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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

Free Webinar: Research Methodology 101

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.

You Might Also Like:

Example of two research proposals (Masters and PhD-level)

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  • How to Write Your Methods

example of a research paper methodology

Ensure understanding, reproducibility and replicability

What should you include in your methods section, and how much detail is appropriate?

Why Methods Matter

The methods section was once the most likely part of a paper to be unfairly abbreviated, overly summarized, or even relegated to hard-to-find sections of a publisher’s website. While some journals may responsibly include more detailed elements of methods in supplementary sections, the movement for increased reproducibility and rigor in science has reinstated the importance of the methods section. Methods are now viewed as a key element in establishing the credibility of the research being reported, alongside the open availability of data and results.

A clear methods section impacts editorial evaluation and readers’ understanding, and is also the backbone of transparency and replicability.

For example, the Reproducibility Project: Cancer Biology project set out in 2013 to replicate experiments from 50 high profile cancer papers, but revised their target to 18 papers once they understood how much methodological detail was not contained in the original papers.

example of a research paper methodology

What to include in your methods section

What you include in your methods sections depends on what field you are in and what experiments you are performing. However, the general principle in place at the majority of journals is summarized well by the guidelines at PLOS ONE : “The Materials and Methods section should provide enough detail to allow suitably skilled investigators to fully replicate your study. ” The emphases here are deliberate: the methods should enable readers to understand your paper, and replicate your study. However, there is no need to go into the level of detail that a lay-person would require—the focus is on the reader who is also trained in your field, with the suitable skills and knowledge to attempt a replication.

A constant principle of rigorous science

A methods section that enables other researchers to understand and replicate your results is a constant principle of rigorous, transparent, and Open Science. Aim to be thorough, even if a particular journal doesn’t require the same level of detail . Reproducibility is all of our responsibility. You cannot create any problems by exceeding a minimum standard of information. If a journal still has word-limits—either for the overall article or specific sections—and requires some methodological details to be in a supplemental section, that is OK as long as the extra details are searchable and findable .

Imagine replicating your own work, years in the future

As part of PLOS’ presentation on Reproducibility and Open Publishing (part of UCSF’s Reproducibility Series ) we recommend planning the level of detail in your methods section by imagining you are writing for your future self, replicating your own work. When you consider that you might be at a different institution, with different account logins, applications, resources, and access levels—you can help yourself imagine the level of specificity that you yourself would require to redo the exact experiment. Consider:

  • Which details would you need to be reminded of? 
  • Which cell line, or antibody, or software, or reagent did you use, and does it have a Research Resource ID (RRID) that you can cite?
  • Which version of a questionnaire did you use in your survey? 
  • Exactly which visual stimulus did you show participants, and is it publicly available? 
  • What participants did you decide to exclude? 
  • What process did you adjust, during your work? 

Tip: Be sure to capture any changes to your protocols

You yourself would want to know about any adjustments, if you ever replicate the work, so you can surmise that anyone else would want to as well. Even if a necessary adjustment you made was not ideal, transparency is the key to ensuring this is not regarded as an issue in the future. It is far better to transparently convey any non-optimal methods, or methodological constraints, than to conceal them, which could result in reproducibility or ethical issues downstream.

Visual aids for methods help when reading the whole paper

Consider whether a visual representation of your methods could be appropriate or aid understanding your process. A visual reference readers can easily return to, like a flow-diagram, decision-tree, or checklist, can help readers to better understand the complete article, not just the methods section.

Ethical Considerations

In addition to describing what you did, it is just as important to assure readers that you also followed all relevant ethical guidelines when conducting your research. While ethical standards and reporting guidelines are often presented in a separate section of a paper, ensure that your methods and protocols actually follow these guidelines. Read more about ethics .

Existing standards, checklists, guidelines, partners

While the level of detail contained in a methods section should be guided by the universal principles of rigorous science outlined above, various disciplines, fields, and projects have worked hard to design and develop consistent standards, guidelines, and tools to help with reporting all types of experiment. Below, you’ll find some of the key initiatives. Ensure you read the submission guidelines for the specific journal you are submitting to, in order to discover any further journal- or field-specific policies to follow, or initiatives/tools to utilize.

Tip: Keep your paper moving forward by providing the proper paperwork up front

Be sure to check the journal guidelines and provide the necessary documents with your manuscript submission. Collecting the necessary documentation can greatly slow the first round of peer review, or cause delays when you submit your revision.

Randomized Controlled Trials – CONSORT The Consolidated Standards of Reporting Trials (CONSORT) project covers various initiatives intended to prevent the problems of  inadequate reporting of randomized controlled trials. The primary initiative is an evidence-based minimum set of recommendations for reporting randomized trials known as the CONSORT Statement . 

Systematic Reviews and Meta-Analyses – PRISMA The Preferred Reporting Items for Systematic Reviews and Meta-Analyses ( PRISMA ) is an evidence-based minimum set of items focusing  on the reporting of  reviews evaluating randomized trials and other types of research.

Research using Animals – ARRIVE The Animal Research: Reporting of In Vivo Experiments ( ARRIVE ) guidelines encourage maximizing the information reported in research using animals thereby minimizing unnecessary studies. (Original study and proposal , and updated guidelines , in PLOS Biology .) 

Laboratory Protocols has developed a platform specifically for the sharing and updating of laboratory protocols , which are assigned their own DOI and can be linked from methods sections of papers to enhance reproducibility. Contextualize your protocol and improve discovery with an accompanying Lab Protocol article in PLOS ONE .

Consistent reporting of Materials, Design, and Analysis – the MDAR checklist A cross-publisher group of editors and experts have developed, tested, and rolled out a checklist to help establish and harmonize reporting standards in the Life Sciences . The checklist , which is available for use by authors to compile their methods, and editors/reviewers to check methods, establishes a minimum set of requirements in transparent reporting and is adaptable to any discipline within the Life Sciences, by covering a breadth of potentially relevant methodological items and considerations. If you are in the Life Sciences and writing up your methods section, try working through the MDAR checklist and see whether it helps you include all relevant details into your methods, and whether it reminded you of anything you might have missed otherwise.

Summary Writing tips

The main challenge you may find when writing your methods is keeping it readable AND covering all the details needed for reproducibility and replicability. While this is difficult, do not compromise on rigorous standards for credibility!

example of a research paper methodology

  • Keep in mind future replicability, alongside understanding and readability.
  • Follow checklists, and field- and journal-specific guidelines.
  • Consider a commitment to rigorous and transparent science a personal responsibility, and not just adhering to journal guidelines.
  • Establish whether there are persistent identifiers for any research resources you use that can be specifically cited in your methods section.
  • Deposit your laboratory protocols in, establishing a permanent link to them. You can update your protocols later if you improve on them, as can future scientists who follow your protocols.
  • Consider visual aids like flow-diagrams, lists, to help with reading other sections of the paper.
  • Be specific about all decisions made during the experiments that someone reproducing your work would need to know.

example of a research paper methodology


  • Summarize or abbreviate methods without giving full details in a discoverable supplemental section.
  • Presume you will always be able to remember how you performed the experiments, or have access to private or institutional notebooks and resources.
  • Attempt to hide constraints or non-optimal decisions you had to make–transparency is the key to ensuring the credibility of your research.
  • How to Write a Great Title
  • How to Write an Abstract
  • How to Report Statistics
  • How to Write Discussions and Conclusions
  • How to Edit Your Work

The contents of the Peer Review Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

The contents of the Writing Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

There’s a lot to consider when deciding where to submit your work. Learn how to choose a journal that will help your study reach its audience, while reflecting your values as a researcher…

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15 Research Methodology Examples

research methodologies examples, explained below

Research methodologies can roughly be categorized into three group: quantitative, qualitative, and mixed-methods.

