difference between systematic and narrative literature review

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.

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Literature Review vs Systematic Review

• Literature Review vs. Systematic Review
• Primary vs. Secondary Sources
• Databases and Articles
• Specific Journal or Article

Subject Guide

Definitions

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

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Systematic Review, Scoping Review, Narrative Review – What’s the Difference?

Literature review articles use database searches to identify, collate, and analyze available evidence on a topic. Systematic reviews, scoping reviews, and narrative reviews are different evidence-collection and synthesis approaches.

But which type of review is (and isn’t) right for your research question? And how reliable are the findings of different review types?

There are distinctive features, aims, and scope between systematic reviews, scoping reviews, and narrative reviews . Let’s look at each and then pair them up to know which one you’ll need, whether you need ideas and references or you’re looking to write your own review.

• What you’ll learn in this post
• The difference (and similarity) between a systematic review, scoping review, and narrative review.
• The features and value of each of these types of review.
• Side-by-side feature comparison charts of each review type.
• Where to educate yourself on reviews, and how to get expert guidance from published researchers.

What is a systematic review?

Definition and history, key functions and features, what is a scoping review, what is a narrative review, main differences between a systematic review and a scoping review, main differences between a systematic review and a narrative review, main differences between a scoping review and a narrative review.

We don’t have a universal or standard definition of systematic reviews . A systematic review usually is a critical assessment of all the literature addressing a well-defined question. It aims to give the best possible answer based on available evidence.

Systematic reviews follow structured and predefined methods to identify, appraise, and synthesize the relevant literature. They use specific inclusion and exclusion criteria based on strict protocols, such as the PRISMA statement or Cochrane Protocol .

A meta-analysis is a systematic review that, in addition to a narrative summary, combines all the studies’ results into a single statistical analysis. The PRISMA 2020 Checklist offers guidance on how to conduct a meta-analysis.

Systematic reviews ensure that the results are reliable and meaningful to end-users, so they’re widely considered the strongest source for evidence-based healthcare .

Systematic reviews in healthcare began to appear in the 1970s and 1980s . Groups promoting evidence-based healthcare, like Cochrane and the Joanna Briggs Institute (JBI), emerged in the 1990s.

Systematic reviews have been widely used since then. They are necessary for clinicians to keep up to date with their field. They are also often used to inform the development of clinical guidelines and practice .

A systematic review aims to:

• Uncover the international evidence on a particular topic
• Confirm current practice; address uncertainty or variation in practice; identify new practices
• Find and inform areas for future research
• Locate and investigate mixed or conflicting results
• Produce statements to guide decision-making

Traditionally, researchers mainly carried out systematic reviews to assess the effectiveness of health interventions. In this respect, PROSPERO serves as an international database of registered systematic reviews in health and social care sciences. Or in other fields where there is a health-related outcome.

A 2020 systematic review appraising the most effective interventions for depression in heart failure patients is a good example of this approach.They explored six common interventions, medical and non-medical. It found that collaborative care and psychotherapy were the most effective treatments.

But systematic reviews have gone beyond assessing a treatment’s feasibility, appropriateness, meaningfulness, or effectiveness. They’re widely used to measure the cost-effectiveness or impact of socioeconomic interventions.

This review gives an economic appraisal of the clinical outcomes and economic effectiveness of different economic evaluations used for pharmacy services studies in health systems. It found these evaluations are increasingly used to understand which healthcare services provide value for money amid limited healthcare resources.

Systematic reviews are essential for robustly addressing specific questions. But sometimes they might not be able to meet your specific aims or research project requirements. Or you might need a methodologically rigorous and structured preliminary scoping activity to inform how future systematic reviews are done.

That’s where scoping reviews come into play. They’re sometimes called scoping exercises/scoping studies . Scoping reviews rapidly map the size, characteristics, or scope of existing literature in a field of interest. They can help you locate research gaps and needs.

Scoping reviews are “younger” than systematic reviews. They emerged in the early 2000s . There used to be some confusion around their definition and the steps involved in the scoping review process. But, in 2015, a methodological working group of the JBI produced formal guidance for conducting scoping reviews. Likewise, the PRISMA extension for scoping reviews was published in 2018.

Researchers usually carry out a scoping review to:

• Identify the types of evidence in a given field. For example, a scoping review by Challen et al. sought to find the types of available evidence regarding the source and quality of publications and grey literature around emergency planning.
• Clarify crucial concepts or terms in the literature.
• Examine how research is conducted on a specific topic or field. A scoping review of that kind explored the scope of the literature around interventions aimed to improve health care quality in populations with osteoarthritis.
• Identify key characteristics or factors related to a concept.
• As a precursor to a systematic review (examining emerging evidence to confirm the relevance of inclusion criteria and potential questions).
• Identify and analyze knowledge gaps.

A narrative review is a thorough and critical overview of previously published research on the author’s specific topic of interest. It’s also referred to as a traditional review or a literature review.

Narrative reviews are helpful in the following ways:

• You can read them as a general and accurate guide to what is already known about a given topic.
• They are a key part of the research process. They help you establish a theoretical and methodological framework or context for your research.
• By doing a literature review, you can locate existing patterns and trends. This helps you find the gaps in your field and formulate a meaningful research question.

So, like the systematic and scoping reviews, a narrative review appraises, critiques, and summarizes a topic’s available research.

For example, this narrative review sums up the evidence on exercise interventions in improving the health aspects of patients with preclinical Alzheimer’s disease.This narrative review is provided for the clinical development programs for non-oral, non-injectable formulations of dihydroergotamine (DHE) to treat migraine.

But, narrative reviews are far less systematic and rigorous. They’re evidence-based but not always considered massively helpful in terms of the scientific evidence they bring . They’re much more prone to selection bias.

For example, a review paper comparing seven narrative reviews with two systematic reviews found that narrative reviews of the same studies reached different conclusions. So, when you read or assess a narrative review, watch out for certain biases in data search methods.

Systematic reviews and scoping reviews similarly use rigorous and transparent methods to comprehensively identify and analyze all the relevant literature. Their differences in aims and scope are subtle but clear.

Systematic reviews differ greatly from narrative reviews.

As seen, systematic reviews answer a narrow question through detailed and comprehensive literature searches. But narrative reviews are more descriptive. They provide authors’ subjective perspectives on a focused but broader topic.

Scoping reviews and narrative reviews have similar differences to systematic reviews and narrative reviews. Their key difference is that narrative reviews do not follow a standardized methodology.

Any of the above reviews is a big undertaking, and very rewarding. When you need some help in any stage of the process, we have a big range of services. We’ll connect you with publication experts to guide you through the process. Explore Edanz research services here .

Also be sure to grab the free systematic review “12P” checklist below!

The 12P Method for Systematic Reviews

We’ve squeezed all the steps and stages of a typical systematic review onto one page.

You can print it out A4-sized and use it as a handy checklist, or A3-sized for your laboratory wall. You can even share it with your co-authors.

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Why Systematic Review rather than Narrative Review?

1 Department of Psychiatry, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea.

2 Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA.

Sir: Recently review articles including systematic and narrative reviews have been significantly increasing in most psychiatric journals in the world alongside "Psychiatry Investigation (PI)". Since the launch of the "PI" at March 2004, there have been a number of review articles; indeed 54 papers were published as format of regular review papers or special articles in the "PI" from 2004 to 2014. However, of the 54 papers, only one review paper partially met the contemporary criteria of systematic review, otherwise were written as a format of narrative review for diverse topics such as epidemiological findings, concept and hypothesis of certain psychiatric disease, current understandings on certain disease, psychopharmacology, and treatment guidelines. This is unsatisfactory when reflecting the fact that systematic reviews have been rapidly and increasingly replacing traditional narrative (explicit) reviews as a standard platform of providing and updating currently available research findings as confident evidence. Most journals have started to change their policy in acceptance of review papers, they have been giving a priority to systematic review only as a regular review article and excluding narrative reviews, to provide the best evidence for all basic and clinical questions and further hypotheses. Of course, there should be Pros and Cons between systematic and narrative reviews; for instance, the major advantage of systematic reviews is that they are based on the findings of comprehensive and systematic literature searches in all available resources, with minimization of selection bias avoiding subjective selection bias, while narrative reviews, if they can be written experts in certain research area, can provide experts' intuitive, experiential and explicit perspectives in focused topics. 1

The absence of objective and systematic selection criteria in review method substantially results in a number of methodological shortcomings leading to clear bias of the author's interpretation and conclusions. Such differences are quite clear when referring to the review paper of Drs. Cipriani and Geddess, 2 where 7 narrative and 2 systematic reviews were compared and found that narrative reviews including same studies reached different conclusions against each other, indicating the difficulties of appraising and using narrative reviews to have conclusion on specific topic. Hence, narrative reviews may be evidence-based, but they are not truly useful as scientific evidence.

Even in reported as systematic review, it is also frequent that those papers are not true systematic review or they have certain bias in data search method and conclusions. For instance, due to lack of satisfactory pharmacotherapy for post-traumatic stress disorder (PTSD) and its frequent comorbid psychotic symptoms, a possible role of atypical antipsychotics (AAs) for PTSD has been consistently proposed. 3 In fact various AAs have demonstrated positive antidepressant and ant-anxiety effects in a number of small-scale, open-label studies (OLSs) or randomised, controlled clinical trials (RCTs). 4 In this context, a recent systematic review (4 olanzapine, 7 risperidone and 1 ziprasidone trials) by Wang et al. 5 has also suggested the positive prospect on the role of AAs for the treatment of PTSD; however, the review has a number of faulty and wrong selection of clinical trials data and interpretation of studies included in their review. The authors neglected wide range of clinical information such as patient characteristics (particularly, initial severity of disease), comorbidity issues, trial duration issues, trial design characteristics, primary endpoint difference, study sponsoring; that is, heterogeneity of clinical trials would substantially influence the quality and clinical implications of the study results. The basic problem of non-systematic search of data is that beneath the shining surface, it seems that the authors utilizing it often misunderstand the true value, underpinning meanings and correct nature of the data, or their true limitations and strengths, and they often go too far or short with the interpretation. 6 Indeed, the main conclusion of a narrative review may often be based on evidence, but such reviews themselves are not rigorous evidence since such reviews are too selective and thus little good quality information could be included. 2 In addition, I found one olanzapine trial was OLS but they included the study in the result (this is a mixture of data yielding a huge heterogeneity). 7 This clearly indicates they were not consistent in collection of the study for their review. Olanzapine has a lot of OLSs beyond the study, likewise other AAs also have a plenty of OLSs. Regarding an inclusion of OLSs for systematic reviews, an interesting metaanalyses are available on the role of olanzapine for adolescent bipolar disorder 8 and aripiprazole augmentation therapy 9 for depression. According to Pae et al. 9 the treatment effects were not significantly different between OLSs and RCTs in efficacy of aripiprazole augmentation for treating depression; the pooled effect size was statistically significant in both study design and also in a meta-analysis regression, study design was not a significant predictor of mean change in the primary endpoint, clearly indicating that OLSs are useful predictors of the potential safety and efficacy of a given compound. This finding was also supported by another meta-analysis. 8 Hence, the value of OLSs should be carefully re-evaluated for practical information source, development of new drugs or acquisition for new indications, and should not be neglected for data research, especially for narrative reviews. Furthermore, Dr. Wang et al. 5 did not include one important RCT; quetiapine has a RCT for PTSD, 10 which was presented in the thematic meeting of the CINP 2009. A 12-week RCT was conducted for 80 PTSD patients. Finally, Wang et al. 5 surprisingly did not present any effect size (ES) for studies, although such calculations are conventionally included in the review papers. Another critical example is Hickie and Rogers's review, 11 according to their article, agomelatine was efficacious antidepressant; however, subsequent researchers who avoided selection bias have clearly demonstrated its weak efficacy as an antidepressant. 12 Therefore, reflecting two review papers, 5 , 11 we can realize that inappropriate aggregation of studies may definitely bias conclusion. Hence, entire published and unpublished dataset should be considered in systematic review, especially, when clinical data is not sufficient and the medication has no officially approved indication by the regulatory agency.

To summarize, systematic review should include followings respecting recommendation from currently available systematic review guidelines (e.g., The Cochrane Library www.cochrane.org ); clear basic and clinical hypothesis, predefined protocol, designation of search resources, through data search (regardless of publication), transparent selection criteria, qualification of studies selected, synthesis of study data and information, relevant summary and conclusion. Table 1 compares systematic and narrative reviews ( Table 1 ). Since the evidence-based medicine is the current trend and also mandatory for establishment of heath policy, the PI should also turn to encourage submission of systematic reviews rather than narrative reviews.

Acknowledgments

This work was supported by a grant of the Korean Health Technology R&D Project, Ministry of Health & Welfare, Republic of Korea (HI12C0003).

Narrative vs systematic vs scoping review: What’s the difference?

