the difference between systematic review and literature review

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Systematic Literature Review or Literature Review?

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As a researcher, you may be required to conduct a literature review. But what kind of review do you need to complete? Is it a systematic literature review or a standard literature review? In this article, we’ll outline the purpose of a systematic literature review, the difference between literature review and systematic review, and other important aspects of systematic literature reviews.

What is a Systematic Literature Review?

The purpose of systematic literature reviews is simple. Essentially, it is to provide a high-level of a particular research question. This question, in and of itself, is highly focused to match the review of the literature related to the topic at hand. For example, a focused question related to medical or clinical outcomes.

The components of a systematic literature review are quite different from the standard literature review research theses that most of us are used to (more on this below). And because of the specificity of the research question, typically a systematic literature review involves more than one primary author. There’s more work related to a systematic literature review, so it makes sense to divide the work among two or three (or even more) researchers.

Your systematic literature review will follow very clear and defined protocols that are decided on prior to any review. This involves extensive planning, and a deliberately designed search strategy that is in tune with the specific research question. Every aspect of a systematic literature review, including the research protocols, which databases are used, and dates of each search, must be transparent so that other researchers can be assured that the systematic literature review is comprehensive and focused.

Most systematic literature reviews originated in the world of medicine science. Now, they also include any evidence-based research questions. In addition to the focus and transparency of these types of reviews, additional aspects of a quality systematic literature review includes:

• Clear and concise review and summary
• Comprehensive coverage of the topic
• Accessibility and equality of the research reviewed

Systematic Review vs Literature Review

The difference between literature review and systematic review comes back to the initial research question. Whereas the systematic review is very specific and focused, the standard literature review is much more general. The components of a literature review, for example, are similar to any other research paper. That is, it includes an introduction, description of the methods used, a discussion and conclusion, as well as a reference list or bibliography.

A systematic review, however, includes entirely different components that reflect the specificity of its research question, and the requirement for transparency and inclusion. For instance, the systematic review will include:

• Eligibility criteria for included research
• A description of the systematic research search strategy
• An assessment of the validity of reviewed research
• Interpretations of the results of research included in the review

As you can see, contrary to the general overview or summary of a topic, the systematic literature review includes much more detail and work to compile than a standard literature review. Indeed, it can take years to conduct and write a systematic literature review. But the information that practitioners and other researchers can glean from a systematic literature review is, by its very nature, exceptionally valuable.

This is not to diminish the value of the standard literature review. The importance of literature reviews in research writing is discussed in this article . It’s just that the two types of research reviews answer different questions, and, therefore, have different purposes and roles in the world of research and evidence-based writing.

Systematic Literature Review vs Meta Analysis

It would be understandable to think that a systematic literature review is similar to a meta analysis. But, whereas a systematic review can include several research studies to answer a specific question, typically a meta analysis includes a comparison of different studies to suss out any inconsistencies or discrepancies. For more about this topic, check out Systematic Review VS Meta-Analysis article.

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The difference between a systematic review and a literature review

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Covidence takes a look at the difference between the two

Most of us are familiar with the terms systematic review and literature review. Both review types synthesise evidence and provide summary information. So what are the differences? What does systematic mean? And which approach is best 🤔 ?

‘ Systematic ‘ describes the review’s methods. It means that they are transparent, reproducible and defined before the search gets underway. That’s important because it helps to minimise the bias that would result from cherry-picking studies in a non-systematic way. 

This brings us to literature reviews. Literature reviews don’t usually apply the same rigour in their methods. That’s because, unlike systematic reviews, they don’t aim to produce an answer to a clinical question. Literature reviews can provide context or background information for a new piece of research. They can also stand alone as a general guide to what is already known about a particular topic. 

Interest in systematic reviews has grown in recent years and the frequency of ‘systematic reviews’ in Google books has overtaken ‘literature reviews’ (with all the usual Ngram Viewer warnings – it searches around 6% of all books, no journals). 

Let’s take a look at the two review types in more detail to highlight some key similarities and differences 👀.

🙋🏾‍♂️ What is a systematic review?

Systematic reviews ask a specific question about the effectiveness of a treatment and answer it by summarising evidence that meets a set of pre-specified criteria. 

The process starts with a research question and a protocol or research plan. A review team searches for studies to answer the question using a highly sensitive search strategy. The retrieved studies are then screened for eligibility using the inclusion and exclusion criteria (this is done by at least two people working independently). Next, the reviewers extract the relevant data and assess the quality of the included studies. Finally, the review team synthesises the extracted study data and presents the results. The process is shown in figure 2 .

The results of a systematic review can be presented in many ways and the choice will depend on factors such as the type of data. Some reviews use meta-analysis to produce a statistical summary of effect estimates. Other reviews use narrative synthesis to present a textual summary.

Covidence accelerates the screening, data extraction, and quality assessment stages of your systematic review. It provides simple workflows and easy collaboration with colleagues around the world.

When is it appropriate to do a systematic review?

If you have a clinical question about the effectiveness of a particular treatment or treatments, you could answer it by conducting a systematic review. Systematic reviews in clinical medicine often follow the PICO framework, which stands for:

👦 Population (or patients)

💊 Intervention

💊 Comparison

Here’s a typical example of a systematic review title that uses the PICO framework: Alarms [intervention] versus drug treatments [comparison] for the prevention of nocturnal enuresis [outcome] in children [population]

Key attributes

• Systematic reviews follow prespecified methods
• The methods are explicit and replicable
• The review team assesses the quality of the evidence and attempts to minimise bias
• Results and conclusions are based on the evidence

🙋🏻‍♀️ What is a literature review?

Literature reviews provide an overview of what is known about a particular topic. They evaluate the material, rather than simply restating it, but the methods used to do this are not usually prespecified and they are not described in detail in the review. The search might be comprehensive but it does not aim to be exhaustive. Literature reviews are also referred to as narrative reviews.

Literature reviews use a topical approach and often take the form of a discussion. Precision and replicability are not the focus, rather the author seeks to demonstrate their understanding and perhaps also present their work in the context of what has come before. Often, this sort of synthesis does not attempt to control for the author’s own bias. The results or conclusion of a literature review is likely to be presented using words rather than statistical methods.

When is it appropriate to do a literature review?

We’ve all written some form of literature review: they are a central part of academic research ✍🏾. Literature reviews often form the introduction to a piece of writing, to provide the context. They can also be used to identify gaps in the literature and the need to fill them with new research 📚.

• Literature reviews take a thematic approach
• They do not specify inclusion or exclusion criteria
• They do not answer a clinical question
• The conclusions might be influenced by the author’s own views

🙋🏽 Ok, but what is a systematic literature review?

A quick internet search retrieves a cool 200 million hits for ‘systematic literature review’. What strange hybrid is this 🤯🤯 ?

Systematic review methodology has its roots in evidence-based medicine but it quickly gained traction in other areas – the social sciences for example – where researchers recognise the value of being methodical and minimising bias. Systematic review methods are increasingly applied to the more traditional types of review, including literature reviews, hence the proliferation of terms like ‘systematic literature review’ and many more.

Beware of the labels 🚨. The terminology used to describe review types can vary by discipline and changes over time. To really understand how any review was done you will need to examine the methods critically and make your own assessment of the quality and reliability of each synthesis 🤓.

Review methods are evolving constantly as researchers find new ways to meet the challenge of synthesising the evidence. Systematic review methods have influenced many other review types, including the traditional literature review. 

Covidence is a web-based tool that saves you time at the screening, selection, data extraction and quality assessment stages of your systematic review. It supports easy collaboration across teams and provides a clear overview of task status.

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Laura Mellor. Portsmouth, UK

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Know the Difference! Systematic Review vs. Literature Review

It is common to confuse systematic and literature reviews as both are used to provide a summary of the existent literature or research on a specific topic.  Even with this common ground, both types vary significantly.  Please review the following chart (and its corresponding poster linked below) for the detailed explanation of each as well as the differences between each type of review.

• What's in a name? The difference between a Systematic Review and a Literature Review, and why it matters by Lynn Kysh, MLIS, University of Southern California - Norris Medical Library
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Literature Review Research

Literature review vs. systematic review.

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Resources for Systematic Reviews

• NIH Systematic Review Protocols and Protocol Registries Systematic review services and information from the National Institutes of Health.
• Purdue University Systematic Reviews LibGuide Purdue University has created this helpful online research guide on systematic reviews. Most content is available publicly but please note that some links are accessible only to Purdue students.

It is common to confuse literature and systematic reviews because both are used to provide a summary of the existing literature or research on a specific topic. Despite this commonality, these two reviews vary significantly. The table below highlights the differences.

Kysh, Lynn (2013). Difference between a systematic review and a literature review. figshare. Poster. https://doi.org/10.6084/m9.figshare.766364.v1

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• URL: https://tcsedsystem.libguides.com/literature_review

Literature Review vs Systematic Review

Literature review vs. systematic review, your librarian.

It’s common to confuse systematic and literature reviews because both are used to provide a summary of the existent literature or research on a specific topic. Regardless of this commonality, both types of review vary significantly. The following table provides a detailed explanation as well as the differences between systematic and literature reviews. 

Kysh, Lynn (2013): Difference between a systematic review and a literature review. [figshare]. Available at:  http://dx.doi.org/10.6084/m9.figshare.766364

Primary vs. Secondary Research

Parts of the Article

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• URL: https://libguides.sjsu.edu/LitRevVSSysRev

Literature Review

• What is a Literature Review?
• What is a good literature review?
• Types of Literature Reviews
• What are the parts of a Literature Review?
• What is the difference between a Systematic Review and a Literature Review?

Systematic vs Literature

Systematic reviews and literature reviews are commonly confused. The main difference between the two is that systematic reviews answer a focused question whereas literature reviews contextualize a topic.

Kysh, Lynn (2013): Difference between a systematic review and a literature review. Available at: https://figshare.com/articles/Difference_between_a_systematic_review_and_a_literature_review/766364

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 Review not just what scholars are saying, but how are they saying it. Some questions to ask:

• How are they organizing their ideas?
• What methods have they used to study the problem?
• What theories have been used to explain, predict, or understand their research problem?
• What sources have they cited to support their conclusions?
• How have they used non-textual elements [e.g., charts, graphs, figures, etc.] to illustrate key points?

When you begin to write your literature review section, you'll be glad you dug deeper into how the research was designed and constructed because it establishes a means for developing more substantial analysis and interpretation of the research problem.

Hart, Chris.  Doing a Literature Review: Releasing the Social Science Research Imagination . Thousand Oaks, CA: Sage Publications, 1998.

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• Systematic Review | Definition, Example, & Guide

Systematic Review | Definition, Example & Guide

Published on June 15, 2022 by Shaun Turney . Revised on November 20, 2023.

A systematic review is a type of review that uses repeatable methods to find, select, and synthesize all available evidence. It answers a clearly formulated research question and explicitly states the methods used to arrive at the answer.

They answered the question “What is the effectiveness of probiotics in reducing eczema symptoms and improving quality of life in patients with eczema?”

In this context, a probiotic is a health product that contains live microorganisms and is taken by mouth. Eczema is a common skin condition that causes red, itchy skin.

Table of contents

What is a systematic review, systematic review vs. meta-analysis, systematic review vs. literature review, systematic review vs. scoping review, when to conduct a systematic review, pros and cons of systematic reviews, step-by-step example of a systematic review, other interesting articles, frequently asked questions about systematic reviews.

A review is an overview of the research that’s already been completed on a topic.

What makes a systematic review different from other types of reviews is that the research methods are designed to reduce bias . The methods are repeatable, and the approach is formal and systematic:

• Formulate a research question
• Develop a protocol
• Search for all relevant studies
• Apply the selection criteria
• Extract the data
• Synthesize the data
• Write and publish a report

Although multiple sets of guidelines exist, the Cochrane Handbook for Systematic Reviews is among the most widely used. It provides detailed guidelines on how to complete each step of the systematic review process.

Systematic reviews are most commonly used in medical and public health research, but they can also be found in other disciplines.

Systematic reviews typically answer their research question by synthesizing all available evidence and evaluating the quality of the evidence. Synthesizing means bringing together different information to tell a single, cohesive story. The synthesis can be narrative ( qualitative ), quantitative , or both.

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Systematic reviews often quantitatively synthesize the evidence using a meta-analysis . A meta-analysis is a statistical analysis, not a type of review.

A meta-analysis is a technique to synthesize results from multiple studies. It’s a statistical analysis that combines the results of two or more studies, usually to estimate an effect size .

A literature review is a type of review that uses a less systematic and formal approach than a systematic review. Typically, an expert in a topic will qualitatively summarize and evaluate previous work, without using a formal, explicit method.

Although literature reviews are often less time-consuming and can be insightful or helpful, they have a higher risk of bias and are less transparent than systematic reviews.

Similar to a systematic review, a scoping review is a type of review that tries to minimize bias by using transparent and repeatable methods.

However, a scoping review isn’t a type of systematic review. The most important difference is the goal: rather than answering a specific question, a scoping review explores a topic. The researcher tries to identify the main concepts, theories, and evidence, as well as gaps in the current research.

Sometimes scoping reviews are an exploratory preparation step for a systematic review, and sometimes they are a standalone project.

A systematic review is a good choice of review if you want to answer a question about the effectiveness of an intervention , such as a medical treatment.

To conduct a systematic review, you’ll need the following:

• A precise question , usually about the effectiveness of an intervention. The question needs to be about a topic that’s previously been studied by multiple researchers. If there’s no previous research, there’s nothing to review.
• If you’re doing a systematic review on your own (e.g., for a research paper or thesis ), you should take appropriate measures to ensure the validity and reliability of your research.
• Access to databases and journal archives. Often, your educational institution provides you with access.
• Time. A professional systematic review is a time-consuming process: it will take the lead author about six months of full-time work. If you’re a student, you should narrow the scope of your systematic review and stick to a tight schedule.
• Bibliographic, word-processing, spreadsheet, and statistical software . For example, you could use EndNote, Microsoft Word, Excel, and SPSS.

A systematic review has many pros .

• They minimize research bias by considering all available evidence and evaluating each study for bias.
• Their methods are transparent , so they can be scrutinized by others.
• They’re thorough : they summarize all available evidence.
• They can be replicated and updated by others.

Systematic reviews also have a few cons .

• They’re time-consuming .
• They’re narrow in scope : they only answer the precise research question.

The 7 steps for conducting a systematic review are explained with an example.