  • Qualitative Research : This methodology is based on obtaining deep, contextualized, non-numerical data. It can occur, for example, through open-ended questioning of research particiapnts in order to understand human behavior. It’s all about describing and analyzing subjective phenomena such as emotions or experiences.
  • Quantitative Research: This methodology is rationally-based and relies heavily on numerical analysis of empirical data . With quantitative research, you aim for objectivity by creating hypotheses and testing them through experiments or surveys, which allow for statistical analyses.
  • Mixed-Methods Research: Mixed-methods research combines both previous types into one project. We have more flexibility when designing our research study with mixed methods since we can use multiple approaches depending on our needs at each time. Using mixed methods can help us validate our results and offer greater predictability than just either type of methodology alone could provide.

Below are research methodologies that fit into each category.


Qualitative Research Methodologies

1. case study.

Conducts an in-depth examination of a specific case, individual, or event to understand a phenomenon.

Instead of examining a whole population for numerical trend data, case study researchers seek in-depth explanations of one event.

The benefit of case study research is its ability to elucidate overlooked details of interesting cases of a phenomenon (Busetto, Wick & Gumbinger, 2020). It offers deep insights for empathetic, reflective, and thoughtful understandings of that phenomenon.

However, case study findings aren’t transferrable to new contexts or for population-wide predictions. Instead, they inform practitioner understandings for nuanced, deep approaches to future instances (Liamputtong, 2020).

2. Grounded Theory

Grounded theory involves generating hypotheses and theories through the collection and interpretation of data (Faggiolani, n.d.). Its distinguishing features is that it doesn’t test a hypothesis generated prior to analysis, but rather generates a hypothesis or ‘theory’ that emerges from the data.

It also involves the application of inductive reasoning and is often contrasted with the hypothetico-deductive model of scientific research. This research methodology was developed by Barney Glaser and Anselm Strauss in the 1960s (Glaser & Strauss, 2009). 

The basic difference between traditional scientific approaches to research and grounded theory is that the latter begins with a question, then collects data, and the theoretical framework is said to emerge later from this data.

By contrast, scientists usually begin with an existing theoretical framework , develop hypotheses, and only then start collecting data to verify or falsify the hypotheses.

3. Ethnography

In ethnographic research , the researcher immerses themselves within the group they are studying, often for long periods of time.

This type of research aims to understand the shared beliefs, practices, and values of a particular community by immersing the researcher within the cultural group.

Although ethnographic research cannot predict or identify trends in an entire population, it can create detailed explanations of cultural practices and comparisons between social and cultural groups.

When a person conducts an ethnographic study of themselves or their own culture, it can be considered autoethnography .

Its strength lies in producing comprehensive accounts of groups of people and their interactions.

Common methods researchers use during an ethnographic study include participant observation , thick description, unstructured interviews, and field notes vignettes. These methods can provide detailed and contextualized descriptions of their subjects.

Example Study

Liquidated: An Ethnography of Wall Street by Karen Ho involves an anthropologist who embeds herself with Wall Street firms to study the culture of Wall Street bankers and how this culture affects the broader economy and world.

4. Phenomenology

Phenomenology to understand and describe individuals’ lived experiences concerning a specific phenomenon.

As a research methodology typically used in the social sciences , phenomenology involves the study of social reality as a product of intersubjectivity (the intersection of people’s cognitive perspectives) (Zahavi & Overgaard, n.d.).

This philosophical approach was first developed by Edmund Husserl.

5. Narrative Research

Narrative research explores personal stories and experiences to understand their meanings and interpretations.

It is also known as narrative inquiry and narrative analysis(Riessman, 1993).

This approach to research uses qualitative material like journals, field notes, letters, interviews, texts, photos, etc., as its data.

It is aimed at understanding the way people create meaning through narratives (Clandinin & Connelly, 2004).

6. Discourse Analysis

A discourse analysis examines the structure, patterns, and functions of language in context to understand how the text produces social constructs.

This methodology is common in critical theory , poststructuralism , and postmodernism. Its aim is to understand how language constructs discourses (roughly interpreted as “ways of thinking and constructing knowledge”).

As a qualitative methodology , its focus is on developing themes through close textual analysis rather than using numerical methods. Common methods for extracting data include semiotics and linguistic analysis.

7. Action Research

Action research involves researchers working collaboratively with stakeholders to address problems, develop interventions, and evaluate effectiveness.

Action research is a methodology and philosophy of research that is common in the social sciences.

The term was first coined in 1944 by Kurt Lewin, a German-American psychologist who also introduced applied research and group communication (Altrichter & Gstettner, 1993).

Lewin originally defined action research as involving two primary processes: taking action and doing research (Lewin, 1946).

Action research involves planning, action, and information-seeking about the result of the action.

Since Lewin’s original formulation, many different theoretical approaches to action research have been developed. These include action science, participatory action research, cooperative inquiry, and living educational theory among others.

Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing (Ellison & Drew, 2019) is a study conducted by a school teacher who used video games to help teach his students English. It involved action research, where he interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience, and iterated on his teaching style based on their feedback (disclaimer: I am the second author of this study).

See More: Examples of Qualitative Research

Quantitative Research Methodologies

8. experimental design.

As the name suggests, this type of research is based on testing hypotheses in experimental settings by manipulating variables and observing their effects on other variables.

The main benefit lies in its ability to manipulate specific variables to determine their effect on outcomes which is a great method for those looking for causational links in their research.

This is common, for example, in high-school science labs, where students are asked to introduce a variable into a setting in order to examine its effect.

9. Non-Experimental Design

Non-experimental design observes and measures associations between variables without manipulating them.

It can take, for example, the form of a ‘fly on the wall’ observation of a phenomenon, allowing researchers to examine authentic settings and changes that occur naturally in the environment.

10. Cross-Sectional Design

Cross-sectional design involves analyzing variables pertaining to a specific time period and at that exact moment.

This approach allows for an extensive examination and comparison of distinct and independent subjects, thereby offering advantages over qualitative methodologies such as case studies or surveys.

While cross-sectional design can be extremely useful in taking a ‘snapshot in time’, as a standalone method, it is not useful for examining changes in subjects after an intervention. The next methodology addresses this issue.

The prime example of this type of study is a census. A population census is mailed out to every house in the country, and each household must complete the census on the same evening. This allows the government to gather a snapshot of the nation’s demographics, beliefs, religion, and so on.

11. Longitudinal Design

Longitudinal research gathers data from the same subjects over an extended period to analyze changes and development.

In contrast to cross-sectional tactics, longitudinal designs examine variables more than once, over a pre-determined time span, allowing for multiple data points to be taken at different times.

A cross-sectional design is also useful for examining cohort effects , by comparing differences or changes in multiple different generations’ beliefs over time.

With multiple data points collected over extended periods ,it’s possible to examine continuous changes within things like population dynamics or consumer behavior. This makes detailed analysis of change possible.

