literature review and systematic

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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Methodology

• How to Write a Literature Review | Guide, Examples, & Templates

How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

• Search for relevant literature
• Evaluate sources
• Identify themes, debates, and gaps
• Outline the structure
• Write your literature review

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

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Table of contents

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

• Quick Run-through
• Step 1 & 2

When you write a thesis , dissertation , or research paper , you will likely have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

• Demonstrate your familiarity with the topic and its scholarly context
• Develop a theoretical framework and methodology for your research
• Position your work in relation to other researchers and theorists
• Show how your research addresses a gap or contributes to a debate
• Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

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Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

• Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
• Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
• Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
• Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

Download Word doc Download Google doc

Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research problem and questions .

Make a list of keywords

Start by creating a list of keywords related to your research question. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list as you discover new keywords in the process of your literature search.

• Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
• Body image, self-perception, self-esteem, mental health
• Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some useful databases to search for journals and articles include:

• Your university’s library catalogue
• Google Scholar
• Project Muse (humanities and social sciences)
• Medline (life sciences and biomedicine)
• EconLit (economics)
• Inspec (physics, engineering and computer science)

You can also use boolean operators to help narrow down your search.

Make sure to read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

• What question or problem is the author addressing?
• What are the key concepts and how are they defined?
• What are the key theories, models, and methods?
• Does the research use established frameworks or take an innovative approach?
• What are the results and conclusions of the study?
• How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
• What are the strengths and weaknesses of the research?

Make sure the sources you use are credible , and make sure you read any landmark studies and major theories in your field of research.

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It is important to keep track of your sources with citations to avoid plagiarism . It can be helpful to make an annotated bibliography , where you compile full citation information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

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To begin organizing your literature review’s argument and structure, be sure you understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

• Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
• Themes: what questions or concepts recur across the literature?
• Debates, conflicts and contradictions: where do sources disagree?
• Pivotal publications: are there any influential theories or studies that changed the direction of the field?
• Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

• Most research has focused on young women.
• There is an increasing interest in the visual aspects of social media.
• But there is still a lack of robust research on highly visual platforms like Instagram and Snapchat—this is a gap that you could address in your own research.

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarizing sources in order.

Try to analyze patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organize your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.

Methodological

If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

• Look at what results have emerged in qualitative versus quantitative research
• Discuss how the topic has been approached by empirical versus theoretical scholarship
• Divide the literature into sociological, historical, and cultural sources

Theoretical

A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text , your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, you can follow these tips:

• Summarize and synthesize: give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: don’t just paraphrase other researchers — add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically evaluate: mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: use transition words and topic sentences to draw connections, comparisons and contrasts

In the conclusion, you should summarize the key findings you have taken from the literature and emphasize their significance.

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

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

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Research bias

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

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

There are several reasons to conduct a literature review at the beginning of a research project:

• To familiarize yourself with the current state of knowledge on your topic
• To ensure that you’re not just repeating what others have already done
• To identify gaps in knowledge and unresolved problems that your research can address
• To develop your theoretical framework and methodology
• To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

The literature review usually comes near the beginning of your thesis or dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

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

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

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Systematic Reviews and Meta Analysis

• Getting Started
• Guides and Standards
• Review Protocols
• Databases and Sources
• Randomized Controlled Trials
• Controlled Clinical Trials
• Observational Designs
• Tests of Diagnostic Accuracy
• Software and Tools
• Where do I get all those articles?
• Collaborations
• EPI 233/528
• Countway Mediated Search
• Risk of Bias (RoB)

Systematic review Q & A

What is a systematic review.

A systematic review is guided filtering and synthesis of all available evidence addressing a specific, focused research question, generally about a specific intervention or exposure. The use of standardized, systematic methods and pre-selected eligibility criteria reduce the risk of bias in identifying, selecting and analyzing relevant studies. A well-designed systematic review includes clear objectives, pre-selected criteria for identifying eligible studies, an explicit methodology, a thorough and reproducible search of the literature, an assessment of the validity or risk of bias of each included study, and a systematic synthesis, analysis and presentation of the findings of the included studies. A systematic review may include a meta-analysis.

For details about carrying out systematic reviews, see the Guides and Standards section of this guide.

Is my research topic appropriate for systematic review methods?

A systematic review is best deployed to test a specific hypothesis about a healthcare or public health intervention or exposure. By focusing on a single intervention or a few specific interventions for a particular condition, the investigator can ensure a manageable results set. Moreover, examining a single or small set of related interventions, exposures, or outcomes, will simplify the assessment of studies and the synthesis of the findings.

Systematic reviews are poor tools for hypothesis generation: for instance, to determine what interventions have been used to increase the awareness and acceptability of a vaccine or to investigate the ways that predictive analytics have been used in health care management. In the first case, we don't know what interventions to search for and so have to screen all the articles about awareness and acceptability. In the second, there is no agreed on set of methods that make up predictive analytics, and health care management is far too broad. The search will necessarily be incomplete, vague and very large all at the same time. In most cases, reviews without clearly and exactly specified populations, interventions, exposures, and outcomes will produce results sets that quickly outstrip the resources of a small team and offer no consistent way to assess and synthesize findings from the studies that are identified.

If not a systematic review, then what?

You might consider performing a scoping review . This framework allows iterative searching over a reduced number of data sources and no requirement to assess individual studies for risk of bias. The framework includes built-in mechanisms to adjust the analysis as the work progresses and more is learned about the topic. A scoping review won't help you limit the number of records you'll need to screen (broad questions lead to large results sets) but may give you means of dealing with a large set of results.

This tool can help you decide what kind of review is right for your question.

Can my student complete a systematic review during her summer project?

Probably not. Systematic reviews are a lot of work. Including creating the protocol, building and running a quality search, collecting all the papers, evaluating the studies that meet the inclusion criteria and extracting and analyzing the summary data, a well done review can require dozens to hundreds of hours of work that can span several months. Moreover, a systematic review requires subject expertise, statistical support and a librarian to help design and run the search. Be aware that librarians sometimes have queues for their search time. It may take several weeks to complete and run a search. Moreover, all guidelines for carrying out systematic reviews recommend that at least two subject experts screen the studies identified in the search. The first round of screening can consume 1 hour per screener for every 100-200 records. A systematic review is a labor-intensive team effort.

How can I know if my topic has been been reviewed already?

Before starting out on a systematic review, check to see if someone has done it already. In PubMed you can use the systematic review subset to limit to a broad group of papers that is enriched for systematic reviews. You can invoke the subset by selecting if from the Article Types filters to the left of your PubMed results, or you can append AND systematic[sb] to your search. For example:

"neoadjuvant chemotherapy" AND systematic[sb]

The systematic review subset is very noisy, however. To quickly focus on systematic reviews (knowing that you may be missing some), simply search for the word systematic in the title:

"neoadjuvant chemotherapy" AND systematic[ti]

Any PRISMA-compliant systematic review will be captured by this method since including the words "systematic review" in the title is a requirement of the PRISMA checklist. Cochrane systematic reviews do not include 'systematic' in the title, however. It's worth checking the Cochrane Database of Systematic Reviews independently.

You can also search for protocols that will indicate that another group has set out on a similar project. Many investigators will register their protocols in PROSPERO , a registry of review protocols. Other published protocols as well as Cochrane Review protocols appear in the Cochrane Methodology Register, a part of the Cochrane Library .

