the Ethikkommission Nordwestschweiz (ref: EKNZ 2016 − 01094) for the CITRUS study, by the Ethics Committee of Basel (ref: EKBB 369/08) for the ProPAED study, and by the Gregorio Marañón Ethics Committee (code 359/21) for the pTBred network. Written informed consent to participate in this study was provided by the legal guardian or next of kin of the participants.

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Neudecker, D., Fritisch, N., Sutter, T. et al. Evaluation of serological assays for the diagnosis of childhood tuberculosis disease: a study protocol. BMC Infect Dis 24 , 481 (2024). https://doi.org/10.1186/s12879-024-09359-0

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• Apple cider vinegar for weight management in Lebanese adolescents and young adults with overweight and obesity: a randomised, double-blind, placebo-controlled study
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• http://orcid.org/0000-0002-0214-242X Rony Abou-Khalil 1 ,
• Jeanne Andary 2 and
• Elissar El-Hayek 1
• 1 Department of Biology , Holy Spirit University of Kaslik , Jounieh , Lebanon
• 2 Nutrition and Food Science Department , American University of Science and Technology , Beirut , Lebanon
• Correspondence to Dr Rony Abou-Khalil, Department of Biology, Holy Spirit University of Kaslik, Jounieh, Lebanon; ronyaboukhalil{at}usek.edu.lb

Background and aims Obesity and overweight have become significant health concerns worldwide, leading to an increased interest in finding natural remedies for weight reduction. One such remedy that has gained popularity is apple cider vinegar (ACV).

Objective To investigate the effects of ACV consumption on weight, blood glucose, triglyceride and cholesterol levels in a sample of the Lebanese population.

Materials and methods 120 overweight and obese individuals were recruited. Participants were randomly assigned to either an intervention group receiving 5, 10 or 15 mL of ACV or a control group receiving a placebo (group 4) over a 12-week period. Measurements of anthropometric parameters, fasting blood glucose, triglyceride and cholesterol levels were taken at weeks 0, 4, 8 and 12.

Results Our findings showed that daily consumption of the three doses of ACV for a duration of between 4 and 12 weeks is associated with significant reductions in anthropometric variables (weight, body mass index, waist/hip circumferences and body fat ratio), blood glucose, triglyceride and cholesterol levels. No significant risk factors were observed during the 12 weeks of ACV intake.

Conclusion Consumption of ACV in people with overweight and obesity led to an improvement in the anthropometric and metabolic parameters. ACV could be a promising antiobesity supplement that does not produce any side effects.

• Weight management
• Lipid lowering

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information.

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https://doi.org/10.1136/bmjnph-2023-000823

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WHAT IS ALREADY KNOWN ON THIS TOPIC

Recently, there has been increasing interest in alternative remedies to support weight management, and one such remedy that has gained popularity is apple cider vinegar (ACV).

A few small-scale studies conducted on humans have shown promising results, with ACV consumption leading to weight loss, reduced body fat and decreased waist circumference.

WHAT THIS STUDY ADDS

No study has been conducted to investigate the potential antiobesity effect of ACV in the Lebanese population. By conducting research in this demographic, the study provides region-specific data and offers a more comprehensive understanding of the impact of ACV on weight loss and metabolic health.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

The results might contribute to evidence-based recommendations for the use of ACV as a dietary intervention in the management of obesity.

The study could stimulate further research in the field, prompting scientists to explore the underlying mechanisms and conduct similar studies in other populations.

Introduction

Obesity is a growing global health concern characterised by excessive body fat accumulation, often resulting from a combination of genetic, environmental and lifestyle factors. 1 It is associated with an increased risk of numerous chronic illnesses such as type 2 diabetes, cardiovascular diseases, several common cancers and osteoarthritis. 1–3

According to the WHO, more than 1.9 billion adults were overweight worldwide in 2016, of whom more than 650 million were obese. 4 Worldwide obesity has nearly tripled since 1975. 4 The World Obesity Federation’s 2023 Atlas predicts that by 2035 more than half of the world’s population will be overweight or obese. 5

According to the 2022 Global Nutrition Report, Lebanon has made limited progress towards meeting its diet-related non-communicable diseases target. A total of 39.9% of adult (aged ≥18 years) women and 30.5% of adult men are living with obesity. Lebanon’s obesity prevalence is higher than the regional average of 10.3% for women and 7.5% for men. 6 In Lebanon, obesity was considered as the most important health problem by 27.6% and ranked fifth after cancer, cardiovascular, smoking and HIV/AIDS. 7

In recent years, there has been increasing interest in alternative remedies to support weight management, and one such remedy that has gained popularity is apple cider vinegar (ACV), which is a type of vinegar made by fermenting apple juice. ACV contains vitamins, minerals, amino acids and polyphenols such as flavonoids, which are believed to contribute to its potential health benefits. 8 9

It has been used for centuries as a traditional remedy for various ailments and has recently gained attention for its potential role in weight management.