12. Quasi-Experimental Design

Quasi-experimental design involves manipulating variables for analysis, but uses pre-existing groups of subjects rather than random groups.

Because the groups of research participants already exist, they cannot be randomly assigned to a cohort as with a true experimental design study. This makes inferring a causal relationship more difficult, but is nonetheless often more feasible in real-life settings.

Quasi-experimental designs are generally considered inferior to true experimental designs.

13. Correlational Research

Correlational research examines the relationships between two or more variables, determining the strength and direction of their association.

Similar to quasi-experimental methods, this type of research focuses on relationship differences between variables.

This approach provides a fast and easy way to make initial hypotheses based on either positive or negative correlation trends that can be observed within dataset.

Methods used for data analysis may include statistic correlations such as Pearson’s or Spearman’s.

Mixed-Methods Research Methodologies

14. sequential explanatory design (quan→qual).

This methodology involves conducting quantitative analysis first, then supplementing it with a qualitative study.

It begins by collecting quantitative data that is then analyzed to determine any significant patterns or trends.

Secondly, qualitative methods are employed. Their intent is to help interpret and expand the quantitative results.

This offers greater depth into understanding both large and smaller aspects of research questions being addressed.

The rationale behind this approach is to ensure that your data collection generates richer context for gaining insight into the particular issue across different levels, integrating in one study, qualitative exploration as well as statistical procedures.

15. Sequential Exploratory Design (QUAL→QUAN)

This methodology goes in the other direction, starting with qualitative analysis and ending with quantitative analysis.

It starts with qualitative research that delves deeps into complex areas and gathers rich information through interviewing or observing participants.

After this stage of exploration comes to an end, quantitative techniques are used to analyze the collected data through inferential statistics.

The idea is that a qualitative study can arm the researchers with a strong hypothesis testing framework, which they can then apply to a larger sample size using qualitative methods.

When I first took research classes, I had a lot of trouble distinguishing between methodologies and methods.

The key is to remember that the methodology sets the direction, while the methods are the specific tools to be used. A good analogy is transport: first you need to choose a mode (public transport, private transport, motorized transit, non-motorized transit), then you can choose a tool (bus, car, bike, on foot).

While research methodologies can be split into three types, each type has many different nuanced methodologies that can be chosen, before you then choose the methods – or tools – to use in the study. Each has its own strengths and weaknesses, so choose wisely!

Altrichter, H., & Gstettner, P. (1993). Action Research: A closed chapter in the history of German social science? Educational Action Research , 1 (3), 329–360.

Audi, R. (1999). The Cambridge dictionary of philosophy . Cambridge ; New York : Cambridge University Press.

Clandinin, D. J., & Connelly, F. M. (2004). Narrative Inquiry: Experience and Story in Qualitative Research . John Wiley & Sons.

Creswell, J. W. (2008). Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research . Pearson/Merrill Prentice Hall.

Faggiolani, C. (n.d.). Perceived Identity: Applying Grounded Theory in Libraries .

Gauch, H. G. (2002). Scientific Method in Practice . Cambridge University Press.

Glaser, B. G., & Strauss, A. L. (2009). The Discovery of Grounded Theory: Strategies for Qualitative Research . Transaction Publishers.

Kothari, C. R. (2004). Research Methodology: Methods and Techniques . New Age International.

Kuada, J. (2012). Research Methodology: A Project Guide for University Students . Samfundslitteratur.

Lewin, K. (1946). Action research and minority problems. Journal of Social Issues , 2,  4 , 34–46.

Mills, J., Bonner, A., & Francis, K. (2006). The Development of Constructivist Grounded Theory. International Journal of Qualitative Methods , 5 (1), 25–35.

Mingers, J., & Willcocks, L. (2017). An integrative semiotic methodology for IS research. Information and Organization , 27 (1), 17–36.

OECD. (2015). Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development . Organisation for Economic Co-operation and Development.

Peirce, C. S. (1992). The Essential Peirce, Volume 1: Selected Philosophical Writings (1867–1893) . Indiana University Press.

Reese, W. L. (1980). Dictionary of Philosophy and Religion: Eastern and Western Thought . Humanities Press.

Riessman, C. K. (1993). Narrative analysis . Sage Publications, Inc.

Saussure, F. de, & Riedlinger, A. (1959). Course in General Linguistics . Philosophical Library.

Thomas, C. G. (2021). Research Methodology and Scientific Writing . Springer Nature.

Zahavi, D., & Overgaard, S. (n.d.). Phenomenological Sociology—The Subjectivity of Everyday Life .


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What is Research Methodology? Definition, Types, and Examples

example of a research paper methodology

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.

Writing the methods section of a research paper? Let Paperpal help you achieve perfection  

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.

Let Paperpal help you write the perfect research methods section. Start now!

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.
  • Types of research methodology. Eduvoice website. Accessed August 16, 2023.
  • The basics of research methodology: A key to quality research. Voxco. Accessed August 16, 2023.
  • Sampling methods: Types with examples. QuestionPro website. Accessed August 16, 2023.
  • What is qualitative research? Methods, types, approaches, examples. Researcher.Life blog. Accessed August 15, 2023.
  • What is quantitative research? Definition, methods, types, and examples. Researcher.Life blog. Accessed August 15, 2023.
  • Data analysis in research: Types & methods. QuestionPro website. Accessed August 16, 2023.
  • Factors to consider while choosing the right research methodology. PhD Monster website. Accessed August 17, 2023.
  • What is research methodology? Research and writing guides. Accessed August 14, 2023.
  • Ethical considerations. Business research methodology website. Accessed August 17, 2023.

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This paper is in the following e-collection/theme issue:

Published on 21.2.2024 in Vol 26 (2024)

Effects of eHealth Interventions on 24-Hour Movement Behaviors Among Preschoolers: Systematic Review and Meta-Analysis

Authors of this article:

Author Orcid Image

  • Shan Jiang 1 , MSc   ; 
  • Johan Y Y Ng 1 , PhD   ; 
  • Kar Hau Chong 2 , PhD   ; 
  • Bo Peng 1 , MSc   ; 
  • Amy S Ha 1 , PhD  

1 Department of Sports Science and Physical Education, The Chinese University of Hong Kong, Hong Kong, China (Hong Kong)

2 School of Health and Society and Early Start, Faculty of the Arts, Social Sciences and Humanities, University of Wollongong, Wollongong, Australia

Corresponding Author:

Amy S Ha, PhD

Department of Sports Science and Physical Education

The Chinese University of Hong Kong

G05 Kwok Sports Building, Shatin, N.T.

China (Hong Kong)

Phone: 852 3943 6083

Email: [email protected]

Background: The high prevalence of unhealthy movement behaviors among young children remains a global public health issue. eHealth is considered a cost-effective approach that holds great promise for enhancing health and related behaviors. However, previous research on eHealth interventions aimed at promoting behavior change has primarily focused on adolescents and adults, leaving a limited body of evidence specifically pertaining to preschoolers.

Objective: This review aims to examine the effectiveness of eHealth interventions in promoting 24-hour movement behaviors, specifically focusing on improving physical activity (PA) and sleep duration and reducing sedentary behavior among preschoolers. In addition, we assessed the moderating effects of various study characteristics on intervention effectiveness.

