How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-Analyses, and Meta-Syntheses

Affiliations.

  • 1 Behavioural Science Centre, Stirling Management School, University of Stirling, Stirling FK9 4LA, United Kingdom; email: [email protected].
  • 2 Department of Psychological and Behavioural Science, London School of Economics and Political Science, London WC2A 2AE, United Kingdom.
  • 3 Department of Statistics, Northwestern University, Evanston, Illinois 60208, USA; email: [email protected].
  • PMID: 30089228
  • DOI: 10.1146/annurev-psych-010418-102803

Systematic reviews are characterized by a methodical and replicable methodology and presentation. They involve a comprehensive search to locate all relevant published and unpublished work on a subject; a systematic integration of search results; and a critique of the extent, nature, and quality of evidence in relation to a particular research question. The best reviews synthesize studies to draw broad theoretical conclusions about what a literature means, linking theory to evidence and evidence to theory. This guide describes how to plan, conduct, organize, and present a systematic review of quantitative (meta-analysis) or qualitative (narrative review, meta-synthesis) information. We outline core standards and principles and describe commonly encountered problems. Although this guide targets psychological scientists, its high level of abstraction makes it potentially relevant to any subject area or discipline. We argue that systematic reviews are a key methodology for clarifying whether and how research findings replicate and for explaining possible inconsistencies, and we call for researchers to conduct systematic reviews to help elucidate whether there is a replication crisis.

Keywords: evidence; guide; meta-analysis; meta-synthesis; narrative; systematic review; theory.

  • Guidelines as Topic
  • Meta-Analysis as Topic*
  • Publication Bias
  • Review Literature as Topic
  • Systematic Reviews as Topic*
  • Academic Resources
  • Grey Literature: Resources
  • Conducting a Systematic Review
  • "How to" videos: searching
  • Reference Management Software: Zotero This link opens in a new window
  • Further Support

Systematic Reviews: Introduction

  • What is a systematic review?
  • How does it differ from a systematic literature review?

psychological systematic literature review

A systematic review is a review of research literature (often limited to randomised controlled trials) that is searched for in a systematic or exact manner, and only includes studies that have met strict inclusion criteria. The methodology of the review often follows a internationally recognized systematic review standard or guideline. 

PRISMA definition

"A systematic review is a review of a clearly formulated question that uses systematic and explicit methods to identify, select, and critically appraise relevant research, and to collect and analyze data from the studies that are included in the review." (PRISMA, 2015)

A systematic literature search is a literature review which demonstrates that you have compiled a list of appropriate search terms and includes the structure of your search history, which provides the evidence on which your assignment is based.  You may be told that you need to conduct a systematic review when in fact you just need to perform a literature search in a systematic manner. 

This is a less rigorous process than a systematic review. A systematic review usually covers a wider scope; you would be expected to look at all the available research in the area in question, systematically searching multiple academic databases.

If you are unsure about the differences between a systematic review and a literature review take a look at this guide:  What’s in a Name? The difference between a Systematic Review and a Literature Review and Why it Matters .

Systematic reviews: your research question

Your research question

  • Inclusion and exclusion criteria
  • PICO framework
  • PICO: example

psychological systematic literature review

Where possible, select a research topic that you have some basic knowledge in, or are familiar with in.  If this is not possible, seek guidance from your supervisor on the most relevant terminology for your chosen topic.  This will make it easier to devise your research question, ensuring you are using the most appropriate and relevant phrasing.This is especially important when you come to build your search strategy, as the wording of your research question research question will frame your initial search. 

The search terms, phrases, words and subject headings you use in your systematic search play a vital role in your systematic review, because they determine the number and range of results you will get from each database. I f your question is too wide-reaching so will your search, and you will be overwhelmed with  an unmanageable number of search results. You also have to think very carefully about the limitations of your search - such as whether or not you will have a specific date range or limit to a particular study design.  Remember, the clue is in the name - be  systematic  in your approach. 

Inclusion and exclusion criteria 

Before you start to build your search strategy you will need to decide on your review's inclusion and exclusion criteria. This will have a bearing on your search strategy, and potentially determine which studies your systematic search captures. Systematic reviews are measured against a set of specific criteria outlined at the start.  Your inclusion and exclusion criteria dictates which studies will be included in your systematic review (they meet all aspects of your inclusion criteria) and those that will be excluded (does not match your inclusion criteria fully, or meets the exclusion criteria).  You need to think very carefully about the limitations of your research - will you limit to a specific date range or to a particular study design for example.  Remember, the clue is in the name - be  systematic  in your approach. 

Research question:

"For UK children under 5 years of age with a suspected diagnosis of ADHD, what are the recommended clinical assessments used for diagnosis?" 

Inclusion criteria:

  • children 0-5 years old 
  • suspected ADHD
  • limited to clinical assessments specifically, for diagnosis
  • UK population studies only

Exclusion criteria:

  • any member of the population over the age of 5 
  • animal studies
  • pre-determined diagnosis of ADHD 
  • assessments not defined as "clinical" 
  • studies of populations outside of the UK

PICO Framework

In order to structure your search strategy  it can be helpful to use a structured framework.They are designed to help you formulate your research question, search strategy, and inclusion and exclusion criteria. The PICO framework is a popular framework for physiological and health sciences systematic reviews.

PICO stands for:

Population / Patient

Intervention 

You do not have to structure your research to fit into all of the above - it is not prescriptive, but merely a framework to guide you in building your search strategy. Your research question may not have a defined comparative intervention, for example, so you may only use PIO for your framework. 

PICO example

Research question: What impact does Cognitive Behavioural Therapy (CBT) versus pharmaceutical therapy have as treatments for diagnosed anxiety in children  in reducing their anxiety?

Systematic Reviews: the search

  • Your search strategy
  • Where to search
  • Search techniques
  • PRESS checklist
  • Sample strategy

Your search strategy - where to start

student taking notes on laptop

The search terms, phrases, words and subject headings you use in your search play a vital role in your systematic review, because they determine the number and range of results you will get from each database. 

Start with your research question to pick out the  keywords  you will use as the basis of your search. A common practice in systematic review searches is to refer back to the framework you used to structure your research question, such as the PICO framework . This framework gives a clear picture of not only the terms you want to use in your search, but also how you will combine or connect them together in the database.

Using PICO framework for your search 

Research question: Is Cognitive Behavioural Therapy (CBT) more effective than pharmaceutical therapy as a treatment for diagnosed anxiety in teenagers aged 13-18 in managing symptoms of anxiety?

Framework  

Search terms identified: 

  • teen/teenager
  • 13-18 year olds
  • anxiety 
  • CBT/cognitive behavioural the rapy
  • pharmaceutical/medication
  • Improved   management of symptoms

Where to search - Databases

We have grouped the key databases and online resources for psychology in the Key Resources tab . Your dissertation supervisor may also suggest or advise you on the various databases suitable to your search. Some of the most commonly searched databases include: PsycINFO, Web of Science, Cochrane, Scopus, and PubMed. The links for these can be found in the Key Resources tab. 

Where to search - Grey Literature

Depending on your research, you may also need to search grey literature sources in addition to academic database collections. Have a look at the grey literature tab  on the left hand side more information about what defines grey literature and the sources you can search. 

Search techniques 

Consider your keywords carefully 

notice board with keywords pinned

It's often helpful to look at the abstracts and reference lists of studies or papers you have already engaged with on your topic for a sense of what terminology and specific words/phrases are most common. 

Once you have made a comprehensive list of all the keywords you want to include in your search you need to combine them using what are known as Boolean operators or search connectors. 

Boolean search operators 

In order to combine multiple facets of your search together in a database you will need to use the search operators: AND, OR, NOT. Using operators is common in systematic reviews, and improves the efficiency of your search resulting in more relevant results. Watch the Boolean searching videos to learn more about how to use operators.

Proximity operators 

Using proximity operators in your search allows you to  search for two or more words that occur within a certain number of words from each other. Proximity operators can be helpful when you don't want to limit yourself to searching an exact phrase, for example "diagnosed anxiety", but where you still want to refine your search to a degree. Each database will have its own method of proximity searching, but generally your search looks something like: diagnosed NEAR/3 anxiety - NEAR signifying near to, and 3 signifying the number of words that can appear between "diagnosed" and "anxiety". To ensure proximity searching is available in the database you are searching, have a look for their "search tips" or "search help" page. 

PRESS (Peer Review of Electronic Search Strategies)

Checklist on paper

The PRESS checklist is a comprehensive evidence-based checklist that does just that. It covers six key aspects of search strategies: 

  • the translation of the research question into a search strategy
  • the use of any Boolean or proximity operators
  • the keywords used 
  • spelling, syntax, and commands
  • database filters / limits intended for use
  • database Subject headings intended for use not essential, and may not apply to your strategy)

Each aspect above has a set of questions to check against your search strategy. The full checklist can be downloaded here . 

Research question

Is Cognitive Behavioural Therapy (CBT) more effective than pharmaceutical therapy as a treatment for diagnosed anxiety in teenagers aged 13-18 in managing symptoms of anxiety?

Step 1: Framework

Step 2: Identify search terms

Step 3: Build search strategy with Boolean operators / commands / proximity operators

Systematic Reviews: guidelines and protocols

  • Standards and guidelines
  • Cochrane handbook
  • Choosing a standard/guideline

Standards and guidelines 

psychological systematic literature review

These can serve as guidelines for the structure of your review, from what headings/sections to include, (such as methods, search strategy, etc) to best practice protocols for search strategies, reporting, etc. 

​ The School of Psychology recommends its students follow the PRISMA reporting guidance when conducting a systematic review. 

PRISMA standards

PRISM A  (Preferred Reporting Items for Systematic Reviews and  Meta-Analyses )  is an evidence-based protocol for reporting on systematic reviews and meta-analyses. The School of Psychology recommends its students follow the PRISMA reporting guidance when conducting a systematic review. The PRISMA checklist makes this easy, providing a checklist of criteria to be adhered to for each of the sections of your review, for example: introduction, methods, results, etc.

Useful PRISMA links: 

  • PRISMA Checklist  (checklist of sections to include in your systematic review, eg: methods, results, etc.) 
  • PRISMA flow chart   (charts the number of records identified, included and excluded, and the reasons for exclusions.)
  • Citing PRISMA

Cochrane Handbook 

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Cochrane Handbook for Systematic Reviews of Interventions  

Choosing a systematic review standard/guideline

The School of Psychology recommends its students follow the PRISMA reporting guidance when conducting a systematic review, but it is also helpful to read through the Cochrane Handbook of Systematic Review, particularly if your research topic spans both medical and human sciences.

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Guidelines for Systematic Reviews

  • PRISMA Checklist The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) has developed a 27 checklist items pertaining to the content of a systematic review and meta-analysis, which include the title, abstract, methods, results, discussion and funding.
  • NIH Guidelines This website provides guidelines developed by the Institute of Medicine (IOM). more... less... In 2011, the Institute of Medicine (IOM) defined a systematic evidence review as "a scientific investigation that focuses on a specific question and uses explicit, prespecified scientific methods to identify, select, assess, and summarize the findings of similar but separate studies. It may include a quantitative synthesis (meta-analysis), depending on the available data."

Register your Systematic Review

Prospero Registry

"PROSPERO is an international database of prospectively registered systematic reviews in health and social care, welfare, public health, education, crime, justice, and international development, where there is a health related outcome." (Website- About)

Conducting a Literature Review

  • The Literature Review (25 minutes Video - opens in a new window)) This in-depth video lecture explains how to write a Literature Review, and examines which elements are required in one. This video was created the Student Learning Centre at Massey University, Auckland.

Systematic Reviews - What to Consider

Before you Begin: 

  • Did you know, it takes an average of 18 months to complete a systematic review?
  • Did you know that it's recommended to have at least 3 people on a systematic review team? 
  • Did you know that a systematic review answers a very specific type of research question? Is your question a good fit for a systematic review? 

Contact your librarian, Emily Hart , to learn more about systematic reviews. 

Types of Reviews

Comparison of Review Types from Cornell University Libraries

" A systematic review is a review of the literature that is conducted in a methodical manner based on a pre-specified protocol and with the aim of synthesizing the retrieved information often by means of a meta-analysis."

" A literature review is a descriptive and/or analytic summary of the existing material relating to some topic or area of study."

(Sage Research Methods Online)

Systematic Review vs. Literature Review - What's the Difference?

psychological systematic literature review

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Systematic Literature Review

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 Outlined below is a systematic approach to conducting a literature review using the PICO(T) principle.