• Next: Guides and Standards >>
• Last Updated: Feb 26, 2024 3:17 PM
• URL: https://guides.library.harvard.edu/meta-analysis

Literature Reviews pp 19–30 Cite as

Systematic Literature Review

• Ana Paula Cardoso Ermel   ORCID: orcid.org/0000-0002-3874-9792 5 ,
• D. P. Lacerda   ORCID: orcid.org/0000-0002-8011-3376 6 ,
• Maria Isabel W. M. Morandi   ORCID: orcid.org/0000-0003-1337-1487 7 &
• Leandro Gauss   ORCID: orcid.org/0000-0001-5708-5912 8  
• First Online: 31 August 2021

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This chapter presents the concept of Systematic Literature Review (SLR) and how it differs from the traditional ways of describing and portraying the literature. Moreover, it critically analyzes the common underlying structure among the SLR methods developed over the past years as well as highlights the improvements required.

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Systematic Literature Review or Literature Review?

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Table of Contents

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

What is a Systematic Literature Review?

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

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

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

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

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

Systematic Review vs Literature Review

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

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

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

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

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

Systematic Literature Review vs Meta Analysis

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

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Systematic, Scoping, and Other Literature Reviews: Overview

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What Is a Systematic Review?

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

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

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

Getting Help with Reviews

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

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

Doing a Systematic Review

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

Adapted from

Types of reviews, systematic review.

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

Meta-Analysis

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

Scoping Review

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

Rapid Review

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

Narrative Review

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

Umbrella Review

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

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

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How-to conduct a systematic literature review: A quick guide for computer science research

Angela carrera-rivera.

a Faculty of Engineering, Mondragon University

William Ochoa

Felix larrinaga.

b Design Innovation Center(DBZ), Mondragon University

Associated Data

• No data was used for the research described in the article.

Performing a literature review is a critical first step in research to understanding the state-of-the-art and identifying gaps and challenges in the field. A systematic literature review is a method which sets out a series of steps to methodically organize the review. In this paper, we present a guide designed for researchers and in particular early-stage researchers in the computer-science field. The contribution of the article is the following:

• • Clearly defined strategies to follow for a systematic literature review in computer science research, and
• • Algorithmic method to tackle a systematic literature review.

Graphical abstract

Specifications table

Method details

A Systematic Literature Review (SLR) is a research methodology to collect, identify, and critically analyze the available research studies (e.g., articles, conference proceedings, books, dissertations) through a systematic procedure [12] . An SLR updates the reader with current literature about a subject [6] . The goal is to review critical points of current knowledge on a topic about research questions to suggest areas for further examination [5] . Defining an “Initial Idea” or interest in a subject to be studied is the first step before starting the SLR. An early search of the relevant literature can help determine whether the topic is too broad to adequately cover in the time frame and whether it is necessary to narrow the focus. Reading some articles can assist in setting the direction for a formal review., and formulating a potential research question (e.g., how is semantics involved in Industry 4.0?) can further facilitate this process. Once the focus has been established, an SLR can be undertaken to find more specific studies related to the variables in this question. Although there are multiple approaches for performing an SLR ( [5] , [26] , [27] ), this work aims to provide a step-by-step and practical guide while citing useful examples for computer-science research. The methodology presented in this paper comprises two main phases: “Planning” described in section 2, and “Conducting” described in section 3, following the depiction of the graphical abstract.

Defining the protocol is the first step of an SLR since it describes the procedures involved in the review and acts as a log of the activities to be performed. Obtaining opinions from peers while developing the protocol, is encouraged to ensure the review's consistency and validity, and helps identify when modifications are necessary [20] . One final goal of the protocol is to ensure the replicability of the review.

Define PICOC and synonyms

The PICOC (Population, Intervention, Comparison, Outcome, and Context) criteria break down the SLR's objectives into searchable keywords and help formulate research questions [ 27 ]. PICOC is widely used in the medical and social sciences fields to encourage researchers to consider the components of the research questions [14] . Kitchenham & Charters [6] compiled the list of PICOC elements and their corresponding terms in computer science, as presented in Table 1 , which includes keywords derived from the PICOC elements. From that point on, it is essential to think of synonyms or “alike” terms that later can be used for building queries in the selected digital libraries. For instance, the keyword “context awareness” can also be linked to “context-aware”.

Planning Step 1 “Defining PICOC keywords and synonyms”.

Formulate research questions

Clearly defined research question(s) are the key elements which set the focus for study identification and data extraction [21] . These questions are formulated based on the PICOC criteria as presented in the example in Table 2 (PICOC keywords are underlined).

Research questions examples.

Select digital library sources

The validity of a study will depend on the proper selection of a database since it must adequately cover the area under investigation [19] . The Web of Science (WoS) is an international and multidisciplinary tool for accessing literature in science, technology, biomedicine, and other disciplines. Scopus is a database that today indexes 40,562 peer-reviewed journals, compared to 24,831 for WoS. Thus, Scopus is currently the largest existing multidisciplinary database. However, it may also be necessary to include sources relevant to computer science, such as EI Compendex, IEEE Xplore, and ACM. Table 3 compares the area of expertise of a selection of databases.

Planning Step 3 “Select digital libraries”. Description of digital libraries in computer science and software engineering.

Define inclusion and exclusion criteria

Authors should define the inclusion and exclusion criteria before conducting the review to prevent bias, although these can be adjusted later, if necessary. The selection of primary studies will depend on these criteria. Articles are included or excluded in this first selection based on abstract and primary bibliographic data. When unsure, the article is skimmed to further decide the relevance for the review. Table 4 sets out some criteria types with descriptions and examples.

Planning Step 4 “Define inclusion and exclusion criteria”. Examples of criteria type.

Define the Quality Assessment (QA) checklist

Assessing the quality of an article requires an artifact which describes how to perform a detailed assessment. A typical quality assessment is a checklist that contains multiple factors to evaluate. A numerical scale is used to assess the criteria and quantify the QA [22] . Zhou et al. [25] presented a detailed description of assessment criteria in software engineering, classified into four main aspects of study quality: Reporting, Rigor, Credibility, and Relevance. Each of these criteria can be evaluated using, for instance, a Likert-type scale [17] , as shown in Table 5 . It is essential to select the same scale for all criteria established on the quality assessment.

Planning Step 5 “Define QA assessment checklist”. Examples of QA scales and questions.

Define the “Data Extraction” form

The data extraction form represents the information necessary to answer the research questions established for the review. Synthesizing the articles is a crucial step when conducting research. Ramesh et al. [15] presented a classification scheme for computer science research, based on topics, research methods, and levels of analysis that can be used to categorize the articles selected. Classification methods and fields to consider when conducting a review are presented in Table 6 .

Planning Step 6 “Define data extraction form”. Examples of fields.

The data extraction must be relevant to the research questions, and the relationship to each of the questions should be included in the form. Kitchenham & Charters [6] presented more pertinent data that can be captured, such as conclusions, recommendations, strengths, and weaknesses. Although the data extraction form can be updated if more information is needed, this should be treated with caution since it can be time-consuming. It can therefore be helpful to first have a general background in the research topic to determine better data extraction criteria.

After defining the protocol, conducting the review requires following each of the steps previously described. Using tools can help simplify the performance of this task. Standard tools such as Excel or Google sheets allow multiple researchers to work collaboratively. Another online tool specifically designed for performing SLRs is Parsif.al 1 . This tool allows researchers, especially in the context of software engineering, to define goals and objectives, import articles using BibTeX files, eliminate duplicates, define selection criteria, and generate reports.