Step 1: Formulate a research question

Formulating the research question is probably the most important step of a systematic review. A clear research question will:

• Allow you to more effectively communicate your research to other researchers and practitioners
• Guide your decisions as you plan and conduct your systematic review

A good research question for a systematic review has four components, which you can remember with the acronym PICO :

• Population(s) or problem(s)
• Intervention(s)
• Comparison(s)

You can rearrange these four components to write your research question:

• What is the effectiveness of I versus C for O in P ?

Sometimes, you may want to include a fifth component, the type of study design . In this case, the acronym is PICOT .

• Type of study design(s)
• The population of patients with eczema
• The intervention of probiotics
• In comparison to no treatment, placebo , or non-probiotic treatment
• The outcome of changes in participant-, parent-, and doctor-rated symptoms of eczema and quality of life
• Randomized control trials, a type of study design

Their research question was:

• What is the effectiveness of probiotics versus no treatment, a placebo, or a non-probiotic treatment for reducing eczema symptoms and improving quality of life in patients with eczema?

Step 2: Develop a protocol

A protocol is a document that contains your research plan for the systematic review. This is an important step because having a plan allows you to work more efficiently and reduces bias.

Your protocol should include the following components:

• Background information : Provide the context of the research question, including why it’s important.
• Research objective (s) : Rephrase your research question as an objective.
• Selection criteria: State how you’ll decide which studies to include or exclude from your review.
• Search strategy: Discuss your plan for finding studies.
• Analysis: Explain what information you’ll collect from the studies and how you’ll synthesize the data.

If you’re a professional seeking to publish your review, it’s a good idea to bring together an advisory committee . This is a group of about six people who have experience in the topic you’re researching. They can help you make decisions about your protocol.

It’s highly recommended to register your protocol. Registering your protocol means submitting it to a database such as PROSPERO or ClinicalTrials.gov .

Step 3: Search for all relevant studies

Searching for relevant studies is the most time-consuming step of a systematic review.

To reduce bias, it’s important to search for relevant studies very thoroughly. Your strategy will depend on your field and your research question, but sources generally fall into these four categories:

• Databases: Search multiple databases of peer-reviewed literature, such as PubMed or Scopus . Think carefully about how to phrase your search terms and include multiple synonyms of each word. Use Boolean operators if relevant.
• Handsearching: In addition to searching the primary sources using databases, you’ll also need to search manually. One strategy is to scan relevant journals or conference proceedings. Another strategy is to scan the reference lists of relevant studies.
• Gray literature: Gray literature includes documents produced by governments, universities, and other institutions that aren’t published by traditional publishers. Graduate student theses are an important type of gray literature, which you can search using the Networked Digital Library of Theses and Dissertations (NDLTD) . In medicine, clinical trial registries are another important type of gray literature.
• Experts: Contact experts in the field to ask if they have unpublished studies that should be included in your review.

At this stage of your review, you won’t read the articles yet. Simply save any potentially relevant citations using bibliographic software, such as Scribbr’s APA or MLA Generator .

• Databases: EMBASE, PsycINFO, AMED, LILACS, and ISI Web of Science
• Handsearch: Conference proceedings and reference lists of articles
• Gray literature: The Cochrane Library, the metaRegister of Controlled Trials, and the Ongoing Skin Trials Register
• Experts: Authors of unpublished registered trials, pharmaceutical companies, and manufacturers of probiotics

Step 4: Apply the selection criteria

Applying the selection criteria is a three-person job. Two of you will independently read the studies and decide which to include in your review based on the selection criteria you established in your protocol . The third person’s job is to break any ties.

To increase inter-rater reliability , ensure that everyone thoroughly understands the selection criteria before you begin.

If you’re writing a systematic review as a student for an assignment, you might not have a team. In this case, you’ll have to apply the selection criteria on your own; you can mention this as a limitation in your paper’s discussion.

You should apply the selection criteria in two phases:

• Based on the titles and abstracts : Decide whether each article potentially meets the selection criteria based on the information provided in the abstracts.
• Based on the full texts: Download the articles that weren’t excluded during the first phase. If an article isn’t available online or through your library, you may need to contact the authors to ask for a copy. Read the articles and decide which articles meet the selection criteria.

It’s very important to keep a meticulous record of why you included or excluded each article. When the selection process is complete, you can summarize what you did using a PRISMA flow diagram .

Next, Boyle and colleagues found the full texts for each of the remaining studies. Boyle and Tang read through the articles to decide if any more studies needed to be excluded based on the selection criteria.

When Boyle and Tang disagreed about whether a study should be excluded, they discussed it with Varigos until the three researchers came to an agreement.

Step 5: Extract the data

Extracting the data means collecting information from the selected studies in a systematic way. There are two types of information you need to collect from each study:

• Information about the study’s methods and results . The exact information will depend on your research question, but it might include the year, study design , sample size, context, research findings , and conclusions. If any data are missing, you’ll need to contact the study’s authors.
• Your judgment of the quality of the evidence, including risk of bias .

You should collect this information using forms. You can find sample forms in The Registry of Methods and Tools for Evidence-Informed Decision Making and the Grading of Recommendations, Assessment, Development and Evaluations Working Group .

Extracting the data is also a three-person job. Two people should do this step independently, and the third person will resolve any disagreements.

They also collected data about possible sources of bias, such as how the study participants were randomized into the control and treatment groups.

Step 6: Synthesize the data

Synthesizing the data means bringing together the information you collected into a single, cohesive story. There are two main approaches to synthesizing the data:

• Narrative ( qualitative ): Summarize the information in words. You’ll need to discuss the studies and assess their overall quality.
• Quantitative : Use statistical methods to summarize and compare data from different studies. The most common quantitative approach is a meta-analysis , which allows you to combine results from multiple studies into a summary result.

Generally, you should use both approaches together whenever possible. If you don’t have enough data, or the data from different studies aren’t comparable, then you can take just a narrative approach. However, you should justify why a quantitative approach wasn’t possible.

Boyle and colleagues also divided the studies into subgroups, such as studies about babies, children, and adults, and analyzed the effect sizes within each group.

Step 7: Write and publish a report

The purpose of writing a systematic review article is to share the answer to your research question and explain how you arrived at this answer.

Your article should include the following sections:

• Abstract : A summary of the review
• Introduction : Including the rationale and objectives
• Methods : Including the selection criteria, search method, data extraction method, and synthesis method
• Results : Including results of the search and selection process, study characteristics, risk of bias in the studies, and synthesis results
• Discussion : Including interpretation of the results and limitations of the review
• Conclusion : The answer to your research question and implications for practice, policy, or research

To verify that your report includes everything it needs, you can use the PRISMA checklist .

Once your report is written, you can publish it in a systematic review database, such as the Cochrane Database of Systematic Reviews , and/or in a peer-reviewed journal.

In their report, Boyle and colleagues concluded that probiotics cannot be recommended for reducing eczema symptoms or improving quality of life in patients with eczema. Note Generative AI tools like ChatGPT can be useful at various stages of the writing and research process and can help you to write your systematic review. However, we strongly advise against trying to pass AI-generated text off as your own work.

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

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Prospective cohort study

Research bias

• Implicit bias
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic
• Social desirability bias

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

A systematic review is secondary research because it uses existing research. You don’t collect new data yourself.

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Home » Education » Difference Between Literature Review and Systematic Review

Difference Between Literature Review and Systematic Review

Main difference – literature review vs systematic review.

Literature review and systematic review are two scholarly texts that help to introduce new knowledge to various fields. A literature review, which reviews the existing research and information on a selected study area, is a crucial element of a research study. A systematic review is also a type of a literature review. The main difference between literature review and systematic review is their focus on the research question ; a systematic review is focused on a specific research question whereas a literature review is not.

This article highlights,

1. What is a Literature Review?        – Definition, Features, Characteristics

2. What is a Systematic Review?        – Definition, Features, Characteristics

What is a Literature Review

A literature review is an indispensable element of a research study. This is where the researcher shows his knowledge on the subject area he or she is researching on. A literature review is a discussion on the already existing material in the subject area. Thus, this will require a collection of published (in print or online) work concerning the selected research area. In simple terms, a literature is a review of the literature in the related subject area.

A good literature review is a critical discussion, displaying the writer’s knowledge on relevant theories and approaches and awareness of contrasting arguments. A literature review should have the following features (Caulley, 1992)

• Compare and contrast different researchers’ views
• Identify areas in which researchers are in disagreement
• Group researchers who have similar conclusions
• Criticize the methodology
• Highlight exemplary studies
• Highlight gaps in research
• Indicate the connection between your study and previous studies
• Indicate how your study will contribute to the literature in general
• Conclude by summarizing what the literature indicates

The structure of a literature review is similar to that of an article or essay, unlike an annotated bibliography . The information that is collected is integrated into paragraphs based on their relevance. Literature reviews help researchers to evaluate the existing literature, to identify a gap in the research area, to place their study in the existing research and identify future research.

What is a Systematic Review

A systematic review is a type of systematic review that is focused on a particular research question . The main purpose of this type of research is to identify, review, and summarize the best available research on a specific research question. Systematic reviews are used mainly because the review of existing studies is often more convenient than conducting a new study. These are mostly used in the health and medical field, but they are not rare in fields such as social sciences and environmental science.  Given below are the main stages of a systematic review:

• Defining the research question and identifying an objective method
• Searching for relevant data that from existing research studies that meet certain criteria (research studies must be reliable and valid).
• Extracting data from the selected studies (data such as the participants, methods, outcomes, etc.
• Assessing the quality of information
• Analyzing and combining all the data which would give an overall result.

Literature Review is a critical evaluation of the existing published work in a selected research area.

Systematic Review is a type of literature review that is focused on a particular research question.

Literature Review aims to review the existing literature, identify the research gap, place the research study in relation to other studies, to evaluate promising research methods, and to suggest further research.

Systematic Review aims to identify, review, and summarize the best available research on a specific research question.

Research Question

In Literature Review, a r esearch question is formed after writing the literature review and identifying the research gap.

In Systematic Review, a research question is formed at the beginning of the systematic review.

Research Study

Literature Review is an essential component of a research study and is done at the beginning of the study.

Systematic Review is not followed by a separate research study.

Caulley, D. N. “Writing a critical review of the literature.”  La Trobe University: Bundoora  (1992).

“Animated Storyboard: What Are Systematic Reviews?” .  cccrg.cochrane.org .  Cochrane Consumers and Communication . Retrieved 1 June 2016.

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What is the difference between a systematic review and a systematic literature review?

By Carol Hollier on 07-Jan-2020 12:42:03

For those not immersed in systematic reviews, understanding the difference between a systematic review and a systematic literature review can be confusing.  It helps to realise that a “systematic review” is a clearly defined thing, but ambiguity creeps in around the phrase “systematic literature review” because people can and do use it in a variety of ways. 

A systematic review is a research study of research studies.  To qualify as a systematic review, a review needs to adhere to standards of transparency and reproducibility.  It will use explicit methods to identify, select, appraise, and synthesise empirical results from different but similar studies.  The study will be done in stages:  

• In stage one, the question, which must be answerable, is framed
• Stage two is a comprehensive literature search to identify relevant studies
• In stage three the identified literature’s quality is scrutinised and decisions made on whether or not to include each article in the review
• In stage four the evidence is summarised and, if the review includes a meta-analysis, the data extracted; in the final stage, findings are interpreted. [1]

Some reviews also state what degree of confidence can be placed on that answer, using the GRADE scale.  By going through these steps, a systematic review provides a broad evidence base on which to make decisions about medical interventions, regulatory policy, safety, or whatever question is analysed.   By documenting each step explicitly, the review is not only reproducible, but can be updated as more evidence on the question is generated.

Sometimes when people talk about a “systematic literature review”, they are using the phrase interchangeably with “systematic review”.  However, people can also use the phrase systematic literature review to refer to a literature review that is done in a fairly systematic way, but without the full rigor of a systematic review. 

For instance, for a systematic review, reviewers would strive to locate relevant unpublished studies in grey literature and possibly by contacting researchers directly.  Doing this is important for combatting publication bias, which is the tendency for studies with positive results to be published at a higher rate than studies with null results.  It is easy to understand how this well-documented tendency can skew a review’s findings, but someone conducting a systematic literature review in the loose sense of the phrase might, for lack of resource or capacity, forgo that step. 

Another difference might be in who is doing the research for the review. A systematic review is generally conducted by a team including an information professional for searches and a statistician for meta-analysis, along with subject experts.  Team members independently evaluate the studies being considered for inclusion in the review and compare results, adjudicating any differences of opinion.   In contrast, a systematic literature review might be conducted by one person. 

Overall, while a systematic review must comply with set standards, you would expect any review called a systematic literature review to strive to be quite comprehensive.  A systematic literature review would contrast with what is sometimes called a narrative or journalistic literature review, where the reviewer’s search strategy is not made explicit, and evidence may be cherry-picked to support an argument.

FSTA is a key tool for systematic reviews and systematic literature reviews in the sciences of food and health.

The patents indexed help find results of research not otherwise publicly available because it has been done for commercial purposes.

The FSTA thesaurus will surface results that would be missed with keyword searching alone. Since the thesaurus is designed for the sciences of food and health, it is the most comprehensive for the field. 

All indexing and abstracting in FSTA is in English, so you can do your searching in English yet pick up non-English language results, and get those results translated if they meet the criteria for inclusion in a systematic review.

FSTA includes grey literature (conference proceedings) which can be difficult to find, but is important to include in comprehensive searches.

FSTA content has a deep archive. It goes back to 1969 for farm to fork research, and back to the late 1990s for food-related human nutrition literature—systematic reviews (and any literature review) should include not just the latest research but all relevant research on a question. 

You can also use FSTA to find literature reviews.

FSTA allows you to easily search for review articles (both narrative and systematic reviews) by using the subject heading or thesaurus term “REVIEWS" and an appropriate free-text keyword.

On the Web of Science or EBSCO platform, an FSTA search for reviews about cassava would look like this: DE "REVIEWS" AND cassava.

On the Ovid platform using the multi-field search option, the search would look like this: reviews.sh. AND cassava.af.

In 2011 FSTA introduced the descriptor META-ANALYSIS, making it easy to search specifically for systematic reviews that include a meta-analysis published from that year onwards.

On the EBSCO or Web of Science platform, an FSTA search for systematic reviews with meta-analyses about staphylococcus aureus would look like this: DE "META-ANALYSIS" AND staphylococcus aureus.

On the Ovid platform using the multi-field search option, the search would look like this: meta-analysis.sh. AND staphylococcus aureus.af.

Systematic reviews with meta-analyses published before 2011 are included in the REVIEWS controlled vocabulary term in the thesaurus.

An easy way to locate pre-2011 systematic reviews with meta-analyses is to search the subject heading or thesaurus term "REVIEWS" AND meta-analysis as a free-text keyword AND another appropriate free-text keyword.