In hypercaloric-fed rats, the daily consumption of ACV showed a lower rise in blood sugar and lipid profile. 10 In addition, ACV seems to decrease oxidative stress and reduces the risk of obesity in male rats with high-fat consumption. 11

A few small-scale studies conducted on humans have shown promising results, with ACV consumption leading to weight loss, reduced body fat and decreased waist circumference. 12 13 In fact, It has been suggested that ACV by slowing down gastric emptying, might promote satiety and reduce appetite. 14–16 Furthermore, ACV intake seems to ameliorate the glycaemic and lipid profile in healthy adults 17 and might have a positive impact on insulin sensitivity, potentially reducing the risk of type 2 diabetes. 8 10 18

Unfortunately, the sample sizes and durations of these studies were limited, necessitating larger and longer-term studies for more robust conclusions.

This work aims to study the efficacy and safety of ACV in reducing weight and ameliorating the lipid and glycaemic profiles in a sample of overweight and obese adolescents and young adults of the Lebanese population. To the best of our knowledge, no study has been conducted to investigate the potential antiobesity effect of ACV in the Lebanese population.

Materials and methods

Participants.

A total of 120 overweight and obese adolescents and young adults (46 men and 74 women) were enrolled in the study and assigned to either placebo group or experimental groups (receiving increasing doses of ACV).

The subjects were evaluated for eligibility according to the following inclusion criteria: age between 12 and 25 years, BMIs between 27 and 34 kg/m 2 , no chronic diseases, no intake of medications, no intake of ACV over the past 8 weeks prior to the beginning of the study. The subjects who met the inclusion criteria were selected by convenient sampling technique. Those who experienced heartburn due to vinegar were excluded.

Demographic, clinical data and eating habits were collected from all participants by self-administered questionnaire.

Study design

This study was a double-blind, randomised clinical trial conducted for 12 weeks.

Subjects were divided randomly into four groups: three treatment groups and a placebo group. A simple randomisation method was employed using the randomisation allocation software. Groups 1, 2 and 3 consumed 5, 10 and 15 mL, respectively, of ACV (containing 5% of acetic acid) diluted in 250 mL of water daily, in the morning on an empty stomach, for 12 weeks. The control group received a placebo consisting of water with similar taste and appearance. In order to mimic the taste of vinegar, the placebo group’s beverage (250 mL of water) contained lactic acid (250 mg/100 mL). Identical-looking ACV and placebo bottles were used and participants were instructed to consume their assigned solution without knowing its identity. The subject’s group assignment was withheld from the researchers performing the experiment.

Subjects consumed their normal diets throughout the study. The contents of daily meals and snacks were recorded in a diet diary. The physical activity of the subjects was also recorded. Daily individual phone messages were sent to all participants to remind them to take the ACV or the placebo. A mailing group was also created. Confidentiality was maintained throughout the procedure.

At weeks 0, 4, 8 and 12, anthropometric measurements were taken for all participants, and the level of glucose, triglycerides and total cholesterol was assessed by collecting 5 mL of fasting blood from each subject.

Anthropometric measurements

Body weight was measured in kg, to the nearest 0.01 kg, by standardised and calibrated digital scale. Height was measured in cm, to the nearest 0.1 cm, by a stadiometer. Anthropometric measurements were taken for all participants, by a team of trained field researchers, after 10–12 hours fast and while wearing only undergarments.

Body mass indices (BMIs) were calculated using the following equation:

The waist circumference measurement was taken between the lowest rib margin and the iliac crest while the subject was in a standing position (to the nearest 0.1 cm). Hip circumference was measured at the widest point of the hip (to the nearest 0.1 cm).

The body fat ratio (BFR) was measured by the bioelectrical impedance analysis method (OMRON Fat Loss Monitor, Model No HBF-306C; Japan). Anthropometric variables are shown in table 1 .