Build digital library search strings

Search strings are built considering the PICOC elements and synonyms to execute the search in each database library. A search string should separate the synonyms with the boolean operator OR. In comparison, the PICOC elements are separated with parentheses and the boolean operator AND. An example is presented next:

(“Smart Manufacturing” OR “Digital Manufacturing” OR “Smart Factory”) AND (“Business Process Management” OR “BPEL” OR “BPM” OR “BPMN”) AND (“Semantic Web” OR “Ontology” OR “Semantic” OR “Semantic Web Service”) AND (“Framework” OR “Extension” OR “Plugin” OR “Tool”

Gather studies

Databases that feature advanced searches enable researchers to perform search queries based on titles, abstracts, and keywords, as well as for years or areas of research. Fig. 1 presents the example of an advanced search in Scopus, using titles, abstracts, and keywords (TITLE-ABS-KEY). Most of the databases allow the use of logical operators (i.e., AND, OR). In the example, the search is for “BIG DATA” and “USER EXPERIENCE” or “UX” as a synonym.

Example of Advanced search on Scopus.

In general, bibliometric data of articles can be exported from the databases as a comma-separated-value file (CSV) or BibTeX file, which is helpful for data extraction and quantitative and qualitative analysis. In addition, researchers should take advantage of reference-management software such as Zotero, Mendeley, Endnote, or Jabref, which import bibliographic information onto the software easily.

Study Selection and Refinement

The first step in this stage is to identify any duplicates that appear in the different searches in the selected databases. Some automatic procedures, tools like Excel formulas, or programming languages (i.e., Python) can be convenient here.

In the second step, articles are included or excluded according to the selection criteria, mainly by reading titles and abstracts. Finally, the quality is assessed using the predefined scale. Fig. 2 shows an example of an article QA evaluation in Parsif.al, using a simple scale. In this scenario, the scoring procedure is the following YES= 1, PARTIALLY= 0.5, and NO or UNKNOWN = 0 . A cut-off score should be defined to filter those articles that do not pass the QA. The QA will require a light review of the full text of the article.

Performing quality assessment (QA) in Parsif.al.

Data extraction

Those articles that pass the study selection are then thoroughly and critically read. Next, the researcher completes the information required using the “data extraction” form, as illustrated in Fig. 3 , in this scenario using Parsif.al tool.

Example of data extraction form using Parsif.al.

The information required (study characteristics and findings) from each included study must be acquired and documented through careful reading. Data extraction is valuable, especially if the data requires manipulation or assumptions and inferences. Thus, information can be synthesized from the extracted data for qualitative or quantitative analysis [16] . This documentation supports clarity, precise reporting, and the ability to scrutinize and replicate the examination.

Analysis and Report

The analysis phase examines the synthesized data and extracts meaningful information from the selected articles [10] . There are two main goals in this phase.

The first goal is to analyze the literature in terms of leading authors, journals, countries, and organizations. Furthermore, it helps identify correlations among topic s . Even when not mandatory, this activity can be constructive for researchers to position their work, find trends, and find collaboration opportunities. Next, data from the selected articles can be analyzed using bibliometric analysis (BA). BA summarizes large amounts of bibliometric data to present the state of intellectual structure and emerging trends in a topic or field of research [4] . Table 7 sets out some of the most common bibliometric analysis representations.

Techniques for bibliometric analysis and examples.

Several tools can perform this type of analysis, such as Excel and Google Sheets for statistical graphs or using programming languages such as Python that has available multiple  data visualization libraries (i.e. Matplotlib, Seaborn). Cluster maps based on bibliographic data(i.e keywords, authors) can be developed in VosViewer which makes it easy to identify clusters of related items [18] . In Fig. 4 , node size is representative of the number of papers related to the keyword, and lines represent the links among keyword terms.

[1] Keyword co-relationship analysis using clusterization in vos viewer.

This second and most important goal is to answer the formulated research questions, which should include a quantitative and qualitative analysis. The quantitative analysis can make use of data categorized, labelled, or coded in the extraction form (see Section 1.6). This data can be transformed into numerical values to perform statistical analysis. One of the most widely employed method is frequency analysis, which shows the recurrence of an event, and can also represent the percental distribution of the population (i.e., percentage by technology type, frequency of use of different frameworks, etc.). Q ualitative analysis includes the narration of the results, the discussion indicating the way forward in future research work, and inferring a conclusion.

Finally, the literature review report should state the protocol to ensure others researchers can replicate the process and understand how the analysis was performed. In the protocol, it is essential to present the inclusion and exclusion criteria, quality assessment, and rationality beyond these aspects.

The presentation and reporting of results will depend on the structure of the review given by the researchers conducting the SLR, there is no one answer. This structure should tie the studies together into key themes, characteristics, or subgroups [ 28 ].

SLR can be an extensive and demanding task, however the results are beneficial in providing a comprehensive overview of the available evidence on a given topic. For this reason, researchers should keep in mind that the entire process of the SLR is tailored to answer the research question(s). This article has detailed a practical guide with the essential steps to conducting an SLR in the context of computer science and software engineering while citing multiple helpful examples and tools. It is envisaged that this method will assist researchers, and particularly early-stage researchers, in following an algorithmic approach to fulfill this task. Finally, a quick checklist is presented in Appendix A as a companion of this article.

CRediT author statement

Angela Carrera-Rivera: Conceptualization, Methodology, Writing-Original. William Ochoa-Agurto : Methodology, Writing-Original. Felix Larrinaga : Reviewing and Supervision Ganix Lasa: Reviewing and Supervision.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

Funding : This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant No. 814078.

Carrera-Rivera, A., Larrinaga, F., & Lasa, G. (2022). Context-awareness for the design of Smart-product service systems: Literature review. Computers in Industry, 142, 103730.

1 https://parsif.al/

Data Availability

Easy guide to conducting a systematic review

Affiliations.

• 1 Discipline of Child and Adolescent Health, University of Sydney, Sydney, New South Wales, Australia.
• 2 Department of Nephrology, The Children's Hospital at Westmead, Sydney, New South Wales, Australia.
• 3 Education Department, The Children's Hospital at Westmead, Sydney, New South Wales, Australia.
• PMID: 32364273
• DOI: 10.1111/jpc.14853

A systematic review is a type of study that synthesises research that has been conducted on a particular topic. Systematic reviews are considered to provide the highest level of evidence on the hierarchy of evidence pyramid. Systematic reviews are conducted following rigorous research methodology. To minimise bias, systematic reviews utilise a predefined search strategy to identify and appraise all available published literature on a specific topic. The meticulous nature of the systematic review research methodology differentiates a systematic review from a narrative review (literature review or authoritative review). This paper provides a brief step by step summary of how to conduct a systematic review, which may be of interest for clinicians and researchers.

Keywords: research; research design; systematic review.

© 2020 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).

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Systematic Reviews

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What Makes a Systematic Review Different from Other Types of Reviews?

• Planning Your Systematic Review
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• Grey Literature
• Managing & Appraising Results
• Further Resources

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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Systematic Reviews

Describes what is involved with conducting a systematic review of the literature for evidence-based public health and how the librarian is a partner in the process.

Several CDC librarians have special training in conducting literature searches for systematic reviews.  Literature searches for systematic reviews can take a few weeks to several months from planning to delivery.