On the Web of Science or EBSCO platform, the FSTA search would look like this: DE "REVIEWS" AND meta-analysis AND carbohydrate*

On the Ovid platform using the multi-field search option, the search would look like this: reviews .s h. AND meta-analysis.af. AND carbohydrate*.af.  

Related resources:

• Literature Searching Best Practise Guide
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Literature Review: Know the Difference! Systematic Review vs. Literature Review

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• What's in a name? The difference between a Systematic Review and a Literature Review, and why it matters.

Evidence Pyramid

The evidence pyramid (image above) visually depicts the evidential strength of different research designs. Studies with the highest internal validity, characterized by a high degree of quantitative analysis, review, analysis, and stringent scientific methodology, are at the top of the pyramid. Observational research and expert opinion reside at the bottom of the pyramid. In evidence-based practice the systematic review is considered the highest level of information and is at the top of the pyramid.  ( The pyramid was produced by  HLWIKI Canada  and is CC).

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Systematic Reviews and Meta-Analysis: A Guide for Beginners

Joseph l. mathew.

Department of Pediatrics, Advanced Pediatrics Centre, PGIMER, Chandigarh, India

Systematic reviews involve the application of scientific methods to reduce bias in review of literature. The key components of a systematic review are a well-defined research question, comprehensive literature search to identify all studies that potentially address the question, systematic assembly of the studies that answer the question, critical appraisal of the methodological quality of the included studies, data extraction and analysis (with and without statistics), and considerations towards applicability of the evidence generated in a systematic review. These key features can be remembered as six ‘A’; Ask, Access, Assimilate, Appraise, Analyze and Apply. Meta-analysis is a statistical tool that provides pooled estimates of effect from the data extracted from individual studies in the systematic review. The graphical output of meta-analysis is a forest plot which provides information on individual studies and the pooled effect. Systematic reviews of literature can be undertaken for all types of questions, and all types of study designs. This article highlights the key features of systematic reviews, and is designed to help readers understand and interpret them. It can also help to serve as a beginner’s guide for both users and producers of systematic reviews and to appreciate some of the methodological issues.

Additional material related to this paper is available with the online version at www.indianpediatrics.net

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Q. What is the difference between a systematic review and a systematic literature review?

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Answered By: Anna Stebbing Last Updated: Feb 09, 2024     Views: 11075

DISCOVER and the Library Catalogue have been replaced by Library Search . We're busy updating all of our links, but in the meantime, please use Library Search when searching for resources or managing your Library Account.

‘Systematic’ describes the review’s methods. It means that they are transparent, reproducible and defined before the search gets underway. That’s important because it helps to minimise the bias that would result from cherry-picking studies in a non-systematic way. 

Literature reviews don’t usually apply the same rigour in their methods. That’s because, unlike systematic reviews, they don’t aim to produce an answer to a clinical question. Literature reviews can provide context or background information for a new piece of research. They can also stand alone as a general guide to what is already known about a particular topic. 

Summary adapted from: Mellor, L. (2022) ‘The difference between a systematic review and a literature review’, https://www.covidence.org/ , no date. Available at: https://www.covidence.org/blog/the-difference-between-a-systematic-review-and-a-literature-review/ (Accessed: 23 May 2022).

Your supervisor may ask you to do a systematic review, when what they actually want you to do is a systematic review of the literature. There are a few key differences:

Summary adapted from: Kysh, L. (2013) ‘What's in a name? The difference between a systematic review and a literature review and why it matters’, https://figshare.com/ , 8 August. Available at:   https://figshare.com/articles/Difference_between_a_systematic_review_and_a_literature_review/766364 

(Accessed: 23 May 2022).

You can find supporting online resources including videos on title Doing a Systematic Review, 2nd edition available as an ebook and as print copies in the library .

Your  Liaison Librarian  can also provide further help and advice.

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Educational resources and simple solutions for your research journey

Systematic Review vs. Literature Review: Some Essential Differences

Most budding researchers are confused between systematic review vs. literature review. As a PhD student or early career researcher, you must by now be well versed with the fact that literature review is the most important aspect of any scientific research, without which a study cannot be commenced. However, literature review is in itself an ‘umbrella term’, and there are several types of reviews, such as systematic literature reviews , that you may need to perform during your academic publishing journey, based upon their specific relevance to each study.   

Your research goal, approach, and design will finally influence your choice of systematic review vs literature review . Apart from systematic literature review , some other common types of literature review are 1 :   

• Narrative literature review – used to identify gaps in the existing knowledge base  
• Scoping literature review – used to identify the scope of a particular study  
• Integrative literature review – used to generate secondary data that upon integration can be used to define new frameworks and perspectives  
• Theoretical literature review – used to pool all kinds of theories associated with a particular concept  

The most commonly used form of review, however, is the systematic literature review . Compared to the other types of literature reviews described above, this one requires a more rigorous and well-defined approach. The systematic literature review can be divided into two main categories: meta-analysis and meta-synthesis. Meta-analysis is related to identifying patterns and relationships within the data, by using statistical procedures. Meta-synthesis on the other hand, is concerned with integrating findings of multiple qualitative research studies, not necessarily needing statistical procedures.  

Table of Contents

Difference between systematic review and literature review

In spite of having this basic understanding, however, there might still be a lot of confusion when it comes to finalizing between a systematic review vs literature review of any other kind. Since these two types of reviews serve a similar purpose, they are often used interchangeably and the difference between systematic review and literature review is overlooked.  In order to ease this confusion and smoothen the process of decision-making it is essential to have a closer look at a systematic review vs. literature review and the differences between them 2.3 :   

  Tips to keep in mind when performing a literature review  

While the above illustrated similarities and differences between systematic review and literature review might be helpful as an overview, here are some additional pointers that you can keep in mind while performing a review for your research study 4 :  

• Check the authenticity of the source thoroughly while using an article in your review.  
• Regardless of the type of review that you intend to perform, i t is important to ensure that the landmark literature, the one that first spoke about your topic of interest, is given prominence in your review. These can be identified with a simple Google Scholar search and checking the most cited articles.  
• Make sure to include all the latest literature that focuses on your research question.   
• Avoid including irrelevant data by revisiting your aims, objectives, and research questions as often as possible during the review process.  
• If you intend to submit your review in any peer-reviewed journal, make sure to have a defined structure based upon your selected type of review .  
• If it is a systematic literature review , make sure that the research question is clear and cri sp and framed in a manner that is subjected to quantitative analysis.  
• If it is a literature review of any other kind, make sure that you include enough checkpoints to minimize biases in your conclusions . You can use an integrative approach to show how different data points fit together, however, it is also essential to mention and describe data that doesn’t fit together in order to produce a balanced review. This can also help identify gaps and pave the way for designing future studies on the topic.   

We hope that the above article was helpful for you in understanding the basics of literature review and to know the use of systemic review vs. literature review.

Q: When to do a systematic review?

A systematic review is conducted to synthesize and analyze existing research on a specific question. It’s valuable when a comprehensive assessment of available evidence is required to answer a well-defined research question. Systematic reviews follow a predefined protocol, rigorous methodology, and aim to minimize bias. They’re especially useful for informing evidence-based decisions in healthcare and policy-making.

Q: When to do a literature review?

A literature review surveys existing literature on a topic, providing an overview of key concepts and findings. It’s conducted when exploring a subject, identifying gaps, and contextualizing research. Literature reviews are valuable at the beginning of a study to establish the research landscape and justify the need for new research.

Q: What is the difference between a literature review and a scoping review?

A literature review summarizes existing research on a topic, while a scoping review maps the literature to identify research gaps and areas for further investigation. While both assess existing literature, a scoping review tends to have broader inclusion criteria and aims to provide an overview of the available research, helping researchers understand the breadth of a topic before narrowing down a research question.

Q: What’ is the difference between systematic Literature Review and Meta Analysis?

A systematic literature review aims to comprehensively identify, select, and analyze all relevant studies on a specific research question using a rigorous methodology. It summarizes findings qualitatively. On the other hand, a meta-analysis is a statistical technique applied within a systematic review. It involves pooling and analyzing quantitative data from multiple studies to provide a more precise estimate of an effect size. In essence, a meta-analysis is a quantitative synthesis that goes beyond the qualitative summary of a systematic literature review.

References:  

• Types of Literature Review – Business Research Methodology. https://research-methodology.net/research-methodology/types-literature-review/  
• Mellor, L. The difference between a systematic review and a literature review. Covidence. https://www.covidence.org/blog/the-difference-between-a-systematic-review-and-a-literature-review \
• Basu, G. SJSU Research Guides – Literature Review vs Systematic Review.  https://libguides.sjsu.edu/LitRevVSSysRev/definitions  
• Jansen, D., Phair, D. Writing A Literature Review: 7 Common (And Costly) Mistakes To Avoid. Grad Coach, June 2021. https://gradcoach.com/literature-review-mistakes/  

R Discovery is a literature search and research reading platform that accelerates your research discovery journey by keeping you updated on the latest, most relevant scholarly content. With 250M+ research articles sourced from trusted aggregators like CrossRef, Unpaywall, PubMed, PubMed Central, Open Alex and top publishing houses like Springer Nature, JAMA, IOP, Taylor & Francis, NEJM, BMJ, Karger, SAGE, Emerald Publishing and more, R Discovery puts a world of research at your fingertips.  

Try R Discovery Prime FREE for 1 week or upgrade at just US$72 a year to access premium features that let you listen to research on the go, read in your language, collaborate with peers, auto sync with reference managers, and much more. Choose a simpler, smarter way to find and read research – Download the app and start your free 7-day trial today !  

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Systematic Review vs. Literature Review…What’s Best for Your Needs?

We at the MSK Library are often called upon to help our researchers with searches. Whether it’s a literature review  or a systematic review depends on the needs of the patron, but what is the difference between these two and when are they needed? Both systematic and literature (or comprehensive) reviews are a gathering of available information on a certain subject. The difference comes in the depth of the research and the reporting of the conclusions. Let’s take a look.

A literature or comprehensive review brings together information on a topic in order to provide an overview of the available literature on a certain subject. Research materials are gathered through searching one or more databases and qualitatively brought together in the review. Literature reviews can be the first step in perusing a topic for a further study to get an idea of the current state of the science available but they can also be their own publication. Complete our  Literature Search form if you would like us to find information on a review or other project you are working in.

Systematic reviews look at a topic more in depth using a scientific method. By looking at not only the available literature, but also theses/dissertations, abstracts/conference proceedings, and other grey literature sources, systematic reviews seek to be all-encompassing in showing results on a topic. To complete a systematic review, a team of researchers select a clinical question to be answered and specify eligibility criteria for their resources before synthesizing the information to answer their question. Multiple databases are searched in order to find every possible article on the topic. Not only are the results of the searches presented, but the search strategy, assessments and interpretations of research are also included in this form of review. Here at MSK, we use the PRISMA Statement  to provide a helpful structure when working on systematic reviews. Take a look at our Systematic Review LibGuide to learn more about this investigation into the literature.

5 differences between a systematic review and other types of literature review

September 26, 2017.

There are many types of reviews of the medical and public health evidence, each with its own benefits and challenges. In this blog post, we detail five key differences between a systematic review and other types of reviews, including narrative and comprehensive reviews.

First, we must define some terms. “Literature review” is a general term that describes a summary of the evidence on a certain topic. Literature reviews can be very simple or highly complex, and they can use a variety of methods for finding, assessing, and presenting evidence. A “systematic review” is a specific type of review that uses rigorous and transparent methods in an effort to summarize all of the available evidence with little to no bias. A good systematic review adheres to the international standards set forth in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 27-item checklist. 1 Reviews that are less rigorous are often called “narrative,” “comprehensive,” or simply “literature reviews.”

So, what are the 5 key differences between a systematic review and other types of review?

1. The goal of the review The goal of a literature review can be broad and descriptive (example: “ Describe the available treatments for sleep apnea ”) or it can be to answer a specific question (example: “ What is the efficacy of CPAP for people with sleep apnea? ”). The goal of a systematic review is to answer a specific and focused question (example: “ Which treatment for sleep apnea reduces the apnea-hypopnea index more: CPAP or mandibular advancement device? ”). People seeking to make evidence-based decisions look to systematic reviews due to their completeness and reduced risk of bias.

2. Searching for evidence Where and how one searches for evidence is an important difference. While literature reviews require only one database or source, systematic reviews require more comprehensive efforts to locate evidence. Multiple databases are searched, each with a specifically tailored search strategy (usually designed and implemented by a specialist librarian). In addition, systematic reviews often include attempts to find data beyond typical databases. Systematic reviewers might search conference abstracts or the web sites of professional associations or pharmaceutical companies, and they may contact study authors to obtain additional or unpublished data. All of these extra steps reflect an attempt to minimize bias in the summary of the evidence. 3. Assessing search results In a systematic review, the parameters for inclusion are established at the start of the project and applied consistently to search results. Usually, such parameters take the form of PICOs (population, intervention, comparison, outcomes). Reviewers hold search results against strict criteria based on the PICOs to determine appropriateness for inclusion. Another key component of a systematic review is dual independent review of search results; each search result is reviewed by at least two people independently. In many other literature reviews, there is only a single reviewer. This can result in bias (even if it is unintentional) and missed studies.

4. Summary of findings In a systematic review, an effort is usually made to assess the quality of the evidence, often using risk of bias assessment, at the study level and often across studies. Other literature reviews rarely assess and report any formal quality assessment by individual study. Risk of bias assessment is important to a thorough summary of the evidence, since conclusions based on biased results can be incorrect (and dangerous, at worst). Results from a systematic review can sometimes be pooled quantitatively (e.g., in a meta-analysis) to provide numeric estimates of treatment effects, for example.

5. Utility of results Due to the rigor and transparency applied to a systematic review, it is not surprising that the results are usually of higher quality and at lower risk of bias than results from other types of literature review. Literature reviews can be useful to inform background sections of papers and reports and to give the reader an overview of a topic. Systematic reviews are used by professional associations and government agencies to issue guidelines and recommendations; such important activities are rarely based on a non-systematic review. Clinicians may also rely on high quality systematic reviews to make evidence-based decisions about patient care.

Each type of review has a place in the scientific literature. For narrow, specific research questions, a systematic review can provide a thorough summary and assessment of all of the available evidence. For broader research questions, other types of literature review can summarize the best available evidence using targeted search strategies. Ultimately, the choice of methodology depends on the research question and the goal of the review.

[1] Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyse s: The PRISMA Statement. PLoS Med 6(7): e1000097. doi:10.1371/journal.pmed1000097.

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Systematic reviews vs meta-analysis: what’s the difference?