Follow the steps to:

  • formulate an answerable question/issue
  • refine concepts and keywords
  • develop search strategies
  • critically appraise literature
  • complete the Research Planner

Step 1: Question Type

Step 2: pico(t) principle.

The PICO(T) principle is a framework in which to formulate a question or issue of interest. Questions should be answerable and refined, so to identify each of the components in the PICO formula. This will allow for keywords to be easily defined and more effective search results returned.

P  Population/Problem

I   Intervention

C  Comparison/Control

O  Outcome

(T) Timeframe

An answerable question would ask: In P how does I compared with C affect the O ?

Step 3: Prepare for Searching

Identify the Search Terms

  • Consider what the main concepts of the question are
  • Identify keywords and synonyms

 Combine your search terms using Boolean Operators

AND    Look for articles that include all identified keywords

OR      Look for articles that include any identified keywords

NOT    Exclude articles that contain this specific keyword

Step 4: Effective Searching

MeSH - Medical Subject Headings Is a controlled vocabulary and is used for the purpose of indexing journals and books. They are pre-determined concepts/terms which describe content in discipline specific, indexing databases PubMed, Medline and Cinahl databases include MeSH Headings or Cinhal Subject Headings, which can also serve as a Thesaurus. Searching the databases using MeSH terms allows for terms to be searched as a Major Concept (the search will return only records for which the subject heading is a major point of the article) and also provides the ability to Explode (expands the subject heading to retrieve all references indexed to that term, plus any narrower terms that are connected)

Discipline specific Databases

Medline:  One of the most acknowledged biomedicine databases, Medline's coverage includes basic research in the biomedical and clinical sciences as well as major health related subjects including nursing and allied health. Its records are indexed using MeSH.  PubMed is the publicly accessible version of Medline.

Cochrane Library:   P rovides access to a collection of databases that contain high-quality, independent evidence to inform health care decision-making. These databases include: Cochrane Reviews, Database of Abstracts of Reviews of Effects - DARE (Other Reviews), Clinical Trials and NHS Economic Evaluation Database.

PubMed: PubMed Clinical Queries allows you to find critically appraised information indexed in MEDLINE. PubMed uses a broad definition of systematic reviews. It includes systematic reviews, meta-analyses, reviews of clinical trials, evidence-based medicine, consensus development conferences, and guidelines.

Scopus:  Offers peer-reviewed journals in the scientific, technical, medical and social science fields. An excellent source for locating Authors' works.

Step 5: Critical Appraisal

Critical appraisal is applying a systematic approach to analyse and identify unbiased/biased and valid literature. A literature review should not be a list summarising each article retrieved. Instead, it should appear as organised sections into themes or concepts, synthesised and evaluated, according to the research question.

Set your criteria to assist in critically appraising the literature e.g.,

  • Does the literature directly relate to the question?
  • What are the strengths and limitations of the literature and how does it contribute to the study?

Read more about Critical Appraisal under the Evidence Based Nursing tab  

Use CASP (Critical Appraisal Skills Program) to analyse and critique the literature

Step 6: Research Planner

  • Research Planner Use the Planner to record your search strategies etc

Use the Research Planner to assist in developing a recordable framework for the Literature Review

Tools to Manage References

Students are required to use APA Style referencing

       Recite - APA 

EndNote is software that allows you to record, organise and use references and PDF files. It assists in producing bibliographies and will generate citations and bibliographies in specific styles (e.g. APA 6th) into word documents. Read more about EndNote

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Systematic, Scoping, and Other Literature Reviews: Overview

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What Is a Systematic Review?

Regular literature reviews are simply summaries of the literature on a particular topic. A systematic review, however, is a comprehensive literature review conducted to answer a specific research question. Authors of a systematic review aim to find, code, appraise, and synthesize all of the previous research on their question in an unbiased and well-documented manner. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) outline the minimum amount of information that needs to be reported at the conclusion of a systematic review project. 

Other types of what are known as "evidence syntheses," such as scoping, rapid, and integrative reviews, have varying methodologies. While systematic reviews originated with and continue to be a popular publication type in medicine and other health sciences fields, more and more researchers in other disciplines are choosing to conduct evidence syntheses. 

This guide will walk you through the major steps of a systematic review and point you to key resources including Covidence, a systematic review project management tool. For help with systematic reviews and other major literature review projects, please send us an email at  [email protected] .

Getting Help with Reviews

Organization such as the Institute of Medicine recommend that you consult a librarian when conducting a systematic review. Librarians at the University of Nevada, Reno can help you:

  • Understand best practices for conducting systematic reviews and other evidence syntheses in your discipline
  • Choose and formulate a research question
  • Decide which review type (e.g., systematic, scoping, rapid, etc.) is the best fit for your project
  • Determine what to include and where to register a systematic review protocol
  • Select search terms and develop a search strategy
  • Identify databases and platforms to search
  • Find the full text of articles and other sources
  • Become familiar with free citation management (e.g., EndNote, Zotero)
  • Get access to you and help using Covidence, a systematic review project management tool

Doing a Systematic Review

  • Plan - This is the project planning stage. You and your team will need to develop a good research question, determine the type of review you will conduct (systematic, scoping, rapid, etc.), and establish the inclusion and exclusion criteria (e.g., you're only going to look at studies that use a certain methodology). All of this information needs to be included in your protocol. You'll also need to ensure that the project is viable - has someone already done a systematic review on this topic? Do some searches and check the various protocol registries to find out. 
  • Identify - Next, a comprehensive search of the literature is undertaken to ensure all studies that meet the predetermined criteria are identified. Each research question is different, so the number and types of databases you'll search - as well as other online publication venues - will vary. Some standards and guidelines specify that certain databases (e.g., MEDLINE, EMBASE) should be searched regardless. Your subject librarian can help you select appropriate databases to search and develop search strings for each of those databases.  
  • Evaluate - In this step, retrieved articles are screened and sorted using the predetermined inclusion and exclusion criteria. The risk of bias for each included study is also assessed around this time. It's best if you import search results into a citation management tool (see below) to clean up the citations and remove any duplicates. You can then use a tool like Rayyan (see below) to screen the results. You should begin by screening titles and abstracts only, and then you'll examine the full text of any remaining articles. Each study should be reviewed by a minimum of two people on the project team. 
  • Collect - Each included study is coded and the quantitative or qualitative data contained in these studies is then synthesized. You'll have to either find or develop a coding strategy or form that meets your needs. 
  • Explain - The synthesized results are articulated and contextualized. What do the results mean? How have they answered your research question?
  • Summarize - The final report provides a complete description of the methods and results in a clear, transparent fashion. 

Adapted from

Types of reviews, systematic review.

These types of studies employ a systematic method to analyze and synthesize the results of numerous studies. "Systematic" in this case means following a strict set of steps - as outlined by entities like PRISMA and the Institute of Medicine - so as to make the review more reproducible and less biased. Consistent, thorough documentation is also key. Reviews of this type are not meant to be conducted by an individual but rather a (small) team of researchers. Systematic reviews are widely used in the health sciences, often to find a generalized conclusion from multiple evidence-based studies. 

Meta-Analysis

A systematic method that uses statistics to analyze the data from numerous studies. The researchers combine the data from studies with similar data types and analyze them as a single, expanded dataset. Meta-analyses are a type of systematic review.

Scoping Review

A scoping review employs the systematic review methodology to explore a broader topic or question rather than a specific and answerable one, as is generally the case with a systematic review. Authors of these types of reviews seek to collect and categorize the existing literature so as to identify any gaps.

Rapid Review

Rapid reviews are systematic reviews conducted under a time constraint. Researchers make use of workarounds to complete the review quickly (e.g., only looking at English-language publications), which can lead to a less thorough and more biased review. 

Narrative Review

A traditional literature review that summarizes and synthesizes the findings of numerous original research articles. The purpose and scope of narrative literature reviews vary widely and do not follow a set protocol. Most literature reviews are narrative reviews. 

Umbrella Review

Umbrella reviews are, essentially, systematic reviews of systematic reviews. These compile evidence from multiple review studies into one usable document. 

Grant, Maria J., and Andrew Booth. “A Typology of Reviews: An Analysis of 14 Review Types and Associated Methodologies.” Health Information & Libraries Journal , vol. 26, no. 2, 2009, pp. 91-108. doi: 10.1111/j.1471-1842.2009.00848.x .

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Understanding and Evaluating Systematic Reviews and Meta-analyses

Michael bigby.

From the Department of Dermatology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA

A systematic review is a summary of existing evidence that answers a specific clinical question, contains a thorough, unbiased search of the relevant literature, explicit criteria for assessing studies and structured presentation of the results. A systematic review that incorporates quantitative pooling of similar studies to produce an overall summary of treatment effects is a meta-analysis. A systematic review should have clear, focused clinical objectives containing four elements expressed through the acronym PICO (Patient, group of patients, or problem, an Intervention, a Comparison intervention and specific Outcomes). Explicit and thorough search of the literature is a pre-requisite of any good systematic review. Reviews should have pre-defined explicit criteria for what studies would be included and the analysis should include only those studies that fit the inclusion criteria. The quality (risk of bias) of the primary studies should be critically appraised. Particularly the role of publication and language bias should be acknowledged and addressed by the review, whenever possible. Structured reporting of the results with quantitative pooling of the data must be attempted, whenever appropriate. The review should include interpretation of the data, including implications for clinical practice and further research. Overall, the current quality of reporting of systematic reviews remains highly variable.

Introduction

A systematic review is a summary of existing evidence that answers a specific clinical question, contains a thorough, unbiased search of the relevant literature, explicit criteria for assessing studies and structured presentation of the results. A systematic review can be distinguished from a narrative review because it will have explicitly stated objectives (the focused clinical question), materials (the relevant medical literature) and methods (the way in which studies are assessed and summarized).[ 1 , 2 ] A systematic review that incorporates quantitative pooling of similar studies to produce an overall summary of treatment effects is a meta-analysis.[ 1 , 2 ] Meta-analysis may allow recognition of important treatment effects by combining the results of small trials that individually might lack the power to consistently demonstrate differences among treatments.[ 1 ]

With over 200 speciality dermatology journals being published, the amount of data published just in the dermatologic literature exceeds our ability to read it.[ 3 ] Therefore, keeping up with the literature by reading journals is an impossible task. Systematic reviews provide a solution to handle information overload for practicing physicians.

Criteria for reporting systematic reviews have been developed by a consensus panel first published as Quality of Reporting of Meta-analyses (QUOROM) and later refined as Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA).[ 4 , 5 ] This detailed, 27-item checklist contains items that should be included and reported in high quality systematic reviews and meta-analyses. The methods for understanding and appraising systematic reviews and meta-analyses presented in this paper are a subset of the PRISMA criteria.