Fill out a search request form here  or contact the Stephen B. Thacker CDC Library by email  [email protected] or telephone 404-639-1717.

Campbell Collaboration

Cochrane Collaboration

Eppi Centre

Joanna Briggs Institute

McMaster University

PRISMA Statement

Systematic Reviews – CRD’s Guide

Systematic Reviews of Health Promotion and Public Health Interventions

The Guide to Community Preventive Services

Look for systematic reviews that have already been published. 

• To ensure that the work has not already been done.
• To provides examples of search strategies for your topic

Look in PROSPERO for registered systematic reviews.

Search Cochrane and CRD-York for systematic reviews.

Search filter for finding systematic reviews in PubMed

Other search filters to locate systematic reviews

A systematic review attempts to collect and analyze all evidence that answers a specific question.  The question must be clearly defined and have inclusion and exclusion criteria. A broad and thorough search of the literature is performed and a critical analysis of the search results is reported and ultimately provides a current evidence-based answer  to the specific question.

Time:  According to Cochrane , it takes 18 months on average to complete a Systematic Review.

The average systematic review from beginning to end requires 18 months of work. “…to find out about a healthcare intervention it is worth searching research literature thoroughly to see if the answer is already known. This may require considerable work over many months…” ( Cochrane Collaboration )

Review Team: Team Members at minimum…

• Content expert
• 2 reviewers
• 1 tie breaker
• 1 statistician (meta-analysis)
• 1 economist if conducting an economic analysis
• *1 librarian (expert searcher) trained in systematic reviews

“Expert searchers are an important part of the systematic review team, crucial throughout the review process-from the development of the proposal and research question to publication.” ( McGowan & Sampson, 2005 )

*Ask your librarian to write a methods section regarding the search methods and to give them co-authorship. You may also want to consider providing a copy of one or all of the search strategies used in an appendix.

The Question to Be Answered: A clearly defined and specific question or questions with inclusion and exclusion criteria.

Written Protocol: Outline the study method, rationale, key questions, inclusion and exclusion criteria, literature searches, data abstraction and data management, analysis of quality of the individual studies, synthesis of data, and grading of the evidience for each key question.

Literature Searches:  Search for any systematic reviews that may already answer the key question(s).  Next, choose appropriate databases and conduct very broad, comprehensive searches.  Search strategies must be documented so that they can be duplicated.  The librarian is integral to this step of the process. Before your librarian creates a search strategy and starts searching in earnest you should write a detailed PICO question , determine the inclusion and exclusion criteria for your study, run a preliminary search, and have 2-4 articles that already fit the criteria for your review.

What is searched depends on the topic of the review but should include…

• At least 3 standard medical databases like PubMed/Medline, CINAHL, Embase, etc..
• At least 2 grey literature resources like Clinicaltrials.gov, COS Conference Papers Index, Grey Literature Report,  etc…

Citation Management: EndNote is a bibliographic management tools that assist researchers in managing citations.  The Stephen B. Thacker CDC Library oversees the site license for EndNote.

To request installation:   The library provides EndNote  to CDC staff under a site-wide license. Please use the ITSO Software Request Tool (SRT) and submit a request for the latest version (or upgraded version) of EndNote. Please be sure to include the computer name for the workstation where you would like to have the software installed.

EndNote Training:   CDC Library offers training on EndNote on a regular basis – both a basic and advanced course. To view the course descriptions and upcoming training dates, please visit the CDC Library training page .

For assistance with EndNote software, please contact [email protected]

Vendor Support and Services:   EndNote – Support and Services (Thomson Reuters)  EndNote – Tutorials and Live Online Classes (Thomson Reuters)

Getting Articles:

Articles can be obtained using DocExpress or by searching the electronic journals at the Stephen B. Thacker CDC Library.

IOM Standards for Systematic Reviews: Standard 3.1: Conduct a comprehensive systematic search for evidence

The goal of a systematic review search is to maximize recall and precision while keeping results manageable. Recall (sensitivity) is defined as the number of relevant reports identified divided by the total number of relevant reports in existence. Precision (specificity) is defined as the number of relevant reports identified divided by the total number of reports identified.

Issues to consider when creating a systematic review search:   

• All concepts are included in the strategy
• All appropriate subject headings are used
• Appropriate use of explosion
• Appropriate use of subheadings and floating subheadings
• Use of natural language (text words) in addition to controlled vocabulary terms
• Use of appropriate synonyms, acronyms, etc.
• Truncation and spelling variation as appropriate
• Appropriate use of limits such as language, years, etc.
• Field searching, publication type, author, etc.
• Boolean operators used appropriately
• Line errors: when searches are combined using line numbers, be sure the numbers refer to the searches intended
• Check indexing of relevant articles
• Search strategy adapted as needed for multiple databases
• Cochrane Handbook: Searching for Studies See Part 2, Chapter 6

A step-by-step guide to systematically identify all relevant animal studies

Materials listed in these guides are selected to provide awareness of quality public health literature and resources. A material’s inclusion does not necessarily represent the views of the U.S. Department of Health and Human Services (HHS), the Public Health Service (PHS), or the Centers for Disease Control and Prevention (CDC), nor does it imply endorsement of the material’s methods or findings. HHS, PHS, and CDC assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by HHS, PHS, and CDC. Opinion, findings, and conclusions expressed by the original authors of items included in these materials, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of HHS, PHS, or CDC. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by HHS, PHS, or CDC.

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• Open access
• Published: 06 December 2022

What improves access to primary healthcare services in rural communities? A systematic review

• Zemichael Gizaw 1 ,
• Tigist Astale 2 &
• Getnet Mitike Kassie 2  

BMC Primary Care volume  23 , Article number:  313 ( 2022 ) Cite this article

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To compile key strategies from the international experiences to improve access to primary healthcare (PHC) services in rural communities. Different innovative approaches have been practiced in different parts of the world to improve access to essential healthcare services in rural communities. Systematically collecting and combining best experiences all over the world is important to suggest effective strategies to improve access to healthcare in developing countries. Accordingly, this systematic review of literature was undertaken to identify key approaches from international experiences to enhance access to PHC services in rural communities.

All published and unpublished qualitative and/or mixed method studies conducted to improvement access to PHC services were searched from MEDLINE, Scopus, Web of Science, WHO Global Health Library, and Google Scholar. Articles published other than English language, citations with no abstracts and/or full texts, and duplicate studies were excluded. We included all articles available in different electronic databases regardless of their publication years. We assessed the methodological quality of the included studies using mixed methods appraisal tool (MMAT) version 2018 to minimize the risk of bias. Data were extracted using JBI mixed methods data extraction form. Data were qualitatively analyzed using emergent thematic analysis approach to identify key concepts and coded them into related non-mutually exclusive themes.

Our analysis of 110 full-text articles resulted in ten key strategies to improve access to PHC services. Community health programs or community-directed interventions, school-based healthcare services, student-led healthcare services, outreach services or mobile clinics, family health program, empanelment, community health funding schemes, telemedicine, working with traditional healers, working with non-profit private sectors and non-governmental organizations including faith-based organizations are the key strategies identified from international experiences.

This review identified key strategies from international experiences to improve access to PHC services in rural communities. These strategies can play roles in achieving universal health coverage and reducing disparities in health outcomes among rural communities and enabling them to get healthcare when and where they want.