I often get asked what the difference between a narrative review and a systematic review is, or what the difference between a narrative review and a scoping review is. This is also something I wondered about when I was new to the world of research.

Let’s first look at what a systematic review and scoping review are. A systematic review is done to identify research studies published on a certain topic, with the primary aim to recommend best practice on a certain topic and inform policy. This is very useful if there are discrepancies in the way in which a certain practice is performed, but also to recommend new approaches to practice. A scoping review is done to determine the research out there on a certain topic. Scoping reviews do not involve a critical appraisal process like systematic reviews do, but they are also conducted using a rigorous and systematic process. This video elaborates on the difference between systematic and scoping reviews.

A narrative review, also referred to as a traditional review, summarises and presents the available research on a topic. You will commonly see a traditional or narrative review as part of a thesis or dissertation. A narrative review is more biased than systematic and scoping reviews as it relies on the author’s background knowledge on a topic.

Zachary Munn, and his colleagues, all of them systematic review experts, alludes to the difference in a very useful article published in 2018 . Munn et al list the differences between scoping reviews and narrative reviews, but the same goes for the difference between systematic reviews and narrative reviews. Scoping reviews:

1. “Are informed by an a priori protocol;

2. Are systematic and often include exhaustive searching for information;

3. Aim to be transparent and reproducible;

4. Include steps to reduce error and increase reliability (such as the inclusion of multiple reviewers);

5. Ensure data is extracted and presented in a structured way”.

In Table 1 of this article , the difference between the three types of review becomes clear.

How do you know if an article is a narrative review or a systematic review or scoping review? These three look different to one another. In the video below, we look at an example of each.

Now that you know the difference between a narrative review, a scoping and a systematic review, you are ready to decide if a narrative review needs to be done or should it be a systematic or scoping review. If you know that you need to do a systematic review or scoping review, but you are not sure what the difference is, or if you can’t decide what type of systematic review you want to do, or even if you want to figure out the difference between a systematic review and meta-analysis, have a look at the Systematic Reviews playlist on the Research Masterminds YouTube channel to get your questions answered. And while you are at it, subscribe to the Research Masterminds YouTube channel .

One last thing, if you are a (post)graduate student working on a masters or doctoral research project, and you are passionate about life, adamant about completing your studies successfully and ready to get a head-start on your academic career, this opportunity is for you! An awesome membership site - a safe haven offering you coaching, community and content to boost your research experience and productivity. Check it out! https://researchmasterminds.com/academy

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Systematic, Scoping and Narrative Reviews

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• Samiran Nundy 4 ,
• Atul Kakar 5 &
• Zulfiqar A. Bhutta 6  

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A Systematic Review is an attempt to distill the essence of a large number of studies in medicine by first asking a research question and then first identifying and later synthesizing carefully chosen studies of a high quality which might provide the answers. A more precise definition is ‘a summary of the medical literature that uses explicit and reproducible methods to systematically search, critically appraise and synthesise the results of multiple primary studies related to each other by using strategies to reduce bias and random errors’ [1].

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Systematic Reviewing

Critical Appraisal of Systematic Reviews and Meta-Analyses

Systematic Reviews and Meta-Analysis: A Guide for Beginners

Joseph L. Mathew

1 What Is a Systematic Review?

A Systematic Review is an attempt to distill the essence of a large number of studies in medicine by first asking a research question and then first identifying and later synthesizing carefully chosen studies of a high quality which might provide the answers. A more precise definition is ‘a summary of the medical literature that uses explicit and reproducible methods to systematically search, critically appraise and synthesise the results of multiple primary studies related to each other by using strategies to reduce bias and random errors’ [ 1 ].

In 1979, Archibald Cochrane, a Scottish doctor, proposed: ‘It is surely a great criticism of our profession that we have not organised a critical summary, by specialty or subspecialty, adapted periodically, of all relevant randomised controlled trials’. Cochrane was one of the founding fathers of evidence-based medicine (Fig. 29.1 ). He highlighted and advocated the importance of critically summarizing the findings of research studies and designated the systematic review as a method of providing such a summary. This ultimately led to the development of the Cochrane Collaboration in 1993 [ 2 ]. The findings of systematic reviews are now widely used for clinical decision-making and have become integral towards the development of sound clinical practice guidelines and recommendations. In fact, they now occupy the summit of the pyramid for the quality of evidence.

Shows the quality of evidence from various types of research papers

2 How Is a Systematic Review Done?

It is done using the following steps:

Step 1 —Defining the research question clearly and formulating criteria for which reports to include.

Searching for and selecting these studies and collecting their data. This will involve a review of all the available databases and citation indexes like the Web of Science, Embase, PubMed and others using different search technologies or even artificial intelligence-based tools. Each study should conform to the PRISMA (Preferred Reporting Items for Systemic Reviews and Meta-Analyses) guidelines or the standards of the Cochrane Collaboration [ 3 ].

The PRISMA guidelines (Fig. 29.2 ) are steps that depict the flow of information through the different phases of a systematic review. It maps out the number of records identified, included and excluded, and the reasons for exclusions.

PRISMA guidelines

Step 2 —Assess their risk of bias. The review should use an objective and transparent approach for collection and synthesizing the data to minimize bias.

Step 3 —Analyse the data and undertake a meta-analysis. This may involve using complex statistical methods and the more data that is analyzed the more confident we can be of the result.

Step 4 —Write conclusions. Present the results and summarize the findings. Interpret the results, draw conclusions and suggest a message.

3 Why Is a Systematic Review Useful?

Many clinical decisions are guided by published studies but, unfortunately, there are now too many to choose from for a busy clinician. These studies often vary in their design, methodological quality, population involved and the intervention or condition considered. To take a rational clinical decision involves trying to reconcile the results of studies that provide different answers to the same question. Because it is often impractical for readers to track down and read all of the primary studies, systematic review articles are an important source of summarized evidence on a particular topic [ 4 , 5 ].

4 What Are Its Weaknesses?

Most systematic reviews focus on a single question when more than one may be relevant in a particular situation, e.g., the best treatment for variceal bleeding in a developed country may be endoscopic sclerotherapy but not in a person in a developing country who is poor, has good liver function and does not have access to sophisticated medical facilities. In him or her a portosystemic shunt operation and a one-time procedure may be the more appropriate.

Then search strategies are often not provided in detail, the selection of studies may be biased, and only the positive results may reach publication. It also takes about 6 months to complete a single systematic review [ 6 , 7 ].

5 What Is a Meta-Analysis? How Does It Differ from a Systematic Review?

A meta-analysis is a summary of data collected from multiple sources by collating it and helping to frame guidelines. While a systematic review includes the entire process of collecting, reviewing and presenting all available evidence, a meta-analysis only refers to the statistical technique of extracting and combining the data to produce a summary [ 7 , 8 ].

6 What Are Scoping and Narrative Reviews? How Do They Differ from a Systematic Review?

A Scoping review is a preliminary assessment of the potential size and scope of the available research literature. It aims to identify the nature and extent of research evidence (usually including ongoing research) and present an overview of a potentially large and diverse body of literature pertaining to a broad topic. In contrast, a systematic review attempts to collate empirical evidence from a relatively smaller number of studies pertaining to a focused research question.

A Narrative review is the type first-year college students often learn as a general approach. Its purpose is to identify a few studies that describe a problem of interest. Narrative reviews have no predetermined research question or specified search strategy, only a topic of interest. They are not systematic and follow no specified protocol. No standards or protocols guide the review. Although the reviewers will learn about the problem, they will not arrive at a comprehensive understanding of the state of the science related to the problem [ 9 , 10 ]. No strict rules are there for narrative review and can be done using the keywords.

7 Conclusions

A Systemic review gives a comprehensive and complete plan and search approach to study a topic of interest. This reduces the bias by recognizing, assessing and creating all relevant studies on a particular topic.

Systematic reviews can be ambiguous, not helpful, or even harmful when data are incorrectly handled.

A Meta-analysis involves using statistical methods to create the data from several studies into a single quantitative study.

Outcomes from a meta-analysis may help to estimate the effect of treatment or risk factors for disease, or other outcomes.

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Samiran Nundy

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Institute for Global Health and Development, The Aga Khan University, South Central Asia, East Africa and United Kingdom, Karachi, Pakistan

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Nundy, S., Kakar, A., Bhutta, Z.A. (2022). Systematic, Scoping and Narrative Reviews. In: How to Practice Academic Medicine and Publish from Developing Countries?. Springer, Singapore. https://doi.org/10.1007/978-981-16-5248-6_29

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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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Reproduced from Grant, M. J. and Booth, A. (2009), A typology of reviews: an analysis of 14 review types and associated methodologies. Health Information & Libraries Journal, 26: 91–108. doi:10.1111/j.1471-1842.2009.00848.x

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What Is a Systematic Review?

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

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

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

Getting Help with Reviews

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

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

Doing a Systematic Review

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

Adapted from

Types of reviews, systematic review.

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

Meta-Analysis

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

Scoping Review

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

Rapid Review

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

Narrative Review

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

Umbrella Review

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

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

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Traditional reviews vs. systematic reviews

Posted on 3rd February 2016 by Weyinmi Demeyin

Millions of articles are published yearly (1) , making it difficult for clinicians to keep abreast of the literature. Reviews of literature are necessary in order to provide clinicians with accurate, up to date information to ensure appropriate management of their patients. Reviews usually involve summaries and synthesis of primary research findings on a particular topic of interest and can be grouped into 2 main categories; the ‘traditional’ review and the ‘systematic’ review with major differences between them.

Traditional reviews provide a broad overview of a research topic with no clear methodological approach (2) . Information is collected and interpreted unsystematically with subjective summaries of findings. Authors aim to describe and discuss the literature from a contextual or theoretical point of view. Although the reviews may be conducted by topic experts, due to preconceived ideas or conclusions, they could be subject to bias.

Systematic reviews are overviews of the literature undertaken by identifying, critically appraising and synthesising results of primary research studies using an explicit, methodological approach(3). They aim to summarise the best available evidence on a particular research topic.

The main differences between traditional reviews and systematic reviews are summarised below in terms of the following characteristics: Authors, Study protocol, Research question, Search strategy, Sources of literature, Selection criteria, Critical appraisal, Synthesis, Conclusions, Reproducibility, and Update.

Traditional reviews

• Authors: One or more authors usually experts in the topic of interest
• Study protocol: No study protocol
• Research question: Broad to specific question, hypothesis not stated
• Search strategy: No detailed search strategy, search is probably conducted using keywords
• Sources of literature: Not usually stated and non-exhaustive, usually well-known articles. Prone to publication bias
• Selection criteria: No specific selection criteria, usually subjective. Prone to selection bias
• Critical appraisal: Variable evaluation of study quality or method
• Synthesis: Often qualitative synthesis of evidence
• Conclusions: Sometimes evidence based but can be influenced by author’s personal belief
• Reproducibility: Findings cannot be reproduced independently as conclusions may be subjective
• Update: Cannot be continuously updated

Systematic reviews

• Authors: Two or more authors are involved in good quality systematic reviews, may comprise experts in the different stages of the review
• Study protocol: Written study protocol which includes details of the methods to be used
• Research question: Specific question which may have all or some of PICO components (Population, Intervention, Comparator, and Outcome). Hypothesis is stated
• Search strategy: Detailed and comprehensive search strategy is developed
• Sources of literature: List of databases, websites and other sources of included studies are listed. Both published and unpublished literature are considered
• Selection criteria: Specific inclusion and exclusion criteria
• Critical appraisal: Rigorous appraisal of study quality
• Synthesis: Narrative, quantitative or qualitative synthesis
• Conclusions: Conclusions drawn are evidence based
• Reproducibility: Accurate documentation of method means results can be reproduced
• Update: Systematic reviews can be periodically updated to include new evidence

Decisions and health policies about patient care should be evidence based in order to provide the best treatment for patients. Systematic reviews provide a means of systematically identifying and synthesising the evidence, making it easier for policy makers and practitioners to assess such relevant information and hopefully improve patient outcomes.

• Fletcher RH, Fletcher SW. Evidence-Based Approach to the Medical Literature. Journal of General Internal Medicine. 1997; 12(Suppl 2):S5-S14. doi:10.1046/j.1525-1497.12.s2.1.x. Available from:  http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1497222/
• Rother ET. Systematic literature review X narrative review. Acta paul. enferm. [Internet]. 2007 June [cited 2015 Dec 25]; 20(2): v-vi. Available from: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-21002007000200001&lng=en. http://dx.doi.org/10.1590/S0103-21002007000200001
• Khan KS, Ter Riet G, Glanville J, Sowden AJ, Kleijnen J. Undertaking systematic reviews of research on effectiveness: CRD’s guidance for carrying out or commissioning reviews. NHS Centre for Reviews and Dissemination; 2001.