The items that are the essential features of a systematic review include having clear objectives, explicit criteria for study selection, an assessment of the quality of included studies, criteria for which studies can be combined, appropriate analysis and presentation of results and practical conclusions that are based on the evidence evaluated [ Table 1 ]. Meta-analysis is only appropriate if the included studies are conceptually similar. Meta-analyses should only be conducted after a systematic review.[ 1 , 6 ]

Criteria for evaluating a systematic review or the meta-analysis

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A Systematic Review Should Have Clear, Focused Clinical Objectives

A focused clinical question for a systematic review should contain the same four elements used to formulate well-built clinical questions for individual studies, namely a Patient, group of patients, or problem, an Intervention, a Comparison intervention and specific Outcomes.[ 7 ] These features can be remembered by the acronym PICO. The interventions and comparison interventions should be adequately described so that what was done can be reproduced in future studies and in practice. For diseases with established effective treatments, comparisons of new treatments or regimens to established treatments provide the most useful information. The outcomes reported should be those that are most relevant to physicians and patients.[ 1 ]

Explicit and Thorough Search of the Literature

A key question to ask of a systematic review is: “Is it unlikely that important, relevant studies were missed?” A sound systematic review can be performed only if most or all of the available data are examined. An explicit and thorough search of the literature should be performed. It should include searching several electronic bibliographic databases including the Cochrane Controlled Trials Registry, which is part of the Cochrane Library, Medline, Embase and Literatura Latino Americana em Ciências da Saúde. Bibliographies of retrieved studies, review articles and textbooks should be examined for studies fitting inclusion criteria. There should be no language restrictions. Additional sources of data include scrutiny of citation lists in retrieved articles, hand-searching for conference reports, prospective trial registers (e.g., clinical trials.gov for the USA and clinical trialsregister.eu for the European union) and contacting key researchers, authors and drug companies.[ 1 , 8 ]

Reviews should have Pre-defined Explicit Criteria for what Studies would be Included and the Analysis should Include Only those Studies that Fit the Inclusion Criteria

The overwhelming majority of systematic reviews involve therapy. Randomized, controlled clinical trials should therefore be used for systematic reviews of therapy if they are available, because they are generally less susceptible to selection and information bias in comparison with other study designs.[ 1 , 9 ]

Systematic reviews of diagnostic studies and harmful effects of interventions are increasingly being performed and published. Ideally, diagnostic studies included in systematic reviews should be cohort studies of representative populations. The studies should include a criterion (gold) standard test used to establish a diagnosis that is applied uniformly and blinded to the results of the test(s) being studied.[ 1 , 9 ]

Randomized controlled trials can be included in systematic reviews of studies of adverse effects of interventions if the events are common. For rare adverse effects, case-control studies, post-marketing surveillance studies and case reports are more appropriate.[ 1 , 9 ]

The Quality (Risk of Bias) of the Primary Studies should be Critically Appraised

The risk of bias of included therapeutic trials is assessed using the criteria that are used to evaluate individual randomized controlled clinical trials. The quality criteria commonly used include concealed, random allocation; groups similar in terms of known prognostic factors; equal treatment of groups; blinding of patients, researchers and analyzers of the data to treatment allocation and accounting for all patients entered into the trial when analyzing the results (intention-to-treat design).[ 1 ] Absence of these items has been demonstrated to increase the risk of bias of systematic reviews and to exaggerate the treatment effects in individual studies.[ 10 ]

Structured Reporting of the Results with Quantitative Pooling of the Data, if Appropriate

Systematic reviews that contain studies that have results that are similar in magnitude and direction provide results that are most likely to be true and useful. It may be impossible to draw firm conclusions from systematic reviews in which studies have results of widely different magnitude and direction.[ 1 , 9 ]

Meta-analysis should only be performed to synthesize results from different trials if the trials have conceptual homogeneity.[ 1 , 6 , 9 ] The trials must involve similar patient populations, have used similar treatments and have measured results in a similar fashion at a similar point in time.

Once conceptual homogeneity is established and the decision to combine results is made, there are two main statistical methods by which results are combined: random-effects models (e.g., DerSimonian and Laird) and fixed-effects models (e.g., Peto or Mantel-Haenszel).[ 11 ] Random-effects models assume that the results of the different studies may come from different populations with varying responses to treatment. Fixed-effects models assume that each trial represents a random sample of a single population with a single response to treatment [ Figure 1 ]. In general, random-effects models are more conservative (i.e., random-effects models are less likely to show statistically significant results than fixed-effects models). When the combined studies have statistical homogeneity (i.e., when the studies are reasonably similar in direction, magnitude and variability), random-effects and fixed-effects models give similar results.

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Fixed-effects models (a) assume that each trial represents a random sample (colored curves) of a single population with a single response to treatment. Random-effects models (b) assume that the different trials’ results (colored curves) may come from different populations with varying responses to treatment.

The point estimates and confidence intervals of the individual trials and the synthesis of all trials in meta-analysis are typically displayed graphically in a forest plot [ Figure 2 ].[ 12 ] Results are most commonly expressed as the odds ratio (OR) of the treatment effect (i.e., the odds of achieving a good outcome in the treated group divided by the odds of achieving a good result in the control group) but can be expressed as risk differences (i.e., difference in response rate) or relative risk (probability of achieving a good outcome in the treated group divided by the probability in the control group). An OR of 1 (null) indicates no difference between treatment and control and is usually represented by a vertical line passing through 1 on the x-axis. An OR of greater or less than 1 implies that the treatment is superior or inferior to the control respectively.

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Annotated results of a meta-analysis of six studies, using random effects models reported as odd ratios using MIX version 1.7 (Bax L, Yu LM, Ikeda N, Tsuruta H, Moons KGM. Development and validation of MIX: comprehensive free software for meta-analysis of causal research data. BMC Med Res Methodol http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1626481/ ). The central graph is a typical Forest Plot

The point estimate of individual trials is indicated by a square whose size is proportional to the size of the trial (i.e., number of patients analyzed). The precision of the trial is represented by the 95% confidence interval that appears in Forest Plots as the brackets surrounding point estimate. If the 95% confidence interval (brackets) does not cross null (OR of 1), then the individual trial is statistically significant at the P = 0.05 level.[ 12 ] The summary value for all trials is shown graphically as a parallelogram whose size is proportional to the total number of patients analyzed from all trials. The lateral tips of the parallelogram represent the 95% confidence interval and if they do not cross null (OR of 1), then the summary value of the meta-analysis is statistically significant at the P = 0.05 level. ORs can be converted to risk differences and numbers needed to treat (NNTs) if the event rate in the control group is known [ Table 2 ].[ 13 , 14 ]

Deriving numbers needed to treat from a treatment's odds ratio and the observed or expected event rates of untreated groups or individuals

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The difference in response rate and its reciprocal, the NNT, are the most easily understood measures of the magnitude of the treatment effect.[ 1 , 9 ] The NNT represents the number of patients one would need to treat in order to achieve one additional cure. Whereas the interpretation of NNT might be straightforward within one trial, interpretation of NNT requires some caution within a systematic review, as this statistic is highly sensitive to baseline event rates.[ 1 ]

For example, if a treatment A is 30% more effective than treatment B for clearing psoriasis and 50% of people on treatment B are cleared with therapy, then 65% will clear with treatment A. These results correspond to a rate difference of 15% (65-50) and an NNT of 7 (1/0.15). This difference sounds quite worthwhile clinically. However if the baseline clearance rate for treatment B in another trial or setting is only 30%, the rate difference will be only 9% and the NNT now becomes 11 and if the baseline clearance rate is 10%, then the NNT for treatment A will be 33, which is perhaps less worthwhile.[ 1 ]

Therefore, NNT summary measures within a systematic review should be interpreted with caution because “control” or baseline event rates usually differ considerably between studies.[ 1 , 15 ] Instead, a range of NNTs for a range of plausible control event rates that occur in different clinical settings should be given, along with their 95% confidence intervals.[ 1 , 16 ]

The data used in a meta-analysis can be tested for statistical heterogeneity. Methods to tests for statistical heterogeneity include the χ 2 and I.[ 2 , 11 , 17 ] Tests for statistical heterogeneity are typically of low power and hence detecting statistical homogeneity does not mean clinical homogeneity. When there is evidence of heterogeneity, reasons for heterogeneity between studies – such as different disease subgroups, intervention dosage, or study quality – should be sought.[ 11 , 17 ] Detecting the source of heterogeneity generally requires sub-group analysis, which is only possible when data from many or large trials are available.[ 1 , 9 ]

In some systematic reviews in which a large number of trials have been performed, it is possible to evaluate whether certain subgroups (e.g. children versus adults) are more likely to benefit than others. Subgroup analysis is rarely possible in dermatology, because few trials are available. Subgroup analyses should always be pre-specified in a systematic review protocol in order to avoid spurious post hoc claims.[ 1 , 9 ]

The Importance of Publication Bias

Publication bias is the tendency that studies that show positive effects are more likely to be published and are easier to find.[ 1 , 18 ] It results from allowing factors other than the quality of the study to influence its acceptability for publication. Factors such as the sample size, the direction and statistical significance of findings, or the investigators’ perception of whether the findings are “interesting,” are related to the likelihood of publication.[ 1 , 19 , 20 ] Negative studies with small sample size are less likely to be published.[ 1 , 19 , 20 ] Studies published are often dominated by the pharmaceutical company sponsored trials of new, expensive treatments often compared with the placebo.

For many diseases, the studies published are dominated by drug company-sponsored trials of new, expensive treatments. Such studies are almost always “positive.”[ 1 , 21 , 22 ] This bias in publication can result in data-driven systematic reviews that draw more attention to those medicines. Systematic reviews that have been sponsored directly or indirectly by industry are also prone to bias through over-inclusion of unpublished “positive” studies that are kept “on file” by that company and by not including or not finishing registered trials whose results are negative.[ 1 , 23 ] The creation of study registers (e.g. http://clinicaltrials.gov ) and advance publication of research designs have been proposed as ways to prevent publication bias.[ 1 , 24 , 25 ] Many dermatology journals now require all their published trials to have been registered beforehand, but this policy is not well policed.[ 1 ]

Language bias is the tendency for studies that are “positive” to be published in an English-language journal and be more quickly found than inconclusive or negative studies.[ 1 , 26 ] A thorough systematic review should therefore not restrict itself to journals published in English.[ 1 ]

Publication bias can be detected by using a simple graphic test (funnel plot), by calculating the fail-safe N, Begg's rank correlation method, Egger regression method and others.[ 1 , 9 , 11 , 27 , 28 ] These techniques are of limited value when less than 10 randomized controlled trials are included. Testing for publication bias is often not possible in systematic reviews of skin diseases, due to the limited number and sizes of trials.[ 1 , 9 ]

Question-driven systematic reviews answer the clinical questions of most concern to practitioners. In many cases, studies that are of most relevance to doctors and patients have not been done in the field of dermatology, due to inadequate sources of independent funding.[ 1 , 9 ]

The Quality of Reporting of Systematic Reviews

The quality of reporting of systematic reviews is highly variable.[ 1 ] One cross-sectional study of 300 systematic reviews published in Medline showed that over 90% were reported in specialty journals. Funding sources were not reported in 40% of reviews. Only two-thirds reported the range of years that the literature was searched for trials. Around a third of reviews failed to provide a quality assessment of the included studies and only half of the reviews included the term “systematic review” or “meta-analysis” in the title.[ 1 , 29 ]

The Review should Include Interpretation of the Data, Including Implications for Clinical Practice and Further Research

The conclusions in the discussion section of a systematic review should closely reflect the data that have been presented within that review. Clinical recommendations can be made when conclusive evidence is found, analyzed and presented. The authors should make it clear which of the treatment recommendations are based on the review data and which reflect their own judgments.[ 1 , 9 ]

Many reviews in dermatology, however, find little evidence to address the questions posed. The review may still be of value even if it lacks conclusive evidence, especially if the question addressed is an important one.[ 1 , 30 ] For example, the systematic review may provide the authors with the opportunity to call for primary research in an area and to make recommendations on study design and outcomes that might help future researchers.[ 1 , 31 ]

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Letter to the editor concerning: “The serotonin theory of depression: a systematic umbrella review of the evidence”

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We read with great interest the article by Moncrieff et al. presenting a systematic umbrella review of the evidence of the serotonin theory of depression [ 1 ]. The authors conducted a meaningful and relevant review, and we appreciate the continued attention in the scientific literature to the challenge of molecular psychiatry of serotonin theory in predominantly depressive disorders.

The biological perspective plays a crucial role in psychiatry; mental disorders are increasingly understood in terms of biological mechanisms linked to changes in the structure, chemistry, and function of the brain, and that mental illness does indeed have a biological basis [ 2 ]. However, George L. Engel presented the biopsychosocial model (BPS) as a medical model to explain mental illnesses in 1977. Since then, this model has become widely accepted around the world [ 3 ], At the same time, as described in some of the reviewed articles, research systematically explained the interaction of three major dimensions (biological, psychological, and social) in the development of psychiatric disorders [ 4 ].

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Moncrieff J, Cooper RE, Stockmann T, Amendola S, Hengartner MP, Horowitz MA. The serotonin theory of depression: a systematic umbrella review of the evidence. Mol Psychiatry. 2022;1–14. Available from: http://www.ncbi.nlm.nih.gov/pubmed/35854107 .

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Porter RJ. The biopsychosocial model in mental health. Aust N Z J Psychiatry. 2020;54:773–4.

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Cipriani A, Furukawa TA, Salanti G, Chaimani A, Atkinson LZ, Ogawa Y, et al. Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis. Lancet. 2018;391:1357–66. https://doi.org/10.1016/S0140-6736(17)32802-7 .