Posted on 24th July 2023 by Verónica Tanco Tellechea

You may hear the terms ‘systematic review’ and ‘meta-analysis being used interchangeably’. Although they are related, they are distinctly different. Learn more in this blog for beginners.

What is a systematic review?

According to Cochrane (1), a systematic review attempts to identify, appraise and synthesize all the empirical evidence to answer a specific research question. Thus, a systematic review is where you might find the most relevant, adequate, and current information regarding a specific topic. In the levels of evidence pyramid , systematic reviews are only surpassed by meta-analyses. 

To conduct a systematic review, you will need, among other things: 

• A specific research question, usually in the form of a PICO question.
• Pre-specified eligibility criteria, to decide which articles will be included or discarded from the review. 
• To follow a systematic method that will minimize bias.

You can find protocols that will guide you from both Cochrane and the Equator Network , among other places, and if you are a beginner to the topic then have a read of an overview about systematic reviews.

What is a meta-analysis?

A meta-analysis is a quantitative, epidemiological study design used to systematically assess the results of previous research (2) . Usually, they are based on randomized controlled trials, though not always. This means that a meta-analysis is a mathematical tool that allows researchers to mathematically combine outcomes from multiple studies.

When can a meta-analysis be implemented?

There is always the possibility of conducting a meta-analysis, yet, for it to throw the best possible results it should be performed when the studies included in the systematic review are of good quality, similar designs, and have similar outcome measures.

Why are meta-analyses important?

Outcomes from a meta-analysis may provide more precise information regarding the estimate of the effect of what is being studied because it merges outcomes from multiple studies. In a meta-analysis, data from various trials are combined and generate an average result (1), which is portrayed in a forest plot diagram. Moreover, meta-analysis also include a funnel plot diagram to visually detect publication bias.

Conclusions

A systematic review is an article that synthesizes available evidence on a certain topic utilizing a specific research question, pre-specified eligibility criteria for including articles, and a systematic method for its production. Whereas a meta-analysis is a quantitative, epidemiological study design used to assess the results of articles included in a systematic-review. 

Remember: All meta-analyses involve a systematic review, but not all systematic reviews involve a meta-analysis.

If you would like some further reading on this topic, we suggest the following:

The systematic review – a S4BE blog article

Meta-analysis: what, why, and how – a S4BE blog article

The difference between a systematic review and a meta-analysis – a blog article via Covidence

Systematic review vs meta-analysis: what’s the difference? A 5-minute video from Research Masterminds:

• About Cochrane reviews [Internet]. Cochranelibrary.com. [cited 2023 Apr 30]. Available from: https://www.cochranelibrary.com/about/about-cochrane-reviews
• Haidich AB. Meta-analysis in medical research. Hippokratia. 2010;14(Suppl 1):29–37.

Verónica Tanco Tellechea

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As seen in a previous blog from Davide, modern neuroscience often interfaces with other medical specialities. In this blog, he provides a summary of new evidence about the potential of a therapeutic strategy born at the crossroad between neurology, immunology and oncology.

About Systematic Reviews

The Difference Between Narrative Review and Systematic Review

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Reviews in scientific research are tools that help synthesize literature on a topic of interest and describe its current state. Different types of reviews are conducted depending on the research question and the scope of the review. A systematic review is one such review that is robust, reproducible, and transparent. It involves collating evidence by using all of the eligible and critically appraised literature available on a certain topic. To know more about how to do a systematic review , you can check out our article at the link. The primary aim of a systematic review is to recommend best practices and inform policy development. Hence, there is a need for high-quality, focused, and precise methods and reporting. For more exploratory research questions, methods such as a scoping review are employed. Be sure you understand the difference between a systematic review and a scoping review , if you don’t, check out the link to learn more.

When the word “review” alone is used to describe a research paper, the first thing that should come to mind is that it is a literature review. Almost every researcher starts off their career with literature reviews. To know the difference between a systematic review and a literature review , read on here.  Traditional literature reviews are also sometimes referred to as narrative reviews since they use narrative analysis to synthesize data. In this article, we will explore the differences between a systematic review and a narrative review, in further detail.

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Narrative Review vs Systematic Review

Both systematic and narrative reviews are classified as secondary research studies since they both use existing primary research studies e.g. case studies. Despite this similarity, there are key differences in their methodology and scope. The major differences between them lie in their objectives, methodology, and application areas.

Differences In Objective

The main objective of a systematic review is to formulate a well-defined research question and use qualitative and quantitative methods to analyze all the available evidence attempting to answer the question. In contrast, narrative reviews can address one or more questions with a much broader scope. The efficacy of narrative reviews is irreplaceable in tracking the development of a scientific principle, or a clinical concept. This ability to conduct a wider exploration could be lost in the restrictive framework of a systematic review.

Differences in Methodology

For systematic reviews, there are guidelines provided by the Cochrane Handbook, ROSES, and the PRISMA statement that can help determine the protocol, and methodology to be used. However, for narrative reviews, such standard guidelines do not exist. Although, there are recommendations available.

Systematic reviews comprise an explicit, transparent, and pre-specified methodology. The methodology followed in a systematic review is as follows,

• Formulating the clinical research question to answer (PICO approach)
• Developing a protocol (with strict inclusion and exclusion criteria for the selection of primary studies)
• Performing a detailed and broad literature search
• Critical appraisal of the selected studies
• Data extraction from the primary studies included in the review
• Data synthesis and analysis using qualitative or quantitative methods [3].
• Reporting and discussing results of data synthesis.
• Developing conclusions based on the findings.

A narrative review on the other hand does not have a strict protocol to be followed. The design of the review depends on its author and the objectives of the review. As yet, there is no consensus on the standard structure of a narrative review. The preferred approach is the IMRAD (Introduction, Methods, Results, and Discussion) [2]. Apart from the author’s preferences, a narrative review structure must respect the journal style and conventions followed in the respective field.

Differences in Application areas

Narrative reviews are aimed at identifying and summarizing what has previously been published. Their general applications include exploring existing debates, the appraisal of previous studies conducted on a certain topic, identifying knowledge gaps, and speculating on the latest interventions available. They are also used to track and report on changes that have occurred in an existing field of research. The main purpose is to deepen the understanding in a certain research area. The results of a systematic review provide the most valid evidence to guide clinical decision-making and inform policy development [1]. They have now become the gold standard in evidence-based medicine [1].

Although both types of reviews come with their own benefits and limitations, researchers should carefully consider the differences between them before making a decision on which review type to use.

• Aromataris E, Pearson A. The systematic review: an overview. AJN. Am J Nurs. 2014;114(3):53–8.
• Green BN, Johnson CD, Adams A. Writing narrative literature reviews for peer-reviewed journals: secrets of the trade. J Chiropratic Medicine 2006;5:101–117.
• Linares-Espinós E, Hernández V, Domínguez-Escrig JL, Fernández-Pello S, Hevia V, Mayor J, et al. Metodología de una revisión sistemática. Actas Urol Esp. 2018;42:499–506.

3 Reasons to Connect

The Relationship Between Self-Regulated Learning and Executive Functions—a Systematic Review

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• Open access
• Published: 22 August 2024
• Volume 36 , article number  95 , ( 2024 )

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• Laura Dörrenbächer-Ulrich   ORCID: orcid.org/0000-0002-8361-9030 1 &
• Marius Bregulla 1  

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Self-regulated learning (SRL) and executive functions (EF) are broad concepts stemming from different research areas. They have been defined and modeled in various ways and are repeatedly related to each other in the literature, but so far, no systematic analyses of these relations have been published. Therefore, a systematic analysis of their relationships described in the literature was conducted. Nineteen studies were synthesized concerning different categories (age groups, measurement methods, role of metacognition, relation to achievement, and longitudinal/intervention studies). In general, primarily low to moderate correlational relationships between SRL and EF were reported, with no detectable pattern depending on the age group. Measurement methods used to capture SRL and EF seem to influence the size of the correlations, with indirect measures correlating higher than direct/indirect measures. In addition, there is evidence that metacognition mediates the relationship between EF and SRL. In general, the notion that EF predicts SRL but not vice versa is supported. Following the systematic review, the results are critically discussed in the light of non-generalizable samples, measurement methods, and results interpretation issues. Suggestions for theory building and promising future research are given.

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Pursuing goals is essential to human life and is relevant to various contexts, such as academics, working, social life, well-being, and health behavior. Concerning academic goals, adaptive learning goal-related behavior is entitled to self-regulated learning (Boekaerts, 1999 ). Self-regulated learning (SRL) is a construct that describes how individuals actively initiate goal-directed learning processes and control and regulate their cognitive processes within academic contexts (Puustinen & Pulkkinen, 2001 ). As this definition discloses, metacognition is an essential part of SRL (“control and regulate”) and is defined as encompassing higher-order cognitive processes that help to monitor, control, and adapt information processes on a lower level (Roebers, 2017 ). The term higher-order cognitive processes is also used to refer to executive functions (EF) as they describe the top-down regulation of cognitive and behavioral processes (Miyake et al., 2000 ). As the previous definitions made clear, several conceptualizations are highly relevant when describing goal-directed behavior (SRL, metacognition, EF), and it is not obviously clear how to differentiate between these concepts. In this context, Kim et al. ( 2023 ) speak of jingle-jangle fallacies, as the same terms are used for different conceptualizations resp. similar conceptualizations are named differently. Moreover, there is convincing evidence that SRL, metacognition, and EF are linked to academic achievement (e.g., Dent & Koenka, 2016 ; McClelland et al., 2013 ).

In order to disentangle the abovementioned conceptual overlaps, several reviews have delved into the literature and offered highly relevant insights: Dinsmore et al. ( 2008 ) carried out a review to shed light on the conceptual overlaps and differences between general self-regulation (execution of general goal-directed behavior; Hofmann et al., 2012 ), SRL, and metacognition, Kim et al. ( 2023 ) reviewed the literature on SRL and metacognition to integrate scientific views from cognitive and educational psychology. Referring to EF, Hofmann et al. ( 2012 ) wrote a pertinent review on the relationship between EF and general self-regulation, while Roebers ( 2017 ) illuminated the links between EF and metacognition within her seminal review. In order to complete the circle, the present systematic review aims to synthesize hitherto existing literature on the relationship between SRL and EF, as no review to date has focused on this conceptual overlap. We, therefore, explicitly do not integrate metacognition and general self-regulation into our search process, as such reviews already exist. Moreover, we aim to focus on self-regulated learning processes (and therefore representing an educational psychology perspective) and their relationship to EF. The review results should give new insights into and help structure associations between SRL and EF and uncover possible directional connections between both constructs. Summarizing and analyzing the current state of research is necessary to expedite theoretical work on this aim and stimulate empirical studies that further help disentangle both constructs.

Theoretical Background

Self-regulated learning: background, definition, models.

The well-known works of Bandura ( 1986 ) can be seen as the general theoretical foundation for research on self-regulation, introducing behavior, emotion, self-efficacy, and motivation as regulatory areas (Dinsmore et al., 2008 ). Although most of the articles on self-regulation were published in social psychology and personality journals (Boekaerts et al., 2000 ), from the 1990s on, the concept was applied to the academic domain, generating the term “self-regulated learning” (SRL). While there is no single widely accepted definition that would suffice all SRL research (Boekaerts, 1999 ), Perels et al. ( 2020 ) mention that even though numerous different definitions exist, they are united by using three key components: A cognitive component (processing of information, strategic knowledge, and learning strategies), a motivational component (activities that serve to initiate and sustain the learning process, in addition to action-promoting attributions of successes and failures, and self-efficacy beliefs), and a metacognitive component (planning of the learning process, observing oneself in the learning situation, reflecting on and subsequently adapting the learning behavior by evaluating its usefulness for the learning goal). Following that, recent reviews describe SRL as incorporating cognitive, metacognitive, motivational, emotional, and behavioral aspects of learning (Panadero, 2017 ; Zeidner & Stoeger, 2019 ).

One definition of SRL that encompasses the aforementioned main components in a condensed manner and is meant when referring to SRL in this review comes from Pintrich ( 2000 , p. 453): “self-regulated learning is … an active, constructive process whereby learners set goals for their learning and then attempt to monitor, regulate, and control their cognition, motivation, and behavior, guided and constrained by their goals and the contextual features in the environment”. Pintrich ( 2000 ) makes several assumptions to come to this definition: Firstly, learners do not just passively receive information but actively use information coming from the environment and from their minds to construct their own meanings, set their own goals, and choose learning strategies. Secondly, there needs to be the assumption that learners can at least partially monitor, control, and regulate their cognition, motivation, and behavior. Thirdly, Pintrich argues that a criterion or goal must be set and worked towards, and the subsequent process can be regulated and adapted when one is in danger of missing one’s goal. Lastly, self-regulatory endeavors are assumed to mediate between the described personal and contextual characteristics and eventual achievement.

SRL as a construct has been heavily researched over the last three decades. As a consequence of this and the fact that different definitions emphasize different aspects of the construct, a range of theoretical models have been proposed (see Panadero, 2017 ; Tinajero et al., 2024 ). However, Zeidner and Stoeger ( 2019 ) note that many commonalities between models emerge. According to most models, successful self-regulation in a learning context occurs when students actively engage in the learning process and take measures to actively adapt their behavior, personal processes, and external conditions to attain their goals. In his recent review, Panadero ( 2017 ) shows that Pintrich’s ( 2000 ) and Zimmerman’s ( 2000 ) models, which give a comprehensive overview of distinct SRL phases and areas of regulation, are most frequently used in the literature, with Zimmerman’s model being the most cited (Panadero, 2017 ; Tinajero et al., 2024 ). Moreover, both models are based on the same theory (i.e., Bandura’s ( 1986 ) social cognitive theory) and therefore bear resemblance (Puustinen & Pulkkinen, 2001 ). Besides such process models of SRL, component models focus on describing the competencies that positively impact SRL (Winne & Perry, 2000 ). To differentiate and provide a more thorough overview of the literature for the systematic analysis, Boekaerts’ three-layered model of SRL ( 1999 ) will be examined in addition to Zimmerman’s model ( 2000 ). In their review article, Tinajero et al. ( 2024 ) describe Zimmerman’s model ( 2000 ) as adopting a distant focus that established the process structure of SRL, while Boekaerts’ model ( 1999 ) adopts a more task-focused approach. Therefore, both models are helpful to cover the whole SRL construct.