Weyinmi Demeyin

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No Comments on Traditional reviews vs. systematic reviews

THE INFORMATION IS VERY MUCH VALUABLE, A LOT IS INDEED EXPECTED IN ORDER TO MASTER SYSTEMATIC REVIEW

Thank you very much for the information here. My question is : Is it possible for me to do a systematic review which is not directed toward patients but just a specific population? To be specific can I do a systematic review on the mental health needs of students?

Hi Rosemary, I wonder whether it would be useful for you to look at Module 1 of the Cochrane Interactive Learning modules. This is a free module, open to everyone (you will just need to register for a Cochrane account if you don’t already have one). This guides you through conducting a systematic review, with a section specifically around defining your research question, which I feel will help you in understanding your question further. Head to this link for more details: https://training.cochrane.org/interactivelearning

I wonder if you have had a search on the Cochrane Library as yet, to see what Cochrane systematic reviews already exist? There is one review, titled “Psychological interventions to foster resilience in healthcare students” which may be of interest: https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD013684/full You can run searches on the library by the population and intervention you are interested in.

I hope these help you start in your investigations. Best wishes. Emma.

La revisión sistemática vale si hay solo un autor?

HI Alex, so sorry for the delay in replying to you. Yes, that is a very good point. I have copied a paragraph from the Cochrane Handbook, here, which does say that for a Cochrane Review, you should have more than one author.

“Cochrane Reviews should be undertaken by more than one person. In putting together a team, authors should consider the need for clinical and methodological expertise for the review, as well as the perspectives of stakeholders. Cochrane author teams are encouraged to seek and incorporate the views of users, including consumers, clinicians and those from varying regions and settings to develop protocols and reviews. Author teams for reviews relevant to particular settings (e.g. neglected tropical diseases) should involve contributors experienced in those settings”.

Thank you for the discussion point, much appreciated.

Hello, I’d like to ask you a question: what’s the difference between systematic review and systematized review? In addition, if the screening process of the review was made by only one author, is still a systematic or is a systematized review? Thanks

Hi. This article from Grant & Booth is a really good one to look at explaining different types of reviews: https://onlinelibrary.wiley.com/doi/10.1111/j.1471-1842.2009.00848.x It includes Systematic Reviews and Systematized Reviews. In answer to your second question, have a look at this Chapter from the Cochrane handbook. It covers the question about ‘Who should do a systematic review’. https://training.cochrane.org/handbook/current/chapter-01

A really relevant part of this chapter is this: “Systematic reviews should be undertaken by a team. Indeed, Cochrane will not publish a review that is proposed to be undertaken by a single person. Working as a team not only spreads the effort, but ensures that tasks such as the selection of studies for eligibility, data extraction and rating the certainty of the evidence will be performed by at least two people independently, minimizing the likelihood of errors.”

I hope this helps with the question. Best wishes. Emma.

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Difference Between Systematic Review and Narrative Reviews

• Watching now: Chapter 1: A Comparison of Systematic and Narrative Literature Reviews Start time: 00:00:00 End time: 00:02:54

Video Type: Tutorial

(2020). Difference between systematic review and narrative reviews [Video]. Sage Research Methods. https:// doi. org/10.4135/9781529627206

"Difference Between Systematic Review and Narrative Reviews." In Sage Video . : Muhammad Shakil Ahmad, 2020. Video, 00:02:54. https:// doi. org/10.4135/9781529627206.

, 2020. Difference Between Systematic Review and Narrative Reviews , Sage Video. [Streaming Video] London: Sage Publications Ltd. Available at: <https:// doi. org/10.4135/9781529627206 & gt; [Accessed 1 Apr 2024].

Difference Between Systematic Review and Narrative Reviews . Online video clip. SAGE Video. London: SAGE Publications, Ltd., 17 Nov 2022. doi: https:// doi. org/10.4135/9781529627206. 1 Apr 2024.

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A comparison of systematic and narrative literature reviews highlighting their distinct characteristics and goals.

Chapter 1: A Comparison of Systematic and Narrative Literature Reviews

• Start time: 00:00:00
• End time: 00:02:54
• Product: Sage Research Methods Video: Qualitative and Mixed Methods
• Type of Content: Tutorial
• Title: Difference Between Systematic Review and Narrative Reviews
• Publisher: Muhammad Shakil Ahmad
• Series: Systematic Literature Review : A Practical Guide
• Publication year: 2020
• Online pub date: November 17, 2022
• Discipline: Sociology , History , Economics , Criminology and Criminal Justice , Marketing , Science , Technology , Education , Computer Science , Business and Management , Mathematics , Medicine , Public Health , Counseling and Psychotherapy , Psychology , Health , Anthropology , Social Policy and Public Policy , Dentistry , Nursing , Political Science and International Relations , Geography , Social Work , Communication and Media Studies , Engineering
• Methods: Mixed methods , Literature review , Systematic review
• Duration: 00:02:54
• DOI: https:// doi. org/10.4135/9781529627206
• Keywords: literature reviews , narrative research , qualitative research methods , Systematic reviews Show all Show less
• Online ISBN: 9781529627206 Copyright: Copyright 2020, Muhammad Shakil Ahmad More information Less information

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Systematic and scoping reviews: A comparison and overview

Affiliations.

• 1 Division of Vascular Surgery, Western University, London, Ontario, Canada.
• 2 Division of Vascular Surgery, Western University, London, Ontario, Canada. Electronic address: [email protected].
• PMID: 36414363
• DOI: 10.1053/j.semvascsurg.2022.09.001

In this article, we compare and contrast methods of reviewing, summarizing, and synthesizing the literature, including systematic reviews, scoping reviews, and narrative reviews. Review articles are essential to help investigators wade through the plethora of exponentially growing medical literature. In the era of evidence-based medicine, a systematic approach is required. A systematic review is a formalized method to address a specific clinical question by analyzing the breadth of published literature while minimizing bias. Systematic reviews are designed to answer narrow clinical questions in the PICO (population, intervention, comparison, and outcome) format. Alternatively, scoping reviews use a similar systematic approach to a literature search in order to determine the breadth and depth of knowledge on a topic; to clarify definitions, concepts, and themes; or sometimes as a precursor to a systematic review or hypothesis generator to guide future research. However, scoping reviews are less constrained by a priori decisions about which interventions, controls, and outcomes may be of interest. Traditional narrative reviews still have a role in informing practice and guiding research, particularly when there is a paucity of high-quality evidence on a topic.

Copyright © 2022. Published by Elsevier Inc.

Publication types

• Systematic Review
• Evidence-Based Medicine*
• Research Design*

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Systematic Review Service

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• Step 8: Write and Publish the Review
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Review Type Definitions

There are many different types of reviews. Here are some of the most common ones the MSK Library assists with:

Narrative reviews , or literature reviews, offer flexibility in regards to "how the research or clinical question is formulated (or the scope of the review established), how literature is evaluated and how the findings are organised and presented." ( Source )

Scoping reviews  "are an ideal tool to determine the scope or coverage of a body of literature on a given topic and give clear indication of the volume of literature and studies available as well as an overview (broad or detailed) of its focus." They require most of the same steps as systematic reviews. ( Source )

Systematic reviews  "[attempt] to collate all empirical evidence that fits pre-specified eligibility criteria in order to answer a specific research question. [They use] explicit, systematic methods that are selected with a view to minimizing bias, thus providing more reliable findings from which conclusions can be drawn and decisions made" ( Source )

Meta-analyses  follow "a research process used to systematically synthesise or merge the findings of single, independent studies, using statistical methods to calculate an overall or 'absolute' effect." They adhere to systematic review methods, with an additional statistical analysis. ( Source )

Learn more about these and other kinds of reviews.

Review Type Comparison Table

Different review types have different requirements, scopes, and standards:

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SYSTEMATIC REVIEW article

The relationship between psychopathy and autism: a systematic review and narrative synthesis.

• 1 School of Health and Social Care, University of Essex, Colchester, United Kingdom
• 2 Centre for Research in Intellectual and Developmental Disabilities (CIDD), University of Warwick, Coventry, United Kingdom
• 3 Coventry and Warwickshire Partnership National Health Service (NHS) Trust, Coventry, United Kingdom
• 4 Worcestershire Health and Care National Health Service (NHS) Trust, Worcester, United Kingdom

Background and methods: The aim of this systematic review was to synthesise research examining the relationship between autism and psychopathy to: (a) better understand the relationship between these two constructs, and (b) describe the clinical manifestation of the two when they co-occur. A systematic search of the literature returned 36 studies.

Results: Across all ages, autistic individuals and those with elevated autistic traits but no autistic diagnoses appeared to have increased callous and unemotional traits or psychopathy relative to the general population. Several studies evidenced that although both constructs are associated with empathetic dysfunction, the underlying mechanisms differ. In adults, psychopathy/psychopathic traits were associated with diminished affective empathy and intact cognitive empathy, whilst the opposite was seen autistic adults and those with elevated autistic traits. In children, those with autistic traits or a diagnosis of autism had diminished cognitive empathy, but not affective empathy, while the relationship between callous and unemotional traits/psychopathy and empathy amongst children was less clear. The co-occurrence of autism and psychopathy was seen to lead to additional empathic and cognitive impairment, but findings were mixed making it challenging to clearly describe the clinical manifestation.

Conclusion: There remains a paucity of research investigating the interaction between autism and psychopathy and included studies were characterised by multiple measurement difficulties. Attention should be directed toward developing better methods for identifying psychopathic traits in autistic individuals to advance our understanding of the relationship between autism and psychopathy to allow for the development of appropriate care pathways for this population.

Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=413672 , identifier CRD42023413672.

1 Introduction

1.1 autism, psychopathy and criminality.

Autism is a neurodevelopmental disorder characterised by social and communication deficits and restricted or repetitive patterns of behaviour ( 1 ), with prevalence currently estimated as one in 100 ( 2 ). Aggression is not a core symptom of autism but rates of aggression in autistic children and adolescents range from 25% ( 3 ) to 53% ( 4 ). This aspect of autism has been growing in interest with research increasingly focusing on the relationship between autism and psychopathy.

Psychopathy is characterised by shallow emotional response, a diminished capacity for empathy or remorse, callousness, and poor behavioural control ( 5 , 6 ). Prevalence in the general population is estimated at 4.5%, with a higher prevalence among offenders ( 7 ). It has long been associated with criminal and violent behaviour and is a key predictor of recidivism ( 8 ). Psychopathy can be categorised into primary and secondary psychopathy; primary psychopathy results from largely genetic and biological influences, and secondary psychopathy is related to adverse environmental factors (such as developmental trauma/maltreatment) ( 9 ). Primary psychopathy is associated with increased emotionally stability, fearlessness, and being more self-assured than secondary psychopathy, which is often associated with greater psychopathology. As children and young people are still developing, they are not considered capable of presenting with psychopathy; instead, a precursor is observed, referred to as callous and unemotional traits [CUTs; ( 10 )].

Whilst the link between psychopathy and criminality is well evidenced ( 11 ), the relationship between autism and criminality is less clear. Collins et al. ( 12 ) reported that criminality rates amongst those with autism ranged from 0.2% ( 13 ) to 62.8% ( 14 ) within their systematic review, indicating an overrepresentation of autism amongst offenders. Despite this, the review suggested that there is little evidence that autistic individuals have an increased risk of committing crimes, highlighting methodological limitations which impacted the reliability of conclusions. It was hypothesised that social communication difficulties may make autistic individuals more likely to be viewed as risky, encounter the criminal justice system, and receive custodial sentences.

1.2 The role of empathy

Autism and psychopathy are both characterised by empathic dysfunction which plays a role in their behavioural phenotypes, and whilst they may appear to share surface similarities, the underlying difficulties may differ ( 15 ). Empathy involves understanding and sharing others’ emotions, thoughts or feelings and can be divided into cognitive (understanding thoughts and feelings) and affective (sharing emotional experiences) empathy ( 15 ). It has been proposed that autistic people struggle with cognitive empathy but not affective empathy, whereas the opposite is found within psychopathy ( 16 – 18 ).

Cognitive empathy requires theory of mind (ToM)/perspective taking skills, and together with affective empathy both are required when making moral decisions ( 19 ). Autistic people who have difficulties with cognitive empathy may inadvertently cause harm to others due to difficulty interpreting the behaviour of others ( 20 ), while individuals with psychopathy are more likely to engage in criminality and have difficulties with affective empathy and emotion recognition, but present with intact ToM skills ( 15 , 21 ). Those with psychopathy are thought to have difficulties with recognising aversive emotions in others (e.g., fear and sadness) resulting from deficits in amygdala and orbital/ventrolateral frontal cortex function ( 22 ) and these difficulties interfere with learning and subsequent avoidance. For example, fearfulness is aversive, and if attenuated, an individual may behave in self-gratifying manner without concern about the consequence as they experience no fear of negative consequences for themselves or others. There is also evidence of difficulties with recognising non-aversive emotions ( 23 ) which may be related to difficulties with attention allocation to the eyes of others ( 24 ). Diminished affective empathy, paired with the ability to mentalise, enables psychopaths to successfully manipulate others for personal gain ( 15 ). This contrasts with autistic individuals who experience aversive emotions if they believe they have caused harm ( 20 ). Therefore, although both autism and psychopathy are characterised by empathic dysfunction, behaviour and decision-making are very different and driven by distinct empathetic pathways.