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A systematic review of school refusal

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  • Sümeyye Ulaş   ORCID: orcid.org/0000-0003-3353-7448 1 &
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Considering the problems associated with school attendance, school refusal is an adjustment problem that tends to become increasingly prevalent. The present study identifies the patterns reported in the literature on school refusal and outlines the structure and sub-components of school refusal. Therefore, the systematic review method was selected as the research method for this study. The data sources of this study consist of 40 research articles that fell within the purview of WoS and were either included or excluded according to predetermined inclusion and exclusion criteria. Using MAXQDA 2020, both content and descriptive analyses were conducted in synthesizing the data sources. As a result of the analysis, the study year, method, data collection tool, data collection procedure, data analysis, and sample were examined as descriptive characteristics. Analyzing the content characteristics, five themes were identified: risk factors for school refusal, school refusal symptoms, school refusal protective factors, approaches, and techniques for intervention in school refusal, and consequences of school refusal. The findings are provided by discussing the related literature.

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Introduction

Refusing to go to school or having trouble focusing and staying on schoolwork for an entire school day is a symptom of school refusal, which is a frequent mental health issue originating from anxiety and fear (Kearney, 2008 ; Kearney & Albano, 2004 ). Although school phobia and truancy are discussed in the literature as possible explanations for attendance issues, Kearney ( 2007 ) proposed the term “school refusal.” In this sense, “school refusal” refers to a child’s reluctance to attend school or the difficulty the child has in spending most of the day in the classroom. School refusal is a significant problem affecting approximately 1–5% of all school-aged children, with similar prevalence rates between the sexes, and it tends to be more prevalent among children aged between 5 and 10 years (Fremont, 2003 ). In another study, the percentage of children having the problem of absenteeism due to school refusal was reported to be 4% (Havik et al., 2015 ).

In this context, the behavioral symptoms listed are primarily associated with anxiety. Anxiety can manifest itself in children through different levels of behavioral, physiological, and emotional reactions. Separation anxiety, which is a natural consequence of dysfunctional attachment processes between parents and children, is considered as an essential factor in school refusal (Bitsika et al., 2022 ). Negative emotions and disruptive behaviors such as anger or aggression (Heyne & Boon, 2023 ), social withdrawal (Benarous et al., 2022 ), sleep problems (Maeda et al., 2019 ), difficulty in focusing, and dysphoria may accompany a child’s school refusal (Nayak et al., 2018 ). In addition, emotional instability intense sensitivity in interpersonal relationships, problems in relationships with peers and feelings of loneliness, exposure to peer bullying (Bitsika et al., 2022 ; Ochi et al., 2020 ), and low academic performance (Filippello et al., 2020 ) can be listed as factors that increase the susceptibility of students to experience school refusal.

School refusal, which is associated with school dropout, has a pattern associated with conditions such as substance use, the tendency to violence, suicidality, risky sexual behaviors, involvement in crime, anxiety disorders, psychological adjustment problems (Seçer & Ulaş, 2020 ), and anti-social behavior development (Rocque et al., 2017 ). According to these findings, students’ problematic school absenteeism is linked to various demographic, behavioral, and academic factors (Seçer & Ulaş, 2020 ). It was reported that the reasons for children experiencing school refusal to resort to these behaviors are to attract the attention of other important people (55.1%), avoid stimuli that trigger negative affect (20.4%), and seek concrete reinforcements outside of school (20.4%) (Kearney et al., 2005 ).

An increasing number of studies are carried out, indicating that school refusal is a negativity that threatens young people’s academic and everyday lives in both short and long term (Fernández-Sogorb et al., 2022 ; Fujita et al., 2022 ; Gonzálvez et al., 2023 ; Elliott & Gainor, 2023 ; Leduc et al., 2022 ; Tekin & Aydın, 2022 ). It was reported that it is challenging to return students, who have not attended school for a while, that the child may experience an intense feeling of helplessness in the face of accumulated homework and the amount of work that needs to be compensated, and that there may be a feeling of not belonging to and stress due to the thought of being socially isolated from their classmates. Moreover, a child’s refusal to attend school often causes distress and tension among family members in the short term. It requires parents to constantly have a dialogue with counselors, school psychologists, principals, teachers, and other educators (Kearney, 2007 ). Long-term effects may include the child’s engagement in criminal activities and/or dropping out of school. School dropout is considered to be a severe problem in an individual’s life and may cause negative personal and interpersonal problems. In adulthood, one may encounter unemployment, decline in social functioning, psychological issues, substance abuse, financial difficulties, and decline in family functioning (Rocque et al., 2017 ).

Risk factors related to school refusal

In a review study carried out by Ingul et al. ( 2019 ) aiming to identify risk factors of and early symptoms related to school refusal, it was reported that early symptoms of school refusal include school absenteeism, somatic complaints, depression, and anxiety. In addition, the study listed the risk factors for school refusal as the transition process between school levels, difficulties in emotional regulation, low self-efficacy, negative thinking tendency, inadequate problem-solving skills, insufficient teacher support and supervision, unpredictability of school experiences, bullying, social isolation, loneliness, inadequate collaboration between home and school, parent’s psychological well-being, excessive parental protection, and dysfunctional family processes. Furthermore, empirical studies revealed that perceived social support from teachers, parents, and classmates, parental demand level, test anxiety (Nwosu et al., 2022 ; Havik et al., 2015 ), and low family functionality (Gonzálves et al., 2019 ) are also risk factors for school refusal.

The assessment conducted by Filippello et al. ( 2018 ) indicated that causal relationships between personal characteristics and school refusal have not yet been deeply established. In this regard, personality traits, emotional regulation, and emotional intelligence characteristics have been subjected to risk analysis for school refusal. The findings showed that neurotic personality structure and inappropriate emotional regulation strategies are risk factors for school refusal. Gonzálves et al. ( 2019 ), in a profile analysis of risks for school refusal, reported that social anxiety is an important risk factor for school refusal. Additionally, neurodevelopmental disorders such as autism spectrum disorder can also be considered a risk factor for school refusal. A study comparing school refusal behaviors of typically developing children and those diagnosed with autism found that children with autism exhibit higher levels of school refusal (Munkhaugen et al., 2017 ). It highlights the need for diversifying the sample structure in school refusal research.

Empirical studies on school refusal

Given that school refusal is considered a problem within school attendance issues and its effects can persist throughout one’s lifetime, an assessment can be made regarding the importance of empirical studies on school refusal. Examining the relevant literature, review studies indicate that experimental studies examining school refusal lack a strong scientific basis (Maynard et al., 2014 ) and predominantly favor cognitive-behavioral therapy (Heyne et al., 2020 ; Maynard et al., 2014 ). Despite the effectiveness of this therapeutic approach for conditions such as depression and anxiety, it is considered inadequate for school refusal due to its heterogeneous nature, thus requiring specific interventions (Heyne & Sauter, 2013 ). However, experimental studies demonstrated the effectiveness of cognitive-behavioral therapy in improving school refusal (Maynard et al., 2015 ). The “Back2School” program, developed as an adaptation of cognitive-behavioral therapy, was created aiming to ensure school attendance and effectively intervened with 60 children aged 7 to 16 years as part of the program (Thastum et al., 2019 ).

Dialectical behavior therapy is a more contemporary approach when compared to cognitive-behavioral therapy for school refusal. In this approach, a multi-component structure is utilized in order to directly address the emotional and behavioral dysregulation mechanisms that sustain school refusal behavior. Furthermore, it includes real-time coaching for the child and the parent as needed and in context (Chu et al., 2015 ). It was determined that the age of the child is an important factor for the success of intervention approaches and younger children benefit more (Maynard et al., 2015 ). Thus, Ulaş ( 2022 ) carried out a study involving parent-child interaction therapy for preschool children’s school refusal behavior and this method was reported to be effective. Therefore, it can be stated that early interventions are crucial for addressing problematic behaviors and parent-mediated interaction-based interventions have gained prominence in addressing childhood behavioral and emotional problems in recent times (Niec, 2018 ).

The present study

Although school plays a significant role in determining an individual’s life path, actions such as school refusal can negatively affect these processes. Therefore, it is necessary to detect, intervene, and prevent problems, such as school refusal, at an early stage. However, it can be stated that studies on school refusal in the literature have been carried out using either a relational pattern (Filippello et al., 2019 , 2020 ; Seçer & Ulaş, 2020 ) or a descriptive pattern (Delgado et al., 2019 ; Gonzálvez et al., 2021a , b ; Nwosu et al., 2022 ), and studies carried out using an applied or experimental design (Roué et al., 2021 ; Strömbeck et al., 2021 ) can be considered a minority in this comparison. However, it indicates that there has been very little progress in school refusal treatment within our century, and the reason for this is the heterogeneous nature of this problem (Elliot & Place, 2018 ; Nwosu et al., 2022 ).

Therefore, Inglés et al. ( 2015 ) suggested carrying out studies on the establishment of a conceptual and theoretical framework regarding school refusal. In this parallel, the present study aims to present the overall framework of patterns and heterogeneous structure of the existing literature on school refusal, including experimental or descriptive research articles. Furthermore, when compared to systematic review studies carried out to date, the study carried out by Li et al. ( 2021 ) focused on identifying somatic symptoms related to school refusal. The systematic review study carried out by Leduc et al. ( 2022 ) analyzed school refusal from an ecological perspective. Tekin and Aydın ( 2022 ) aimed to determine the patterns of relationships between school refusal and anxiety. Ingul et al. ( 2019 ), on the other hand, focused on school-based risk factors and early symptoms related to school refusal. In this study as well, taking a holistic perspective, the consideration of risk factors, protective factors, symptoms, and intervention efforts related to school refusal can be regarded as a distinguishing feature from other studies in the literature. In addition, the use of MAXQDA analysis software in the analysis process of this study can be considered an innovative aspect for systematic review studies.

The literature suggests that there are various types of school attendance problem (school refusal, truancy, school phobia, dropout, school withdrawal, etc.) and they should be distinguished from each other (Heyne, 2019 ). In this context, school refusal is considered a cause of public health problems such as school dropout (Thastum et al., 2019 ). Therefore, in this study, a search was made using the keywords of school refusal in order to reveal the general structure of the subject “school refusal”. Therefore, this study aimed to determine the research trends related to the problem area by analyzing research articles on school refusal in terms of their descriptive features and to reveal the structure of the concept of school refusal through content and descriptive analysis to synthesize the findings of the studies. The questions to be answered during the research are “What are the scientific research trends on school refusal?” and “What are the structure and components of school refusal?”

In this study, answering the research questions under investigation will allow for achieving significant findings in both theoretical and practical aspects, particularly in the field of educational psychology. At this point, the synthesis of literature on risk factors, protective factors, intervention approaches, outcomes, etc., related to school refusal problem will provide supportive insights for school psychologists and researchers in their preventive and intervention activities. Furthermore, it can be stated that the findings obtained here could serve as a guideline for education policymakers regarding certain regulations addressing school refusal, which is one of the issues of school attendance problems.

Materials and methods

This study was designed as a systematic review based on the objectives of the researchers. In a systematic review, what is currently known through previous studies on a subject or phenomenon is examined (Zawacki-Richter et al., 2020 ). Systematic review studies have some basic characteristics, such as the existence of a clearly defined set of objectives with predefined eligibility criteria, a clear and repeatable methodology, a systematic search aiming to identify all studies that will meet the eligibility criteria, an assessment of the validity of the findings of the included studies (for example, by assessing the risk of bias), and a systematic report and synthesis of the characteristics and findings of the studies included (Higgins & Green, 2008 ).

In this context, the steps followed in the research can be listed as determining the systematic review questions, drawing the conceptual framework, determining the inclusion criteria, determining the strategies for searching the studies, determining the studies to be examined, coding the studies, determining the nature of the included studies, and synthesis.

Data sources

The data sources of the present study were determined in accordance with the inclusion and exclusion criteria given below.

The inclusion criteria are:

Being accessible with the “school refusal” keyword in Web of Science (WoS).

Being published between the years 2012 and 2021.

Being open access.

Being published in the English language.

The reasons for the inclusion criteria established by researchers are the use of current studies for the “time limitation”, accessing the complete records for “open access”, use of the universal language used in science for “the English language”, and the use of the most important scientific literature database for “Web of Science database” (Harzing & Alakangas, 2016 ).

The exclusion criteria are:

If the study accessed is not directly related to school refusal but found as a result of a search with a keyword; in other words, school refusal is not a basic variable for the study reached, but only in the text of the article,

Studies that are not research articles (reviews, thesis, editorial letters, or theoretical articles),

Scale adaptation studies,

Being published after May 2021,

Studies testing practices outside the field of psychology (e.g., pharmacological treatments).