Methods: We searched 6 electronic databases (PubMed, Ovid, SPORTDiscus, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials) for experimental studies with a randomization procedure that examined the effectiveness of eHealth interventions on 24-hour movement behaviors among preschoolers aged 2 to 6 years in February 2023. The study outcomes included PA, sleep duration, and sedentary time. A meta-analysis was conducted to assess the pooled effect using a random-effects model, and subgroup analyses were conducted to explore the potential effects of moderating factors such as intervention duration, intervention type, and risk of bias (ROB). The included studies underwent a rigorous ROB assessment using the Cochrane ROB tool. Moreover, the certainty of evidence was evaluated using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) assessment.

Results: Of the 7191 identified records, 19 (0.26%) were included in the systematic review. The meta-analysis comprised a sample of 2971 preschoolers, which was derived from 13 included studies. Compared with the control group, eHealth interventions significantly increased moderate to vigorous PA (Hedges g =0.16, 95% CI 0.03-0.30; P =.02) and total PA (Hedges g =0.37, 95% CI 0.02-0.72; P =.04). In addition, eHealth interventions significantly reduced sedentary time (Hedges g =−0.15, 95% CI −0.27 to −0.02; P =.02) and increased sleep duration (Hedges g =0.47, 95% CI 0.18-0.75; P =.002) immediately after the intervention. However, no significant moderating effects were observed for any of the variables assessed ( P >.05). The quality of evidence was rated as “moderate” for moderate to vigorous intensity PA and sedentary time outcomes and “low” for sleep outcomes.

Conclusions: eHealth interventions may be a promising strategy to increase PA, improve sleep, and reduce sedentary time among preschoolers. To effectively promote healthy behaviors in early childhood, it is imperative for future studies to prioritize the development of rigorous comparative trials with larger sample sizes. In addition, researchers should thoroughly examine the effects of potential moderators. There is also a pressing need to comprehensively explore the long-term effects resulting from these interventions.

Trial Registration: PROSPERO CRD42022365003;


Physical activity (PA), sedentary behavior (SB), and sleep are integrated as “24-hour movement behaviors” owing to the collective effect on daily movement patterns. The 24-hour movement paradigm acknowledges the possibility of categorizing these behaviors according to their intensity levels across a full day. This encompasses a diverse range of activities, including sleep; SB (eg, screen time, reclining, or lying down); and light, moderate, or vigorous PA [ 1 ]. Globally, the “24-hour movement behaviors” paradigm has already been recognized and adopted into movement guidelines [ 2 ]. In 2020, the World Health Organization (WHO) released guidelines on PA and SB that incorporate all 3 movement behaviors [ 3 ]. The health benefits of engaging in PA, getting the recommended sleep, and reducing sedentary time are well documented. Recent reviews have shown a positive association between PA; sleep; and a wide range of child outcomes related to mental health, cognition, and cardiometabolism [ 4 - 6 ]. In addition, it is worth mentioning that different domains of SB can have varying health effects. For instance, non–screen-based sedentary activities such as reading or studying have been associated with favorable cognitive development in children [ 7 ]. Conversely, screen-based sedentary time, also referred to as “screen time,” has been found to have adverse effects on health-related outcomes [ 8 ]. Moreover, prior research has indicated that imbalances in 24-hour movement behaviors—specifically, elevated sedentary screen time coupled with diminished levels of PA and sleep—could potentially increase the risk of depression [ 9 ] and result in poor health-related quality of life [ 10 ]. Therefore, any change in one of the movement behaviors may lead to a compensatory increase or decrease in one or both behaviors.

However, insufficient healthy levels of 24-hour movement behaviors in early childhood have remained one of the most critical global public health challenges [ 11 , 12 ]. According to the WHO guidelines [ 3 ], preschool children are recommended to engage in adequate daily PA, consisting of 180 minutes, with 60 minutes dedicated to moderate to vigorous PA (MVPA). In addition, they should ensure sufficient sleep, ranging from 10 to 13 hours, while limiting sedentary recreational screen time to no more than 60 minutes per day. Unfortunately, a significant proportion of preschoolers do not meet the PA guidelines (<50% across studies) [ 13 ]. Furthermore, previous studies have consistently demonstrated that preschoolers exceed the screen time recommendations set by the WHO. A comprehensive meta-analysis of 44 studies revealed that only 35.6% of children aged between 2 and 5 years met the guideline of limiting daily screen time to 1 hour. Moreover, when examining the integration of 24-hour movement behaviors [ 8 ], another meta-analysis discovered that only 13% of children worldwide adhere to all 3 behavior guidelines [ 14 ].

Preschoolers play a crucial role in laying the foundation for long-term physical health and overall well-being [ 15 , 16 ]. Improving PA levels, minimizing SB, and prioritizing quality sleep in young children have multiple benefits, including positively influencing their physical fitness [ 17 , 18 ], promoting the development of motor and cognitive skills [ 19 , 20 ], and preventing childhood obesity [ 21 ] and associated health issues [ 14 , 22 , 23 ]. Several studies have shown that these healthy behavior patterns can shape lifelong habits that extend from childhood through adolescence and into adulthood [ 5 , 24 ].

Although these statistics are concerning, attempts to address the issue through various interventions have yielded inconsistent findings [ 25 - 28 ]. For instance, a meta-analysis of PA intervention studies involving preschoolers revealed only small to moderate effects in enhancing PA, suggesting room for improvement in achieving the desired outcomes [ 29 ]. In a meta-analysis conducted by Fangupo et al [ 30 ], no intervention effect was observed on daytime sleep duration for young children. Interestingly, earlier research has also elucidated overflow effects stemming from interventions focusing on a specific behavior, impacting other behaviors that were not the primary target. A systematic review highlighted that interventions aimed at enhancing PA in children aged <5 years led to a reduction in screen time by approximately 32 minutes [ 31 ]. It is crucial to understand that as time is finite, the durations dedicated to PA, sedentary time, and sleep are interconnected within 24 hours. Thus, we need effective interventions for preschool children that holistically address all components of 24-hour movement behaviors.

eHealth broadly refers to a diverse array of information and communication technologies used to facilitate the delivery of health care [ 32 , 33 ]. The rapid evolution of digitalization in recent decades has led to the widespread adoption of eHealth in interventions [ 28 , 34 ]. Recent reviews [ 35 - 38 ] suggest that with the global proliferation of eHealth interventions, health promotion via these platforms is evolving to become more accessible and user-friendly, garnering acceptance among adolescents and adults. Previous reviews have underscored the effectiveness of these digital platforms in enhancing various movement behavior outcomes across diverse age groups, including children aged 6 to 12 years [ 39 ], adolescents [ 40 ], adults [ 41 ], and older adults [ 42 ]. Specifically, a meta-analysis indicated that eHealth interventions have successfully promoted PA among individuals with noncommunicable diseases [ 43 ]. Another review showed that computer, mobile, and wearable technologies have the potential to mitigate sedentary time effectively [ 41 ]. Previous studies have targeted different participant groups to investigate the impact of eHealth on sleep outcomes. Deng et al [ 44 ] conducted a meta-analysis demonstrating that eHealth interventions for adults with insomnia are effective in improving sleep and can be considered a promising treatment. Nevertheless, a review focusing on healthy adolescents found that there has not been any school-based eHealth interventions focusing on sleep outcomes [ 45 ].