1.3 Aims and rationale

Little is known about the co-existence of autism and psychopathy. Rogers et al. ( 25 ), proposed the ‘double hit’ hypothesis, whereby autistic individuals may also show additional impairments in empathy, best explained by the presence of psychopathy as a distinct and additional disorder. However, research in this area is limited. Therefore, the aim of the current study was to systematically review the literature to: (a) understand the relationship between psychopathy and autism, and (b) to describe the clinical manifestation of the two constructs when they co-occur. Studies examining this relationship are critical in furthering our knowledge of this small but clinically significant population group and may help to inform the types of interventions appropriate for those who meet the criteria for both constructs, and especially those who encounter criminal justice as a consequence of their behaviour. The review will encompass traits of each disorder to reflect the spectrum nature of both constructs. Research on children with CUTs (considered a pre-cursor to adult psychopathy) will be included because early identification can help prevent serious risk through successful early intervention.

This systematic review was conducted according to PRISMA guidelines ( 26 ) and was registered with PROSPERO (registration number CRD42023413672).

2.1 Search strategy

Relevant studies were identified by systematic searching of the following databases: PsychINFO; CINAHL Ultimate; Medline Ultimate. Google Scholar was also searched and backward searching of identified papers was completed. Grey literature was searched through www.opengrey.eu . Initial searches were undertaken in March 2023 and completed in April 2023. Key terms were searched using English and American terminology, spelling, and truncation to ensure that all variant word endings were identified. Search terms were combined using the term ‘AND’ , Table 1 .

Table 1 Summary of search terms.

To ensure searches produced relevant results only, the above search terms were restricted to title only and a further specified term of ‘NOT psychopathology’ was included within the title or abstract. This was because initial searches without this clarification produced multiple inapplicable results. Searches were restricted to English language and academic journals or dissertations, in line with the eligibility criteria below, Table 2 .

Table 2 Eligibility criteria.

Due to limited research in this area, no limiters or restrictions were placed upon study design or study date.

2.2 Screening and article selection

Article selection was completed by author KM, with 30% of search results also screened by an independent, masked, second rater (HW), with an interrater agreement of 100%. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) ( 26 ) guidance was used to refine studies and can be seen in Figure 1 which details article selection. First, duplicates were electronically removed using EBSCO. Abstracts were then screened against the eligibility criteria and results were rejected which did not meet criteria. This included book chapters or papers not specifically looking at both autism and psychopathy in some manner. Full text screening of remaining articles was then completed.

Figure 1 PRISMA diagram showing screening and identification of eligible studies ( 27 ).

3.1 Data extraction

The following data were extracted from each paper: author and country, study population and participant characteristics, measure of autism/psychopathy/CUTs administered and main findings. These data were considered relevant to either quality appraisal of the studies or relevant for synthesis of findings in relation research question. Thirty percent of papers were checked by HW, with an inter-rater agreement of 88%. All disagreements were resolved through discussion.

3.2 Quality appraisal

Prior to evidence synthesis, a critical appraisal of the literature is required to enable a judgement about bias and subsequent effectiveness. Study quality was assessed using the ‘Checklist for Analytical Cross-Sectional Studies’ ( 28 ). This tool is used to assess the methodological quality of each included study and assess sources of bias. One included study ( 29 ) was a longitudinal cohort study and therefore the ‘Checklist for Cohort Studies’ was used instead ( 30 ). These tools are recognised as a reliable tool for use in systematic reviews to evaluate variation in study designs and methodology ( 31 ). Again, 30% of papers were checked by HW, with an inter-rater agreement of 82% and disagreements resolved through discussion.

3.3 Synthesis

A narrative synthesis approach was adopted due to the broad spectrum of included research. This was conducted in line with guidance by Popay et al. ( 32 ), who describe this technique as a synthesis of studies relying on the use of words to summarise and explain findings.

4.1 Study settings and sample size

Of the 214 papers identified during initial searches, 92 duplicates were removed, 71 were not relevant and 13 were reviews or editorial pieces. The full text article was unavailable for one paper, and another was theoretical only, leaving 36 studies that met the eligibility criteria and were included, Figure 1 . Table 3 shows 22 studies that recruited children and Table 4 shows 14 studies that included adult participants.

Table 3 Studies investigating the relationship between psychopathy/ callous unemotional traits and autism/autistic traits in children.

Table 4 Studies Investigating the Relationship Between Psychopathy/Psychopathic Traits and Autism/Autistic Traits in Adults.

Studies were conducted in 11 Western countries: UK (17), USA (5), Netherlands (3), Sweden (2), Finland (2), Cyprus (2), Spain (1), Switzerland (1), Germany (1), Portugal (1) and Australia (1). Twenty studies recruited from community settings, including schools and universities, and a further five were recruited from existing cohort/longitudinal studies. Five studies recruited from clinical settings such as child behaviour clinics and six recruited from forensic settings. One study focused specifically on sex offenders ( 43 ). Sample sizes ranged from seven ( 43 ), in an unpublished thesis, to several thousand in large scale twin studies ( 46 , 88 ).

4.2 Participant characteristics

A total of 12115 children were recruited across the included studies, including 6654 males and 5461 females. Of these, 746 had primary diagnoses of autism, autistic traits, or were identified as being at familial risk of autism, although many also had co-morbid diagnoses or additional behavioural difficulties. Three hundred and nineteen were considered to have oppositional defiant disorder, conduct disorder/problems, CUT or psychopathic traits, whilst 11032 were either identified as typically developing or no information was provided. Eighteen participants only had a diagnosis of ADHD. A total of 1888 adults were recruited across our included studies, including 1133 males, 752 females and 3 people who identified as non-binary. Of these, 163 had diagnoses of autism or had autistic traits, 80 had psychopathic traits and the remaining were either considered typically developing or the information was not provided.

Twenty-four studies included males and females, whereas 12 only recruited males. Participant age ranged from seven months ( 29 ) to 63 years ( 71 ). One study included participants with intellectual disability ( 65 ), and three studies included those with mixed ability levels: Leno et al. ( 41 ) reported a mean IQ of 84.7, Leno et al. ( 40 ) reported a mean IQ of 72.5, and Soderstrom et al. ( 75 ) reported that 17% of participants had an IQ below 70.

4.3 Quality appraisal

Quality appraisal ratings are found in Tables 1 and 2 . Scores ranged from two to eight, with five fulfilling the full criteria ( 17 , 39 , 70 – 72 ). An unpublished thesis ( 43 ), scored two out of eight. This low score was due to the small sample size (N=7) meaning that the statistical analysis was judged as inappropriate, whilst there was little information on eligibility criteria, confounding variables or appropriateness of the measures used.

4.4 Measurement tools

Some studies involved administering a gold standard diagnostic tool to participants including the Autism Diagnostic Observation Schedule (ADOS) ( 89 ) and the Autism Diagnostic Interview-Revised (ADI-R) ( 50 ), while two studies did not confirm existing diagnoses ( 16 , 48 ), although both had large sample sizes, making this a time-consuming exercise. Commonly used measures of autistic traits were the Autism Quotient (AQ), the Social Communication Questionnaire (SCQ), and the Social Responsiveness Scale (SRS). These were considered reliable and valid measures, and appropriate screening tools. Research has shown that screening tools are not entirely predictive of diagnosis ( 90 ), making it important to differentiate between autistic traits and a formal diagnosis of autism across studies.

There was large variation in the measurement of psychopathy/CUTs. Many studies used the Inventory of Callous Unemotional Traits (ICU) ( 59 ), which is a 24-item scale designed to measure CUTs in children. Whilst this is a well-researched and validated measure (see Cardinale and Marsh ( 10 ) for a review), no study has validated its use in autistic children. Several studies used this measure ( 34 , 37 , 40 , 47 , 65 ). Other researchers ( 16 , 25 , 41 ) administered the Antisocial Process Screening Device (APSD) ( 53 ), measuring the wider construct of psychopathy in young people, but again, this has not been validated for use with autistic children. Rogers et al. ( 25 ), acknowledged this and confirmed that the APSD positively correlated with conduct problems as expected, suggesting convergent validity.

The authors of three studies ( 72 , 75 , 76 ) administered the Psychopathy Check List-Revised (PCL-R) ( 6 ), which is considered to be a gold standard tool. All other studies relied on self-report measures of psychopathy, which should be viewed critically as psychopathic individuals tend to lack insight into the nature of their psychopathology ( 91 ). Additionally, using self-report measures with those known to be manipulative and deceptive increases the risk of response bias ( 92 ). Research about the reliability and validity of self-report measures of psychopathy in autistic people is lacking. There is evidence that self-report personality measures used with autistic children are questionable ( 93 ), and three of the included studies used a psychopathy self-report measure with children ( 39 , 43 , 48 ). Vilas et al. ( 48 ) acknowledged the limitations of this and administered multiple measures to circumvent this problem. The use of a single measure of psychopathy is advised against ( 91 ); however, only five studies administered multiple measures ( 34 , 43 , 48 , 72 , 76 ).

5 Autism and callous and unemotional traits in children

5.1 estimated prevalence.

Leno et al. ( 40 ) reported that 22% of autistic children scored above their designated cut off to indicate the presence of CUTs. However, some participants completed the full ICU measure and others a shortened version. Ideally, prevalence studies should include a representative sample and exclude any possible biases; the full ICU should have been administered to all participants, and their autism diagnosis confirmed. Two groups of researchers administered the ASPD, reporting different rates of CUTs. Leno et al. ( 41 ) reported that 51% of autistic adolescents fell into their category of high CUTs. In contrast, Rogers et al. ( 25 ) reported that their sample had a mean CUT score of 4.77, which is considered an ‘average’ CUT score. However, methodological differences between these studies make comparison challenging.

5.2 Autistic traits and callous and unemotional traits

Three studies ( 33 , 35 , 36 ) with large, mixed gender samples reported a positive correlation between CUTs and autistic traits ( r = .40, r = 0.60 and r = .51 respectively) amongst typically developing children. Studies reporting higher correlations recruited participants based upon having either low or high empathy levels which may have inflated the correlation.

5.3 Autism and psychopathy

Three studies made use of samples of those with an existing autism diagnosis ( 25 , 40 , 46 ). Svensson et al. ( 46 ) undertook a large twin study (N = 8762), and administered the Child Problematic Trait Inventory – Short Version to index psychopathy. They reported a significant relationship between psychopathy and autism amongst boys, r = .38, and girls, r = .33, bearing in mind that there may be validity issues with their choice of measure ( 94 ). Leno et al. ( 40 ) reported that higher CUTs were associated with more severe autistic traits, lower levels of prosocial behaviour and increased conduct problems. In contrast, Rogers et al. ( 25 ) reported no relationship between CUTs or psychopathy and autism and cognitive abilities in a much smaller study of autistic boys.

5.4 Empathy

As expected, there was evidence that autism/autistic traits and CUTs/psychopathy in children is associated with distinct empathetic profiles. Children with autistic traits demonstrated deficits in cognitive empathy with intact affective empathy ( 35 , 44 , 45 ), and the same relationship was observed in children with diagnoses of autism ( 16 , 17 , 39 , 48 ). These results appeared consistent despite the variation in the measurement of empathy and methods across studies. The relationship between CUTs/psychopathy and empathy appeared less clear; some studies reported diminished affective empathy and intact cognitive empathy ( 16 , 17 ), whilst others reported diminished affective and cognitive empathy ( 35 , 44 ).

Studies looking at the relationship between CUTs and autistic traits had contradictory results. While Pijper et al. ( 45 ) reported a negative association between CUTs and affective empathy in their sample of 10-year-old boys with conduct disorder as expected, the relationship was moderated by autistic traits; those with higher autistic traits and CUTs exhibited less impaired affective empathy. In contrast, Pasalich et al. ( 44 ) found that 5-year-old boys and girls with conduct disorder and high levels of both CUTs and autistic traits displayed the most pronounced deficits in affective empathy. These contradictory findings may be explained by: (a) sex differences: there is limited evidence that high CUTs and high autistic traits are associated with decreased affective empathy in girls only ( 35 ) and Pijper et al. ( 45 ) only included a sample of boys, and (b) difficulties with the measurement of empathy: both Georgiou et al. ( 35 ) and Pasalich et al. ( 44 ) used the Griffith Empathy Measure ( 95 ) and there is evidence that the affective empathy scale lacks construct validity ( 96 ). Age may also have impacted on these findings as there is evidence of improved performance with age on both types of empathy in all participants ( 17 ), as would be expected, and Pijper et al. ( 45 ) included older children relative to Pasalich et al. ( 44 ). Nonetheless, it’s worth noting that another study reported no relationship between age and empathy ( 35 ).