The primary aim of researchers in determining the exclusion criteria is to access research articles directly related to education and psychology and studies examining the school refusal. For instance, studies that were identified through a search using the keyword of school refusal but are excluded from the scope of this study due to the fact that they only contain a mention of school refusal in the discussion section were not included. Preferring research articles as the source of data, the present study focuses on identifying and analyzing factors related to school refusal in accordance with the research objective.

In this context, the stages of determining the data sources are given in Fig.  1 and the data sources of the study are presented in Table  1 .

figure 1

PRISMA flowchart. Page et al., ( 2021 )

Study selection and data extraction

The Web of Science database was searched by two researchers in terms of titles and abstracts. Studies that were seem to not have not suitable titles or abstracts were excluded. The suitable ones were obtained in full-text format. Then, a detailed examination was conducted based on the inclusion and exclusion criteria of the study. The studies that fell within the scope of the research were independently coded by two researchers. Coding differences between the two researchers were discussed and resolved through consensus.

To address important threats to the reliability of the study, such as selection bias and reporting bias, all steps related to the included data sources were confirmed, discussed, and agreed upon among the researchers to mitigate these biases, ensuring the study’s credibility. Accordingly, both researchers played a role in determining whether the studies met the inclusion criteria. Both researchers worked together in the analysis and reporting of the obtained data sources. In this study, the researchers worked by coding the concrete data with the principle of accountability over the MAXQDA 2020 software to avoid the risk of bias. This project file is provided as an attachment.

Following the searches based on inclusion and exclusion criteria, the researchers addressed 40 research articles presented in Table  1 within the scope of two separate research questions: the characteristics related to scientific research (methodology, data collection tools, etc.), and the characteristics related to the field of school refusal.

Results regarding research question 1

The first research question, “What are the scientific research trends in studies on school refusal?” was determined as the initial query to be answered. In this process, the researchers aimed to reveal the descriptive characteristics of studies on school refusal. The findings obtained in this direction are presented in Fig.  2 .

figure 2

Descriptive characteristics of data sources. Note: This figure was created by the researchers using the MAXQDA software

Figure  2 shows that the researchers examined six different aspects of the studies that were data sources for this study: year, methodology, participants, data collection tools, data analysis methods, and data collection procedures.

Considering that the search for data sources was completed in May 2021, it can be stated that publications on school refusal exhibited an increasing trend. Examining the research methods used in those studies, it can be concluded that the studies primarily used quantitative research methods. In the category of data collection tools , which is a part of research methods, scales were preferred commonly and interviews were preferred rarely. However, a quantitative study provided no information about data collection. The data collection procedure , another category of the study, was carried out face-to-face mostly.

The data analysis category, on the other hand, is divided into sub-categories such as difference analysis, relational analysis, and qualitative data analysis. It can be said that regression analyses were mostly preferred in relational analyses. In the qualitative analysis subcategory includes thematic analysis, interpretive phenomenological analysis, and inductive analysis. In the data analysis category, it can be interpreted that differential analyses are used extensively.

The last category regarding the descriptive characteristics of the studies examined was the structure of the participants (sample) . It can be seen that sampling consisted of preschool students, primary school students, high school students, the clinical group, students with special needs, healthcare professionals, school staff, and parents.

As a result, it was observed that the school refusal problem is a current problem area, and quantitative research methods and techniques have been employed in order to understand the heterogeneous nature of this problem. Furthermore, it is very important to carry out studies with a sample structure that includes students from all grade levels, students with special needs, as well as professionals and parents. This approach allows for a multi-dimensional assessment of school refusal.

Results regarding research question 2

The primary aim of this research is to create a pattern of variables related to school refusal through the content analysis of previous studies on school refusal. In this regard, the second research question being addressed is “What are the structure and components of school refusal?” In this process, the researchers aimed to synthesize the findings of studies on school refusal.

In the analysis process, the codes obtained from the data sources were grouped into five categories: risk factors for school refusal, symptoms of school refusal, protective factors for school refusal, consequences of school refusal, intervention techniques and approaches to school refusal. The findings are shown in Fig.  3 .

figure 3

The Structure and Components of School Refusal. Note: This figure was created by the researchers with the MAXQDA software

Results regarding the risk factors for school refusal

Subcategories were created for the category of risk factors for school refusal: risk factors originating from individual characteristics, risk factors arising from environmental characteristics, and risk factors arising from family characteristics.

Exposure to peer bullying, reactive attachment disorder, perfectionism, low self-perception, lack of emotion and impulse control, difficult childhood experiences and trauma, depression, health-related factors, anxiety, and low self-efficacy codes were included in the risk factors arising from individual characteristics. Exposure to peer bullying was analyzed particularly as verbal and cyberbullying types, whereas anxiety was analyzed as general anxiety, school-related anxiety, and social anxiety (avoiding entering a new environment and negative emotions and being evaluated in all dimensions). In addition, in the category of health-related factors, among neurodevelopmental disorders, the autism spectrum disorder and attention deficit and hyperactivity disorder were included. In the category of childhood difficulties experienced and traumas, psychological fragility, behavioral disorders such as stealing, neuroticism, and learned helplessness were included.

Parental depression, negative living conditions, high expectations of the family from school, families not sharing the school mission, high-performance pressure from parents to the child, low education level of family, and living with a single parent at home codes are included in the risk factor subcategory arising from family characteristics .

The risk factors arising from environmental characteristics are the attendance of children with special needs in regular schools, social inequalities, the pressure on teachers to catch up with curriculum and being a minority from different cultures codes.

Category of symptoms for school refusal

The second category was determined as school refusal symptoms . Inadequate interactions between parents and children, intolerance to time spent in classroom, school-related anxiety, insufficient peer interaction, unpleasant feelings towards school, absenteeism, avoidance of school attendance, high-level aggression, and antisocial behavior codes were rated as the most common symptoms.

Category of factors for school refusal

The third category was determined to be a protective factor against school refusal . In this category, protective factors originating from individual characteristics, protective factors arising from environmental characteristics, and protective factors arising from family characteristics are included.

Effective friendships, having learning goals, extraversion, high self-esteem, having a well-adjusted profile, commitment to school values, prosocial behaviors, high academic endurance, high social skills, and high social functionality codes are some of the individual characteristics included in the protective factors. Positive perceptions of family function, high family harmony, high socioeconomic level, and effective teacher and family relationship codes are among the protective factors originating from family characteristics . Protective factors originating from environmental characteristics consist of codes such as positive teacher-student relationship, perceived teacher support, and early intervention for existing psychiatric problems.

Category of consequences of school refusal

Another category was the consequences of school refusal . This category consisted of social withdrawal, low academic achievement, depression, emotional exhaustion, and low school attachment codes. In this context, studies have shown that the depression code can be both a risk factor and a result of school refusal.

Category of intervention technics and approaches to school refusal

Finally, the categories of intervention techniques and approaches to school refusal were created, and the inclusion of trauma intervention techniques in school curriculum, school-based quick feedback practice, cognitive behavioral therapy, parent counseling, and time-out technique were determined as the codes in this category.

Conclusion and discussion

Figure  2 illustrates the results achieved from the examinations and analyses conducted to analyze the research tendencies of the studies conducted on school refusal, which is the first research question of the current study. It is important that studies on the causes and consequences of school refusal gained weight in recent years. When compared to other factors, significant attention has been paid to quantitative studies that analyze this phenomenon. This can be attributed to the fact that school refusal is a relatively new area of research in the literature. It is also one of the present study’s significant findings that there has not yet been any study with mixed methods research that aims to combine the strengths of quantitative and qualitative studies of school refusal. School refusal differs from other problems and its causality cannot be explained simply.

As a matter of fact, as a result of the conceptualization study by Karthika and Devi ( 2020 ), in which they sought the answer to the question of whether school refusal is a psychosocial or psychiatric problem, they framed school refusal as a comorbid problem with one or more psychiatric problems. Even though it is a psychiatric problem, it is not included as a separate diagnosis in the DSM-V or ICD-10 due to its heterogeneous causality and association with many problems (Roué et al., 2021 ).

Regarding the first research question, it was also determined that the sample structure preferred in the studies primarily included high school students (between the ages of 10 and 18), which corresponds to the adolescence period (Strömbeck et al., 2021 ; Seçer & Ulaş, 2020 ). When compared to other demographics, high school students are more likely to have a school refusal problem that eventually leads to dropouts because of the crucial responsibilities of their life stages. This may be why researchers have focused so much attention on the phenomenon of high school students’ school refusal. However, previous studies draw attention to the importance of early-period studies on the school refusal (Maynard et al., 2015 ). A study was also carried out not only with students but also with school staff, healthcare professionals, and parents (Devenney & O’Toole, 2021 ; Gallé-Tessonneau & Heyne, 2020 ) can be interpreted as the factors affecting the school refusal problem should be examined from a broad perspective.

As a result of the analyses conducted in order to determine the structure and components of school refusal, which was the second question of the study, school refusal was seen to have five components. Among individual risk factors, anxiety, depression, exposure to bullying, and health-related factors were the codes repeated frequently.

In this context, Devenney and O’Toole’s ( 2021 ) study on instructors concluded that there is a strong relationship between school refusal and anxiety, which may even be a traumatizing experience. The same study revealed that performance pressure on children, separation anxiety, and peer exclusion are significant predictors of school refusal. According to the results of a study carried out on adolescents by Delgado et al. ( 2019 ), children who were victims of cyberbullying had a higher level of school refusal in comparison to those who were not. In this context, it can be stated that social anxiety, which is closely related to bullying, is a significant risk factor for school refusal (Gonzálvez et al., 2019 ). Ochi et al. ( 2020 ), on the other hand, found that being exposed to bullying is an important risk factor for school refusal in children with autism as well as in children without developmental disorders.

Therefore, it can be stated that school refusal is accompanied by separation anxiety, which is one of the anxiety types, in younger age groups (5–12), whereas it is accompanied by social phobia in older age groups (13–16) (Ingul & Nordahl, 2013 ). In addition, situations that increase students’ susceptibility to school refusal include negative affectivity, intense sensitivity in interpersonal relationships, problems in relationships with peers, feelings of loneliness, emotional distress, depression, and low self-efficacy perception (Devenney & O’Toole, 2021 ; Bitsika et al., 2021 ).

When examining the familial risk factors associated with school refusal, it was determined that families with high-performance expectations from their children and inadequate engagement in basic school duties are significant risk factors. In this context, as reported in the study carried out by Ulaş and Seçer ( 2022 ), the high level of performance expectations of families leads students to be perfect and not tolerant of mistakes. As a result of the intense effort and sense of competition brought about by this, students’ school burnout was evaluated as inevitable. Thus, school burnout may be a risk factor for school refusal (Liu et al., 2021 ). Another risk factor in the same category is parental depression. Children’s mental health is significantly affected by that of parents (Adams & Emerson, 2020 ). Marin et al. ( 2019 ) determined that parents’ stress, depression, and psychological control levels significantly predicted children’s school refusal levels.

In the environmental risk factor category for school refusal, the code of being from different cultures and being in a minority position draws attention. Rosenthal et al. ( 2020 ) investigated the experiences of immigrant parents of adolescents who were diagnosed with school refusal. In particular, social inequalities or exposure to racism were found to be the main challenges for these parents. In addition, parents may experience feelings of guilt because their children’s future has been interrupted since they migrated, which may open the door to issues such as parenting stress and depression.

The second component of school refusal is school refusal symptoms. It was found that students who experience school refusal in this category tend to show high levels of aggression, have unpleasant feelings towards school (Devenney & O’Toole, 2021 ), have inadequate parent-child interactions (Gallé-Tessonneau & Heyne, 2020 ), have insufficient peer interaction (Gallé-Tessonneau & Heyne, 2020 ; Filippello et al., 2018 ), absenteeism, intolerance to classroom time, and avoidance of school (Gallé-Tessonneau & Heyne, 2020 ). Behaviors generally observed among children with school refusal are defined by Kearney ( 2007 ) as physical problems, such as non-specific anxiety or worrying that something bad will happen, tension from being around others, or having to perform, general sadness of having to go to school, irritability and restlessness, stomachache, headache, tremor, nausea, vomiting, frequent urination, muscle tension, diarrhea, lightheadedness or fainting, palpitations, dizziness, shortness of breath, hyperventilation, sweating, and tantrums, such as insomnia, extreme tiredness, crying, screaming, kicking, and shaking.