Zimmerman’s Social Cognitive Model of Self-Regulation

By referring to self-regulation as “self-generated thoughts, feelings, and actions that are planned and cyclically adapted to the attainment of personal goals” (Zimmerman, 2000 , p. 14), Zimmerman introduces a cyclical viewpoint that is not only essential to his social cognitive model of self-regulation but also to many other SRL models (Panadero, 2017 ). His process model explicitly focuses on describing process phases and the requirements to be met in the respective phase (see Fig. 1 b). It is cyclical because the feedback resulting from prior behavior can influence or be used to adjust current behavior. This leads to a model that resembles a simple control loop in which a current actual status is compared with a target status, and depending on the difference, behavioral or cognitive adjustments will or will not be made (Perels et al., 2020 ). Zimmerman ( 2000 ) deems these reoccurring adjustments necessary because personal, behavioral, and environmental factors continuously change during learning processes.

The forethought phase splits into task analysis and self-motivation beliefs: task analysis involves goal setting, where students analyze task features and the requirements for performance. Goal setting is conditioned by essential self-motivational beliefs like self-efficacy (beliefs about one’s ability to perform effectively), outcome expectations (what final result is expected), what value the task has, and how goal-oriented and interested the performer is. Considering these beliefs, the overall motivation for the task will be determined, as well as the effort and the activation of self-regulatory strategies. In the following performance or volitional control phase, the actual execution of the task takes place, including self-control and self-observation processes.

The self-control part reflects a process that aims to keep concentration and interest high with the help of various strategies (e.g., self-instructions or self-praise; Panadero & Alonso-Tapia, 2014 ). Self-observation can be described as a comparison between the expert model and what the student is doing and the assessment of one's performance (metacognitive monitoring) (Panadero & Alonso-Tapia., 2014 ). For the self-reflection phase, self-judgment and self-reaction are the two fundamental processes. They emerge after a task or performance has concluded and play an essential part in how a person responds to their (learning) experience. Judging oneself requires comparing the information gathered during the action with a standard or goal. During self-judgments, learners will also want to find causal attributions regarding the results of their learning session by analyzing their accomplishments or shortcomings and drawing conclusions about their abilities or invested effort (Puustinen & Pulkkinen, 2001 ). These attributions result in positive and negative emotions, which can impact motivation and regulation in future performances. Self-reaction includes satisfaction or dissatisfaction and adaptive or defensive interferences. Returning to the cyclical aspect of Zimmerman’s ( 2000 ) model, the late self-reflection phase prepares the next forethought phase.

Boekaerts’ Three-Layered Model of SRL

The three-layered model of SRL (Boekaerts, 1999 ) consists of three concentrical ellipses (see Fig. 1 a): The inner ellipse stands for the regulation of processing modes and is enclosed by the regulation of the learning process ellipse; both are encompassed by an ellipse that signifies the regulation of the self. The innermost ellipse can be seen as the typical way students learn. For self-regulation to occur on this level of the model, i.e., dealing adequately with a particular learning task by being able to adapt the course of action, the learner must perceive the choice between different cognitive strategies (Winne & Perry, 2000 ). The middle layer of the model represents the regulation of the learning processes, i.e. the learner guides and directs their learning process by monitoring whether they perform the task as planned in the inner ellipse. This is achieved using metacognitive knowledge and metacognitive strategies, including orienting, planning, executing, monitoring, evaluating, and correcting (Weinstein & Mayer, 1986 ). Regulation on this level is done internally when students can set their own goals, but some do need external regulation, for example, the guidance of a teacher or parent. The outer layer integrates the regulation of the self, including aspects like volition and motivation. If learning activities are self-initiated, they are more likely driven by personal goals compared to externally initiated learning, which is mainly imposed by the wishes and expectations of others. In general, the learner’s overarching goals are potent drivers of behavior and can reveal how a learner regulates the self. The following section will give an overview of EF’s definitions and model to lay this construct's theoretical foundation for the systematic review.

a Cyclical model of self-regulation (Zimmerman, 2000 ) and  b three-layered model of SRL (Boekaerts, 1999 )

Executive Functions: Background, Definitions, Models

Executive functions (EF) describe a family of top-down or higher-order cognitive processes that are involved in goal-directed, flexible, and adaptive behavior and execute cognitive control through attentional, decision-making, and coordinative functions (Diamond, 2013 ; Miyake et al., 2000 ). Since the 1960s, Luria (e.g., Luria et al., 1967 ) systematically studied frontal lobe injuries and the accompanying effects (Suchy, 2009 ) and later described the functions of the frontal lobes as taking on an executive role (Goldstein et al., 2014a , b ; Luria, 1980 ). Therefore, neuroanatomy and neuropsychology had a significant impact on the emergence of EF research. Overview articles on EF (Jurado & Rosselli, 2007 ; Suchy, 2009 ) often include clinical populations like patients who suffered brain damage from accidents or diseases in their concept assessment. Furthermore, Jurado and Rosselli ( 2007 ) list an extensive collection of neuroimaging research that links cognitive abilities associated with EF, like planning, attentional control, cognitive flexibility, and verbal/nonverbal fluency, to brain areas like the frontal lobes, different subcortical structures, and thalamic pathways. Additionally to neuropsychological research, other lines of research played an essential part in developing the EF construct: Broadbent ( 1958 ) contributed to the topic via the distinction between automatic and controlled processes, and Shiffrin and Schneider ( 1977 ) proposed the concept of selective attention. Baddeley’s ( 1992 ) influential working memory model includes a component named the central executive, which is assumed to have specific control over attention and cognitive processes. Norman and Shallice ( 1986 ) see evidence for a so-called supervisory attentional system that can replace automatic action with intentional behavior. As with SRL, EF has been approached in many ways, leading to different understandings of the concept.

EF has become an umbrella term for a whole collection of cognitive processes and abilities, including “stopping prepotent or automatic responses, resisting distraction or interference from irrelevant information in the environment or memory, switching between task sets, aspects of working memory processes, dual tasking, planning, monitoring, and verbal and design fluency” (Friedman & Miyake, 2017 , p. 186). This, and the fact that Goldstein et al. ( 2014a , b ) cited over 30 construct definitions from EF researchers, makes it not trivial to define the concept for general use in this work. Based on the approaches to define EF supposed by Suchy ( 2009 ), we consider it beneficial to include neurocognitive processes (like working memory, sequencing, inhibition, initiation, and response selection), use constructivist definitions, and consider a list of complex skills (like planning, reasoning, problem-solving, and judgment). Executive functions are directive capacities responsible for a person’s ability to engage in purposeful, organized, strategic, self-regulated, goal-directed processing of perceptions, emotions, thoughts, and actions.

Although some models treat EF as a unitary construct, many EF researchers see evidence for EF being a multidimensional construct (Karr et al., 2018 ). In order to account for multidimensional models and the elementary neurocognitive processes approach, the well-established model of Miyake et al. ( 2000 ) will be explored in more detail. Miyake et al. ( 2000 ) build their model on three frequently proposed dimensions of EF: shifting, updating, and inhibition. The authors approach the topic via evidence for performance differences across executive tasks in clinical populations (e.g., Godefroy et al., 1999 ). Another consideration is that although the interrelations between different EF tasks are low, this does not necessarily indicate distinguishable EF because of the task impurity problem (Miyake & Shah, 1999 ). This means that when EF is being tested, the process requires other cognitive skills or functions that may be independent of EF-related brain structures but are reflected in the test results (Rabbitt, 1997 ).

To counter these challenges, Miyake et al. ( 2000 ) choose a latent variable analysis to explore EF’s organization and cognitive role. The latent EF used in this model has the advantage that it is, compared to more complex proposed EF-like problem-solving, relatively elementary and limited in functionality and, therefore, can be operationalized more precisely (Miyake et al., 2000 ). Shifting requires switching between tasks or mental sets and results in different temporal costs that may stem from a differing ability to engage and disengage from tasks or handle interference from previous tasks (Miyake et al., 2000 ). Updating (or working memory ) refers to a function that involves monitoring what kind of information is presented and relevant for the task at the moment and actively changing the information stored in the working memory by replacing old, irrelevant representations with new, relevant ones (Morris & Jones, 1990 ). Inhibition is consciously suppressing prevalent, automatic, or prepotent responses when needed (Miyake et al., 2000 ). Using confirmatory factor analysis, the authors conclude that a three-factor model for shifting, updating, and inhibition fits the gathered data best when statistically compared to the various conceivable two-factor models and a one-factor model. However, further model comparisons showed that three completely separable factors were statistically unlikely, suggesting that the EFs assessed had at least some fundamental commonality.

Several other models build upon the model of Miyake and expand it: Diamond ( 2013 ) amplified these primary EF and hypothesized that they could build the basis for complex and higher-ranked functions such as reasoning, problem-solving, and planning. By arranging different tasks on a continuum from simple to complex EF requirements, Luciana et al. ( 2005 ) aimed at integrating both simple and complex EF within one model: While spatial memory span is seen as a simple function with relatively low cognitive requirements, behavioral organization during spatial self-ordered search tasks is seen as a complex function with relatively high cognitive requirements. In contrast, Prencipe et al. ( 2011 ) use a differentiation based on the dominating involvement of the EF processes in other processes. While “cold” EFs (e.g., working memory) are mainly responsible for abstract processes, “hot” EFs (e.g., decision-making during delay of gratification situations) are influenced more by affective and motivational stimuli. Cold EFs, therefore, can be seen as the regulation basis for hot EFs (Hofmann et al., 2012 ). Both perspectives could be integrated if hot EFs were seen as more complex than cold EFs due to their emotional relevance. Figure 2 illustrates how all three perspectives could be integrated within one model (author, year).

Extended illustrative structure of EF. Processes on the left correspond to a model by Luciana et al. ( 2005 ); processes on the right correspond to a model by Prencipe et al. ( 2011 ), both integrating the primary EF functions of Miyake et al. ( 2000 ) and the higher-level functions of Diamond ( 2013 ) (adapted from author, year)

Similarities and Differences between SRL and EF

Based on the previous sections and the presented models, it can be resumed that SRL and EF have conceptual overlaps: Both constructs describe goal-related behavior and, therefore, higher-order cognitive processes with dynamic and regulatory functions that aim at monitoring, controlling, and regulating information processing and optimizing lower-level task processing (Roebers, 2017 ). Nevertheless, research histories of both constructs strongly differ as research on EF stems from frontal lobe functioning studies in clinical neuropsychology and also from developmental psychology (Roebers, 2017 ), while SRL is a concept of educational psychology that directly resulted from school studies (Dinsmore et al., 2008 ). In the following, we will describe several topics that help to uncover similarities and differences between SRL and EF.

Components of SRL and EF

When comparing SRL and EF on the component level, the review of Hofmann et al. ( 2012 ) can be very helpful as the authors proposed how EF components could be transferred to general self-regulation: while working memory is assumed to support the representation of goals, control of attention and shielding from distractions, inhibition is hypothesized to inhibit impulses and habitual behaviors that endanger goal achievement. Shifting could help individuals to switch flexibly between different strategies or multiple goals. As this transfer to self-regulation is not learning-specific, we illustrate how EF components could support SRL components (see also Hoyle & Dent, 2018 ): While working memory is necessary to process the information on the lowest level (cognitive component of SRL), it is also needed to monitor and control information processing (metacognitive component of SRL) as well as to actively represent goals and use these goals to control attention (motivational component of SRL). Inhibition is assumed to mainly support the motivational component of SRL as volitional strategies have to be used to maintain the motivation for goal achievement (and therefore shield learning processes from distracting thoughts). Shifting is hypothesized to mainly support metacognition, as the flexible adaption of the strategy used should result from monitoring and controlling learning processes. In line with this, Bol and Garner ( 2011 ) try to conceptualize SRL as an application of EF (for the context of learning in distance education environments with electronically enhanced texts). In general, they see “executive functions as neurocognitive processes that promote self-regulation at both the basic cognitive (e.g., attentional control) and metacognitive (e.g., planning and self-monitoring) levels” (Bol & Garner, 2011 , p. 114). The authors suggest EF variations may influence the SRL cycle during interactions with electronic learning material. Low EF, therefore, could lead to difficulties in goal setting and strategic planning, resulting in the inability to switch learning strategies when necessary. Moreover, they assume that EF supports attentional control, which is imperative during the volitional stage of SRL. Referring to the categorization of Prencipe et al. ( 2011 ), cold EF seems more likely to be related to the (meta-)cognitive component of SRL, while hot EF most likely are strongly related to the motivational component of SRL. For the differentiation between simple and complex EF (Diamond, 2013 ; Luciana et al., 2005 ), the transfer to SRL is not as easy as SRL strategies most likely can be seen as complex (due to their general reliance on metacognitive knowledge and skills).

In conclusion, regarding the theoretical component level of both SRL (cognition, metacognition, and motivation; referring to the model of Boekaerts, 1999 ) and EF (working memory, inhibition, shifting; referring to the model of Miyake et al., 2000 ), it can be assumed that EF components support the different SRL components in various ways with some EF components are likely to have a more substantial influence on SRL components than others (e.g., working memory seems to support all three SRL components, while inhibition and shifting mainly support one SRL component). Regarding process models of SRL, such as Zimmerman’s model ( 2000 ), it is evident that SRL is more than the sum of the components: The cyclical nature of the model highlights that an optimal SRL process encompasses different phases (which all comprise several SRL components themselves). One phase can only be executed in an optimal goal-oriented way if the previous phase has been passed successfully. Each phase gives hints to the learners about whether the behavior is still goal-oriented and where they can regulate their behavior through strategy application. The feedback loop from the reflection to the following planning phase is enormously important as the learner can conclude previous learning cycles and the possible outcomes (success/failure). This cyclical nature is missing in the above-described EF models and helps to differentiate both constructs. In EF models, the different components are more collocated, and how they interfere with one another is not apparent nor theoretically deduced. This is also obvious when looking at the model of Miyake et al. ( 2000 ), who used a latent variables analysis approach. The three-factor model was the best-fitting model compared to the two-factor and one-factor models.

• Metacognition

In general, metacognition is defined as “thinking about thinking” or, more specifically, as “knowledge and cognition about cognitive phenomena (Flavell, 1979 , p. 906). In his seminal work, Flavell ( 1979 ) distinguished between metacognitive knowledge and metacognitive experiences: Metacognitive knowledge describes knowledge or beliefs about the interaction of different factors and their influence on the outcomes of cognitive processes. This knowledge can refer to persons (e.g., some people can better learn through hearing than through reading), task demands/goals (e.g., some tasks/goals are easier to accomplish/achieve than others), and strategies to achieve these goals (e.g., repeating is a valuable strategy to learn word lists but not to understand Maths). Metacognitive experiences are conscious reflections about cognition and primarily arise in cognitively challenging situations that require a lot of decisions, planning, and evaluation. Metacognitive experiences interact with and help to form and develop metacognitive knowledge. Besides metacognitive knowledge and metacognitive experiences, Veenman et al. ( 2006 ) introduce metacognitive skills, which are about a “person’s procedural knowledge for regulating one’s problem-solving and learning activities” (e.g., planning a learning task; p. 4).