5.5 Cognitive profile

There was some evidence that psychopathy and autism are distinct constructs and the interaction of these may create a distinct cognitive profile. Bedford et al. ( 29 ) reported that reduced infant regulatory function (a precursor to executive functioning) is associated with later autistic traits but not CUTs in their longitudinal study, suggesting the two constructs are associated with differing executive functioning abilities. However, they did not include data for children older than seven years, and thus lacked information about continued development. When exploring the interaction of CUTs and autistic traits, Tye et al. ( 47 ) reported that autistic children with high CUTs exhibited enhanced conflict monitoring skills. Whilst this indicates a potentially advantageous role of CUTs on executive functioning in this group of children, the study was a small-scale preliminary study using a specific task to assess conflict monitoring, which may not be generalisable to other executive functioning skills. Two studies found that CUTs/psychopathic traits in autistic children were unrelated to the executive functioning skills associated with autism ( 25 , 41 ).

5.6 Emotion recognition

Nine studies explored emotion recognition. Ibrahim et al. ( 37 ) reported that autistic children with CUTs displayed reduced amygdala activity to fearful faces compared to those with autism only. Conversely, Rogers et al. ( 25 ) found that all autistic children demonstrated fear recognition, regardless of the presence or absence of psychopathic traits, although this study focused on the wider construct of psychopathy (not CUTs). Results for sadness differed, with Rogers et al. ( 25 ) reporting that autistic boys with high psychopathic traits had poorer sadness recognition than those with low psychopathic traits. These studies used morphed faces ( 25 ) or still pictures ( 37 ) which may not accurately reflect how emotions are viewed during in-person social interactions. Bedford et al. ( 33 ) theorised that dynamic expressions are a more accurate representation of social interactions and compared static pictures with short video clips of people performing facial expressions. They reported that CUTs in typically developing children were associated with reduced emotion recognition for static facial expressions depicting anger and happiness. This association was not observed for dynamic facial expressions and disappeared when controlling for autistic traits. In contrast, autistic traits were associated with poorer overall emotion recognition for both static and dynamic expressions. Leno et al. ( 40 ) adapted the emotion recognition stimuli from Bedford et al. ( 33 ) and investigated emotion recognition in autistic adolescents, reporting that all participants demonstrated impairment in recognition of fearful faces with no relationship with autism severity or CUTs.

Several studies investigated the role of eye gaze on emotion recognition ( 33 , 34 , 40 , 42 ). Bours et al. ( 34 ) reported that autistic adolescents and adolescents with CUTs both showed reduced fixations of the eye regions compared to typically developing adolescents. When considering the interaction of autism and CUTs, Leno et al. ( 40 ) found that CUTs in autistic adolescents was associated with longer times to identify fear and reduced eye contact during viewing of fearful faces. Leno et al. ( 42 ) then investigated the effect of cueing attention to the eyes in children with either CUTs or autistic traits, finding that this improved fear recognition in children with CUTs (no improvement in other emotions) but had the opposite effect on overall emotion recognition in their autistic trait group, suggesting different underlying mechanisms. However, the relationship between autistic traits, emotion recognition and gaze cueing was non-significant after controlling for conduct problems, emphasising the importance of considering co-occurring psychiatric traits.

Finally, Georgiou and Fanti ( 36 ) investigated the relationship between emotional recognition and physiological reactivity and reported that boys with CUTs exhibited low skin conductance reactivity during sad and fearful stimuli, whilst no associations were found amongst girls with CUTs or children of either gender with autistic traits. CUTs were associated with stronger heart reactivity to fear stimuli amongst children with low levels of autistic traits. They theorised that low skin conductance reflected fearlessness in children with CUTs, whilst stronger heart rate reflected thrill seeking. Unfortunately, the authors did not measure anxiety which may impact physiological responses.

6 Autism and psychopathy in adults

6.1 prevalence.

Barnard-Brak and Richman ( 66 ) looked at the prevalence of autistic and psychopathic traits amongst a community sample (N = 723) without a diagnosis of autism, finding that 10% met screening cut off to indicate autistic traits and 12% met screening cut off to indicate psychopathic traits; 30% of the autistic trait group also meet criteria for psychopathic traits. The study relied on brief self-report measures of autistic [AQ-10; ( 79 )] and psychopathic traits =[Dirty Dozen Scale; ( 82 )], which are not diagnostic, and findings should be viewed in the context this limitation.

6.2 The relationship between autistic and psychopathic traits

Several studies commented on the correlation between psychopathy and autism, with wide variation in the source of participants, measures, and methodology and all administering self-reports of psychopathic and autistic traits. In community samples, Barnard-Brak and Richman ( 66 ), reported a weak but significant positive corelation, r = .19, whilst other studies reported no significant correlation ( 70 , 71 ). No correlation was found between autistic and psychopathic traits in a forensic setting ( 71 ).

On the other hand, Soderstrom et al. ( 75 ) recruited violent offenders and administered the gold standard, PCL-R, and reported a significant but small positive correlation between PCL-R total, factor two (unemotionality), factor three (behavioural dyscontrol), and autistic traits. No correlation between autistic traits and factor one (interpersonal) was found. Only one study differentiated primary and secondary psychopathy, reporting a positive correlation between autistic traits and secondary psychopathy traits only ( 74 ). All the aforementioned studies measured autistic traits, and only one study recruited adults with a diagnosis of autism and intellectual disability, observing a small but significant positive relationship between autism and CUTs ( 65 ).

6.3 Empathy

Many studies recruited typically developing individuals without a diagnosis of autism and grouped them according to whether they had high or low autistic or psychopathic traits, drawing comparisons. As expected, findings indicated that psychopathic traits were associated with diminished affective empathy and intact cognitive empathy ( 18 , 73 , 77 ) whilst autistic traits are associated with reduced cognitive empathy but not affective empathy ( 18 , 69 ). Of note, these studies all recruited participants with a mean age of 20-21 years, an age at which the human brain is still developing, and therefore results may not be applicable to older adults. In one study, Oliver et al. ( 73 ) failed to find a relationship between autistic traits and all measures of empathy, but the cognitive empathy test used was subject to ceiling effects, reducing the sensitivity of this task.

Studies of emotional contagion (thought to reflect affective empathy) highlighted impairment in typically developing adults with psychopathic traits and individuals with autistic traits, with greatest impairment observed in those with psychopathic traits ( 68 ). Helt et al. ( 68 ) observed that individuals with high traits of either autism or psychopathy both showed reduced yawn contagion, but the psychopathic trait group also showed reduced contagion of itching. The relationship between autistic traits and yawn contagion was moderated by eye gaze suggesting that some of the reduced contagion was due to less time spent looking at the eyes. These findings contribute to the evidence that psychopathy is associated with diminished affective empathy to a greater extent than autism. Similar results were found in autistic adults with a diagnosis; Noppari et al. ( 72 ) recruited violent offenders with high psychopathic traits, autistic adults and a typically developing comparison group. They observed weakened somatomotor responses in both their violent offender group and their autistic group (compared to their comparison group), however the most pronounced deficits were observed in the violent offender group.

Only one study investigated the interaction of psychopathic and autistic traits in relation to empathy. Gillespie et al. ( 67 ) measured primary and secondary psychopathy traits and autistic traits amongst university students and observed diminished cognitive ToM performance in students with both high primary psychopathy traits and autistic traits, concluding that people with co-occurring traits of both constructs have additional empathy impairments. No interaction effect was seen for affective ToM, which was uniquely associated with primary psychopathic tendencies. Unfortunately, this was a small-scale study, relying on self-report measures.

6.4 Cognitive profile

As with children, there was evidence that psychopathy and autism have different cognitive profiles and the authors of two studies compared high and low autistic or psychopathic trait groups on cognitive processes. The first group reported that adults with high autistic traits tend to blame vignette characters for their mistakes more so than those with low autistic traits, while those with high psychopathic traits attributed lower regret and guilt to vignette characters ( 69 ). The second group investigated moral judgment, reporting that the high psychopathic trait group judged misdemeanours less harshly than the low psychopathy group, with no differences in those with high or low autistic traits, leading them to conclude that moral judgement was only affected by psychopathy ( 77 ). Although offering insight into the cognitive profiles of autism and psychopathy, neither study investigated the interaction of the two constructs, and both relied on self-report measures from university students, limiting generalisability.

Two additional studies employed brain imagining techniques in individuals with autistic or psychopathic traits. Leno et al. ( 70 ) investigated neural feedback processing of social and non-social information, reporting atypical neural feedback processing in both trait groups. Autistic traits were associated with decreased sensitivity to social feedback, whilst those with traits of the antisocial domain of psychopathy showed decreased sensitivity to all feedback and those with traits of the interpersonal domain of psychopathy showed attenuated processing of negative feedback only. Skjegstad et al. ( 74 ) reported deficits in both trait groups for socio-affective processing, but again these showed different areas of association; autistic traits were associated with deficits in dorsal auditory processing streams (used for communication context encoding), whilst psychopathic traits were associated with hypoactivity in socio-affective processing networks. This study was exploratory and lacked an a priori power calculation, but both studies suggested distinct neural mechanisms across these constructs. Again, these studies did not investigate the interaction of these traits, failing to shed light on the ‘double hit’ hypothesis.

Regarding the interaction of psychopathy and autistic traits, ( 65 ) investigated the mediating role of CUTs in different types of challenging behaviours in a sample of autistic adults with intellectual disability. They reported that CUTs mediated the relationship between challenging behaviours directed towards the self, but not aggressive behaviours directed towards others, therefore proposing that CUTs may have a protective role for self-directed challenging behaviours. However, results must be viewed tentatively as this was a small-scale study that looked only at frequency and not severity of behaviour amongst those with both intellectual disability and autism.

7 Discussion

This review sought to investigate the relationship between psychopathy and autism and what happens when they co-occur. Thirty-six studies were identified as meeting eligibility criteria, largely published within the last 10 years. The variation in methodologies, study focus, measures and samples recruited, made comparisons difficult, allowing only provisional conclusions to be drawn. Further, few studies investigated the co-occurrence of autism and psychopathy and directly investigated the ‘double hit’ hypothesis making it difficult to draw clear conclusions.

Across all ages, an increased prevalence of CUTs/psychopathy in autistic individuals or in those with high autistic traits appeared to exist relative to the general population and regardless of methodology used. Prevalence rates ranged from 22%-56%, whilst prevalence of psychopathy in the general population is estimated at 4.5% ( 7 ). It remains unclear whether autistic children are at risk of developing CUTs and later psychopathy, or whether autism and CUTs/psychopathy are similar constructs and overlap. Multiple limitations were associated with the measures used, drawing urgency to the need to develop measurement tools sensitive enough to untangle this relationship.

Generally, authors reported a positive correlation between autistic and psychopathic traits amongst children ( 33 , 35 , 36 ). However, the authors of one study reported no significant correlation between autistic symptoms and CUTs in diagnosed autistic boys ( 25 ). In adults, the positive relationship between autistic and psychopathic traits was generally attenuated relative to children ( 66 , 75 ) or not found ( 70 , 71 ). This was also observed in adults with autism and intellectual disability ( 65 ). The relationship between psychopathy and autism amongst adults and children may differ due to issues with the sensitivity of measurement tools and development; autistic and psychopathic traits will likely change with maturation.

Several papers evidenced that although the constructs are both associated with empathy dysfunction, the underlying mechanisms differ. In adults, psychopathy/psychopathic traits were generally found to be associated with diminished affective empathy and intact cognitive empathy, whilst the inverse relationship was seen in autism/autistic traits which is consistent with both theory and other research ( 21 , 97 ). A recent meta-analysis confirmed that psychopathy is associated with diminished affective empathy ( 98 ). Research about autism and affective empathy is inconsistent but points towards fewer deficits in this area compared to cognitive empathy ( 99 ), with some studies reporting intact affective empathy in autistic individuals ( 100 ).

In children, autism/autistic traits were also associated with difficulties with cognitive empathy but not affective empathy while the results for those with CUTs/psychopathy were inconsistent. Some studies reported deficits in both types of empathy and others reported difficulties with affective empathy only. This inconsistency may be due to developmental maturation throughout childhood ( 101 ) or gender, as children of both genders with psychopathic traits had difficulties with cognitive empathy but there was some evidence that males overcame these difficulties during their pubertal years ( 102 ). However, the authors of one study reported no relationship between age and empathy ( 35 ), which is unexpected, whilst another reported improved performance with increasing chronological age ( 17 ); however, they included a broader age range (six to 17 years) of boys only with intact cognitive empathy, whereas Georgiou et al. ( 35 ) included younger boys and girls (three to eight years).

In the current review, the findings from studies about emotion recognition were mixed. In adults and children, CUTs/psychopathy was associated with reduced emotion experience and emotion recognition ability, in particular, recognition of fear and sadness was diminished. These deficits largely remained in the presence of autism, for example, autistic boys with psychopathic traits showed poorer sadness recognition ( 25 ), and reduced amygdala activity to fearful faces was observed in autistic children with CUTs ( 37 ). However, results were inconsistent across studies with one study reporting a non-significant association between CUTs and emotion recognition after controlling for autism ( 33 ).