The third component of school refusal is a protective factor against school refusal. In this context, protective factors are discussed as protective factors originating from individual, family, and environmental characteristics. In particular, examining the protective factors arising from individual characteristics, high level of social functioning, high self-esteem, and learning goals stand out as protective factors. From this aspect, it can be said that students with high social functioning and prosocial behaviors (Filippello et al., 2018 ), academic resilience (Seçer & Ulaş, 2020 ), and self-esteem can eliminate several risk factors for school refusal.

In this study, codes related to protective factors arising from environmental factors were positive teacher-student relations, perception of teacher support, and early intervention in psychiatric problems. Brandseth et al. ( 2019 ) concluded that belonging to the classroom mediated teacher support and mental well-being. This is considered an important protective factor for school refusal, according to studies examining the predictive relationships between school attachment and school refusal (Seçer & Ulaş, 2020 ).

Another category within the protective factors was determined to be the protective factors arising from family characteristics. In this context, children’s perceptions of family harmony and family functioning emerged as codes with an important protective function for school refusal. Gonzálvez et al., ( 2019 ) concluded in their study that it is important to solve family problems in order to prevent school refusal. In a study carried out with adolescents with and without school refusal, parenting self-efficacy perceptions of parents of adolescents with school refusal were lower than those of parents of adolescents without school refusal (Carless et al., 2015 ). Since parental self-efficacy perceptions of parents are an important determinant of family functioning, it can be concluded that high-level family functioning perception has a protective role against school refusal. In addition, studies have shown that the relationship between parents and children, in other words, healthy attachment patterns, have an essential protective function against school refusal (Doobay, 2008 ).

Another component of school refusal was found to be the consequences of school refusal. The codes were low school attachment, low academic achievement, emotional distress, social withdrawal, and depression. On the other hand, Sewell ( 2008 ) listed the consequences of school refusal as low academic achievement in the short term (less than two years), negative peer and family relationships, academic failure in the long term (more than two years), and psychiatric problems. School refusal results in mental health problems, especially anxiety and depression (Devenney & O’Toole, 2021 ). Social withdrawal, the consequence of school refusal, and a symptom of depression have also been frequently discussed in the literature. Social withdrawal and low social functioning (Seçer & Ulaş, 2020 ) are consequences of school refusal. With the decrease in school attachment, the problem of school refusal can lead to early school dropout, which is more broadly defined as perpetuating not going to school without an excuse (Awad-Abouzid et al., 2021 ). School dropouts can cause serious sociological problems as well as mental health problems.

As a result of the discussion on the risk and protective factors, symptoms, and consequences of school refusal, it was found that there is a problem that necessitates early intervention. In this context, the last theme of the study was determined to be the intervention approaches and techniques addressing the school refusal. In this sense, it includes parenting counseling (Strömbeck et al., 2021 ), CBT, school-based rapid return approach (Maeda & Heyne, 2019 ), time-out technique, and inclusion of trauma intervention techniques as a recommendation in school curricula (Devenney & O’Toole, 2021 ) were the codes determined. CBT-based interventions were intense in the studies included in the scope of the study (Strömbeck et al., 2021 ). In studies on anxiety as a risk factor for school refusal, it was reported that there was a decrease in school refusal behaviors and an increase in school attendance with CBT-based interventions in children with anxiety (Doobay, 2008 ; Thastum et al., 2019 ) and depression.

Gradual muscle relaxation, modeling, exposure, cognitive restructuring, social skills, problem-solving, and coping skills were emphasized, and it was concluded that it was effective in the intervention of school refusal (Doobay, 2008 ). It was suggested that parents should be involved in the intervention for a realistic and lasting impact on school refusal (Doobay, 2008 ). In particular, the inclusion of sessions and modules in CBT programs for parents was frequently preferred, and it was concluded to be effective (Reissner et al., 2015 ). Behavioral interventions for school refusal mainly use techniques such as exposure, systematic desensitization (including relaxation training), guided affective imagery, modeling, and shaping (Elliott & Place, 2012 ). However, some therapists may abstain from using exposure because they think that it can be dangerous (Richard & Gloster, 2007 ), increase school refusal (Gryczkowski et al., 2013 ), and negatively affect the therapeutic alliance (Kendall et al., 2009 ). However, Peterman et al. ( 2015 ) provided a handy guide to exposure techniques in response to school refusal resulting from avoiding anxiety-provoking situations.

Nuttall and Woods ( 2013 ) aimed to deal with school refusal by using an ecological approach. Richardson ( 2016 ), on the other hand, used the family therapy approach to intervene with school refusal in children and adolescents. The results showed that systemic family therapy for the treatment of school refusal tends to be significantly effective in younger children when the problem is not fully established and family functioning is high before problematic behavior.

In line with the findings and literature, school refusal can be considered a problem that needs to be prevented and intervened. The consequences of school refusal in the short term cause situations such as decreased academic success, social withdrawal and isolation, increased risk of legal problems such as juvenile delinquency, conflict within the family, and changes in the daily life routines of the family and the individual; in the long term, it cause situations such as dropping out of school, economic deprivation, social, and can cause professional and marital problems, alcohol or substance addiction, crime, and mental impairment (Kearney et al., 2007 ). School attendance problems due to school refusal can lead to a decrease in school success, a weakening of social relationships, a decrease in school belonging, and, ultimately, school dropout. This situation is undoubtedly a stress factor for the family, which limits the family functionality between parents and other children. Parents may feel that they have made mistakes while raising their children, are inadequate, or are blamed by the school staff (Havik et al., 2014 ). Given this situation, which significantly limits the level of social welfare, this study provides both practical and theoretical contributions in developing collaborative multifaceted applications and enabling education politicians to focus on the importance of this issue. By understanding school refusal conceptually and addressing the basic risk and protective factors, it can be evaluated that this study has a facilitating role in creating e-courses, training modules, and psychoeducational contents for students, parents, teachers, and education policymakers.

Future direction

The present study provided recommendations for both researchers and practitioners. It was determined that there is a limited number of randomized controlled trials regarding school refusal (Heyne et al., 2011 ; Maynard et al., 2015 ). As a result of this situation, it was observed that there is a limitation in evidence-based interventions for school refusal. At this point, it is suggested that future researchers should focus on randomized controlled trials regarding school refusal. In addition to standard therapy approaches in randomized controlled studies (such as Cognitive-Behavioral Therapy and Psychodynamic Therapy), it is recommended to develop problem-specific programs or modules based on the adaptations of these therapies (Elliott & Place, 2018 ). Furthermore, the findings suggest studies to be carried out in accordance with the mixed-methods approach, which combines the advantages of both quantitative and qualitative methods, resulting in research with high validity and reliability (Mertens, 2023 ). In addition, the need for multi-level studies is emphasized, and it is recommended to carry out these studies cross-culturally in order to achieve generalizable results.

For practitioners such as educational policymakers, school psychologists, and other experts, it is suggested that they can expand the content of educational programs by making use of the findings of this study, which addresses school refusal as a multifaceted problem with a defined framework. Considering the fact that school attendance problems can lead to individual as well as social issues, these adjustments can be considered necessary. Moreover, it is recommended that parents and school staff also participate in various practices such as training or courses in a comprehensive approach. Indeed, in the present study, collaboration between schools and families, as well as positive teacher-child relationships, were identified as protective factors (Filippello et al., 2019 ). Furthermore, considering that immigrant children, those with developmental problems, and children with various health issues carry risks of school refusal, it is suggested that preventive and intervention programs addressing these groups should be promoted.

Limitations

The fact that only the keyword “school refusal” was used as a keyword in the search process is a limitation. Although WoS is accepted as the most important database in the international scientific literature (Harzing & Alakangas, 2016 ), the fact that other databases were not searched is also a limitation of this study. The inclusion and exclusion criteria (being accessible with the “school refusal” keyword in WoS, being published between 2012 and 2021, being open access, and being published in the English language) for data sources can also be considered as a limitation. As a result of the search made with the keyword “school refusal” in the Web of Science database, it was seen that the studies carried out in the last 10 years (2022 − 2012) constituted 51% of the total. Considering that the first publication year was 1970, the reason for this limitation is to reach more up-to-date school refusal studies. In addition, more publications with 51% are the source of this study. Although publications were made in Russian (1%), German (1%), French (0.6%), and Japanese (0.3%), etc. languages, the publication language of the data sources was limited to English. The reason for this is that 95% of the publications are published in English. In this context, it is recommended to carry out studies that eliminate these limitations in future review studies on school refusal.

Data availability

The datasets for this study can be found in this link. ( https://drive.google.com/file/d/1hkC4zvxMJpuPgUooq-gW0PzHrWaSsOEK/view?usp=share_link )

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Effects of game-based physical education program on enjoyment in children and adolescents: a systematic review and meta-analysis

  • Weilong Mo 1 , 2 ,
  • Jamalsafri Bin Saibon 1 ,
  • Yaming LI 1 ,
  • Jiequan Li 3 &
  • Yanwu He 4  

BMC Public Health volume  24 , Article number:  517 ( 2024 ) Cite this article

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The objective of this study was to conduct a systematic review to summarize and assess the advancements lately made on the enjoyable impacts of game-based physical education interventions on children and adolescents. Additionally, it attempted to identify the effects and variables influencing the enjoyable outcomes of children and adolescents’ engagement in physical education games, through meta-analysis.

This study involves a comprehensive search of different databases like Web of Science, PubMed, Embase, EBSCOhost, Cochrane, and Scopus. Specific criteria are established for the selection process to make sure the relevant literature included. The quality assessment of the included researches is conducted based on the guidelines outlined in the Cochrane 5.1 handbook. Review Manager 5.3 software is employed to synthesis the effect sizes. Additionally, bias is assessed using funnel plots, and to identify potential sources of heterogeneity, subgroup analyses are performed.

A total of 1907 academic papers, out of which 2 articles were identified via other data sources. The present study examined the impact of a pedagogical intervention involving physical education games on the enjoyment experienced by children and adolescents. The results indicated a significant positive effect (MD = 0.53, 95%CI:[0.27,0.79], P  < 0.05) of this intervention on enjoyment. Subgroup analyses further revealed that both boys (MD = 0.31, 95%CI:[0.13,0.50], P  < 0.05) and girls (MD = 0.28, 95%CI:[0.05,0.51], P  < 0.05) experienced increased pleasure compared to traditional physical education. Additionally, children under 12 years of age (MD = 0.41, 95%CI:[0.17,0.64], P  < 0.05) benefited from sessions lasting at least 30 minutes or more per session (MD = 0.40, 95%CI:[0.19,0.60], P  < 0.05), occurring 1 to 3 times per week (MD = 0.28, 95%CI:[0.16,0.40], P  < 0.05), and lasting for more than 3 weeks (MD = 0.81, 95%CI:[0.29,1.34], P  < 0.05). These findings suggest that the implementation of physical education games can be an effective approach to teaching this subject.

Conclusions

1) Interventions using physical games have been shown to yield beneficial outcomes in terms of enhancing the enjoyment experienced by children and adolescents. 2) The effectiveness of treatments aimed at promoting enjoyment among children and adolescents is influenced by several aspects, including gender, age, duration and frequency of physical activity, as well as the specific cycle of activity used.

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Introduction

Enjoyment is a subjective experience with pleasant emotions, such as pleasure, like, and fun [ 1 ]. Children and adolescents are naturally motivated by enjoyable experiences during the learning process, which enhances their academic achievement, involvement and effort in learning [ 2 , 3 , 4 ], this, in turn, leads to more effective and long-lasting learning [ 5 , 6 ]. In contrast, falling enjoyment can diminish their interest and engagement. Therefore, the cultivation of enjoyable feelings in children and adolescents has a crucial role in enhancing educational achievements.

Studies proved that physical education has a beneficial influence on the psychological and physical health of children and adolescents [ 7 , 8 ], as well as on the prevention of disease problems [ 9 ]. The influence of physical education on the enjoyment of children and adolescents, particularly in relation to emotions, has clear benefits [ 10 ]. Physical education activities for children and adolescents not only have the power to enhance individual happiness, but also foster a positive team atmosphere and promote collaboration and socialization [ 11 ]. Thus, it is essential to explore the positive impact of these activities on enjoyment and mental health.