• View inline

Baseline demographic, anthropometric and biochemical variables of the three apple cider vinegar groups (group 1, 2 and 3) and the placebo group (group 4)

Blood biochemical analysis

Serum glucose was measured by the glucose oxidase method. 19 Triglyceride levels were determined using a serum triglyceride determination kit (TR0100, Sigma-Aldrich). Cholesterol levels were determined using a cholesterol quantitation kit (MAK043, Sigma-Aldrich). Biochemical variables are shown in table 1 .

Statistical methods and data analysis

Data are presented as mean±SD. Statistical analyses were performed using Statistical Package for the Social Sciences (SPSS) software (version 23.0). Significant differences between groups were determined by using an independent t-test. Statistical significance was set at p<0.05.

Ethical approval

The study protocol was reviewed and approved by the research ethics committee (REC) of the Higher Centre for Research (HCR) at The Holy Spirit University of Kaslik (USEK), Lebanon. The number/ID of the approval is HCR/EC 2023–005. The participants were informed of the study objectives and signed a written informed consent before enrolment. The study was conducted in accordance to the International Conference and Harmonisation E6 Guideline for Good Clinical Practice and the Ethical principles of the Declaration of Helsinki.

Sociodemographic, nutritional and other baseline characteristics of the participants

A total of 120 individuals (46 men and 74 women) with BMIs between 27 and 34 kg/m 2 , were enrolled in the study. The mean age of the subjects was 17.8±5.7 years and 17.6±5.4 years in the placebo and experimental groups respectively.

The majority of participants, approximately 98.3%, were non-vegetarian and 89% of them reported having a high eating frequency, with more than four meals per day. Eighty-seven per cent had no family history of obesity and 98% had no history of childhood obesity. The majority reported not having a regular exercise routine and experiencing negative emotions or anxiety. All participants were non-smokers and non-drinkers. A small percentage (6.7%) were following a therapeutic diet.

Effects of ACV intake on anthropometric variables

The addition of 5 mL, 10 mL or 15 mL of ACV to the diet resulted in significant decreases in body weight and BMI at weeks 4, 8 and 12 of ACV intake, when compared with baseline (week 0) (p<0.05). The decrease in body weight and BMI seemed to be dose-dependent, with the group receiving 15 mL of ACV showing the most important reduction ( table 2 ).

Anthropometric variables of the participants at weeks 0, 4, 8 and 12

The impact of ACV on body weight and BMI seems to be time-dependent as well. Reductions were more pronounced as the study progressed, with the most significant changes occurring at week 12.

The circumferences of the waist and hip, along with the Body Fat Ratio (BFR), decreased significantly in the three treatment groups at weeks 8 and 12 compared with week 0 (p<0.05). No significant effect was observed at week 4, compared with baseline (p>0.05). The effect of ACV on these parameters seems to be time-dependent with the most prominent effect observed at week 12 compared with week 4 and 8. However it does not seem to be dose dependent, as the three doses of ACV showed a similar level of efficacy in reducing the circumferences of the waist/hip circumferences and the BFR at week 8 and 12, compared with baseline ( table 2 ).

The placebo group did not experience any significant changes in the anthropometric variables throughout the study (p>0.05). This highlights that the observed improvements in body weight, BMI, waist and hip circumferences and Body Fat Ratio were likely attributed to the consumption of ACV.

Effects of ACV on blood biochemical parameters

The consumption of ACV also led to a time and dose dependent decrease in serum glucose, serum triglyceride and serum cholesterol levels. ( table 3 ).

Biochemical variables of the participants at weeks 0, 4, 8 and 12

Serum glucose levels decreased significantly by three doses of ACV at week 4, 8 and 12 compared with week 0 (p<0.05) ( table 3 ). Triglycerides and total cholesterol levels decreased significantly at weeks 8 and 12, compared with week 0 (p<0.05). A dose of 15 mL of ACV for a duration of 12 weeks seems to be the most effective dose in reducing these three blood biochemical parameters.

There were no changes in glucose, triglyceride and cholesterol levels in the placebo groups at weeks 4, 8 and 12 compared with week 0 ( table 3 ).

These data suggest that continued intake of 15 mL of ACV for more than 8 weeks is effective in reducing blood fasting sugar, triglyceride and total cholesterol levels in overweight/obese people.

Adverse reactions of ACV

No apparent adverse or harmful effects were reported by the participants during the 12 weeks of ACV intake.