Peer Review reports

Introduction

Universal health coverage (UHC) is used to provide expanding services to eliminate access barriers. Universal health coverage is defined by the world health organization (WHO) as access to key promotional, preventive, curative and rehabilitative health services for all at an affordable rate and ensuring equity in access. The term universal has been described as the State's legal obligation to provide healthcare to all its citizens, with particular attention to ensuring that all poor and excluded groups are included [ 1 , 2 , 3 ].

Strengthening primary healthcare (PHC) is the most comprehensive, reliable and productive approach to improving people's physical and mental wellbeing and social well-being, and that PHC is a pillar of a sustainable health system for UHC and health-related sustainable development goals [ 4 , 5 ]. Despite tremendous progress over the last decades, there are still unaddressed health needs of people in all parts of the world [ 6 , 7 ]. Many people, particularly the poor and people living in rural areas and those who are in vulnerable circumstances, face challenges to remain healthy [ 8 ].

Geographical and financial inaccessibility, inadequate funding, inconsistent medication supply and equipment and personnel shortages have left the reach, availability and effect of PHC services in many countries disappointingly limited [ 9 , 10 ]. A recent Astana Declaration recognized those aspects of PHC need to be changed to adapt adequately to current and emerging threats to the healthcare system. This declaration discussed that implementation of a need-based, comprehensive, cost-effective, accessible, efficient and sustainable healthcare system is needed for disadvantaged and rural populations in more local and convenient settings to provide care when and where they want it [ 8 ].

Different innovative approaches have been practiced in different parts of the world to improve access to essential healthcare services in rural communities. Systematically collecting and combining best experiences all over the world is important to suggest effective strategies to improve access to healthcare in developing countries. Accordingly, this systematic review of literature was undertaken to identify key approaches from international experiences to enhance access to PHC services in rural communities. The findings of this systematic literature review can be used by healthcare professionals, researchers and policy makers to improve healthcare service delivery in rural communities.

Methodology

Research question.

What improves access to PHC services in rural communities? We used the PICO (population, issue/intervention, comparison/contrast, and outcome) construct to develop the search question [ 11 ]. The population is rural communities or remote communities in developing countries who have limited access to healthcare services. Moreover, we extended the population to developed countries to capture experiences of both developing and developed countries. The issue/intervention is implementation of different community-based health interventions to access to essential healthcare services. In this systematic review, we focused on PHC health services, mainly essential or basic healthcare services, community or public health services, and health promotion or health education. Primary healthcare is “a health care system that addressed social, economic, and political causes of poor health promotes health though health services at the primary care level enhances health of the community” [ 12 ]. Comparison/contrast is not appropriate for this review. The outcome is improved access to essential healthcare services.

Outcome measures

The outcome of this review is access to PHC services, such as preventive, promotive, curative, rehabilitative, and palliative health services which are affordable, convenient or acceptable, and available to all who need care.

Criteria for considering studies for this review

All published and unpublished qualitative and/or mixed method studies conducted to improve access to PHC services were included. Government and international or national organizations reports were also included. Different organizations whose primary mission is health or promotion of community health were selected. We included articles based on these eligibility criteria: context or scope of studies (access to PHC services), article type (primary studies), and publication language (English). Articles published other than English language, citations with no abstracts and/or full texts, reviews, and duplicate studies were excluded. We included all articles available in different electronic databases regardless of their publication years. We didn’t use time of publication for screening.

Information sources and search strategy

We searched relevant articles from MEDLINE, Scopus, Web of Science, WHO Global Health Library, and Google Scholar to access all forms of evidence. An initial search of MEDLINE was undertaken followed by analysis of the text words contained in the title and abstract, and of the index terms used to describe articles. We used the aforementioned performance indicators of PHC delivery and the PICO as we described above to choose keywords. A second search using all identified keywords and index terms was undertaken across all included databases. Thirdly, references of all identified articles were searched to get additional studies. The full electronic search strategy for MEDLINE, a major database we used for this review is included as a supplementary file (Additional file 1 : Appendix 1).

Study selection and assessment of methodological quality

Search results from different electronic databases were exported to Endnote reference manager version 7 to remove duplication. Two independent reviewers (ZG and BA) screened out records. An initial screening of titles and abstracts was done based on the PICO criteria and language of publication. Secondary screening of full-text papers was done for studies we included at the initial screening phase. We further investigated and assessed records included in the full-text articles against the inclusion and exclusion criteria. We sat together and discussed the eligibility assessment. The interrater agreement was 90%. We resolved disagreements by consensus for points we had different rating. We used the PRISMA flow diagram to summarize the study selection processes.

Methodological quality of the included studies was assessed using mixed methods appraisal tool (MMAT) version 2018 [ 13 ]. As it is clearly indicated in the user guide of the MMAT tool, it is discouraged to calculate an overall score from the ratings of each criterion. Instead, it is advised to provide a more detailed presentation of the ratings of each criterion to better inform quality of the included studies. The rating of each criterion was, therefore, done as per the detail explanations included in the guideline. Almost all the included full text articles fulfilled the criteria and all the included full text articles were found to be better quality.

Data extraction

We independently extracted data from papers included in the review using JBI mixed methods data extraction form. This form is only used for reviews that follow a convergent integrated approach, i.e. integration of qualitative data and qualitative data [ 14 ]. The data extraction form was piloted on randomly selected papers and modified accordingly. One reviewer extracted the data from the included studies and the second reviewer checked the extracted data. Disagreements were resolved by discussion between the two reviewers. Information was extracted from each included study on: list of authors, year of publication, study area, population of interest, study type, methods, focus of the studies, main findings, authors’ conclusion, and limitations of the study.

Synthesis of findings

The included full-text articles were qualitatively analyzed using emergent thematic analysis approach to identify key concepts and coded them into related non-mutually exclusive themes. Themes are strategies mentioned or discussed in the included records to improve access to PHC services. Themes were identified manually by reading the included records again and again. We then synthesized each theme by comparing the discussion and conclusion of the included articles.

Systematic review registration number

The protocol of this review is registered in PROSPERO (the registration number is: CRD42019132592) to avoid unplanned duplication and to enable comparison of reported review methods with what was planned in the protocol. It is available at https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019132592 .

Schematic of the systematic review and reporting of the search

We used PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2009 checklist [ 15 ] for reporting of this systematic review.

Study selection

The search strategy identified 1148 titles and abstracts [914 from PubMed (Table 1 ) and 234 from other sources] as of 10 March 2022. We obtained 900 after we removed duplicated articles. Following assessment by title and abstract, 485 records were excluded because these records did not meet the criteria as mentioned in the method section. Additional 256 records were discarded because the records did not discuss the outcome of interest well and some records were systematic reviews. The full text of the remaining 159 records was examined in more detail. It appeared that 49 studies did not meet the inclusion criteria as described in the method section. One hundred ten records met the inclusion criteria and were included in the systematic review or synthesis (Fig.  1 ).

Study selection flow diagram

Of 900 articles resulting from the search term, 110 (12.2%) met the inclusion criteria. The included full-text articles were published between 1993 and 2021. Ninety-two (83.6%) of the included full-text articles were research articles, 5(4.5%) were technical reports, 3 (2.7%) were perspective, 4 (3.6%) was discussion paper, 3(2.7%) were dissertation or thesis, 2 (1.8%) were commentary, and 1 (0.9) was a book. Thirty-six (33%) and 29 (26%) of the included full-text articles were conducted in Africa and North America, respectively (Fig.  2 ).