Compared with traditional physical education, physical education games have several advantages. The implementation of physical play interventions has the potential to facilitate the acquisition of knowledge and skills among children and adolescents [ 12 , 13 ], enabling them to get enjoyment from the process of learning. A combination of entertainment components into traditional physical education (PE) is effective in motivating non-athletic students to actively engage in PE lessons, which cannot be achieved through organized sports [ 14 ]. Liao et al. [ 15 ] further explain that games not only enhance students’ satisfaction with PE lessons, but also facilitate skill development, create a relaxed play environment, foster interpersonal interactions, and offer opportunities for cooperation and socialization.

Hence, the implementation of physical games teaching offers a new and innovative approach within the context of traditional physical education classes [ 16 ]. This approach to learning is not only pleasurable for students, but also meets their requirement for social and physical engagement in the educational process and, most notably, contributes to a key part in sustaining the involvement of children and adolescents in physical education and sports [ 17 ].

Through a comprehensive analysis of 16 academic studies, it has been noticed that further research is needed regarding the efficacy of applying physical education games to enhance enjoyment in children and adolescents. Since the majority of studies show a beneficial effect on enjoyment [ 1 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ]. However, five studies remain uncertain about the impact of these games [ 14 , 27 , 28 , 29 , 30 ], and there is even a case where teaching with games seems to reduce students’ enjoyment [ 27 ]. Currently, there is not enough comprehensive analysis on how physical game teaching impacts the enjoyable feelings of children and adolescents, and also on the potential factors that may influence those effects (such as gender, age, and duration of the interventions).

The aim of this study was to explore the following topics with a meta-analysis: 1) whether teaching games in physical education has a beneficial influence on enjoyment experienced by children and adolescents, and 2) how other essential elements mitigate the influence of games teaching in physical education on enjoyment experienced by children and adolescents. Due to inconsistent findings from earlier research, there is no consensus on the link of physical games for enjoyment in children and adolescents; yet there is optimism that teaching physical play may have a favorable impact on enjoyment.

Search strategy and standards for selection

This research is conducted under the guidance of Cochrane Handbook for the Systematic Review of Interventions [ 31 ] and the PRISMA Statement Specification for Systematic Review and Meta-analysis [ 32 ].

This research explores six databases, namely Web of Science, PubMed, Embase, EBSCOhost, Scopus and Cochrane. PubMed is primarily adopted to identify medical terms (Mesh). The search period spans from the initiation of database collection until July 25, 2023. Both subject terms and the free word approach are included in the search. The following table consists of many columns. This study firstly focuses on the research object and then emphasizes the intervention strategy. In the third line, the result index is built by connecting the search words using the logical operator “or” inside each group of search terms. Additionally, the search phrases are linked by “or” between each set of search terms. Table  1 displays the whole search words used in the six databases.

Criteria for inclusion and exclusion

Research that meet the following requirements are selected for systematic evaluation: (1) the intervention modality is physical game teaching; (2) the subjects are children and adolescents (3–18 years old); (3) the outcome indicator is the inclusion of enjoyment related MeSH and Entry Terms; (4) the use of a control group; and (5) the articles are written in English.

Researches reach the following standards are omitted from systematic evaluation: (1) the intervention method is not physical game teaching; (2) the experimental subjects are infants, adults, animals, and specific populations (psychiatric patients), etc.; (3) the outcome indicator is the absence of pleasure-related subject terms and free words; (4) no control group is included; (5) the articles are written in other non-English languages; (6) review article; and (7) conference articles.

Screening process

Upload the relevant literature to Endnote (version X9) for organization. Following this, duplicate results are screened by two authors (MWL and LYM) independently. The screening process include reviewing titles, review articles, conference papers, and animal experiments. Read the abstracts to exclude articles that fail to meet such criteria as study subjects or interventions. Finally, read the full text of selected articles to exclude those that are inaccessible, non-English and does not provide end point indicators. The process involves an initial screening of eligible articles, a discussion of any discrepancy and reaching a consensus with the third author (LJQ). Ultimately, 16 articles are selected for the systematic analysis. Detailed information about these steps are presented in the PRISMA flowchart (refer to Fig.  1 ).

figure 1

Flowchart for inclusion and exclusion of studies

Extraction of data and quality evaluation

Three authors (MWL, LYM, and LJQ) extract data from eligible papers in an impartial manner. Any divergence is resolved through discussion until an agreement is reached. The extracted information is then placed in the publications respectively [ 1 ]. the extracted information primarily includes the name of the first author and the publication year [ 2 ]. the subjects’ features encompass the total sample size, age, and gender [ 3 ]. detailed data, like duration, frequency, and cycle, about the teaching process of physical education and sport games are included [ 4 ]. the intervention tool employed in the study is a questionnaire or scale designed to measure the degree of pleasure, satisfaction and motivation before and after physical education [ 5 ]. the intervention items utilized in the study are game items specifically employed for physical education [ 6 ]. the outcome indicators encompass various factors, including the level of pleasure, satisfaction, and motivation before and after physical education and sport activities. Pleasure may be defined as the state of experiencing gratification, enjoyment, satisfaction, delight, or fun [ 7 ]. the writers emphasize the importance of significant results.

The Cochrane 5.1 handbook is applied to assess the quality of bias. The evaluation includes one aspect, namely the random allocation procedure and the concealing of allocation schemes. In this research, the evaluation criteria are: 3) participant blinding and outcome assessment, 4) complete outcome data, 5) selective report findings, and 6) bias from other sources. Each criterion is assessed as having either a low risk (an indication for meeting the criterion), a high risk (an indication for not satisfying the criterion), or a medium risk (if not mentioned), with a note explaining the reason for this assessment. Two researchers assesses the article quality independently. Any divergence in their evaluations are solved by discussing with another author. Figure  2 shows the evaluation findings and the detailed information. A sensitivity analysis is conducted whereby each article is systematically removed one at a time. The analysis reveals that the findings are mostly unchanged, which suggests that the results are robust and reliable.

figure 2

Cochrane risk of bias evaluation

Statistical analysis

Review Manager 5.3, a statistical software, is applied to merge effect sizes and assess for bias. In this analysis, the indicator continuous variable is incorporated, making the results presented as mean ± standard deviation (Mean ± SD). The I 2 and Q tests are adopted to evaluate heterogeneity between studies. The fixed-effects model is applied as the I 2  < 50% or p  > 0.1, indicating the studies lack statistical heterogeneity. In contrast, a random-effects model is adopted to evaluate publication bias using funnel plots and to examine the reliability of the findings.

Search results

A comprehensive search for 1907 articles in total is conducted. The databases for search are Web of Science (1473 articles), PubMed (33 articles), Embase (75 articles), EBSCO host (154 articles), Cochrane (95 articles), and Scopus (75 articles). All identified articles are uploaded to Endnote (version X9), a reference management software. By examining the article titles, a total of 207 duplicate items are eliminated from further analysis. The articles are uploaded to Endnote (version X9), and after examining the titles, a total of 207 duplicates are removed. The dataset comprises 321 conference papers, 44 review articles, 31 articles with inconsistent subjects, 1 article applying inconsistent measurement tools, 94 articles employing inconsistent interventions, 66 articles featuring different endpoints as determined after reading the full text. 14 articles presenting results deviate from the mean ± standard deviation format. A total of 27 publications without a control group are identified, and 8 articles written in non-English languages are excluded. Additionally, the full texts of 26 articles are incomplete or unavailable. Hence, a final set of 16 eligible articles is included in the meta-analysis.

Basic features of the included articles

The analysis encompasses 16 articles, which collectively examines 17 studies. The total sample size has 2181 participants, with 1139 individuals assigned to the experimental group and 1042 individuals assigned to the control group. There were 1096 male participants and 1048 female ones. The age of the samples ranges from 4.9 to 15.62 years. The intervention duration covers from 15 to 90 minutes, with frequencies from 1 to 9 times each week. The intervention cycles span from 2 to 14 weeks. The interventions are concentrated on sports and games programs. The assessed outcome indicators include enjoyment and satisfaction, intervention instruments and major findings. See Table 2 for detailed information.

Quality assessment

This research examines the literature about the random assignment process and specifically focuses on six studies that meet the inclusion criteria [ 20 , 22 , 23 , 26 , 28 , 33 ]. The remaining research do not provide details about the randomization process. None of the 17 studies mention whether the allocation is concealed or not in the allocation scheme concealment. In terms of blinding, researchers on the subjects and inform them about the tests. Thus, the subjects are not blinded. Consequently, all 17 studies are deemed to have a high risk. The evaluation of the findings is featured with uncertainty. Two studies had a high incidence of staff turnover as for the completeness of the outcome data [ 20 , 27 ]. None of the 15 studies shows any subject or data loss, and all of them are considered to have low risk. The included studies show no further selective reporting or biases, and all of them are considered to have low risk of bias.

Tests for bias

This research includes outcome indicators for analysis, and the funnel plot demonstrates a distribution that is symmetrical, indicating the absence of publication bias, as seen in the Fig.  3 .

figure 3

Bias funnel plot

Efficacy tests

The relationship between teaching games in physical education and enjoyment of children and adolescents.

Heterogeneity tests were performed on the articles that were included in the analysis. Out of the total, 17 research (comprising 16 papers) indicated an altered association between the enjoyment experienced by children and adolescents in the context of teaching physical education games [ 1 , 14 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 33 ]. The researchers apply a random effects model to collect the findings about the articles’ outcome indicators. This study includes 17 studies and 2181 participants in total, with 1042 in the control group and 1139 in the experimental group. The present research provides evidence supporting the favorable impact of a physical education intervention using games on the positive emotions of children and adolescents in the experimental group (MD = 0.53, 95% CI: [0.27, 0.79], P  < 0.05), as depicted in Fig.  4 .

figure 4

Forest plot depicting the relation between physical game teaching and enjoyment in children and adolescents

Subgroup analyses

The combined impact size data for physical play teaching interventions on children and adolescents show a significant degree of variation. It is achieved by analyzing subgroups based on gender, age, duration, frequency, and cycling as potential influencing factors.

The results of subgroup analyses examining the influence of gender, age, duration, frequency, and cycling on the effects of games in physical education indicate that such games can enhance enjoyment of boys (MD = 0.31, 95% CI:[0.13,0.50], P  < 0.05) and positively affect girls (MD = 0.28, 95%CI:[0.05,0.51], P  < 0.05). Furthermore, it is observed that children aged 12 experienced an increasing enjoyment (MD = 0.41, 95% CI:[0.17,0.64], P  < 0.05), whereas adolescents aged 12 and above do not show a similar increase ( P  > 0.05). The duration of physical education sessions ranging from 30 to 60 minutes (MD = 0.40,95%CI:[0.19,0.60], P  < 0.05) can provide a favorable impact on enjoyment experienced by children and adolescents. Moreover, extending the duration of physical education beyond 60 minutes (MD = 0.55,95%CI:[0.10,1.00], P  < 0.05) may also improve their enjoyment. However, noticeably, durations shorter than 30 minutes do not show the same good effect ( P  > 0.05). It is more feasible to provide physical game teaching within a frequency range of 1 to 3 sessions per week (MD = 0.28,95%CI:[0.16,0.40], P  < 0.05) to elicit enjoyment among children and adolescents. Conversely, it is unsuitable to give physical game instructions, exceeding the threshold of 3 sessions per week ( P  > 0.05). The optimal duration for physical game teaching to elicit enjoyable outcomes in children and adolescents is between 3 to 6 weeks (MD = 0.81, 95%CI:[0.29,1.34], P  < 0.05), but durations beyond 6 weeks are also considered acceptable (MD = 0.29, 95%CI:[0.10,0.48], P  < 0.05). In contrast, it is not a proper option to be engaged in physical games for less than 3 weeks ( P  > 0.05). Hence, such factors as gender, age, duration, frequency, and cycle contribute significantly to the observed variation in satisfaction, as seen in Figs.  5 , 6 , 7 , 8 , 9 .

figure 5

Forest plot depicting gender subgroup relationship between physical game teaching and enjoyment in children and adolescents

figure 6

Forest plot depicting age subgroup relationship between physical game teaching and enjoyment in children and adolescents

figure 7

Forest plot depicting duration subgroup relationship between physical game teaching and enjoyment in children and adolescents

figure 8

Forest plot depicting frequency subgroup relationship between physical game teaching and enjoyment in children and adolescents

figure 9

Forest plot depicting cycle subgroup relation between physical game teaching and enjoyment in children and adolescents

Main research analyses

The results of this study, including the analysis of 17 studies, show that the adoption of physical education game-based intervention has a beneficial effect on the enjoyment levels of children and adolescents. Such corresponds to the idea offered by Tornero and Capella, 2017, which claims that playing games adjusts to the emotional state of children and adolescents [ 34 ]. This advantageous feeling state can further improve their engagement in school sports activities [ 35 , 36 ]. Physiological studies prove that engaging in physical activity or exercise causes the release of endorphins from the pituitary gland and subthalamus. Endorphins are hormones that induce feelings of calmness and pleasure, enhancing mood and creating an enjoyable experience for children and adolescents during physical education programs, including games [ 37 , 38 , 39 ]. Furthermore, when it comes to content, the teaching of physical education games appears to enhance the enjoyment experienced by children and adolescents to a greater extent than the classes of traditional physical education. In their study, Batez et al. (2021) discovered that adolescents in the experimental group who participated in the Teaching Games for Understanding (mini-volleyball) way experienced a greater sense of satisfaction compared to the control group during the post-test phase [ 23 ]. Lopez-Lemus et al. (2023) noticed that analyzing the pre-test and post-test results of both the experimental and control groups revealed that 67 students who were part of the Sport Education (SE)/Teaching for understanding (TGfU) experimental group, specifically focusing on handball, revealed enhancements in-game performance, enjoyment, perceptual skills, and intentions [ 21 ]. Similarly, researches on dance movement games and basketball games show superior levels of enjoyment compared to traditional teaching methods [ 19 , 40 ]. Hence, this research posits that including games into physical education courses may effectively enhance the enjoyment of children and adolescents, making it a recommended approach compared to programmes that do not use games.