Besides Flavell’s work, Nelson and Narens’s ( 1990 ) model is essential when describing metacognition. Their conceptual framework on the relation of metacognition and cognition defines an object-level (basic information processing operations) and a meta-level (learner’s model of the task and cognitive operations during performance). Metacognitive monitoring processes connect both levels cyclically as they transfer information about the object-level to the meta-level. Moreover, the meta-level can initiate control processes and regulate object-level processes to reach a specific goal. Pintrich et al. ( 2000 ) combine the work of Flavell ( 1979 ) and Nelson and Narens ( 1990 ) and state that metacognition comprises metacognitive knowledge, metacognitive monitoring and judgments, and metacognitive control. The authors describe that metacognitive knowledge can either refer to declarative (“What”), procedural (“How”), or conditional (“When” and “Why”) strategy knowledge. In contrast, metacognitive monitoring refers to the learner’s awareness regarding his/her current knowledge or learning process evaluation (Dunlosky and Metcalfe, 2008 ). It is deemed a “situation-specific and context-dependent” process that acts on the object-level and helps the learner regulate the learning process on the meta-level (Händel and Dresel, 2022 , p. 2). Metacognitive judgments (i.e., a probabilistic judgment on performance quality) are indicators for metacognitive monitoring (Nelson and Narens, 1990 ). The process of selecting and using strategies for adapting learning processes is called metacognitive control.

For the overlap between general self-regulation, SRL, and metacognition, Dinsmore et al. ( 2008 ) report seven keywords within their review that unite all three constructs, which are “monitor, control, regulate, cognition, motivation, behavior, and knowledge” (p. 400). It is obvious that the first four keywords are also highly relevant when describing EF and that the overlap between EF and SRL mainly refers to the metacognitive component of SRL (Boekaerts, 1999 ). Metacognition, therefore, seems to play a special role in the relationship between SRL and EF as both correlate with knowledge and control of one’s cognitive processes and with metacognition (Follmer & Sperling, 2016 ). Metacognition is a highly relevant construct on its own, but it is also an essential subcomponent of EF and SRL (Hoyle & Dent, 2018 ). The motivational component of SRL, which refers to initiating learning processes and pursuing goal achievement using volitional strategies, shows partial overlap with what hot EF means.

Developmental Aspects

Concerning developmental aspects, children have already established the foundation for SRL during preschool and primary education (Bronson, 2000 ; Chatzipanteli et al., 2014 ). However, their skill sets are further strengthened and expanded by experiences throughout secondary and tertiary education (Hoyle & Dent, 2018 ). For EF, essential development occurs before the age of six, as the foundations for working memory, inhibition, and updating are laid out at the preschool age (Welsh, 2001 ). These three core components and the advancement of complex thinking, planning, and decision-making can be observed from elementary school to adolescence (Roebers, 2017 ; Welsh, 2001 ). Based on this somewhat earlier onset of development for EF than for metacognition, Roebers ( 2017 ) hypothesizes that EF has a causal role in the development of metacognition in early years, with this influence diminishing when domain-specific knowledge comes into play (which is important for metacognitive development). Karr et al. ( 2018 ) found a divergence of EF from preschool into adulthood. In contrast, Rheinberg et al. ( 2000 ) see a rising demand for SRL abilities with increasingly complex learning materials in higher grades. It could be argued that both concepts are subject to change throughout life. Thus, researchers could try to conclude their relationship from empirically observable parallel or divergent developments.

Measurement

Concerning measurement, SRL is mainly measured in authentic learning environments that ensure external validity, and the studies mostly show a cross-sectional or longitudinal instead of an experimental design (Kim et al., 2023 ). This is frequently done using self-report questionnaires that are sometimes very general (referring to learning tasks in general, e.g., Dörrenbächer & Perels, 2016 ) but sometimes domain- or course-specific (Roth et al., 2016 ). Using more context-sensitive measures such as microanalysis or trace data can help assess SRL in a task-specific and, therefore, more objective way (Dörrenbächer-Ulrich et al., 2021 ). In general, there is no clear answer on how to measure SRL optimally as all assessment methods show benefits and points of criticism (Rovers et al., 2019 ), so the choice of instrument often depends on the theoretical model or the aim of the study. In contrast, EF is mainly measured decontextualized using single tasks to assess specific components of EF or task batteries that assess more than one EF component (Chan et al., 2008 ). For example, the “Stroop Test” is probably the best-known test for assessing the inhibition component of EF. At the same time, the “Wisconsin Card Sorting Test” (Heaton & PAR Staff, 1993 ) is a prominent test to measure the shifting component, and the “Tower of London” (Shallice, 1982 ) is often used to measure the planning component. These tasks are primarily applied in laboratory and highly controlled studies. Besides task-based tests, there are also questionnaires to measure EF (impairment) in everyday situations, such as the “Naturalistic Action Test” (Schwartz et al., 2002 ).

Achievement Criteria and Intervention Studies

For achievement, it can be stated that both SRL and EF show substantial relations to academic performance measures. For SRL, meta-analyses show a positive relationship to achievement but with low effect sizes (e.g., Broadbent & Poon, 2015 ; Dent & Koenka, 2016 ). EF is a valid predictor for academic achievement (McClelland et al., 2013 ; Titz & Karbach, 2014 ) and can explain about 20–60% of school children’s achievement variance (Roebers et al., 2014 ), while this has been shown for elementary up to high school students. As both SRL and EF are positively related to academic achievement, it is helpful to look at the relationship of both constructs to achievement outcomes to find overlaps and differences between SRL and EF.

Literature addressing the fostering of SRL (e.g., Perels et al., 2020 ) or EF (e.g., Dawson & Guare, 2014 ) can serve as another indicator for concept overlaps. For example, if respective interventions aimed at fostering one of the concepts lead to qualitative changes in the other concept (defined as “far transfer”; see Kassai et al., 2019 ), this could indicate conceptual overlaps or entanglements. However, it is essential to consider how the interventions were designed and whether they exclusively foster one or both constructs, in this case, conclusions about conceptual relationships are challenging to draw.

Aims of the Present Systematic Review

The aim of compiling this theoretical background on SRL and EF was to explore the emergence and different definitions of the two concepts and the models that attempt to structure them. As has become evident, the two constructs are broad, defined, and modeled in many ways, and primarily grounded in different research fields. Moreover, we aimed to sum up the similarities and differences between the constructs by comparing their components, their development, ways of measuring both constructs and their relationship to achievement. In the systematic analysis, an effort will be made to structure associations between SRL and EF in a way that allows parallels to be drawn between different categories of relationships across studies. This way, findings from correlational associations could be compared with those from SRL-EF mediation modeling to reach more reliable conclusions about possible concept overlaps or entanglements. Another goal is to clarify whether SRL or EF is an application of the other or whether other directional connections can be found. Embedding these results in the thoroughly researched theoretical background may lead to insights regarding the shortcomings of the analyzed study designs, which may benefit future research. In conclusion, we aimed to investigate the following research questions:

RQ 1: How are SRL and EF related, and does this relationship depend on the age of the study sample or measurement methods?

RQ 2: What role does metacognition play within the relationship of SRL and EF?

RQ 3: How are SRL and EF related to academic achievement?

RQ 4: What are the results of longitudinal or interventional studies on the relationship between SRL and EF?

To compile the literature and systematically compare SRL and EF, a search engine had to be chosen first, and search parameters had to be defined. EBSCO, a provider of research databases, electronic journals, journal subscriptions, e-books, and discovery services, was chosen as the literature source. On its search engine EBSCOhost, the relevant databases “APA PsycArticles”, “APA PsycInfo”, “ERIC” and “PSYNDEX Literature with PSYNDEX Tests” were searched as follows: On January 31, 2024, the search string “TX ( self-regulated learning OR srl) AND TX ( executive function OR executive functioning)” resulted in 214 potential sources. No further restrictions were placed on the search criteria. Thus, non-peer-reviewed sources were also included, and no time limits regarding the date of publication were set. Of the 214 sources found, eleven exact duplicates were removed, leaving 203 sources to be studied in terms of content.

Inclusion and Exclusion Criteria

For this review, several inclusion and exclusion criteria were defined: as this review aims at giving a first overview of studies dealing with the relationship between SRL and EF and therefore aims to integrate both constructs on a general and conceptual level, sources that examined clinical populations, like individuals diagnosed with ADHD (e.g., Sibley et al., 2019 ) or autism spectrum disorder (e.g., Grainger et al., 2016 ) were excluded. Given that all studies were in English, none had to be excluded based on language. All papers that addressed any conceptual relationship or comparison between SRL and EF were considered to meet the inclusion criteria. For example, studies that described correlations (e.g., Effeney et al., 2013 ), mediation models (e.g., Follmer & Sperling, 2016 ), divergences, and convergences of the two concepts (e.g., Garner, 2009 ) were included. At this point, it should be reiterated that the goal is to systematically extract the researchers’ results and conclusions on the relation between SRL and EF, not to compare results focusing exclusively on one of the constructs. Based on the abstracts, 161 papers were excluded according to the above criteria. In contrast, most papers were excluded as they did not focus on self-regulated learning (e.g., they mentioned the construct in the discussion but did not examine it in the main study) or as they did not investigate the relationship between both constructs. If the exclusion and inclusion criteria could not be applied without a doubt, the papers were retained in the literature pool for further analysis. In addition, six studies were excluded because they were not accessible through databases acquired by the University’s libraries. Of the remaining 36 potential sources, an extra 19 were excluded after additional textual examination following the exclusion and inclusion criteria. Both authors made the analysis of these 36 sources, and in the case of non-convergence, the authors discussed why to keep or exclude a paper. As we detected two papers matching our criteria cited within the previously found texts, altogether 19 sources remained for in-depth analysis (see Fig. 3 ; Page et al., 2021 ).

PRISMA 2020 flow diagram. *APA PsycArticles ( n  = 113), APA PsycInfo ( n  = 84), ERIC ( n  = 13), and PSYNDEX Literature with PSYNDEX Tests ( n  = 4)

Categorization Structure for the Analysis

To compile the researchers’ results and conclusions and assess them systematically, first, a structure was designed to categorize them. The categories were formed based on the theoretical foundations and the abovementioned points in which the constructs show differences. We, therefore, categorize the results concerning the age or developmental stage, type of measurement, role of metacognition, relation to achievement, and longitudinal studies/interventions. In order to classify the measures within single studies as referring to SRL or EF, we stuck to the classification used by the original study’s authors.

Correlations of SRL and EF

As it has been expected , most of the analyzed research papers examine relationships between SRL and EF or, more often, relationships between concept subcomponents. In order to categorize the findings and answer our first research question, if relations of SRL and EF differ depending on age or measurement methods, we will analyze the research papers concerning these two factors. For an overview of all studies and core results, see Table 1 . As Bol and Garner’s ( 2011 ) paper was theoretical, we did not integrate it into our results synopsis. The systematic review of Dörrenbächer-Ulrich et al. ( 2023 ) will only be integrated into our theory-building discussion section.

Comparison of Different Age Groups

Overall, we found five studies that examined the relation of SRL and EF in preschoolers , but only four included information on correlational coefficients. In general, the studies found low to moderate relations between SRL and EF in preschoolers: Davis et al. ( 2021 ) studied a sample of children at the end of kindergarten and again, 1 year later, at the end of their first school year. The SRL teacher rating correlated significantly moderately with the direct EF measures at T1 and low to moderate at T2. Using a direct, quantitative SRL measurement tool for preschoolers, Jacob et al. ( 2019b ) found a significant, low correlation to an EF planning assessment task. In the study of Grüneisen et al. ( 2023 ), analyses showed a moderate correlation between hot EF and a composite SRL measure (strategy knowledge test + parent rating). In accordance, Vitiello’s and Greenfield’s ( 2017 ) study resulted in low to low-moderate associations between an EF task battery and a teacher rating scale for approaches to learning (which they equate with SRL).

Four studies dealt with the relationship between SRL and EF in elementary school children , but two used the same sample (Cirino et al., 2018 , 2019 ). In general, correlations between measures of EF and SRL seem to be low in elementary school children. While Cirino et al. ( 2017 ) found the SRL and direct EF measures to be only weakly related to one another, Cirino et al. ( 2018 ) found low correlations between SRL scales and EF measures, with most correlations being non-significant. In a sample of third graders, measures for inhibitory control and cognitive flexibility correlated positively and moderately with SRL scores. In contrast, scores from the backward digit span task did not significantly correlate with SRL scores (Rutherford et al., 2018 ).

Only two studies analyzed the relation of SRL and EF in adolescent learners and partially showed moderate correlations. Effeney et al. ( 2013 ) conducted a study with children aged 10.5 to 17.5 years. They used both a self-report measure for SRL and EF. The EF total score and the SRL global score correlated moderately. Standard regression analysis resulted in the EF global score being a significant predictor of the SRL global score and explaining a significant proportion of variance in the SRL global score (18.8%). The analyses of Gestsdottir et al. ( 2023 ) resulted in non-significant correlations between different EF measures and the Self-efficacy for Self-Regulated Learning questionnaire. Only the working memory reaction time showed a significant moderate correlation.

We identified four articles on the relationship between SRL and EF in college students and adult learners . In general, correlations between measures of SRL and EF tend to be low to moderate in college and adult learners. In a sample of undergraduate students, Follmer and Sperling ( 2016 ) found a significant moderate correlation between the SRL score and an indirect EF measure and a significant but lower correlation between the SRL score and the direct EF measures. Studying the relationship between self-reported SRL and self-reported EF, Garner ( 2009 ) reported low to moderate correlations between the constructs’ components. The SRL subscale on intrinsic goal orientation showed the highest correlation with the EF motivational subscale. Meijs et al. ( 2021 ) measured self-reported SRL strategy use and utilized cognitive tests on working memory, shifting, and processing speed for EF. While time and effort management and complex cognitive strategy use were not predicted by any of the EF measures, simple cognitive strategy use was negatively predicted by processing speed, and critical thinking was positively predicted by shifting. In a sample of college freshmen, Petersen et al. ( 2006 ) used a self-report measure for SRL and EF. The analyses resulted in moderate correlations between the SRL self-report measure subscales and the EF total score (inversely scored). The authors found a shared variance between the SRL and EF measure of 33.2%.