During the past two decades of the last century, childhood and adolescent obesity have dramatically increased healthcare costs. 20 21 Diet and exercise are the basic elements of weight loss. Many complementary therapies have been promoted to treat obesity, but few are truly beneficial.

The present study is the first to investigate the antiobesity effectiveness of ACV, the fermented juice from crushed apples, in the Lebanese population.

A total of 120 overweight and obese adolescents and young adults (46 men and 74 women) with BMIs between 27 and 34 kg/m 2 , were enrolled. Participants were randomised to receive either a daily dose of ACV (5, 10 or 15 mL) or a placebo for a duration of 12 weeks.

Some previous studies have suggested that taking ACV before or with meals might help to reduce postprandial blood sugar levels, 22 23 but in our study, participants took ACV in the morning on an empty stomach. The choice of ACV intake timing was motivated by the aim to study the impact of apple cider vinegar without the confounding variables introduced by simultaneous food intake. In addition, taking ACV before meals could better reduce appetite and increase satiety.

Our findings reveal that the consumption of ACV in people with overweight and obesity led to an improvement in the anthropometric and metabolic parameters.

It is important to note that the diet diary and physical activity did not differ among the three treatment groups and the placebo throughout the whole study, suggesting that the decrease in anthropometric and biochemical parameters was caused by ACV intake.

Studies conducted on animal models often attribute these effects to various mechanisms, including increased energy expenditure, improved insulin sensitivity, appetite and satiety regulation.

While vinegar is composed of various ingredients, its primary component is acetic acid (AcOH). It has been shown that after 15 min of oral ingestion of 100 mL vinegar containing 0.75 g acetic acid, the serum acetate levels increases from 120 µmol/L at baseline to 350 µmol/L 24 ; this fast increase in circulatory acetate is due to its fast absorption in the upper digestive tract. 24 25

Biological action of acetate may be mediated by binding to the G-protein coupled receptors (GPRs), including GPR43 and GPR41. 25 These receptors are expressed in various insulin-sensitive tissues, such as adipose tissue, 26 skeletal muscle, liver, 27 and pancreatic beta cells, 28 but also in the small intestine and colon. 29 30

Yamashita and colleagues have revealed that oral administration of AcOH to type 2 diabetic Otsuka Long-Evans Tokushima Fatty rats, improves glucose tolerance and reduces lipid accumulation in the adipose tissue and liver. This improvement in obesity-linked type 2 diabetes is due to the capacity of AcOH to inhibit the activity of carbohydrate-responsive, element-binding protein, a transcription factor involved in regulating the expression of lipogenic genes such as fatty acid synthase and acetyl-CoA carboxylase. 26 31 Sakakibara and colleagues, have reported that AcOH, besides inhibiting lipogenesis, reduces the expression of genes involved in gluconeogenesis, such as glucose-6-phosphatase. 32 The effect of AcOH on lipogenesis and gluconeogenesis is in part mediated by the activation of 5'-AMP-activated protein kinase in the liver. 32 This enzyme seems to be an important pharmacological target for the treatment of metabolic disorders such as obesity, type 2 diabetes and hyperlipidaemia. 32 33

5'-AMP-activated protein kinase is also known to stimulate fatty acid oxidation, thereby increasing energy expenditure. 32 33 These data suggest that the effect of ACV on weight and fat loss may be partly due to the ability of AcOH to inhibit lipogenesis and gluconeogenesis and activate fat oxidation.

Animal studies suggest that besides reducing energy expenditure, acetate may also reduce energy intake, by regulating appetite and satiety. In mice, an intraperitoneal injection of acetate significantly reduced food intake by activating vagal afferent neurons. 32–34 It is important to note that animal studies done on the effect of acetate on vagal activation are contradictory. This might be due to the site of administration of acetate and the use of different animal models.

In addition, in vitro and in vivo animal model studies suggest that acetate increases the secretion of gut-derived satiety hormones by enter endocrine cells (located in the gut) such as GLP-1 and PYY hormones. 25 32–35

Human studies related to the effect of vinegar on body weight are limited.