Previous research has indicated that fear recognition deficits in psychopathy are associated with poor attention to the eyes, resulting in blunted affect and impaired processing of affective cues in others ( 103 ). This association has been found across many samples, including children with CUTs ( 24 , 103 ), community samples ( 104 ) and psychopathic offenders ( 105 , 106 ), with similar findings in the current review identified by Bours et al. ( 34 ). Regarding the co-occurrence of CUTs and autism, it appears that deficits in eye gaze remain, with autistic children with CUTs taking longer to identify fear and showing reduced eye contact when viewing fearful faces, relative to autistic children with fewer CUTs ( 40 ).

Cueing to the eyes has been shown to improve fear recognition in children with CUTs ( 103 ). This was replicated in a single study identified in the current review, but the converse relationship was found in an autistic trait group who evidenced reduced fear recognition following cueing ( 42 ). It is possible that autistic individuals view eyes as threatening or over-arousing stimuli, thus avoiding this area and missing social processing cues which then interferes with emotion processing ( 107 ). This may explain why cueing to the eyes reduced fear recognition ability in autistic individuals but not in individuals with CUTs.

With regards to the ‘double hit’, Rogers et al. ( 25 ) reported that although psychopathy and autism can co-occur, they are not part of the same construct, finding that autistic boys with CUTs have additional impairments in moral convention distinction and sadness recognition. In the current review, two studies reported increased empathy deficits in individuals with traits of both; Pasalich et al. ( 44 ) found that boys with elevated CUTs and autistic traits showed greater impairment in affective empathy and in adults, and Gillespie et al. ( 67 ) found that the interaction of autistic and psychopathic traits was associated with reduced cognitive ToM but not affective ToM. They defined cognitive ToM as the ability to infer thoughts, intentions and beliefs of another and affective ToM as the ability to understand another’s emotions. These studies offer support to the ‘double hit’ hypothesis, suggesting increased deficits when the constructs co-exist. However, contrasting results were reported by other studies which indicated that the co-occurrence of these constructs offers enhanced skills, including less impaired affective empathy ( 45 ) and greater conflict monitoring skills ( 47 ). Unfortunately, based upon the studies included with the current systematic review, it was difficult to coherently describe the clinical manifestation of co-occurring autism and psychopathy due to some mixed findings. However, our findings offer support to the suggestion that autism and psychopathy are distinct constructs which further alter the empathic ability and cognitive ability of an individual when they co-exist.

7.1 Strengths and limitations

In the current review, the search strategy restricted the search terms to the title only and included the specifier ‘NOT psychopathology’. Although this was done in efforts to screen out inapplicable results, it could have potentially led to the exclusion of some studies. The inclusion of the grey literature was a strength, but only one unpublished thesis was found. It is also important to recognise the wide focus of the review as both a strength and a limitation. Whilst this allowed for inclusion of a broad range of research, the wide focus also made it challenging to draw more specific conclusions, which may have been possible by restricting the eligibility criteria. Psychopathy and autism are highly heterogeneous, and the studies recruited a broad range of participants which is perhaps reflected in the variation of results.

In terms of limitations of the included research, only two studies ( 67 , 74 ) differentiated between primary and secondary psychopathy and none considered the impact of adverse childhood experiences. In psychopathy research, children with CUTs showed strongest deficits in emotion recognition when there was no history of maltreatment, suggesting that this may be a feature of the primary variant only ( 108 ). As adverse childhood experiences are common in autistic children ( 109 ), this is an important variable to consider when seeking to determine the relationship between psychopathy and autism.

7.2 Clinical implications

The increased prevalence of CUTs/psychopathy in autistic individuals underscores the importance of assessing psychopathy as part of the evaluation of autistic offenders or those at risk of offending to better understand their presentation. Understanding this at an early stage could lead to more targeted treatment options. The studies included within this review were characterised by multiple difficulties with measurement, including lack of validated measures for identifying psychopathic traits within autistic individuals, highlighting this as an area requiring attention. There was a lack of intervention studies, however there was some evidence to suggest that interventions to improve eye contact may be a helpful strategy to improve emotion recognition in psychopathic individuals but may have a detrimental impact for autistic individuals ( 42 ). The impact of such interventions for individuals with both psychopathy and autism is unclear but clinicians should be aware of the different underlying mechanisms and consider this with implementation of any emotion recognition strategies used.

7.3 Future directions

Although research in this area appear to have grown substantially since Rogers et al. ( 25 ) introduced the concept of the ‘double hit’ hypothesis, clear gaps remain. Firstly, there remains a lack of research focusing on the interaction of both autism and psychopathy which is critical in furthering our understanding of the clinical manifestation of the two constructs when they co-occur. Age and gender remain relatively unexplored variables, with fewer studies focusing on females which may be important given indicated sex differences in psychopathy ( 110 ). The presentation of primary and secondary psychopathy variants in autistic individuals is unexplored and may be important as autistic individuals experience increased adverse childhood events. Furthermore, future research would benefit from longitudinal studies exploring the developmental trajectory of autistic adults with co-morbid psychopathy or autistic children with CUT. Finally, to aid research in this area, it is essential to establish the validity of measures of psychopathy within autistic individuals, as well as the validity of measures of autism with those scoring high on measures of psychopathy. It was notable that there was a lack of studies about autistic traits amongst those with high psychopathy. These directions will all support better understanding of the relationship between psychopathy and autism and support the development of appropriate care pathways within clinical and forensic systems.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.

Author contributions

KM: Methodology, Formal analysis, Conceptualization, Writing – review & editing, Writing – original draft. HW: Formal analysis, Writing – review & editing. FB: Supervision, Writing – review & editing. PL: Writing – review & editing, Writing – original draft, Supervision, Methodology, Formal analysis, Conceptualization.

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: autism, psychopathy, callous unemotional traits, review - systematic, narrative synthesis

Citation: Maguire K, Warman H, Blumenfeld F and Langdon PE (2024) The relationship between psychopathy and autism: a systematic review and narrative synthesis. 15:1375170. doi: 10.3389/fpsyt.2024.1375170

Received: 23 January 2024; Accepted: 13 March 2024; Published: 27 March 2024.

Reviewed by:

Copyright © 2024 Maguire, Warman, Blumenfeld and Langdon. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Peter E. Langdon, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

International Prehospital Medicine Institute Literature Review, April 2024

This literature review keeps you up to date with current EMS publications and studies.

1. Completeness of Pediatric Versus Adult Patient Assessment Documentation in the National Emergency Medical Services Information System . Cercone A, Ramgopal S, Martin-Gill C. Prehosp Emerg Care, 2024;28:243-252.

2. National analysis of motorcycle associated injuries and fatalities: wearing helmets saves lives. RosanderA, Breeding T, Ngatuvai M, et al. Am J Emerg Med 2023 ;69:108-113.

3. Accuracy of the American College of Surgeons Minimum Criteria for Full Trauma Team Activation for Children . Lerner EB, Drendel AL, Badawy M, et al. Ped Emerg Care 2024;40:187-190.

4. Video Laryngoscopy versus Direct Laryngoscopy for Orotracheal Intubation in the Out-of-Hospital Environment: A Systematic Review and MetaAnalysis . Kent ME, Sciavolino BM, Blickley ZJ, Pasichow SH. Prehosp Emerg Care, 2024;28:221-230.

International Prehospital Medicine Institute Literature Review, March 2024

Pediatric prehospital encounters are relatively uncommon, making up only 5.7% to 7.4% of EMS responses. The American Academy of Pediatrics, the American College of Emergency Physicians, the Emergency Nurses Association, the National Association of EMS Physicians and the National Association of EMT’s have emphasized preparing EMS responders to improve their pediatric competence. These initiatives call for comprehensive patient assessments that require complete and accurate vital signs for all patients evaluated in the out of hospital setting.

The authors conducted a retrospective review of the 2019 NEMSIS dataset involving over 10,000 EMS agencies in 47 states. They included all encounters, both BLS and ALS, which were transported to the hospital. Patients with no age listed, cardiac arrests, non-transports or cancellations, scene assists, interfacility transfers and specialty transports were excluded from their review.

They had identified 34,203,087 EMS activations and from these 18,918,914 were included in their study. Pediatric patients (age <18 years) accounted for 1,212,843 (6.4%) cases). Male patients made up 47.3% of the calls. The proportion of ALS vs BLS for the adult and pediatric populations were similar (adults 84.2% vs 83.6% pediatrics).

Documentation of vital signs increased as the patient population increased in age. Systolic blood pressures were documented in 32.2% of neonates and in 95.5% of the adults. The lowest incidence of complete vital signs was in children < 1 month old (30.8%). Documentation of complete vital signs increased to 89.2% for adolescents and to 91.8% for adults.

The authors also found regional differences with the highest proportion of complete vital signs occurring in the south and lower proportions of complete vital signs documented in the Midwest in the <12 years old population. In addition, higher proportions of complete vital signs were documented in children in all age groups by for profit and non-hospital based ambulance services. The lowest proportion of vital signs documented were in children <12 years old managed by tribal ambulance services.

Other findings included a slight increase in reporting of respiratory rates in all age categories when the patients had respiratory complaints. Pulse oximetry readings were less prevalent in pediatric patients versus adult patients with respiratory complaints. (73.9% vs 95.1%).

In patients with cardiac complaints, 80.9% of the adult patients were placed on cardiac monitors while only 24.4% of the children less than 1 year old had monitors.

Limitations of this study include the fact that the NEMSIS does not include all EMS encounters in the United States. It does, however, report on > 1 million pediatric encounters every year for over 10,000 EMS agencies so this likely provides a generalized view of the state of pediatric assessments. Some of the variables used for adjustment in the multivariable models were subject to higher rates of missing data. They did not review the narrative reports which could have included some of the missing data.

Documentation of complete vital signs in pediatric patients occurs less frequently than in adult patients in the prehospital setting. This finding persists across locations and response levels. This result is particularly concerning and indicates the need for increased education of prehospital providers regarding complete pediatric assessment.

As the number of registered motorcycles has doubled over the last 20 years, the incidence of motorcycle fatalities has also increased. Unlike automobile occupants, motorcyclists often have very limited protection when involved in a collision. Despite data from the National Highway Traffic Safety Administration that shows that use of helmets is associated with an estimate 40% reduction in fatalities amongst riders, motorcyclists claim laws that mandate the use of helmets impinge on their personal freedom. As a result, some states have either repealed mandatory helmet laws or required helmet use by younger riders only. Some data indicated that almost one-third of motorcyclists infrequently or never use a helmet.

A team of researchers assembled by traumatologists at the Orlando Regional Medical Center sought to provide a “comprehensive analysis of current motorcycle injuries, injury types, and the impact of helmet use.” They devised a retrospective cohort study to query the American College of Surgeons Trauma Quality Improvement Program (TQIP)’s participant use file from 2017 – 2020 to abstract data on motorcycle associated injuries and fatalities in relation to helmet use. De-identified data for motorcyclists age 18 or older were included if they suffered blunt or penetrating injury or fatality and had an Injury Severity Score (ISS) of 15 or greater. Cases were excluded if the patient was dead on arrival, had an ISS of 14 or less or lacked key information (age, race, gender or helmet status). The primary outcome was the adjusted motorcycle related in-hospital mortality rate and the secondary outcome with the ICU-length of stay (LOS) in days. Standard statistical analysis was performed and a p value <0.05 was considered statistically significant.

During the study period, more than 43,000 motorcyclists met inclusion criteria. Of this group, only 56.4% (24,389) were using helmets while 43.6% were not. Helmet users were predominantly male (90.4%), white (77.8%) and between the ages of 18 – 34 (37.9%), while non helmet users were similarly male (89.0%), white (80.9%) and between the ages of 18-34 (31.2%). Helmeted motorcyclists had a significantly lower rate of skull fractures compared to non-users (0.5% vs 2.1%, p <0.001), but suffered a greater number of bodily injuries including chest trauma, pelvic fractures and greater than two extremity fractures. Crushed extremities, extremity amputation and paralysis were also significantly higher in the helmeted group. Non-helmet users were significantly more likely (p<0.001) to present with Glasgow Coma Scale (GCS) score of 13 or less (14.9%) than helmeted riders (12.3%). Helmeted motorcyclists had a 35% reduction in the relative risk of dying in the hospital from motorcycle-related injuries compared to non-users (aOR 0.65, 95% CI [0.59-0.70]. Lastly, helmet use was associated with a decreased ICU-LOS compared to non-helmet users.