Comparison of Different Measurement Methods

As EF can be measured using indirect (e.g., questionnaire) and direct (e.g., cognitive tasks) measures, we looked at differences in correlational patterns depending on the assessment method used. Table 1 overviews the SRL and EF measures used and the correlations found. We identified six studies that measured SRL and EF using indirect measures. In general, correlations between both constructs are higher if both are measured using indirect assessment methods (compared to EF measured directly). As can be seen in Table 1 , the studies used differing indirect measures for SRL (e.g., SSRLS, MSLQ, SRSI-SR, LASSI, MAI, TMQ, observational teacher rating; see Supplementary Material for further details concerning the measurement methods) and for EF (BRIEF, EFI, ESQ, EFRS). Nevertheless, all studies found moderate to high correlations between both constructs and their components. The correlations ranged between |.10|<  r  <|.61|.

Concerning studies that measured SRL indirectly and EF directly, we identified twelve studies. These studies also used varying indirect measures for SRL (HWD, HDD, SLQ, CLS, CHILD, MSLQ, SRSI-SR, self-efficacy for SRL questionnaire, knowledge test, teacher ratings, parent ratings, MAI, TMQ, PLBS, inCLASS) and a large variety of direct measure for assessing EF processes (due to the high amount of different direct EF tasks, we do not repeat them here). In contrast to the correlations reported for indirect SRL and indirect EF measures, the correlations between indirect SRL and direct EF measures turn out to be low to moderate and ranged between |.02|<  r  <|.36|, while it has to be stated that some studies also reported negative correlations between both constructs (e.g., Cirino et al., 2018 ).

The Role of Metacognition within the Relation of SRL and EF

Our search indicated five studies that took a closer look at the role of metacognition within the relationship between SRL and EF. In general, all three constructs are related moderately, and there is first evidence that metacognition acts as a mediator between EF and SRL. Effeney et al. ( 2013 ) used self-report measures for SRL and EF. The Behavioural Rating Inventory of Executive Function and Self-Report (BRIEF–SR, Guy et al., 2004 ) consists of the Behavioral Regulation Index (BRI; inhibition, shifting, emotional control, monitoring) and the Metacognitive Index (MI; working memory, planning, organization of materials, task completion) which both are inversely coded. The authors found higher correlations between the BRIEF-MI and SRL measures than between the BRIEF-BRI and SRL measures. Follmer and Sperling ( 2016 ) calculated two models to investigate if metacognition mediates the relationship between EF and SRL: The first model used self-reported metacognition as a mediator between indirect EF and SRL and between direct EF and SRL in the second model. For both models, they found metacognition to act as a mediator between EF and SRL. However, the direct effect of EF on SRL was not significant in the second model, suggesting that the effect of direct EF on indirect SRL was fully mediated by metacognition.

Follmer ( 2021 ) found moderate to high correlations between two indirect EF scores and an indirect metacognition measure. Nevertheless, three direct EF measures were not significantly correlated with the indirect metacognition measure. The moderate to high correlations between indirect metacognition and EF are in line with the result of Garner ( 2009 ), who found indirect metacognition and EF to be significantly correlated. Using exploratory factor analysis for the constructs of EF, SRL, and metacognition, Said ( 2014 ) found three factors that help to differentiate between high-achieving and low-achieving students: The first factor included metacognitive and behavioral EF scales, academic self-efficacy, and time management. Declarative knowledge, procedural knowledge, and knowledge monitoring ability are loaded onto the second factor. The direct EF measures are loaded onto the third factor.

Integrating Academic Achievement into the Relation of SRL and EF

We found five studies that integrated academic achievement measures into the examination of SRL and EF. In general, both constructs are positively related to academic achievement, and the first results hint at a mediating role of SRL in the relationship between EF and achievement. Vitiello and Greenfield ( 2017 ) tested the hypothesis that approaches to learning (which they adequate to SRL) mediate the relationship between EF and change in school readiness in preschoolers. Using structural equation modeling, the authors rejected their hypothesis but noted that the findings link SRL and EF to gains in school readiness. In contrast, the study of Grüneisen et al. ( 2023 ) supports the hypothesis of SRL acting as a mediator for the relationship between EF and achievement within a preschool sample. While EF was not related to academic competence, SRL showed a moderate relation to academic competence, and there was a significant indirect effect from EF via SRL on academic competence.

Within a sample of elementary school children, Rutherford et al. ( 2018 ) investigated the shared associations between SRL, EF, and academic achievement. The direct EF measure was a statistically significant predictor of academic achievement and of the SRL measure, which suggests that facets of EF can support SRL. Additionally, SRL had its own statistically significant direct path to achievement in all mediation models and mediated the effect of EF on achievement (at least partially). The study’s measurement timing supports the conclusion that better EF leads to more successful SRL, so improving EF may lead to higher performance scores via enhancing SRL. In a study with secondary school students (Gestsdottir et al.,  2023 ), SRL showed a positive moderate relationship with grade measures of the same year, while none of the EF measures showed significant relationships with achievement. Nevertheless, for the grades of the following year, there was no significant relationship with the SRL measure but a significant negative relationship with reaction times for the shifting measures (lower reaction times indicate better performance). In a sample of college students, Said ( 2014 ) conducted an exploratory factor analysis to find factors that represent SRL, metacognitive strategies, and EF. The author found three factors in which high-achieving students differed significantly from low-achieving students.

Results from Longitudinal and Interventional Studies

We found four studies using a longitudinal or interventional design that could help to detangle possible causal relationships between SRL and EF. Until now, findings are too scarce to find a general pattern, but the first results hint at the predictive value of EF for SRL but not vice versa. Davis et al. ( 2021 ) conducted a longitudinal study with two measurement points and studied a sample of children at the end of kindergarten and their first school year. Using cross-lagged panel analysis, the author concludes that results support the assumption that children’s EF longitudinally predicts future SRL to a moderate extent but not vice versa. The authors also tested a common factor model that fitted the data well, which they interpreted as indicating that SRL and EF measures could reflect the same underlying construct. Moreover, they tested different models that helped rule out alternative SRL-EF relationships (e.g., early SRL benefitting later EF or reciprocal relations).

Jacob et al. ( 2019a ) examined how an SRL intervention influences SRL and EF in preschoolers with different SRL precursor profiles. Although the intervention showed no effect, their findings suggest that high speech competency, in combination with high self-regulation, plays an essential part in acquiring SRL. However, this advantage did not show up for EF. Gestsdottir et al. ( 2023 ) measured SRL and EF in Grade 6 and several outcome measures (e.g., achievement, depression, anxiety, risky behavior) in Grade 6 and Grade 7. While they found EF deficits to be a stronger predictor for future development than for the concurrent state of risky behavior and internalizing symptoms of depression and anxiety, SRL was a stronger predictor for concurrent than future academic achievement. Even though Cirino et al. ( 2017 ) investigated the effects of SRL/EF training on reading comprehension, the experiment was designed so that SRL and EF training influences on reading comprehension could not be separated.

Synthesis and Assessment of the Systematic Analysis Results

In general, it can be stated that until now, a relatively small number of studies have investigated the relationship of SRL and EF albeit the theoretical overlap of both constructs. In conclusion, a low to moderate correlational relationship between SRL and EF has been confirmed for many SRL and EF measurements, with indirect measures correlating higher. Treated as a subscale of SRL or EF self-report measures, metacognition regularly shows high correlations with other subscales of SRL or EF self-report measures, and there is evidence that it mediates the relationship between SRL and EF. Given these results and the directional models identified, the notion that EF predicts SRL but not vice versa is supported. The results will be synthesized and discussed in the following section, focusing on the single research questions.

How are SRL and EF Related, and Does This Relationship Depend on the Age of the Study Sample or Measurement Methods?

Of the 19 works analyzed, 14 reported correlations between SRL and EF measures or measurement subcomponents, representing the most comprehensive comparison category between the two constructs. Concerning age differences , there are no clear patterns recognizable as most studies report low to moderate correlations of SRL and EF, not depending on age group. This is unsatisfying as we cannot draw any conclusion about developmental trajectories using the results of the reviewed studies. Although we have separated the study results depending on age group and found no effect, the results of Effeney et al. ( 2013 ) confirmed that age impacts the correlation between SRL and EF. This is why, for example, SRL-EF correlations in college students can only be compared to a limited extent to SRL-EF correlations in preschoolers. This is also underlined by the fact that self-report measures for SRL and EF show high correlations, especially for self-report measures (see below). However, these measures strongly depend on the verbal abilities of the participants. It, therefore, is unclear how far self-reports can be compared for age groups that heavily differ concerning the requirements to answer such questionnaires (verbal abilities, metacognitive competencies). To gain deeper insight into age influences on the correlation of SRL and EF, studies are needed that investigate the relationship using comparable measures within different age groups. Multimethod assessment of both SRL and EF using indirect and direct measures for different age groups could be very enlightening concerning age influences concerning the SRL-EF relationship.

What seems to make a more significant distinction regarding sizes of correlations of SRL and EF are the measurement methods used: While studies that measure both SRL and EF indirectly using questionnaires or teacher ratings result in moderate to high correlations between the constructs (e.g., Effeney et al., 2013 ; Follmer & Sperling, 2016 ), studies that measure EF directly instead show low to moderate correlations (e.g., Gestsdottir et al.,  2023 ; Meijs et al., 2021 ). This pattern seems to reflect an underlying influence of common method variance (Söhnchen, 2009 ) and, therefore, must be treated cautiously. It could also result from an acquiescence tendency in self-reports (mainly found in younger children, e.g., Mehrani & Peterson, 2018 ), which questions the validity of such scales. Moreover, the finding aligns with the results of the meta-analysis of Duckworth and Kern ( 2011 ), who found that different self-control questionnaires correlated strongly with different executive function tasks, which showed low convergent validity. In addition, EF mainly was not analyzed using multiple individual measures for each latent variable shifting, updating, and inhibition as proposed by Miyake et al. ( 2000 ), which may have resulted in them not being fully represented. Likewise, measures such as performance on the Tower Task may not fully capture EF (see Complex Executive Tasks in Miyake et al., 2000 ). Another explanation may be that these low correlations result from direct and self-report measures capturing aspects of the constructs that show less overlapping. This seems consistent with the many different approaches to EF mentioned earlier. Notably absent from this review is work reporting correlations between EF self-report measures and SRL non-self-report measures, as well as both direct EF measures and direct SRL measures (e.g., microanalysis; Cleary & Callan, 2018 ). Therefore, permuting measuring instrument methods could help connect the dots, and studies using direct and indirect measures for both SRL and EF could help to detangle the influence of measurement methods and the actual conceptual overlap of both constructs.

In general, all studies used a broad range of differing measures, which complicated the comparison of results. Nevertheless, as there were primarily low to moderate correlations despite using different measurement methods, this seems to speak to the robustness of the relationship between these concepts and, at the same time, underlines the haziness that these constructs can have. This becomes more evident with the fact that in several studies, measures for SRL were constructed with a relatively simple subscale structure and showed low reliability (e.g., HWD in Cirino et al., 2017 ), were newly developed (Jacob et al., 2019b ), or were constructed by selecting behavioral questions from a list, seemingly without prior evaluation trials (Rutherford et al., 2018 ). Concerning EF, a wide range of measures were used within the studies, and this became most evident in the study of Cirino et al. ( 2019 ), who used 27 measures to assess EF. Grouping all the different measures under the same SRL or EF construct exacerbates this fuzziness and limits the validity of statements about SRL-EF relationships. Moreover, the empirical overlap between SRL and EF strongly depends on how the measurement methods define the concepts: One of the highest correlations was found between a self-report questionnaire for SRL (SSRLS) and the BRIEF-SR for EF (Effeney et al., 2013 ; |.15|<  r  <|.61|). In this example, it is evident that both questionnaires show comparable subscales (SSRLS: goal setting and planning, self-efficacy for goal achievement, using task strategies, self-motivation; self-monitoring and self-evaluation; BRIEF-SR: Inhibit, Shift, Emotional Control, Monitor, Working Memory, Plan/Organise, Organisation of Materials, Task Completion) although the SRL questionnaire focuses on academic goals and the EF questionnaires focuses on everyday life goals. Therefore, theoretical foundations of measurement methods must be considered when interpreting the results.

What Role Does Metacognition Play Within the Relationship of SRL and EF?

Studies investigating the mediating role of metacognition within the relationship of SRL and EF speak in favor of this hypothesis, although not many studies have yet examined such models. In the study of Follmer and Sperling ( 2016 ), the mediation effect was more pronounced in a model using direct EF measure scores (inhibition and shifting instead of indirect measure), where the effect of EF on SRL was transmitted fully by metacognition. Effeney et al. ( 2013 ) conclude that their findings lend “support to descriptions of SRL and EF that are couched in terms of metacognition … and give[s] rise to the notion that metacognition occupies the conceptual “middle ground” between EF and SRL” (pp. 787–788). Moreover, Effeney et al. ( 2013 ) see their results supporting the notion that EF shares the “conceptual core” outlined by Dinsmore et al. ( 2008 ), that is, the endeavors that individuals make to watch over their thoughts and actions and act accordingly to gain some degree of control over them. In line with this, Cirino et al. ( 2018 ) identified SRL and metacognition as components of EF. The model that fitted the data best was a bifactor model with a common EF factor and five specific factors for working memory span/manipulation and planning, working memory updating, generative fluency, SRL, and metacognition. Nevertheless, the generally high correlations between EF, SRL, and metacognition and the possible mediating effect of metacognition should also be seen in light of the influence of measurement methods (see above). It is further worth mentioning that the works of Garner ( 2009 ), Effeney et al. ( 2013 ), Follmer and Sperling ( 2016 ), and Follmer ( 2021 ) in a way build on each other, as they all refer to their respective predecessors. This might have led to adapting similar views, taking convergent approaches, using related measures, and obtaining similar results.

How are SRL and EF Related to Academic Achievement?

Concerning the integration of achievement, it can be stated that both SRL and EF are positively related to academic achievement. Said ( 2014 ) presents a three-factorial model of SRL (integrating EF) that can be used to differentiate between low-achieving and high-achieving students with high effect sizes. Concerning the predictive validity of SLR and EF for academic outcomes and achievement, the results pattern found in the included studies is unclear: While in the study of Gestsdottir et al. ( 2023 ), SRL was found to be correlated to academic outcomes with EF measures showing no significant correlations, EF seems to be a stronger predictor than SRL for reading outcomes (Cirino et al., 2019 ) and school readiness (Vitiello & Greenfield, 2017 ). Using mediation models, Rutherford et al. ( 2018 ) showed that SRL mediated the relationship between EF and achievement, with both EF and SRL having their direct pathway to achievement. Grüneisen et al. ( 2023 ) found the same pattern of mediation in a sample of preschoolers, while EF was not related to academic competence in this study. It could be argued that academic achievement is closely linked to SRL, as SRL is usually assessed using academic tasks or contexts (Kim et al., 2023 ), while EF is mainly assessed decontextualized using cognitive tasks (Chan et al., 2008 ). Nevertheless, previous research results rather speak in favor of EF being a stronger predictor for academic achievement than SLR (Dent & Koenka, 2016 ; Titz & Karbach, 2014 ). However, these studies did not include both SRL and EF and, therefore, could not directly compare the predictive value of both constructs. Future studies should aim to specifically compare correlations of SLR and EF to academic achievement and further examine the previously found mediating role of SRL for the relationship between EF and achievement.