Indeed, child-centered strategies such as gamification are used in some digital apps and have been shown to encourage children’s PA [ 46 - 48 ]. A considerable body of work has addressed the pivotal role of parental influence and role modeling in cultivating healthy lifestyle habits in children [ 49 , 50 ]. Physical literacy, a multidimensional concept encompassing various aspects of PA such as the affective, physical, cognitive, and behavioral dimensions, plays a vital role in enhancing PA engagement [ 51 ]. Ha et al [ 52 ] conducted a web-based parent-focused intervention, revealing that enhancing parents’ physical literacy can effectively support children’s participation in PA. By understanding and promoting physical literacy, parents can provide valuable support to their children, fostering a lifelong commitment to healthy and active lifestyles. Although eHealth interventions offer promise, there are conflicting findings regarding their impact, especially when they are parent supported and targeted at young children. A previous meta-analysis examining eHealth interventions targeted at parents found no significant impact on children’s BMI. In addition, no studies have included children aged <5 years [ 50 ]. Similarly, a recent systematic review observed that eHealth interventions aimed at parents showed no significant effectiveness in enhancing PA levels in young children [ 53 ]. However, the prevalence of digital device use in young children has become widespread. For instance, studies conducted in England (the United Kingdom), Estonia, and the United States have reported that, on average, 83% of children aged 5 years use a digital device at least once a week [ 54 ]. Research also revealed that in the United States, approximately three-fourths of children had their own mobile device by the age of 4 years, and nearly all children (96.6%) used mobile devices [ 55 ]. Consequently, there is an urgent need to harness the potential of digital platforms and explore whether they can effectively deliver interventions to preschoolers [ 56 ].

In previous research, there has been a lack of studies examining the effectiveness of eHealth behavior change interventions among preschoolers. Although a systematic review found a significant effect of digital health interventions on the PA of preschoolers [ 53 ], this review did not include sedentary time and sleep in its inclusion criteria, and there is a lack of conclusive statements owing to the insufficient number of studies, and no quantitative methods were available for synthesizing the evidence on the effectiveness of eHealth interventions. To our knowledge, no systematic review or meta-analysis has distinctly investigated the effects of eHealth interventions on 24-hour movement behaviors in preschoolers or the factors that may influence their implementation. Therefore, the aims of this study were (1) to assess the effectiveness of eHealth interventions on 24-hour movement behaviors (improving PA and sleep duration and decreasing sedentary time) and (2) to examine the moderating effects of study characteristics (eg, intervention duration, intervention type, and outcome measurement tools) on intervention effectiveness.

This review was registered with PROSPERO (CRD42022365003) and conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [ 57 ].

Eligibility Criteria

This review included trials with a randomization procedure that examined the outcomes of interventions using information and communication technology. These interventions targeted at least 1 movement behavior in preschool children aged 2 to 6 years. Studies were excluded if (1) the control groups received intervention using eHealth technology and (2) published in a non-English language. Full details are provided in Multimedia Appendix 1 [ 58 ].

Search and Selection

The following databases were systematically searched from inception to February 08, 2023: PubMed, Ovid, SPORTDiscus, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials. We used the search terms “eHealth,” “Physical activity,” “Sedentary behavior,” “Sleep,” “preschooler,” and their Medical Subject Headings terms. The complete search strategy is described in Multimedia Appendix 2 [ 59 - 61 ]. A manual search of the reference lists of the included publications was performed to identify additional eligible studies for potential inclusion. Two independent reviewers (SJ and BP) screened the titles and abstracts and subsequent full-text articles for eligibility. Discrepancies that emerged during the selection process were effectively resolved through a discussion involving 3 authors (SJ, BP, and JYYN).

Data Extraction

A comprehensive data extraction form was developed (SJ) and refined (SJ and BP) based on the Cochrane Handbook for Systematic Reviews of Interventions [ 62 ]. Extracted information included bibliographic details (authors, title, journal, and year); study details (country, design, retention rate); participants’ characteristics (number of children and demographics); intervention type (parent supported, teacher led, or child centered), intervention’s theoretical basis, duration, delivery tool, and intensity; comparison (sample size, activity type); outcomes (behavioral variables with baseline and postintervention means with SDs), and measurement tools. Regarding the categorization of intervention types, we have established a clear classification. Specifically, in child-centered interventions, children are the direct beneficiaries, participating autonomously with less guidance from guardians. This can be accomplished using an exergaming system or designed mobile health games. In parent-supported interventions, parents are involved in educational programs and instructions that improve parents’ knowledge of preschoolers’ healthy movement behaviors. A teacher-led intervention involves supervising preschoolers’ PA during school time or participating in structured PA sessions aimed at improving healthy indicators. For data that were either incomplete or absent within the main text, we sought to reach out to the respective authors through email correspondence.

Risk of Bias

The included studies were assessed for risk of bias (ROB) using the revised Cochrane ROB2 tool [ 63 ]. The following domains of bias were assessed for each study: selection (random sequence generation and allocation concealment), performance and detection (masking of participants, personnel, and assessors), deviations from intended interventions, missing outcome data, measurement of the outcome, appropriateness of analysis (selection of the reported outcome), and bias arising from period and carryover effects (for crossover studies) [ 63 ]. The studies were ranked as low risk, some concerns, or high risk for each domain. The ROB was evaluated independently by 2 authors (SJ and BP). Any discrepancies were resolved through discussions with the author (JYYN).

Outcomes and Data Synthesis

Our outcome targeted any of the following movement behaviors: PA (MVPA and total PA), sedentary time (screen time and sitting time), or sleep duration. Meta-analysis was conducted in R (version 4.2.1; R Group for Statistical Computing) using the meta , metafor , and metareg packages [ 64 ]. A random-effects model (Hartung-Knapp method) was used to calculate pooled estimates (Hedges g , a type of standardized mean difference) to account for variations in participants and measurement methods of movement behavior outcomes [ 65 ]. Multimedia Appendix 3 [ 63 - 65 ] describes the processing of missing data. Hedges g and their corresponding variances were calculated using the pre- and postintervention mean scores and SDs. However, if some studies had changes in baseline and postintervention data or if there were significant differences in their baseline data [ 59 - 61 ], we used the within-group difference in means and their SDs for intervention and control groups to calculate the effect size. Values of 0.2, 0.5, and 0.8 represent small, moderate, and large effect sizes, respectively. A positive effect size indicated a beneficial effect on the intervention group compared with the control group. The between-group heterogeneity of the synthesized effect sizes was examined using the Cochran Q test and I 2 statistics. I 2 values of 25%, 50%, and 75% indicated low, moderate, and high levels of heterogeneity, respectively. Subgroup analyses were conducted based on the following factors: (1) intervention duration (0-3 months vs >3 months) and (2) type of intervention (child centered, parent focused, or teacher led). (3) Types of outcome measurement tools (objective vs self-reported) and (4) ROB (low risk, some concerns, or high risks).

Furthermore, we performed meta-regression analyses to examine the impact of potential moderators on the overall effect size. Potential moderators included 5 variables, as specified in the subgroup analyses, and 2 continuous variables (sample size and intervention length). These variables were selected based on existing evidence that highlights their significant moderating effects on eHealth interventions targeting movement behaviors [ 53 , 66 , 67 ]. Sensitivity analyses were performed using the leave-one-out method. Publication bias was visualized using funnel plot symmetry and quantified using the Eggertest score, for which P <.05 indicates a significant publication bias [ 68 ].