The authors note that their study showed that helmeted riders had significantly decreased odds of dying in the hospital from their injuries and a significantly decreased ICU-LOS compared to non-helmet motorcyclists. The investigators found that those wearing helmets had significantly higher incidence of bodily injury compared to helmet non-users, a finding that has been previously documented. Other researchers had proposed that, because the helmet protects the head, the body can withstand higher forces in collisions. That is, non-helmeted riders with more severe head trauma would succumb more quickly from their brain injury (at the scene or during transport) and not survive long enough for their bodily injury to be identified. Another rational explanation may be that those motorcyclists who wear helmets may feel overconfident in their protection and may therefore operate their motorcycle in a manner that puts them at greater risk for bodily injury (increased speed or recklessness).

One limitation of the study noted by the authors was that the database utilized lacked details regarding the type of motorcycle helmet used (half helmet/skull cap vs open face vs full face), so no comparative analysis could be performed. In addition, the exclusion of those motorcyclists that were declared dead at the scene may have underestimated the effect of wearing a helmet.

The authors fell short of their proposed goal of producing a comprehensive analysis of motorcycle injuries and injury types related to helmet use. While they briefly reported on the various injuries, there was little discussion. These investigators really didn’t present any substantially new findings, however they did confirm previous studies which have documented that helmet use is associated with saving the lives of motorcyclists.

In many EMS systems, providers are required to notify receiving facilities, prior to arrival, of their patient status and chief complaint. Facilities use this information to plan Emergency Department bed assignments and if any specialty resources are required to optimally care for the patient. Those specialty resources include resuscitation teams, sepsis protocols and trauma teams to name a few.

The American College of Surgeons (ACS) recommends that Adult and Pediatric Trauma Centers have prearrival activation criteria for trauma patients arriving via EMS. Current ACS recommendations for prearrival notifications resulting in a trauma team response for pediatric trauma patients include age specific hypotension, gunshot wounds, a Glasgow Coma Scale (GCS) score less than 9, and or an emergent airway. The ACS further recommends that institutions expand prearrival trauma team activation criteria based on several anatomical indicators and local experience with patient populations.

The authors of this paper attempted to evaluate the efficacy of ACS pediatric trauma team activation criteria as well as the expanded local criteria of three Trauma Centers located within three separate cities in the United States. This was a three year, prospective, institution review board consent waived, observational study. The three institutions are located within EMS regions that have protocols in place that direct potentially seriously injured children to ACS credentialed, pediatric trauma centers with notification of their impending arrival. Following arrival and handoff of an injured pediatric patient, a trained interviewer asked the EMS provider responsible for the child’s care if they would consent to take a brief survey on the child’s condition on scene and injuries. Pediatrics were defined as patient’s fifteen years of age or less. If the EMS provider consented to being interviewed, the child’s care and disposition were followed from Emergency Department admission until discharge from the hospital. Interviewers were available between 8 and 16 hours a day.

The investigators conducted 9,483 EMS interviews with providers from both ground and aeromedical EMS programs. All patients came directly from the scene and interfacility transfers were excluded from the study. The average age of patients enrolled into the study was 7.7 years of age. Two percent of the patients (202) required trauma team activations. This cohort of patients often required advanced airways with 2 hours of arrival or surgery within 4 hours. A total of 299 children met ACS minimal criteria for a prearrival trauma team activation. The authors found that this minimum criterion over-triaged 2% of the pediatric patients and under-triaged 44% that should have been met by a trauma team. GCS scores produced the least number of false positives and age specific hypotension produced the greatest number of false positives. Overall, the authors discovered a higher rate of under-triage versus over-triage regardless of the criterion used (ACS minimum criteria, expanded criteria or local criteria). The authors noted that there is no recommended rate of over-triage versus under-triage for pediatric trauma team activations. There have been suggested rates of 5% under-triage and 25% to 50% over-triage being acceptable.

The study group identified many limitations. The interviews with EMS providers post arrival at the hospital were voluntary. Not all providers consented to the interviews and potentially sicker or less sick patients were lost for participation in the study. Interviewers were not available 24/7 resulting in a loss of some study subjects. The authors did not account for levels of trauma team activations at facilities or modification of responses once the patient arrived at the Emergency Department.

The authors concluded that there is a high rate of under-triaged pediatric patients arriving at trauma centers. Local criteria for trauma team activations may decrease the rate of under-triage but will potentially increase the rate of false positives based on unique criteria within the trauma activation protocol.

Appropriate patients benefit from trauma teams awaiting their arrival at the Emergency Department. Overuse of trauma team activations may decrease the team’s response abilities and accessibility to patients within the hospital that would benefit from their expertise. EMS providers must be familiar with their state and local Trauma Point of Entry Protocols and receiving trauma centers’ trauma team activation criteria. The goal should be to activate trauma teams accurately and responsibly.

Effective airway management is a crucial intervention across all healthcare settings, but the out-of-hospital environment, in particular, presents unique challenges. First-pass success, indicating successful intubation on the initial attempt, is a key indicator of effective airway management due to its association with reduced complications such as hypoxia and cardiac arrest. However, success rates vary among providers and settings. Video laryngoscopy (VL) has emerged as a method that may improve first-pass success, particularly in critical scenarios.

The authors performed a systematic review and metaanalysis of the literature. They included studies published in English that were conducted in the out-of-hospital setting and involved live human subjects aged 16 or older. These studies had direct laryngoscopy (DL) as the primary device for the control group, video laryngoscopy (VL) as the primary device for the experimental group, and reported either first-pass success or overall intubation success. The authors’ primary outcome was determining the odds of achieving first-pass success using video laryngoscopy (VL) versus direct laryngoscopy (DL). The authors conducted subgroup analyses to assess how clinician type and the type of VL blade impacted the differences in first-pass success between VL and DL. A total of twenty-five (25) studies were included, yielding 35,489 intubations across all subgroups involving critical care paramedics (CCP) and nurses (CCRN), paramedics, and physicians.

They found that overall success rate for CCPs and CCRNS was the same for VL and DL. In the physician subgroup, VL was favored in 2/6 studies. In the paramedic subgroup, 9/10 studies favored VL. Intubation times were generally shorter with DL compared to VL.

The study has several limitations as noted by the authors. Substantial heterogeneity in the studies was observed across all outcomes and subgroups, potentially influenced by inconsistencies in defining overall intubation success among studies. While first-pass success is a common metric, its significance may vary depending on patient outcomes beyond mere intubation success. Sensitivity analyses excluding observational studies had minimal impact on results, suggesting consistency across methodologies. The performance of video laryngoscopy (VL) and direct laryngoscopy (DL) might differ in various clinical scenarios, such as trauma or airway obstruction, but data were insufficient to detail results by scenario. Moreover, variations in clinician training and experience, especially among critical care paramedics/nurses, may have affected outcomes. Inadequate reporting of bougie usage and differences in VL device design further complicate interpretation. Clarification of clinician training, standardization of terminology, and more detailed reporting in future studies are crucial for addressing these limitations and improving the reliability of meta-analytical findings in airway management research.

Given that airway management significantly impacts outcome for critically ill and injured patients, it is imperative to explore all avenues for enhancing first-pass intubation success rates. While the optimal approach to prehospital airway management remains uncertain, the introduction of video laryngoscopy (VL) offers an additional option. It is worth noting that a study highlighted previously in our literature reviews found that 76% of surveyed paramedics had not performed an intubation in the past year. Furthermore, research suggests that mastering DL and intubation requires a substantial number of procedures, ranging from 36 to over 200, which have become increasingly difficult for paramedic students to obtain. There are no data indicating the number of VL procedures needed to become proficient. Additionally, there is a need for further investigation into the efficacy of using VL as the primary method of visualization versus its role as a backup device.

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• Open access
• Published: 28 March 2024

Impact of obesity on outcomes of extracorporeal membrane oxygenation support: a systematic review and meta-analysis

• Xinhua Huang 1 &
• Xiaoqing Lin 1  

BMC Pulmonary Medicine volume  24 , Article number:  157 ( 2024 ) Cite this article

54 Accesses

Metrics details

Extracorporeal membrane oxygenation (ECMO) is used when standard methods of standard treatment methods are not successful. Obese patients present unique challenges during ECMO due to large body size hindering sufficient flows, difficulties with patient positioning and anatomical landmark identification, and restricted radiology scans. This meta-analysis aims to investigate the impact of obesity on the outcomes of patients undergoing ECMO.

Databases (PubMed, Embase, and Scopus databases) were searched to identify relevant studies published until July 2023. Data were reported as odds ratios (OR) with 95% confidence interval (CI), and the descriptive data were reported as standard difference of means (SDM) by a random effects model.

A literature search identified 345 studies. Of them, 18 studies met the inclusion criteria. The findings from the meta-analysis revealed no significant association between obesity and survival outcomes after ECMO (odds ratio (OR): 0.91, 95% confidence interval (CI): 0.70–1.17, p: 0.46). Moreover, no comparative significant differences were found between obese and non-obese individuals on the duration of ECMO procedure (standardized mean difference (SMD): 0.07, -0.03–0.17), length of hospital stay (-0.03, -0.19 to 0.12), and duration of ventilation support (-0.10, -0.44 to 0.24).

The meta-analysis findings suggest no significant impact of obesity on the survival outcomes after the ECMO procedure. There was no significant impact of obesity on the duration of ECMO procedures, length of hospital stay, and duration of ventilation support.

Peer Review reports

Introduction

Obesity is a global health issue that presents formidable challenges to healthcare providers, particularly during life-saving interventions such as extracorporeal membrane oxygenation (ECMO) procedures [ 1 , 2 , 3 ]. Obesity, as defined by the Centers for Disease Control and Prevention, is characterized by a Body Mass Index (BMI) of 30.0 or higher. BMI is calculated by dividing a person’s weight in kilograms by the square of their height in meters, serving as a screening tool for evaluating body fatness. The CDC classifies BMI into four categories: underweight (BMI less than 18.5), healthy weight (BMI 18.5 to < 25), overweight (BMI 25.0 to < 30), and obesity (BMI 30.0 or higher) [ 4 ]. ECMO is used in patients with severe respiratory or cardiac failure when other conventional treatments fail [ 1 , 5 , 6 , 7 ]. However, for obese patients, the management of ECMO remains particularly complex due to the unique anatomical and physiological characteristics of this group of patients [ 8 , 9 ], the presence of various comorbidities, such as diabetes mellitus and hypertension [ 10 , 11 ], or difficulties in diagnosing and monitoring [ 3 , 8 , 10 , 11 , 12 ]. However, despite these potential issues, obesity has not been identified as a significant risk factor for hospital mortality in patients with acute lung failure and cardiac diseases [ 3 , 10 , 11 , 13 ]. Therefore, existing guidelines do not categorize obesity as an absolute contraindication for ECMO support [ 3 , 10 , 11 ]. There is still a lack of comprehensive reviews summarizing the overall evidence in this area [ 9 , 13 , 14 , 15 , 16 ].

This review and meta-analysis aims to summarize all existing data and evaluate the impact of obesity on outcomes, such as mortality rates post-ECMO, the duration of ECMO procedures, lengths of hospital stays, and ventilation requirements, in patients undergoing ECMO. Our study is particularly relevant to the nursing field due to the integral role nurses play in the care of ECMO patients and may contribute to development of evidence-based guidelines, optimizing the management of obese patients on ECMO and potentially improving their survival and recovery rates in critical care settings.

The review was performed in adherence to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [ 17 ]. The paper was registered at PROSPERO, No. CRD42023448406.

Search strategy

PubMed, Embase, and Scopus databases were searched by using appropriate keywords. We initially compared the complications with ECMO in between obese and non-obese individuals. Search items were as follows: “Obesity,” “Extracorporeal membrane oxygenation,“, “ECMO”, “Body mass index”, “BMI”, “Impact,” “Outcomes,” “Systematic review,” “Meta-analysis,” “ECMO outcomes,” “ECMO complications,” “ECMO survival,” “ECMO mortality,” “Obesity and critical care,” “ECMO and obesity,” “Extracorporeal life support,” “ECMO effectiveness,” “ECMO complications in obese patients.” These terms were combined using the OR operator to ensure comprehensive coverage of relevant literature.

Inclusion criteria (as per the PECOS criteria)

Population: Obese individuals who underwent ECMO procedure.

Exposure: Extracorporeal membrane oxygenation (ECMO) procedures.

Comparison: Non-obese who underwent ECMO procedure.

Outcome: Mortality, ECMO procedure duration, length of hospital stay, and length of ventilation.

Study Design: Randomized controlled trials (RCTs), cohort studies, case-control studies, and observational studies.

Language: English.

Exclusion criteria

Studies are not reporting comparative outcomes between obese and non-obese individuals who underwent ECMO procedures.

Non-English languages studies.

Incomplete studies, unavailable data, case reports, editorials, commentaries, and letters.

The eligibility of the identified studies was independently assessed by two reviewers. Each study underwent a thorough evaluation based on predetermined criteria to ensure its relevance to the research question. The literature search was also independently conducted by the same two reviewers to minimize bias and improve the accuracy of study selection.