Regions where the included full-test articles conducted

Key strategies identified

The analysis of 110 full-text articles resulted in 10 themes. The themes are key strategies to improve access to PHC services in rural communities. The key strategies identified are community health programs or community-directed healthcare interventions, school-based healthcare services, student-led healthcare services, outreach services or mobile clinics, family health program, empanelment, community health funding schemes, telemedicine, promoting the role of traditional medicine, working with non-profit private sectors and non-governmental organizations (NGOs) including faith-based organizations (Table 2 ).

Description of strategies

a. Community health programs or community-directed healthcare interventions

Twenty-four (21.8%) of the full-text articles included in this review discussed that community health programs (CHPs) or community-directed healthcare interventions are best strategies to provide basic health and medical care close to the community to increase access and coverage of essential health services. Community health programs are locally based health promotion, disease prevention, and treatment programs available typically to communities in need and community-directed intervention strategy is an approach in which communities themselves direct the planning and implementation of intervention delivery. Rural communities, especially, in developing countries have no access to healthcare facilities in the near distance and have less chance to receive healthcare from doctors, health officers, nurses or midwives. In response to this critical problems, many countries have been investing heavily in community based primary health care to bring services to rural and remote areas where most of the population lives. Community health programs include construction of health posts or community health centers close to the community and deployment of community health workers (CHWs), such as health extension workers, to reach-out every village, who play a prominent role as the gatekeepers of healthcare in rural communities. Community-directed healthcare intervention is an approach in which communities themselves direct the planning and implementation of healthcare interventions. Community participation remains crucial in the identification of health problems, planning or designing of health interventions and implementation of the interventions, which enhances need-based and demand-driven provision of health services while promoting sustainability and ownership (Additional file 2 : Appendix 2, Table A1).

b. School-based primary healthcare

In this review, 9 of 110 (8.2%) of the included full-text articles pointed out that school-based healthcare services can be effective to improve access to PHC services. School-based health services are health programs that offer health care to children and youth either in a school or on school grounds and usually staffed according to school community needs and resources. School-based health services provide a variety of healthcare services to underserved children, youth and vulnerable populations in a convenient and accessible environment. Access to comprehensive health services via schools leads to improved access to healthcare (Additional file 3 : Appendix 3, Table A2).

c. Student-led healthcare services

In this review, 5 of 110 (4.5%) of the full-text articles discussed that the use of medical and health science students as healthcare service providers can minimize problems related with shortage of health professionals in rural healthcare system and can play appreciable roles to minimize healthcare service access problems in rural communities. Student-led healthcare services are developed through consultation between universities and local health providers and are purposefully designed clinical placements with a focus on clinical educational activities for pre-registration students. Student-led clinics link students, healthcare professionals, community-based organizations, universities, and communities. In this approach, students can gain practical experience in an interdisciplinary setting and through exposure to a community with unique and severe needs (Additional file 4 : Appendix 4, Table A3).

d. Outreach services or mobile clinics

In this systematic literature review, 18 of 110 (16.4%) of the included studies discussed that outreach services or mobile clinics in primary care and rural hospital settings can improve access to PHC services in rural communities. Mobile outreach service is defined as healthcare services provided by a mobile team of trained providers, from a higher-level health facility to a lower-level health facilities or locally available community facilities that are not used for clinical services, such as schools, health posts, or other community structures. Outreach services improve access to specialists and hospital-based services, strengthen connections between specialists and PHC providers, and give the benefits of consultations in primary care settings. Specialist outreach services have the potential to overcome access barriers faced by disadvantaged rural and remote communities. Furthermore, a community-based mobile clinics can be effective in uncovering illness and in directing patients to a healthcare home (Additional file 5 : Appendix 5, Table A4).

e. Family health program

Four (3.6%) of the included full-text articles discussed that family health program (FHP) is highly cost-effective tool for improving access to healthcare services for deprived areas (such as rural communities). Family health program means the program is a program designed to provide primary care as well as the prevention and early treatment of communicable and non-communicable diseases in defined populations by deploying interdisciplinary healthcare teams include physicians, nurses, nurse assistants, and full-time community health agents. It has evolved into a robust approach to providing primary care for defined populations by deploying interdisciplinary healthcare teams. The nucleus of each team includes a physician, a nurse, a nurse assistant, and full-time community health agents. This approach is effective on improving access to healthcare and eliminating health disparities (Additional file 6 : Appendix 6, Table A5).

f. Empanelment

This systematic review of literature identified that empanelment (also known as rostering) is a best strategy to proactively provide coordinated primary healthcare towards achieving universal health coverage. Empanelment is a continuous, iterative set of processes that identify and assign populations to facilities, care teams, or primary care providers who have a responsibility to know their assigned population. It enables health systems to improve health outcomes and to reduce costs. Empanelment establishes a point of care for individuals and simultaneously holds primary healthcare providers and care teams accountable for actively managing care for a specific group of individuals (Additional file 7 : Appendix 7, Table A6).

g. Community health funding schemes

In this systematic review of literature, 11 (10%) of the included articles discussed that community health funding schemes such as community-based health insurance (CBHI) increases access to healthcare services in low-income rural communities. Community-based health insurance schemes are usually voluntary and characterized by community members pooling funds to offset the cost of healthcare. Moreover, this approach is effective to mobilize domestic resources for health at low income levels. For low-income countries, community health financing has modest ability to increase the total amount of funds for healthcare. Properly structured community health financing system can significantly improve efficiency, reduce the cost of healthcare, improve quality and health outcomes, and pool risks. Community-financing schemes could improve preventive services and reduce the incidence of diseases. It could also improve people’s access to healthcare and the quality of services, thus improving their health status. Community health financing could also improve risk pooling and reduce health-induced impoverishment. Community health insurance has potential positive impacts on health and social security (Additional file 8 : Appendix 8, Table A7).

h. Telemedicine

In this review, 13 of 110 (11.8%) articles discussed that telemedicine is one of the solutions for rural subspecialty healthcare delivery. Telemedicine can be defined as the use of technology (computers, video, phone, messaging) by a medical professional to diagnose and treat patients in a remote location. The provision of subspecialty services using telemedicine to a remote and medically underserved population provides improved access to subspecialty care. Telemedicine brings sustainable healthcare to rural populations. Use of information and communication technologies in support of health and health-related fields, including healthcare services, health surveillance, health education, and health research has the potential to greatly improve health service efficiency, expand or scale up treatment delivery to thousands of patients in the rural populations (Additional file 9 : Appendix 9, Table A8).

i. Promoting the role of traditional medicine

Seven (6.4%) of the included articles showed that incorporating traditional healers into public health system addresses healthcare needs of people with limited access to allopathic medicine. Traditional medicine is the sum total of the knowledge, skill, and practices based on the theories, beliefs, and experiences indigenous to different cultures, whether explicable or not, used in the maintenance of health as well as in the prevention, diagnosis, improvement or treatment of physical and mental illness. Knowledge about traditional medicine has a catalyzing effect in meeting health sector development objectives. Integrating traditional medicine into national health systems in combination with national policy and regulation for products, practices and providers can enhance access to PHC services in remote populations (Additional file 10 : Appendix 10, Table A9).

j. Working with non-profit private sectors and non-governmental organizations

In this systematic review, 15 of 110 (13.6%) of the included articles revealed that working with non-profit private sectors and NGOs strengthens the healthcare system. Involving the non-profit private sectors, faith-based organizations (FBOs), and NGOs for health system strengthening eventually contributes to create a healthcare system reflecting an increased efficiency, more equity and good governance in health. International and local NGOs have endeavored to fill the gaps in access to healthcare services, research and advocacy. Non-profit private sectors and NGOs have a key role in improving health in low- and middle-income countries. With networks that reach even the most remote communities, many FBOs are well positioned to promote demand and access for healthcare services. Partnership among FBOs is critical in increasing access to healthcare services, and ensuring sustainability by influencing behaviors at the community, family and individual level. Faith-based organizations play an integral role in the healthcare system by increasing health seeking behaviors and delivering supportive services that address common access and cultural barriers (Additional file 11 : Appendix 11, Table A10).