Quality Assessment of the Overall Evidence

GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) 2 criteria were used to assess the certainty of evidence for the effect of eHealth interventions on the targeted outcomes [ 69 , 70 ]. The GRADE assessment was completed using GRADEpro, and the quality of evidence was classified as high (≥4 points overall), moderate (3 points), low (2 points), or very low (≤1 point) [ 70 ].

Study Selection

The database search yielded 7140 records, with an additional 51 records identified from the reference lists of relevant systematic reviews. There were 64 articles screened for full text, and 45 articles were excluded. The reasons for exclusion are listed in Multimedia Appendix 4 . A total of 19 studies reporting the effectiveness of interventions on movement behaviors were included in the systematic review [ 17 , 59 - 61 , 71 - 85 ], and 13 studies were included in the meta-analysis [ 59 - 61 , 76 - 85 ]. The PRISMA flowchart of the study selection process is shown in Figure 1 and PRISMA checklists are in Multimedia Appendices 5 and 6 .

example of a research paper methodology

Study Characteristics

The study characteristics are described in Table 1 . In the 19 studies, 2971 preschoolers from 6 regions were included. A total of 18 studies were conducted in high-income countries, and only 1 study was conducted in an upper middle–income country, according to the World Bank classification ( Multimedia Appendix 7 ) [ 86 ]. Most included studies were conducted during and after 2017. For the study design, 16 studies were 2-arm randomized controlled trials (RCTs), with 11 using a parallel group design [ 17 , 59 - 61 , 71 - 74 , 76 , 77 , 84 ], 2 being cluster RCTs [ 82 , 83 ], 2 pilot RCTs [ 79 , 81 ], and 1 crossover study [ 85 ]. The remaining 3 studies consisted of 2-arm experimental studies with a randomization procedure [ 75 , 78 , 80 ]. The sample size ranged from 34 preschoolers to 617 preschoolers. The study details are presented in Multimedia Appendices 8 and 9 [ 59 - 61 , 76 - 85 ].

a I: intervention.

b C: control.

c ECEC: early childhood education and care.

d PA: physical activity.

e SB: sedentary behavior.

f mHealth: mobile health.

g MINISTOP: mobile-based intervention intended to stop obesity in preschoolers.

h FMS: fundamental movement skills.

Intervention Details

The included studies used various delivery channels of eHealth technologies for the intervention. Seven studies used smartphone apps [ 59 - 61 , 74 ] and social media (Facebook and WhatsApp) [ 75 , 80 , 82 ]; 3 studies used an exergaming program [ 17 , 73 , 85 ]; 3 studies used the internet, with interventions including informational websites [ 83 , 84 ] and tablet computers [ 72 ]; and several studies used technology to dispatch reminders to exercise and send motivational messages encouraging persistence. Specifically, studies sent text messages and made telephone calls [ 71 , 76 - 79 , 81 ].

The intervention duration ranged from 1 week [ 78 ] to 36 months [ 77 ]. Seven studies had interventions that lasted >3 months [ 59 , 61 , 71 , 76 , 77 , 80 , 82 ]. Only 3 studies included follow-up assessment after intervention, with durations of 6 weeks [ 84 ], 3 months [ 72 ], and 6 months [ 60 ]. Regarding intervention types, this study consisted of 12 studies supported by parents [ 59 - 61 , 71 , 72 , 75 - 77 , 79 - 81 , 84 ], 3 studies led by teachers [ 78 , 82 , 83 ], and 4 studies involving eHealth interventions directed at children [ 17 , 73 , 74 , 85 ].

The comparison groups included a waitlist control group (n=4) [ 74 , 79 , 81 , 84 ], education as usual (n=7) [ 17 , 59 , 75 , 78 , 80 , 82 , 85 ], and an additional non-eHealth intervention (n=8) [ 59 - 61 , 71 - 73 , 76 , 77 ]. A total of 14 studies targeted PA [ 17 , 59 - 61 , 72 - 75 , 77 , 78 , 80 , 81 , 83 , 85 ], 12 studies targeted SB [ 59 - 61 , 71 , 76 - 80 , 82 , 84 , 85 ], and 4 studies targeted sleep duration [ 71 , 76 , 81 , 84 ]. Notably, no studies examined all 3 movement behaviors.


Meta-analyses demonstrated that eHealth interventions produced significant improvements in MVPA (Hedges g =0.16, 95% CI 0.03-0.30; P =.02; 7/13, 54%) and total PA (Hedges g =0.37, 95% CI 0.02-0.72; P =.04; 2/13, 15%), as shown in Figure 2 A [ 77 , 78 , 80 - 83 , 85 ]. For SB outcomes, another meta-analysis showed a significant decrease (Hedges g =−0.15, 95% CI −0.27 to −0.02; P =.02; 8/13, 62%), as shown in Figure 2 B [ 76 - 80 , 82 , 84 , 85 ]. Finally, meta-analysis also showed that there were significant improvements in sleep duration (Hedges g =0.47, 95% CI 0.18-0.75; P <.01; 3/13, 23%), as shown in Figure 2 C [ 76 , 81 , 84 ].

Owing to the heterogeneity among the included studies, the mobile-based intervention intended to stop obesity in preschoolers (MINISTOP) project’s 3 studies solely reported the difference in pre-to-post comparison [ 60 , 61 , 76 ]. Consequently, their inclusion in the pooled analysis with other studies was deemed inappropriate. We analyzed a series of MINISTOP studies separately and presented the findings using a forest plot. The pooled analysis indicated that no significant change in MVPA (Hedges g =−0.03, 95% CI −0.15 to 0.09; P =.66; 3/6, 50%; Multimedia Appendix 10 [ 59 - 61 , 76 - 85 ]) was observed between the intervention and control groups. An intervention effect was found in reducing SB (Hedges g =0.02, 95% CI −0.13 to 0.16; P =.83; 3/6, 50%; Multimedia Appendix 10 ) immediately after the intervention, as indicated in Multimedia Appendix 10 . Nonetheless, this effect was not statistically significant. All the results showed negligible heterogeneity ( I 2 =0).

example of a research paper methodology

Subgroup Analyses and Meta-Regression

Table 2 shows the subgroup analysis and meta-regression results of MVPA and sedentary time according to study characteristics. No significant moderating effects were observed for any of the variables assessed ( P >.05). The complete results of the subgroup analyses are presented in Multimedia Appendix 11 [ 59 - 61 , 76 - 85 ].

a MVPA: moderate to vigorous physical activity.

b N/A: not applicable.

c Teacher focused studies as a reference group.

Sensitivity Analyses and Publication Bias

Sensitivity analysis indicated that no individual study had an excessive influence on the results. The omitted meta-analytic estimates were not significantly different from those associated with the combined analysis, and all estimates were within the 95% CI. Forest plots of the sensitivity analysis for MVPA, sedentary time, and sleep are summarized in Multimedia Appendix 12 [ 59 - 61 , 76 - 85 ]. The significance of Egger’s test results provided evidence for asymmetry of the funnel plots (MVPA: t 5 =3.27; P =.02; Multimedia Appendix 13 ; sedentary time: t 6 =−3.37; P =.02; Multimedia Appendix 14 ). However, we could not distinguish chance from true asymmetry using the funnel plot asymmetry test because <10 studies were included in our meta-analysis [ 86 ].