In instances where discrepancies or differences of opinion arose between the reviewers regarding the inclusion or exclusion of a particular study. The outcome of the discussion between the two reviewers was to address any conflicts and facilitate consensus on the final selection of studies. This consensus-based approach among the reviewers ensured a comprehensive and unbiased selection of studies for inclusion in the meta-analysis.

Quality assessment

To assess the potential bias in the cohort trials included in this study, ROBINS-I tool was used [ 18 ]. Two independent reviewers conducted a thorough evaluation of the methodological quality of the included studies. In cases where discrepancies arose, the outcome of the discussion between the two reviewers was to resolve any disagreements and reach a consensus.

Data extraction

Data were systematically extracted from the selected studies, and included study type, groups involved, sample size, and age of obese and non-obese cohorts, BMIs of the respective groups, type of ECMO procedures, length of hospital stay, duration of ECMO procedure, mortality events, and period of ventilation.

Statistical analysis

The Meta-analysis version 3.0 was employed for the statistical analysis. Only a random effects model was implemented [ 19 ]. The mortality outcomes between obese and non-obese individuals undergoing ECMO procedures was analyzed. Odds ratios (OR) were computed on the basis of the number of events reported in the included studies. The analysis further examined various factors, including the duration of the ECMO procedure, length of hospital stay, and duration of ventilation. For quantifying these changes standard difference of means (SDM) were computed based on the descriptive data provided in the included studies. Heterogeneity among the studies was assessed by I 2 statistics. I 2 values between 0 and 25% indicated negligible heterogeneity, 25–75% indicated moderate heterogeneity, and ≥ 75% indicated substantial heterogeneity [ 20 ]. Publication bias was assessed by Duval and Tweedy’s trim and fill procedure [ 21 ]. Additionally, as we had used both adjusted and unadjusted values for the primary outcome of mortality in our analysis due to paucity of data present in the included studies, we conducted a leave-one-out sensitivity analysis to strengthen the interpretation of our primary outcome. All analyses conducted in this study adhered to a significance level of 5%.

Study selection and characteristics

Among the 345 papers initially retrieved, 18 papers were eligible, as shown in Fig.  1 . All of the included studies were retrospective cohort studies [ 3 , 5 , 8 , 9 , 10 , 11 , 14 , 15 , 16 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ]. The extracted data from these studies are summarized in Table  1 .

PRISMA flowchart

Participant information

The analysis incorporated data from 21,361 patients undergoing ECMO. A total of 15,447 patients (10,075 males, 5129 females) were non-obese, and 5914 (3405 males, 2323 females) were obese. Sex distribution was not reported by four of the included studies [ 5 , 15 , 16 , 24 ]. The mean age of the non-obese and obsess patients was 51.3 ± 10.6 years and 50.1 ± 9.4 years, respectively.

Assessment of study quality

The methodological quality of the cohort studies included in the analysis was evaluated using the ROBINS-I tool [ 18 ]. As summarized in Table  2 , there was a high risk of bias across the included studies. However, it was noted that several studies had missing data, showed signs of deviation from intervention, and selection bias suggesting possible sources of bias (Table  2 ).

Our analysis of 17 cohort studies (Fig.  2 A) indicates a non-significant effect of obesity on overall mortality in patients who underwent ECMO procedure (odds ratio [OR]: 0.91, 95% confidence interval [CI]: 0.70–1.17, p  = 0.46), with moderate heterogeneity (I 2 : 38.5%). Figure  2 B indicates leave one out sensitivity analysis for this analysis.

( A ) The comparative outcome between obese and non-obese patients who underwent ECMO procedure on overall mortality. ( B ) Leave one out sensitivity analysis

Publication bias

To assess publication bias, we employed Duval and Tweedy’s trim and fill method, which estimates the number of missing studies on either side of the mean effect of the funnel plot. According to this method, three studies were missing on the right side of the mean effect. The overall random effect models provided a point estimate and 95% confidence interval for the studies as 0.90 (95% CI 0.85–0.96). The trim and fill imputed point estimates were calculated as 0.92 (95% CI 0.86–0.98). The results of the publication bias assessment are presented in Fig.  3 .

The trim and fill method by Duval and Tweedy provides a visualization of how publication bias can impact study results

ECMO procedure duration

Our analysis of 18 cohort studies (Fig.  4 ) indicates no difference in the duration of ECMO procedure in obese individuals as compared to non-obese individuals (Standardized difference in means: 0.07, 95% CI: -0.03–0.17, p  = 0.16) with negligible heterogeneity (I 2 : 24.5%).

The comparative outcome between obese and non-obese individuals who underwent ECMO procedure on the overall duration of the procedure

Length of hospital stay

Our analysis of 11 cohort studies (Fig.  5 ) indicates a non-significant difference in the length of hospital stay for non-obese individuals as compared to the obese individuals who underwent ECMO procedure (SDM: -0.03, 95% CI: -0.19–0.12, p  = 0.67) with negligible heterogeneity (I 2 : 8.8%).

The comparative outcome between obese and non-obese individuals who underwent ECMO procedure on the length of hospital stay

Duration of ventilation

Our analysis of 4 cohort studies (Fig.  6 ) indicates a non-significant difference in the duration of ventilation for non-obese individuals as compared to the obese individuals who underwent ECMO procedure (SDM: -0.10, 95% CI: -0.44–0.24, p  = 0.57) with negligible heterogeneity (I 2 : 12.9%).

The comparative outcome between obese and non-obese individuals who underwent ECMO procedures during the period of ventilation

The results of our meta-analysis showed no substantial correlation between obesity and post-ECMO mortality outcomes. No difference was found between obese and non-obese patients in terms of ECMO procedure duration, the length of hospital stay, and the duration of ventilation required. Our results are particulary important for nursing professionals who are providing holistic care during ECMO interventions, and may serve to inform nursing practices to tailor their care strategies effectively.

Obesity may lead to complications during ECMO procedures through several possible mechanisms [ 19 , 20 , 23 ]. The increased adipose tissue in obese patients can pose challenges during cannulation, as it obscures the underlying vessels and makes it difficult to identify suitable cannulation sites [ 1 , 3 , 6 , 7 , 8 , 9 , 12 , 19 ]. This may result in suboptimal cannula positioning or vascular injuries during insertion, leading to hemorrhage or improper ECMO flow [ 23 , 29 , 31 ]. Altered respiratory mechanics in obese patients, characterized by reduced lung compliance and increased airway resistance, can impact efficient oxygenation and carbon dioxide removal by the ECMO system [ 23 , 29 ]. As a result, inadequate oxygenation and perfusion can cause hypoxemia and inadequate organ support [ 5 ]. For instance, in obese individuals, changes in chest wall resistance and lung compliance can complicate respiratory function [ 32 ]. With respect to ECMO, oxygenation challenges may arise due to ventilation-perfusion mismatch and atelectasis [ 33 ]. The removal of CO2 is impeded by these altered mechanics, potentially resulting in hypercapnia. While ECMO provides extracorporeal support for both oxygenation and CO2 removal, its efficacy is influenced by various external factors, including pump speed, blood flow rate, and the efficiency of the oxygenator and sweep gas [ 34 ]. It is essential to recognize that the effectiveness of ECMO is not solely determined by the inherent nature of the lung disease; rather, it is a complex interplay of external parameters. In situations where lung mechanics are altered, patients may require a prolonged duration of ECMO support, allowing for sufficient time for the lungs to recover to a point where they can adequately provide oxygenation and ventilation. Therefore, tailoring ECMO configurations and closely monitoring patients for dynamic adjustments are crucial aspects for optimizing outcomes in these cases.Furthermore, obese patients with pre-existing cardiac issues may experience additional strain on the heart due to the hemodynamic load imposed by the ECMO circuit [ 5 , 14 ]. This can lead to myocardial ischemia, arrhythmias, or cardiac arrest [ 17 , 18 ]. Moreover, obesity increases the risk of thromboembolic events, making obese patients more susceptible to clot formation within the ECMO circuit or embolization of clots to vital organs [ 6 , 8 , 13 , 21 ]. Impaired immune function in obese patients also heightens the risk of potentially life-threatening ECMO-related infections [ 3 , 9 , 10 , 12 ].

In our study, we evaluated the comparative mortality outcomes between obese and non-obese patients, undergoing ECMO. A study by Lu, Ortoleva et al. (2022) [ 16 ] also reported lack of association between obesity and mortality in their cohort, and provided several plausible explanations for that observation. Firstly, 944 patients in their cohort had missing BMI data, and the reported in-hospital mortality rate was high (89.1%). Secondly, while comorbidities were considered in the analysis, the severity of illness before cannulation for VA-ECMO was not accounted for. Thirdly, sample size in Lu, Ortoleva et al. (2022) study was small [ 16 ], which might have hindered the detection of existing differences. Interestingly Djordjevic, Ivanov et al. (2022) and Merritt-Genore, Lyden et al. (2020) reported reduced mortality outcomes in their obese cohort as compared to the non-obese cohort who underwent ECMO procedure [ 15 , 29 ]. Here, the authors suggested that perhaps the reduction in the mortality outcomes could be due to the obesity paradox in individuals undergoing ECMO due to the potential benefits provided by the increased adipose tissue. Obese individuals may have greater nutritional and metabolic reserves, which could help them withstand the stress of ECMO support better [ 35 ]. Additionally, adipose tissue produces certain protective hormones that may have favorable effects on cardiovascular function and immune response during critical illness [ 36 , 37 ].

We also did not observe any significant difference in ECMO procedure duration between obese and non-obese individuals. This lack of difference can be explained by recent advancements in ECMO technology and expertise in managing obese patients which minimized any potential procedural delays related specifically to obesity. Additionally, the ECMO circuit could have been adapted to accommodate the larger body size of obese patients, allowing for adequate flow and gas exchange, which could also reduce the differences in procedure duration. Finally, healthcare providers could have developed standardized protocols and tailored strategies for obese patients, optimizing patient positioning and cannula placement, leading to comparable procedure durations. All these reasons can also explain the lack of differences in the duration of hospitalization and ventilation support between obese and non-obese individuals observed in our meta-analysis. Besides, as our findings indicate that obesity does not significantly impact ECMO outcomes. These findings can empower nurses to tailor care strategies for obese patients, address specific challenges, and contribute to collaborative decision-making. Based on this information, nurses can focus on meticulous monitoring, educate and support patients based on evidence, and actively participate in refining protocols to optimize care for obese individuals on ECMO.

Our study, despite its rigorous methodology, is not immune to certain limitations inherent in non-randomized observational studies. Firstly, confounding bias, a common concern in such research designs, arises from the potential influence of unmeasured or unaccounted variables on the observed associations. Although we employed careful study selection criteria and adjusted our analyses where feasible, the diversity in methodologies, patient characteristics, and reporting practices across the included studies introduces the possibility of residual confounding. Addressing confounding bias in the context of our research question is complex. While some studies may have adjusted for relevant factors, the variability in the control of confounders across the literature is a notable limitation. Secondly, there was variation in the reported parameters across the studies included in the review. For instance, mortality and ECMO procedure duration were the most widely evaluated outcomes (i.e., reported by 17 and 18 studies), whereas the duration of ventilation support was only reported by four studies. This variation in unreported data could be a source of heterogeneity in our analyses and could also introduce bias in our results, making generalizability of our findings difficult. Furthermore, while some studies in the literature have employed propensity score matching to address selection bias and confounding, our decision to utilize unadjusted values was pragmatic. The diverse methodologies and variable reporting across studies made it challenging to uniformly apply propensity score matching. This limitation underscores the importance of interpreting our results with caution, recognizing the potential impact of unmeasured confounders. Therefore, we strongly recommend future studies to replicate our findings in large-scale trials with consistent data reporting for obese and non-obese individuals undergoing ECMO procedures to help develop more robust evidence to guide clinicians in selecting appropriate strategies to improve outcomes following ECMO.

Conclusions

In conclusion, this meta-analysis provides valuable insights into the impact of obesity on ECMO outcomes. It indicates that obesity alone does not significantly affect mortality outcomes or the duration of the ECMO procedure. However, healthcare providers should be aware of the challenges that obese patients may face during ECMO and consider tailored management approaches to optimize their care. This study contributes to a better understanding of the role of obesity in ECMO and can aid in improving the clinical decision-making process for this specific patient population.

Data availability

Data is provided within the manuscript or supplementary information files.

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XH and XL developed the concept for this review. XH designed the study. Data collection and analysis were completed by XH and XL interpreted the results. Creation of figures was completed by XH and XL wrote the article. All authors approved the final manuscript.

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Huang, X., Lin, X. Impact of obesity on outcomes of extracorporeal membrane oxygenation support: a systematic review and meta-analysis. BMC Pulm Med 24 , 157 (2024). https://doi.org/10.1186/s12890-024-02971-5

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Received : 09 December 2023

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DOI : https://doi.org/10.1186/s12890-024-02971-5

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