In accordance with our study, a randomised clinical trial conducted by Khezri and his colleagues has shown that daily consumption of 30 mL of ACV for 12 weeks significantly reduced body weight, BMI, hip circumference, Visceral Adiposity Index and appetite score in obese subjects subjected to a restricted calorie diet, compared with the control group (restricted calorie diet without ACV). Furthermore, Khezri and his colleagues showed that plasma triglyceride and total cholesterol levels significantly decreased, and high density lipoprotein cholesterol concentration significantly increased, in the ACV group in comparison with the control group. 13 32–34

Similarly, Kondo and his colleagues showed that daily consumption of 15 or 30 mL of ACV for 12 weeks reduced body weight, BMI and serum triglyceride in a sample of the Japanese population. 12 13 32–34

In contrast, Park et al reported that daily consumption of 200 mL of pomegranate vinegar for 8 weeks significantly reduced total fat mass in overweight or obese subjects compared with the control group without significantly affecting body weight and BMI. 36 This contradictory result could be explained by the difference in the percentage of acetate and other potentially bioactive compounds (such as flavonoids and other phenolic compounds) in different vinegar types.

In Lebanon, the percentage of the population with a BMI of 30 kg/m 2 or more is approximately 32%. The results of the present study showed that in obese Lebanese subjects who had BMIs ranging from 27 and 34 kg/m 2 , daily oral intake of ACV for 12 weeks reduced the body weight by 6–8 kg and BMIs by 2.7–3.0 points.

It would be interesting to investigate in future studies the effect of neutralised acetic acid on anthropometric and metabolic parameters, knowing that acidic substances, including acetic acid, could contribute to enamel erosion over time. In addition to promoting oral health, neutralising the acidity of ACV could improve its taste, making it more palatable. Furthermore, studying the effects of ACV on weight loss in young Lebanese individuals provides valuable insights, but further research is needed for a comprehensive understanding of how the effect of ACV might vary across different age groups, particularly in older populations and menopausal women.

The findings of this study indicate that ACV consumption for 12 weeks led to significant reduction in anthropometric variables and improvements in blood glucose, triglyceride and cholesterol levels in overweight/obese adolescents/adults. These results suggest that ACV might have potential benefits in improving metabolic parameters related to obesity and metabolic disorders in obese individuals. The results may contribute to evidence-based recommendations for the use of ACV as a dietary intervention in the management of obesity. The study duration of 12 weeks limits the ability to observe long-term effects. Additionally, a larger sample size would enhance the generalisability of the results.

Ethics statements

Patient consent for publication.

Consent obtained from parent(s)/guardian(s)

Ethics approval

This study involves human participants and was approved by the research ethics committee of the Higher Center for Research (HCR) at The Holy Spirit University of Kaslik (USEK), Lebanon. The number/ID of the approval is HCR/EC 2023-005. Participants gave informed consent to participate in the study before taking part.

• Pandi-Perumal SR , et al
• Poirier P ,
• Bray GA , et al
• World Health Organization
• Global Nutrition Report
• Geagea AG ,
• Jurjus RA , et al
• Liao H-J , et al
• Serafin V ,
• Ousaaid D ,
• Laaroussi H ,
• Bakour M , et al
• Halima BH ,
• Sarra K , et al
• Fushimi T , et al
• Khezri SS ,
• Saidpour A ,
• Hosseinzadeh N , et al
• Montaser R , et al
• Hlebowicz J ,
• Darwiche G ,
• Björgell O , et al
• Santos HO ,
• de Moraes WMAM ,
• da Silva GAR , et al
• Pourmasoumi M ,
• Najafgholizadeh A , et al
• Walker HK ,
• Sanyaolu A ,
• Qi X , et al
• Nosrati HR ,
• Mousavi SE ,
• Sajjadi P , et al
• Johnston CS ,
• Quagliano S ,
• Sugiyama S ,
• Fushimi T ,
• Kishi M , et al
• Hernández MAG ,
• Canfora EE ,
• Jocken JWE , et al
• Le Poul E ,
• Struyf S , et al
• Goldsworthy SM ,
• Barnes AA , et al
• Priyadarshini M ,
• Fuller M , et al
• Karaki S-I ,
• Hayashi H , et al
• Karaki S-I , et al
• Yamashita H ,
• Fujisawa K ,
• Ito E , et al
• Sakakibara S ,
• Yamauchi T ,
• Oshima Y , et al
• Schimmack G ,
• Defronzo RA ,
• Goswami C ,
• Iwasaki Y ,
• Kim J , et al

Supplementary materials

• Press release

Contributors RA-K: conceptualisation, methodology, data curation, supervision, guarantor, project administration, visualisation, writing–original draft. EE-H: conceptualisation, methodology, data curation, visualisation, writing–review and editing. JA: investigation, validation, writing–review and editing.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests No, there are no competing interests.

Provenance and peer review Not commissioned; externally peer reviewed.

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