ROB of Studies

Multimedia Appendix 15 [ 59 - 61 , 76 - 85 ] summarizes the overall ROB assessment for all the included papers. Six studies were considered to have a low ROB [ 59 , 74 , 76 , 77 , 79 , 85 ], and the remaining 13 were considered to have some concerns regarding the ROB [ 17 , 60 , 61 , 71 - 73 , 75 , 78 , 80 - 84 ]. Furthermore, 7 studies did not disclose randomization methods clearly [ 17 , 72 , 75 , 78 , 80 , 82 , 83 ], so they were rated as having some concerns about random sequence generation. All studies were rated as having a low risk for the measurement of outcomes based on the use of objective measurement tools or reliable questionnaires in each study. Four studies were rated as ‘some concerns’ of reporting bias because neither published study protocols nor registered trial records were presented [ 72 , 75 , 78 , 80 ].

Quality of the Evidence

The GRADE scores are shown in Multimedia Appendix 16 , and we deemed the overall quality of evidence to be moderate to low. The quality of evidence for MVPA and sedentary time outcomes was rated as “moderate,” considering the low ROB, absence of heterogeneity in participants’ outcomes, and high precision in results. As eHealth interventions are often combined with other intervention approaches, all evaluations of directness were assessed as “Indirectness.” There were high imprecisions with the sample size included in the study for total PA and sleep, which were graded as “Low.”

Principal Findings

This study systematically reviewed the effectiveness of eHealth interventions targeting 24-hour movement behaviors among preschool-aged children. Most studies assessed interventions aimed at increasing PA and decreasing SB. Few studies targeted sleep, and no studies have addressed a combination of all 24-hour movement behaviors. Overall, these studies showed trends supporting the effectiveness of eHealth interventions in increasing PA and sleep duration and reducing sedentary time immediately after the intervention; however, only short-term effects were found, and all trials were judged to be of low to moderate quality.

This review demonstrates a small positive effect of eHealth interventions targeting increases in preschooler’s MVPA (Hedges g =0.16) and total PA (Hedges g =0.37) immediately after the intervention. One possible explanation could be that eHealth interventions, while providing new opportunities for PA, might not be sufficient to result in significant overall activity increases. This might require expanding activity opportunities, extending new activity options, and enhancing broader activity strategies to achieve substantial benefits. Our findings echo the argument made in a previous study of young children that PA interventions had a small effect on MVPA [ 87 ]. Another meta-analysis found a positive impact of PA interventions with small to moderate effects on total PA (Hedges g =0.44) and moderate effects on MVPA (Hedges g =0.51) [ 29 ]. There is no conclusive explanation as to why MVPA and total PA were seen to have a smaller effect in our study, but this could be attributed to most interventions thus far concentrating on devising PA programs of diverse intensities without distinct objectives, including low-intensity PA, MVPA, and total PA (eg, activities such as outdoor active play and structured gross motor activity sessions in childcare environments). Moreover, our results are consistent with previous review findings that digital platforms can potentially increase PA among preschoolers [ 53 ]. Hence, future interventions should aim to optimize their effectiveness in increasing PA among young children. In addition, further research is warranted to investigate the mechanisms of the changes associated with these PA outcomes. This will help enhance the size and sustainability of the effects observed in eHealth interventions.

We found no significant improvement in MVPA for mobile app interventions (MINISTOP project). This is in contrast to a review of studies focusing on mobile apps and technologies, which highlighted the significant potential to enhance PA [ 88 ]. It is worth noting that the MINISTOP project aimed to reduce obesity as its primary outcome rather than targeting MVPA. In addition, studies concentrating solely on educating parents without implementing direct interventions for children have not achieved the desired enhancements in MVPA. Thus, we cannot draw conclusions about mobile apps because few intervention studies have used these means of communication for young children and their guardians. Given the small number of studies included in our meta-analysis, the positive, negative, and null findings of the individual studies may have attenuated the results. Thus, considering the popularity and cost-effectiveness of mobile apps in the new generation, future research should investigate the potential of using emerging and novel technologies, such as mobile health, for preschoolers.

Our meta-analysis suggests that eHealth interventions may be an effective strategy for decreasing sedentary time in preschoolers, although the magnitude of the effect was small (Hedges g =−0.15) and short term. Nonetheless, the significance should not be understated, given that many studies indicate that reduced sedentary time during childhood correlates with improved physical and mental health outcomes in subsequent years [ 16 , 21 , 89 ]. In the subgroup analysis, the effect of eHealth interventions on sedentary time varied depending on whether accelerometer or questionnaire measures were used. The questionnaire measures yielded higher levels of sedentary time, although this difference was not statistically significant. This observation aligns with findings from the existing literature, suggesting that questionnaire-based assessments tend to overestimate the actual sedentary time. For a more accurate evaluation of the impact of eHealth interventions, future research should consider using device-based measurement methods [ 90 ].

Interestingly, most eHealth interventions aimed to increase children’s PA and reduce sedentary time with parental support. Previous research has shown that parental and family involvement were among the key intervention components that encouraged significant improvement in children’s health behaviors and a decrease in sedentary time [ 91 , 92 ]. Likewise, Ha et al [ 49 ] found that parents’ physical literacy predicts children’s values toward PA, and concurrent interventions that target enhancing parents’ physical literacy for PA in the family context may be more effective in raising children’s PA values. However, our subgroup analysis showed no significant improvements in MVPA or reductions in sedentary time with the parent-supported interventions. This result also aligns with a prior review indicating that parent-directed digital interventions were ineffective in improving PA [ 53 ]. In that review, 8 studies, all published before 2020, primarily used digital platforms to convey health information and education to parents. Notably, in the wake of the COVID-19 pandemic, there has been a marked increase in research centered on leveraging technology to improve children’s PA, leading to more recent studies in 3 years [ 93 ]. Furthermore, the discourse regarding the comparative value of targeting either parents or children exclusively is not a novel debate within intervention research. In contrast to the review, our study featured a larger sample size and included a quantitative analysis of effect sizes in the interventions. These insights indicate that prevailing eHealth interventions, even with parental support, may fail to effectively engage preschoolers. Recognizing the reciprocal dynamics between parents and young children can offer insights for refining digital interventions. Therefore, preliminary research is imperative to comprehensively understand the perceptions, attitudes, and driving factors of parents. Recognizing the reciprocal dynamics between parents and young children is crucial in understanding how they influence their children’s PA and SB.

Intervention duration is also an essential component for conducting acceptable and highly effective interventions. Another subgroup analysis found that interventions with a duration of <3 months had a significantly greater effect on PA and sedentary time than those with a duration of >3 months, although the results were not significant. This notion is corroborated by another systematic review, which demonstrated the difficulty in sustaining long-term behavior change, potentially attributed to the diminishing effects of behavior change interventions mediated by digital technology [ 41 ].

The meta-analysis, involving 3 studies, revealed an immediate improvement in sleep duration following the intervention. Previous research has extensively examined the influence of sleep duration during the preschool years on physical, cognitive, and psychosocial development. For instance, the systematic review by Chaput et al [ 6 ] involving 25 studies revealed a correlation between shorter sleep duration and diminished emotion regulation in children aged 0 to 4 years. Recent findings also suggest that maintaining an extended sleep duration during the early preschool stages is significant for subsequent behavioral outcomes [ 24 ]. However, few studies have focused on effective interventions to improve sleep outcomes [ 45 , 94 ]. Consequently, further research is warranted to explore the impact of eHealth interventions on sleep outcomes among preschoolers.