What are the Results of Longitudinal or Interventional Studies on the Relationship Between SRL and EF?

Concerning longitudinal and intervention studies, there is not much research yet that can be used to draw a conclusion. Evidence from cross-lagged panel analysis confirms that EF longitudinally predicts future SRL to a moderate extent in children (Davis et al., 2021 ). However, a common factor model allows for the interpretation that EF and SRL measures could equally well reflect the same underlying construct (Davis et al., 2021 ). We only detected one training study, which showed that SRL training did not influence EF (Jacob et al., 2019a ). Unfortunately, the longitudinal study of Gestsdottir et al. (2022) did not report cross-lagged correlations of SRL and EF. Due to this small basis, we cannot draw valid conclusions regarding the longitudinal relationship between SRL and EF yet, albeit present results speak in favor of EF predicting SRL and not vice versa. Future research, therefore, should target longitudinal studies using cross-lagged panel designs. In doing so, mediation analysis could uncover whether metacognition (longitudinally) mediates the relationship between EF and SRL. Training studies investigating far transfer (Kassai et al., 2019 ) to examine if SRL training would influence EF and vice versa would be especially helpful in detangling possible causal relationships.

Limitations of the Systematic Review

With 19 works analyzed, this review accumulated a relatively small set of results, limiting the validity of results that have not been sufficiently replicated. This may be because there is little literature on the subject, but it could also result from the systematic search process. The age of the literature analyzed supports this assertion, as the concepts of interest have been described in detail for well over 20 years in the case of SRL and decades longer in the case of EF, but the bulk of the literature analyzed is from the last 5 years. One reason for this is that in older articles, links between SRL and EF have been discussed on a componential level without mentioning both superordinate constructs (e.g., Bjorklund & Kipp, 1996 ; Pintrich & Zusho, 2002 ). Another reason is using alternative names for SRL or related constructs like self-regulation in academic contexts, approaches to learning, or learning-related skills. In these cases, the search process did not include inclusion in the literature pool, which may have resulted in a significant number of results on this topic being omitted.

Another limiting factor of this work is that in synthesizing the studies to attain some conclusions, results from directly and indirectly measured EF and self-reported and teacher-reported SRL were combined. As discussed above, this could have led to inaccurate conclusions. With more data available, it could become more accessible to determine which measure results can be subsumed and which must be considered separately. Although concerns were raised above about the quality of some measuring instruments, it was not within the scope of this work to verify how well SRL and EF were operationalized in each study. Examining correlating subscales of SRL and EF measures at a more profound (e.g., item) level could help decide which measure results can be compared and synthesized and would increase the precision of conclusions. Besides this measurement-related criticism, several studies had quite specific samples in that they oversampled for struggling readers (Cirino et al., 2017 , 2018 ), examined only male participants from a boys’ private school (Effeney et al., 2013 ), or had participants from predominantly low socioeconomic background (Rutherford et al., 2018 ; Vitiello & Greenfield, 2017 ). It can be assumed that not all results of these studies apply to an average population.

Implications for Theory

As outlined in the theoretical background section, SRL and EF both describe goal-related behavior (Miyake et al., 2000 ; Pintrich et al., 2000 ), including metacognitive monitoring and regulating behavioral aspects (Roebers, 2017 ). Despite this theoretical overlap, SRL and EF have been investigated somewhat unconnectedly, as SRL is a construct of educational psychology. At the same time, EF stems from cognitive and developmental psychology. Building upon the results of the present review, it can be stated that both constructs are related, but the size of correlations found was lower than expected for concepts that show this amount of theoretical overlap. One reason for that probably is the differing contexts when measuring SRL and EF: while SRL is always measured contextualized, referring to learning tasks, EF primarily are measured decontextualized using laboratory tasks. When EF is measured using questionnaires, some contextual factors come into play, but these differ from SRL as they are more related to everyday life. Another possible explanation that deserves further examination comes from the study of Meijs et al. ( 2021 ): The authors partially found negative relations between EF tasks and SRL components (which were also found in the studies of Cirino et al., 2017 , and Gestsdottir et al. 2023 ) and explain this by hypothesizing that students who can shift quickly and show high processing speed need less time for academic thinking and the execution of simple cognitive strategies (and therefore SRL). This would suggest an inverted U-shaped relationship, i.e., that students with relatively high EF show low SRL competencies (as they do not need them or do not frequently use them). Students with relatively low EF competencies should also show low SRL competencies as they do not have the essential regulatory capacities for using SLR strategies. Future research could investigate if a high relationship between SRL and EF is only found for students with average EF competencies (and not for low and high EF competencies).

Referring to the models of SRL presented in the theoretical background, it can be assumed that the authors’ concept definitions are reflected to some degree in the measures used: Fourteen studies refer to either Pintrich ( 2000 ) or Zimmerman ( 2000 ) when defining or describing SRL. Unfortunately, no study has investigated the phases of SRL, albeit using Zimmerman’s cyclical model ( 2000 ). This would be especially interesting as it seems possible that some EF components show higher overlaps to some phase-specific SRL strategies (e.g., inhibition should be mostly relevant for the performance phase of learning when learning needs to be shielded from distractors). Concerning Boekaerts’ ( 1999 ) SRL definitions or models, only two studies mentioned the three components in their theoretical introduction. Examining the components would be particularly helpful to detangle SRL and EF as it may be the case that some SRL components show higher overlap to some EF components (e.g., the metacognitive component of SRL should be highly related to working memory [needed for monitoring of goal progress] or complex EF like planning). We found that twelve studies referred to the EF model of Miyake et al. ( 2000 ) in some way, but few defined EF using this model. This is also obvious when looking at how EF was measured: Only a few studies measured all three components (inhibition, working memory, shifting), and if they did, these were always measured using cognitive tasks. If EF were measured using questionnaires, the components were not differentiated as the questionnaires assessed EF more broadly. In general, authors emphasized different aspects of SRL and EF, but definitions of SRL had more common ground than definitions of EF. This is in line with EF literature, as, for example, Miyake et al.’s ( 2000 ) model is not mentioned at all in some EF overview articles (e.g., Suchy, 2009 ) or only briefly touched upon in the Handbook of Executive Functioning (Goldstein & Naglieri, 2014 ), while in others (e.g., Diamond, 2013 ) it is treated as the standard of EF models. Future studies, therefore, should aim to use more comparable conceptualizations of SRL and EF and also investigate the relationship on a component level so that overlaps between the components of both constructs can be analyzed in more detail. At the moment, it is not possible to draw conclusions about the empirical relationships between the components of SRL and EF that are described in theoretical models as there are too less studies that investigate such component-based relationships.

We now try to compile our findings into a possible integrative framework uniting SRL and EF: Concerning the integration of EF and metacognition, Roebers ( 2017 ) has proposed to view EF and metacognition as being “expressions of the same underlying system of self-regulative processing” (p. 45) while this processing should be domain-general and acting on a second-order level. Monitoring processes are a core central and shared feature of EF and metacognition. Moreover, EF seems to be necessary for metacognitive processes and facilitates them (Roebers, 2017 ), while metacognitive monitoring is seen to be “slower, longer-lasting, more fine-tuned” (p. 46) and dependent on the first-order task. Therefore, the dependency on domain-specific knowledge and prior experience leads to increased metacognitive competencies, differentiating metacognitive processes from EF processes. Concerning the broadness of constructs, Roebers ( 2017 ) argues that the EF framework is broader than the metacognition framework. Kim et al. ( 2023 ) integrate the metacognitive and the SRL framework by stating that metacognition is a more cognitive construct and SRL is an educational construct. While metacognition is measured using experimental tasks, SRL is measured in authentic learning situations and, therefore, reflects an application of metacognitive competencies. What additionally distinguishes SRL from metacognition is the importance of motivational aspects (Boekaerts, 1999 ). Integrating both frameworks of Roebers ( 2017 ) and Kim et al. ( 2023 ) and using the results of our review as support, it can be stated that SRL and EF show conceptual overlap but are not the same. It seems plausible that EF processes promote SRL at a rudimentary cognitive and metacognitive level (Bol & Garner, 2011 ), that metacognitive competencies mediate the relationship between EF and SRL (Effeney et al., 2013 ), and that SRL is a domain-specific application of EF and metacognitive competences (Kim et al., 2023 ). This is underlined by studies showing that SRL is a mediator for the relationship between EF and achievement (Grüneisen et al., 2023 ). From a developmental perspective, EF seems to be a precursor ability for SRL: The findings of a review of Dörrenbächer-Ulrich et al. ( 2023 ) support the hypothesis that EF can be seen as a foundation for SRL and metacognition as the developmental peak of (simple) EF lies in early childhood, while metacognition and SRL show relevant developmental changes in later childhood and adolescence. In conclusion, the present review gives the first indications for a possible theoretical framework describing the relations between EF, metacognition, and SRL. Nevertheless, as only a few studies have tested this relationship empirically, it would be helpful to first invest in theoretical work on possible theory-grounded directional pathways between the constructs. Future research should then experimentally test such theories and models to gain insights into vindicable theory components or to alter and adapt the models based on empirical results.

Implications for Future Research

Much criticism within this review revolves around measurement methods. One challenge future studies could tackle is a differentiated approach to SRL and EF by combining self-report and non-self-report measures for each construct to capture both more comprehensively. For EF, a combination of more complex EF tasks like the Tower Task, multiple basic tasks for shifting, updating, and inhibition like the plus-minus task, and self-report measures like the EFI could be used. Likewise, SRL could be captured by a combination of self-report measures like the MSLQ, teacher reports, and self-assessment through contextual self-regulation measures. The latter, in particular, was not well represented in this review and could be achieved through the use of think-aloud protocols (Greene et al., 2011 ), microanalysis (Cleary & Callan, 2018 ), or structured personal diaries (Schmitz et al., 2011 ). A greater variety of non-self-report SRL measures in studies on the SRL-EF relationship may provide further evidence as to why direct EF measures have lower correlations with the SRL measures used in the studies analyzed here. Conducting such multimethod studies for different age groups could be very enlightening concerning age influences concerning the SRL-EF relationship.

As mentioned earlier, many measures seem to confirm some sort of relationship between SRL and EF, but their many differing subscales make it challenging to summarize correlations from different studies into precise statements. Intuitively, there is a need for the standardization of measuring instruments to increase precision. Of course, there are good reasons for different instruments to adequately capture the concepts in participants of different ages. However, if one wants to be more precise about the relationships between concepts, one needs more precise methods to measure those concepts (Dinsmore et al., 2008 ), and a plethora of measurement tools that represent authors’ unique ways of looking at the concepts seems to run counter to this principle. Nevertheless, a follow-up study that could shed light on the results compiled here could narrow down the study area and systematically extract properties of correlating SRL and EF measure subscales by analyzing their operationalizations.

As the relationship between SRL and EF is not as high as expected based on their theoretical overlap, investigating influential third variables could be helpful. One such variable could be intelligence, as previous research has shown a moderate association between EF and intelligence (Lee et al. 2009 ), and the same holds for metacognition (van der Stel & Veenman, 2008 ). For the studies that used specific samples (e.g., Cirino et al., 2017 , 2018 ; Rutherford et al., 2018 ), it would be instructive to see if their results can be replicated in studies with samples representing a more average population in the respective age group. Further studies in fostering SRL and EF would be informative as the studies analyzed (Cirino et al., 2017 ; Jacob et al., 2019a ) did not report any appreciable effects. Because there is evidence that fostering EF (e.g., Blair & Diamond, 2008 ) and SRL (e.g., Theobald, 2021 ) is generally possible, work in this area should be able to contribute to the understanding of the SRL-EF relationship if they are linked as suggested in this review. These studies could help find overlapping areas of the constructs and confirm or refute the directional models proposed by Davis et al. ( 2021 ) and the mediating role of metacognition (Follmer & Sperling, 2016 ). Training studies investigating far transfer (Kassai et al., 2019 ) to examine if SRL training would influence EF and vice versa would be especially helpful in detangling possible causal relationships. In addition, understanding the SRL-EF relationship would benefit from previously underrepresented longitudinal study designs that can be used for SRL or EF training studies. In the context of longitudinal studies, comparing the predictive value of SLR and EF for academic achievement and examining the previously found mediating role of SRL for the relationship between EF and achievement would be very interesting.

Self-regulated learning (SRL) and executive functions (EF) are broad concepts that stem from different research areas and have been defined and modeled in various ways. In particular, it was noted that EF has a decades-long history in different research areas, which may explain the many different approaches to this construct (Suchy, 2009 ). This systematic review examined literature from several databases that included the terms self-regulated learning and executive function for relationships between both constructs. It was found that most relevant research papers report on a low to moderate correlational relationship between SRL and EF. Metacognition, as measured by self-report instruments, regularly shows high correlations with EF or SRL self-report measure subscales, and there is evidence that it mediates the relationship between EF and SRL. The notion that EF predicts SRL but not vice versa is supported. Criticisms focus on non-generalizable samples, measurement methods that may not adequately capture EF or SRL, and the ease with which the literature on EF and SRL is interpreted in seemingly contradictory ways. Promising future research on this topic should include theory building on the relationship between EF and SRL and testing these theories experimentally. Using more SRL non-self-report measures, a more comprehensive collection of EF and SRL data per sample, and replicating the studies, focusing on longitudinal studies of SRL or EF training, would be very enlightening.

Data Availability

Data is available upon request from the corresponding author.

References marked with an asterisk indicate studies included in the systematic review

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Laura Dörrenbächer-Ulrich and Marius Bregulla wrote the review text. Laura Dörrenbächer-Ulrich had the idea for the review’s concept. Marius Bregulla conducted a systematic literature search and review of the studies. Both authors were involved in publication planning, reading drafts, suggestions for changes, and feedback on the final publication draft. All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

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Dörrenbächer-Ulrich, L., Bregulla, M. The Relationship Between Self-Regulated Learning and Executive Functions—a Systematic Review. Educ Psychol Rev 36 , 95 (2024). https://doi.org/10.1007/s10648-024-09932-8

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