Gender analysis

This study claims that practicing physical sports might affect enjoyment among individuals of different genders, with boys expressing a greater chance of experiencing enjoyment compared to girls. Research has shown that as they get older boys and girls display unique preferences. In a cultural analysis conducted by Joseph et al., 25 African American women were surveyed regarding their engagement in physical activities. The majority of these women reported positive and enjoyable experiences in childhood, but their feelings were not apparent during their youth [ 41 ]. Additionally, female adolescents had a lower frequency of pleasurable meets in physical exercise compared to male adolescents, and they also displayed negative emotions towards engaging in physical activity [ 42 ]. Even so, variations in the level of enjoyment based on gender are likely to be impacted by different types of sports games. Girls have a preference for cooperative activities, particularly dancing games [ 43 ], whereas boys seem to choose competitive fitness games [ 44 ]. In all, both males and females can experience enjoyment in physical education games, still, variations in the level of enjoyment may arise due to factors such as age and the specific type of game. It seems that gender alone is not the sole determinant of enjoyment, and further study is required to identify other contributing factors.

Analysis of age

According to this study, teaching physical education games has a major effect on the enjoyable feelings of children below the age of 12. And yet, it does not have a substantial influence on teenagers aged 12 and above. In the opinion of Velez & Garcia, children between the ages of 9 and 12 have better levels of individual feelings of happiness compared to teenagers aged 13 to 17 [ 45 ]. Play is an essential element in the development of children’s motor skills and is intrinsically linked to enjoyment, which serves as a motivation for children to engage in physical exercise [ 46 ]. According to Bremer et al., a study demonstrated that children between the ages of 6 and 13 with autism who enjoyed their physical education sessions were more likely to engage in other physical activities [ 47 ]. Academic competition at school is an important factor that hinders the development of enjoyable feelings in teens, this is mostly caused by the negative effects of stress-induced depression and anxiety [ 48 ]. Mangerud found that engaging in physical exercise has an impact on the positive emotions of adolescents with anxiety disorders, including their enjoyment of sports circumstances [ 49 ]. As a result, teaching youngsters under the age of 12 physical sports proves to be a more successful method for obtaining enjoyment compared to teenagers aged 12 and above.

Analysis of duration

The present research offers that applying a physical game lesson beyond a duration of 30 minutes has a favorable impact on the enjoyment of children and adolescents, but less than 30 minutes appears to have little to no effect. This corresponds to the findings of the Gil-Madrona, when children participated in 45 minutes of popular cooperative and cooperative-oppositional games [ 50 ]. Physical exercise in children and teenagers increases the release of neurotransmitters including dopamine and (−)-norepinephrine. These substances help to decrease depression and anxiety, leading to increased feelings of euphoria, achievement, and overall well-being, which improve over time [ 51 , 52 , 53 ]. Previous research has shown that children tend to get pleasure from short periods of intense physical activity followed by times of relaxation (similar to outside play), whereas adults may have a preference for lengthier activities [ 54 ]. However, Tobin et al. carried out experiments with participants of varying durations and determined that a 12-minute length of time was considered insufficient for players to become fully engaged in the game, thus serving merely as a warm-up period [ 55 ]. In addition, another study corroborated these findings by establishing that children exhibited diminished motivation and failed to experience enhanced enjoyment when engaging in sports games for a brief duration of 20 minutes [ 56 ]. In the end, engaging in sports games for no less than 30 minutes can lead to improved outcomes and heightened enjoyment for children and adolescents.

Analysis of frequency

The analyses suggested that a teaching intervention based on physical education and games held 1 to 3 times per week is suitable for children and adolescents to experience enjoyment. However, doing more than 3 sessions per week seems unsuitable. Studies indicate a correlation between the frequency of participating in physical activity and experiencing positive emotions [ 57 ]. Furthermore, sustaining a proper frequency of physical activity could promote the feeling of Feelings of happiness. For instance, Batez and Gil-Arias both applied the teaching games for understanding (TGfU) approach in a physical education program, results indicated that students’ level of enjoyment somewhat improved when the games were taught twice weekly [ 23 , 58 ]. However, excessive participation in game activities without sufficient time for rest and recovery can lead to the build-up of lactic acid in the muscles, resulting in increased physical fatigue and negatively impacting the individual’s mood, finally diminishing the enjoyment of the gaming experience [ 59 , 60 , 61 , 62 ]. Temporary breaks can effectively facilitate physical recovery during physical education games, it not only promotes bodily rejuvenation but also enhances the enjoyment of children and adolescents [ 63 ]. Therefore, it is advisable to offer 1–3 lessons per week to optimise the teaching of physical education games.

Analysis of cycles

This study stated that physical education game teaching interventions lasting between 3 to 6 weeks and more than 6 weeks are ideal for improving the enjoyable outcomes of children and adolescents. Conversely, interventions lasting less than 3 weeks are not advisable. This conclusion is supported by the findings of previous studies. Some curriculum interventions like Zetou et al. designed a 4-week ‘Play and Stay’ tennis teaching programme, Jones et al.’s 6-week Teaching Games for Understanding and Fernandez-Rio et al.’s 9-week Gamification [ 22 , 24 , 26 ]. Findings show an increase in students’ enjoyment, linked to the regular meeting of their intrinsic drive in the physical education classroom. Several studies indicated that short physical procedures lasting only 1 week do not effectively assess the intrinsic motivation of participants [ 64 , 65 ], thus posing difficulties with stimulating the generation of enjoyable sensations in persons. Moreover, extended periods of physical play may result in decreased intrinsic motivation or boredom in children and adolescents [ 66 , 67 ]. Fu et al. and Zeng et al. propose that while physical play at first brings joy, enjoyment diminishes over time [ 33 , 68 ]. In conclusion, children and adolescents should engage in playful activities for a minimum of 3 weeks, while also ensuring that the play program offers a variety of activities and rich content to enhance their enjoyment.

This study applies a meta-analysis to examine the significance of teaching games in physical education regarding emotional delight experienced by children and adolescents. Gender, age, duration, frequency and cycles may be the reasons for variances impacting the research outcomes. This research finds that male participants are more likely to show enjoyable behavior compared with their female counterparts as for games teaching in physical courses. However, it should be noted that gender disparities may be influenced by variables like age and the specific kind of sports taught in class. Besides,Children engage in a minimum of 30 minutes every session, attending 1 to 3 sessions per week, so guaranteeing that the physical education and games curriculum is delivered for a span exceeding 3 weeks. This approach aims to foster positive affective experiences among children, thereby facilitating the attainment of optimum outcomes.

Limitations and future research

Apart from the meaningful findings, this research also has some drawbacks. Firstly, it adopts a meta-analytical approach to examine the influence of games teaching in physical education on enjoyment in children and adolescent. It primarily focuses on the outcomes of curriculum and teaching implementation. Consequently, the results may not be applicable to other contexts, such as after-school physical game activities, community physical game activities, and family physical game activities. Furthermore, the 17 studies analyzed in this research have insufficient data on duration, frequency, and period. This insufficient information may influence the statistical accuracy of conducting effect size tests. Additionally, the 17 studies fail to offer any data about the intensity of the activities employed in games teaching in physical education, such as heart rate, oxygen uptake, and respiratory rate. Consequently, future studies can address this gap in knowledge. Additionally, the current research does not ascertain the ideal upper threshold for the duration of engagement in the activity. This aspect warrants further exploration in a later literature review. Additionally, it is crucial to evaluate other variables which may influence the research outcomes, such as the specific nature of the sports game being analyzed. For further study, it would be fruitful to classify different sorts of sports games to improve the whole quality of the research.

Availability of data and materials

All data generated or analysed during this study are included in this published article.

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Acknowledgements

We would like to express our deep appreciation to Professor Jamalsafri Bin Saibon from the School of Educational Studies, Universiti Sains Malaysia (USM), for providing advices and support for this project.

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MWL performed the experiment, LYM and LJQ performed the data analysis, HYW performs a final check of the data, MWL performed the formal analysis and wrote the manuscript, JBS helped perform the analysis with constructive discussions, All authors were involved in discussing the results.

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Mo, W., Saibon, J.B., LI, Y. et al. Effects of game-based physical education program on enjoyment in children and adolescents: a systematic review and meta-analysis. BMC Public Health 24 , 517 (2024). https://doi.org/10.1186/s12889-024-18043-6

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  19. Letter to the editor concerning: "The serotonin theory of ...

    We read with great interest the article by Moncrieff et al. presenting a systematic umbrella review of the evidence of the serotonin theory of depression [1]. The authors conducted a meaningful ...

  20. Systematic literature review of psychological interventions for first

    We conducted a systematic review of the empirical literature examining the effectiveness of psychological interventions for post-traumatic symptomatology in police, firefighters, and paramedic personnel. The review process was guided by the PRISMA statement (Moher et al. [2009].

  21. A Systematic Literature Review of Psychological Interventions for

    We conducted a systematic literature review (SLR) and qualitative synthesis of RCTs of psychological interventions in ALWT1DM. We followed the standards set out in the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) [] and the Cochrane Handbook for Systematic Reviews of Interventions [].We employed the Cochrane risk-of-bias tool to assess study quality [].

  22. Literature Review

    Conducting a Systematic Literature Review Tools for organizing and writing Literature Review Research Log Helps keep track of what you search and where you search. Literature Review Matrix Helps you compare articles. Tips for wrting the Literature Review Includes tips on how to structure your paper. Video on Scoping Search

  23. A Systematic Literature Review of How to Treat Cognitive Psychology

    The motive of this systematic literature review is to focus on how machine learning is effective in the field of psychology as we know that phycology is the branch of science that is related to psychiatry which treats mental health disorders and diseases in the world. This research discusses the criteria of AI techniques that may be useful in ...

  24. A systematic review of school refusal

    Considering the problems associated with school attendance, school refusal is an adjustment problem that tends to become increasingly prevalent. The present study identifies the patterns reported in the literature on school refusal and outlines the structure and sub-components of school refusal. Therefore, the systematic review method was selected as the research method for this study. The ...

  25. Psychological Wellbeing: Asystematic Literature Review

    Psychological Wellbeing: Asystematic Literature Review Dr. M. Dhanabhakyam, Sarath. Published in International Journal of… 14 February 2023 Psychology Psychological well-being is a multifaceted and multi-dimensional construct that encompasses an individual's overall happiness, satisfaction with life, and mental and emotional health.

  26. Effects of game-based physical education program on enjoyment in

    The objective of this study was to conduct a systematic review to summarize and assess the advancements lately made on the enjoyable impacts of game-based physical education interventions on children and adolescents. Additionally, it attempted to identify the effects and variables influencing the enjoyable outcomes of children and adolescents' engagement in physical education games, through ...

  27. Using body sensors for evaluating the impact of smart cycling

    This paper therefore presents a systematic literature review and conceptual framework to support the use of body sensors in evaluations of the impact of SCTs on perceptions, emotions, feelings, affect, and more, during outdoor bicycle rides. The literature review (n = 40) showed that there is scarce research on this specific use of body sensors.