This systematic literature review found that community health programs or community-directed healthcare interventions, school-based healthcare services, student-led healthcare services, outreach services or mobile clinics, family health program, empanelment, community health funding schemes, telehealth, integrative medicine, and working with non-profit private sectors and NGOs are key strategies to improve access to PHC services in rural communities. The identified strategies address the four major pillars of primary healthcare (i.e., community participation, inter-sectoral coordination, appropriate technology, and support mechanism made available) [ 126 ]. Moreover, the identified strategies are effective to improve access to healthcare services to rural communities. Moreover, the identified strategies are effective to solve shortage of manpower and to build knowledge and skill of the local health workforces in rural healthcare system. The ability of a healthcare system to meet health needs of the population depends largely on the knowledge, skills, motivation and deployment of the people responsible for organizing and delivering health services. The results of this review can strengthen the health information system, which are core elements of the healthcare system that ensure community engagement through dissemination and use of timely and reliable health information to rural populations. This review also suggests strategies to narrow down the health disparities among rural populations, which is wide in most Least and Middle Income Countries (LMICs). Healthcare services are usually disproportionately concentrated in major urban areas. As a result, rural communities face growing health disparities, largely attributed to weak policies, inefficiencies, poor leadership, and governance in healthcare system.

This review identified that community health programs or community-directed healthcare interventions address health disparities by ensuring equitable access to health resources in communities where health equity is limited by socioeconomic and geographical factors. Community health programs include identifying and prioritizing public health problems in a specific geographic area; designing and implementing public health interventions (such as establishing community health centers, mobile clinics, and outreach programs); providing services (such as health education, screenings, social support, and counseling), and deploying community health workers to promote healthy behaviors; advocating for improved care for populations at risk; and working with stakeholders to address community healthcare needs [ 16 , 17 , 18 , 127 , 128 , 129 , 130 ]. The community-oriented PHC model which is socially responsive medicine makes a healthcare system more rational, accountable, appropriate, and socially relevant to the public. Consequently, this model serves as a paradigm for reforming healthcare systems. Community-directed interventions can be considered as a realistic means to increase accessibility of interventions at community-level in rural areas [ 32 , 33 , 34 , 35 , 36 , 37 , 38 ]. This approach is best in situations where there are cultural barriers to implement interventions because this strategy is effective to develop ownership in the community. In-service and on-the-job training for community health workers, close supervision and government support, and program evaluation is very important to strengthen the community health program [ 131 , 132 , 133 ].

This review identified that school-based PHC services are effective strategies to improve access to PHC services. School-based health services provide a variety of healthcare services to children, youth and vulnerable populations in a convenient and accessible environment which indirectly improve leadership and governance. Science teachers and home room teachers play important roles to implement this strategy. It impacts on delivering preventive care such as immunizations, managing chronic illnesses and providing reproductive health services for adolescents. Comprehensive health services via schools improve access to healthcare information [ 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 ]. Access to school around the world increased drastically in the last century [ 134 ]. This high schooling rate is a good opportunity to provide healthcare services to school learners in accessible places and to disseminate health messages to families. Prior researches suggest that school-based healthcare services increase access to healthcare by increasing utilization of primary care, prevention services, and health maintenance visits [ 135 , 136 ]. Including science teachers, home room teachers, school principals, students, communities, community health workers, and other interested parties in the school-based healthcare system as main actors or promoters must be considered to sustain the impact. Health and education sectors should work in collaboration with the above-mentioned actors to plan, implement and monitor the progress. School-based healthcare services are preferable in situations when there is high schooling rate and limited access to healthcare institutions. This strategy is also an alternative way in areas where the health seeking behavior of the community is low.

The use of medical and health science students in rural healthcare system was identified as a key strategy to minimize health inequalities in rural communities due to shortages in health workforce and distribution of healthcare resources [ 49 , 50 , 51 , 52 , 53 ]. Student-led health intervention is an alternative approach to provide essential healthcare services to the community where there is shortage of healthcare workers [ 137 , 138 ]. Students will have opportunities to learn professional skills and competencies while they are providing healthcare services to the community. Moreover, benefits for student learning include increased communication, collaboration, and leadership skills [ 53 , 139 ]. Student-led health intervention also enables increased access to services, more time for assessments and treatments, increased depth of health teaching, holistic and integrated healthcare, and free health supports [ 140 , 141 , 142 , 143 ]. However, the use of medical and health science students in the rural healthcare system may have ethical and competency issues. Supporting strategies such as close supervision, preparing clear protocols, and including senior experts in the team should be considered.

This systematic review of literature found that outreach services or mobile clinics can improve access to PHC service delivery in rural populations [ 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 ]. In developing countries, the highest proportion of people lives in rural areas where doctor services are not available. Rural communities travel to major cities to get specialist services. This reflects a desire for closer integration between primary and secondary care. Specialist outreach services or mobile clinics have become one of the effective solution to solve health disparities, to improve access to healthcare services, and to build capacity of local healthcare workforces. This strategy is preferable in situations when there are high loads in tertiary or referral level hospitals and when there is high patient leakage in the referral system [ 63 , 64 , 65 , 66 , 67 , 68 , 69 ]. However, the implementation may not be easy. It needs well established healthcare system and budget. Moreover, the efficiency of care may be lower compared with hospital-based cares and the effect on patients’ health outcomes might be small [ 56 , 57 , 61 ] . Irregular specialist visits in rural areas may not have real impacts unless the services are sustainable with a strong commitment at national and local levels. Outreach activities should be included in health policies with strong leadership, healthcare financing, and private initiatives must be encouraged to maintain the activities over time.

This review revealed that FHP is highly effective tool for improving health for rural communities. The FHP has provided a new, more robust model of primary healthcare services designed to provide accessible, first contact, comprehensive, and whole person care that is coordinated with other healthcare services. It has positive results to improved availability, access to, and use of health services, and improved health indicators, such as reduced infant mortality, improved detection of cases of neglected diseases, and reduced health disparities [ 73 , 144 , 145 , 146 ]. The FHP deploys interdisciplinary healthcare teams. The team includes a physician, a nurse, a nurse assistant, and full-time community health agents. Family health teams are organized geographically. The teams are responsible for delivering public health interventions [ 72 , 74 ]. Family health program is an alternative strategy in rural healthcare system in situations when there are inequities in access to care; when there is high hospitalization rate; when there is low health seeking behavior in the community; and when there is poor case detecting and reporting system. Despite these remarkable achievements, the FHP has some challenges include difficulties in the recruitment and retention of doctors trained appropriately to deliver primary healthcare, large variations in quality of local care, patchy integration of primary care services with existing secondary and tertiary care, and slow adoption of FHP in large population [ 147 ].