Increasing awareness of the interconnected nature of 24-hour movement behaviors highlights their intrinsic interdependence [ 14 ]. However, none of the studies in our review specifically investigated the intervention effects on all 3 movement behaviors. Generally, conventional analytical methods do not adequately consider these indicators during analysis. Therefore, future research should explore alternative approaches, such as compositional analyses, to attain a more profound comprehension of whether an optimal equilibrium is present among SB, light PA, MVPA, and sleep [ 90 , 95 , 96 ]. Furthermore, most studies in our review examined the immediate postintervention effect. Consequently, insights into the enduring nature of alterations in 24-hour movement behaviors remain elusive. Further studies should include long-term follow-up assessments. In addition, it would be interesting to obtain more insights into the feasibility of incorporating wearable devices and apps into the design of eHealth interventions. This information could inform the design of wearables and apps that effectively enhance PA, diminish sedentary time, and enhance sleep, thereby maximizing their impact on public health. Moreover, the overall quality of the interventions was suboptimal, lacking thorough descriptions or proper execution in areas such as randomization, blinded outcome assessment, valid measurement of 24-hour movement behaviors, and adjusted differences between groups. In our meta-analysis, we observed that lower-quality studies exhibited a more pronounced positive impact on the targeted outcomes. Thus, it is essential to interpret the results cautiously, recognizing that there could be an overestimation of the effect of eHealth interventions in studies of lower quality owing to potential bias. This mirrors the findings from previous reviews on eHealth childhood PA [ 53 ] and behavior change interventions among adolescents [ 45 ].

Strengths and Limitations

This systematic review has some strengths. First, this study is the first meta-analysis to quantitatively assess the effects of previously conducted RCTs using eHealth interventions on 24-hour movement behaviors in preschoolers. Second, the review was conducted rigorously, encompassing comprehensive terms and using an extensive systematic search strategy. We focused on robust evidence from RCT studies, assessed the quality using the GRADE approach, and adhered to a preregistered protocol. This meticulous approach reduces the heterogeneity and provides a more precise estimation of the effects.

Nonetheless, several limitations of our study should be noted. First, the quality of the studies included in this review was generally low and lacked rigorous study designs. Second, the small number of studies discerned over the decade spanned by this meta-analysis underscores the nascent state of this research domain, even considering significant technological advancements and their widespread acceptance. Third, although we systematically screened relevant electronic databases to identify studies, the search was restricted to studies published in English. Finally, the lack of evidence regarding sustained effects beyond the immediate postintervention period underscores the need for extended follow-up. Future studies should strive to elucidate strategies for maintaining the intervention effects over the preschooler’s trajectory.

Future Research and Implications

This study highlights the significant avenues for future research. First, further research is warranted to develop eHealth interventions that yield larger effect sizes and higher quality, specifically in identifying effective 24-hour movement behaviors. It is worth noting that none of the eligible eHealth interventions addressed the comprehensive integration of 24-hour movement behaviors in preschoolers, despite the increasing recognition of the interdependence between PA, SB), and sleep. Second, many studies were conducted in Western and high-income countries, prompting the need for further exploration of the effectiveness of eHealth behavior change interventions in other country settings. Third, our study’s focus was primarily on the quantitative aspects of 24-hour movement behaviors, warranting future studies to also delve into the qualitative facets, such as motor skills and sleep quality. In addition, it is crucial to recognize the pivotal role of objective measurement tools in comprehending movement behaviors among young children. Given the sporadic and unstructured nature of preschoolers’ activities, it becomes challenging for parents and teachers to accurately discern shifts in MVPA and SB, even if they have occurred. This highlights the importance of using objective measurement tools for precise insights into these behaviors. Finally, future research in this field should prioritize broadening the focus and incorporate additional dimensions, such as physical, affective, and cognitive indicators. This approach may promote the holistic development of young children and contribute to advancements in the field of health outcomes. By considering these dimensions, researchers can also gain a comprehensive understanding of the various factors that influence children’s overall well-being and physical literacy development.

Given the multifaceted nature of intervention moderators, further research is warranted to establish optimal patterns of daily movement behaviors and to gain deeper insights into the mechanisms underlying change when addressing the amalgamation of 24-hour movement behaviors in preschoolers. Indeed, future interventions should also draw from the effective behavior change techniques used in single-behavior eHealth interventions and apply them to interventions targeting multiple healthy movement behaviors. Moreover, collaborative engagement with parents and teachers throughout both the developmental and implementation phases of these interventions will play a pivotal role in their success. In addition, capitalizing on emerging and novel technologies may offer a valuable avenue to enhance the effectiveness and feasibility of these interventions.


The findings suggest that eHealth interventions may hold promise in improving 24-hour movement behaviors, particularly by increasing PA, improving sleep duration, and reducing sedentary time among preschoolers. However, these effects were relatively modest and transient and were observed primarily immediately after the intervention. Furthermore, the overall quality of the evidence was rated as moderate to low. As a result, there is a pressing need for rigorous and high-quality research endeavors to develop eHealth interventions capable of effectively enhancing both the quantity and quality of 24-hour movement behaviors simultaneously. These interventions should strive to maintain their effects over extended periods.


The authors of this study would like to express their sincere gratitude to the authors who responded to their emails and generously provided detailed information and data regarding their studies. Their cooperation has been instrumental in advancing this study.

Data Availability

The data sets generated during and analyzed during this study are available from the corresponding author on reasonable request.

Authors' Contributions

SJ drafted the manuscript. SJ, ASH, and JYYN were responsible for the concept and design of the study. SJ and BP screened all abstracts full texts, extracted all data, performed the risk of bias, and conducted the quality assessment. SJ performed the statistical analyses. SJ, JYYN, KHC, and ASH critically revised the manuscript for important intellectual content. All authors participated in developing the review’s methodology, contributed to multiple manuscript drafts, and gave their approval for the final version.

Conflicts of Interest

None declared.

Eligibility criteria for study inclusion.

Search strategy.

Missing data processing.

Exclusion studies.

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist.

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) abstract checklist.

Number of studies included per country and income economy.

Summary of intervention details in the included studies.

Characteristics of the included studies including physical activity, sedentary behavior, and sleep outcomes.

Forest plot of the mobile-based intervention intended to stop obesity in preschoolers (MINISTOP) results.

Forest plots of the subgroup analyses of moderate to vigorous physical activity and sedentary behavior.

Sensitive analysis.

Moderate to vigorous physical activity bias funnel.

Sedentary behavior bias funnel.

Risk of bias.

GRADE (Grading of Recommendations Assessment, Development, and Evaluation) assessment results.

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Edited by T de Azevedo Cardoso; submitted 19.09.23; peer-reviewed by W Liang, M Zhou, Y Zhang, EJ Buckler; comments to author 11.10.23; revised version received 04.11.23; accepted 18.01.24; published 21.02.24.

©Shan Jiang, Johan Y Y Ng, Kar Hau Chong, Bo Peng, Amy S Ha. Originally published in the Journal of Medical Internet Research (, 21.02.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on, as well as this copyright and license information must be included.


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