In this review, empanelment has been identified as a best strategy to deliver coordinated primary healthcare towards achieving universal health coverage [ 76 , 77 , 78 , 79 ]. The goal of empanelment is provide people-centered healthcare services based on their needs to ensure that every established patient receives optimal care, whether he/she regularly visits healthcare centers. Major activities in this approach include assignment of all patients to a healthcare provider panel; update panel assignments on a regular basis; and use panel data to educate, and track patients [ 79 ]. Empanelment enables healthcare systems to improve patient experiences, reduce costs, and improve health outcomes. Empanelment is an effective strategy to deliver four key functions: first-contact accessibility, continuity, comprehensiveness, and coordination [ 148 ]. Effective empanelment requires responsibility for the health of a target population, including providing healthcare services based on their health status, which is an important step in moving towards people-centered integrated healthcare [ 79 ].

This review identified that community health funding schemes such as community-based health insurance (CBHI) increases access to healthcare in low-income rural communities. Moreover, this approach is effective to mobilize domestic resources for health at low income levels [ 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 ]. Community-based health insurance is an emerging strategy to provide financial protection against the cost of illness. It is an effective strategy to improve access to quality health services for low-income rural households [ 149 ]. Existence of social capital in the community is a determinant factor for the effectiveness of CBHI as social capital has a positive effect on the community's demand for insurance [ 150 , 151 ]. Moreover, solidarity and trust between the members are the key principles for the good functioning of a CBHI. Solidarity and trust stir-up members who are susceptible to risk to put together their resources for common use [ 149 , 152 , 153 ]. Affordability of premiums or contributions, technical arrangements made by the scheme management, timing of collecting the contributions, trust in the integrity and competence of the managers of the CBHI, The quality of care offered through the CBHI, accessible across different population groups are some of the determinant factors to be considered to increase people’s decision to join the CBHI schemes [ 154 , 155 ].

In this review, telemedicine has been identified as one of the many possible solutions for rural subspecialty healthcare delivery. Telemedicine is a vital technological tool to increase healthcare access, improve care delivery systems, engage in culturally competent outreach, health workforce development, and health information system [ 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 ]. Telemedicine can be a great alternative to the traditional healthcare system in situations like diagnoses of common medical problems; inquiries about various medical issues for home treatments; post-treatment check-ins or follow-up for chronic care; holidays, weekends, late night or any other situation when regular medical care is not possible; patient inability to leave the house; patients who lack regular access to relevant medical expertise in their geographic area ; and etc. However, technological issues are challenges when dealing with telemedicine, especially in developing countries. General problems of Internet connectivity and access to infrastructure can minimize benefits of this strategy. Costs associated with technology can also be a barrier. Furthermore, health technology requires human capacity to use it. Therefore, strengthening the information communication technologies (ICT) and human capacity building on ICT are important to address the health needs of the rural communities.

This systematic review of literature identified that promoting the role of TM solves problems of access to allopathic medicine. Integration of TM in health system will result in increased coverage and access to healthcare services. The role of complementary and alternative medicine for health is undisputed particularly in light of its role in health promotion and well-being. It also supports local health workforces [ 104 , 105 , 106 , 107 , 108 , 109 ]. Incorporating traditional healers into the public health system addresses healthcare needs [ 156 , 157 ]. However, integrating TM to the public healthcare system is challenging. It is a general belief that TM defies scientific procedures in terms of objectivity, measurement, codification and classification [ 157 ]. If integrated, who provides training to medical doctors on the ontology, epistemology and the efficacies of TM in modern medicine [ 157 ]. Due to these, some scholars suggest that both TM and modern medicine be allowed to operate and develop independent of one another [ 158 , 159 ]. Another fundamental challenge to TM is the widespread reported cases of fake healers and healings [ 157 ]. Generally, this strategy is more of feasible in areas where formal trainings on integrative medicine are available. Even though the integration is challenging, the health sector can use traditional healers as health educators or health promoters by providing training and continuous support. It can be also possible to use traditional healers as facilitators in the community-directed approaches. In general TM can be used in the primary healthcare system where no access to allopathic medicine and when conventional medicine is ineffective in treatment of disease [ 160 ].

Working with non-profit private sectors and NGOs has been identified as effective strategies to strengthen the healthcare system in developing countries [ 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 ]. Since governments in developing countries are challenged to meet the health needs of their populations because of financial constraints, limited human resources, and weak health infrastructure; the private sector (especially the non-profit private sectors) and non-governmental organizations can help expand access to healthcare services through its resources, expertise, and infrastructure. However, the presence of an NGO in the operation, may contribute to unrealistic expectations of health services, affecting perceptions of the latter negatively [ 113 ]. Moreover, reports have it that besides other issues in many instances NGOs allocated funds only to disease specific projects (vertical programming) rather than to broad based investments (horizontal programming) [ 161 ]. There are also concerns that donor expenditures in developing countries are not only unsustainable but may be considered as inadequate considering the enormous healthcare burden [ 161 , 162 , 163 , 164 ]. To avoid unrealistic expectations and dissatisfaction, and to increase and sustain the population’s trust in the organization, NGOs should operate in a manner that is as integrated as possible within the existing structure and should work close to the population it serves, with services anchored in the community. Moreover, faith-based organizations contribute in health such as disease prevention, health education or promotion, and community health development beyond psychological and spiritual care [ 119 , 120 , 121 , 122 , 123 , 124 ]. Religious organizations can reach all segments of rural populations. Therefore, integrating PHC services, especially health education and promotion, diseases prevention and community health development with religious organizations intensifies delivery of healthcare services. Working with FBOs is a best way in situations where cultural and faith-based barriers are common and in areas, where access problems are often related to lack of providers. However, religious organizations need intensive training on health promotion and health system to enable them to respond to local contexts within the framework of national policies. Moreover, there should be strong partnership with government agenesis to sustain the effort [ 165 , 166 , 167 , 168 ].

Contribution of this review

Various studies reported one or more strategies to improve access to primary healthcare services. However, the strategies reported by individual studies are not compiled together and there is lack of pooled evidence on effective strategies to improve access to healthcare system. This systematic literature review was, therefore, conducted to compile effective strategies to improve access to healthcare services in rural communities. The review suggests key strategies to improve access to PHC services in rural communities. These suggested strategies are implementable in countries that suffer from shortage of health workers and healthcare financing because all the strategies used locally available opportunities. The local healthcare system needs, therefore, scan the available opportunities in the locality for implementing the suggested strategies and needs to integrate the strategies in the healthcare system to sustain the impacts. Healthcare providers, researchers and policy makers could use the results of this systematic literature review to increase access to healthcare services in hard-to-reach areas. As the strategies are compiled from experiences of different countries (developed and least developed countries), there might be contextual differences like socio-economic, cultural, institutional, and geographical challenges to adopt the identified strategies. Moreover, some of the experiences only come from one or two countries. Therefore, strategy developers and implementers need to consider these contextual challenges or variation during adopting and implementing different strategies.

Strengths and limitations of the study

As a strength, this systematic review explores international (both developed and developing countries) best experiences on primary healthcare service delivery and identified ten key approaches to improve access to PHC services in rural communities. We also searched relevant published or unpublished articles, dissertations or theses, discussion papers, and perspectives from a wide range of sources, such as MEDLINE, Scopus, Web of Science, WHO Global Health Library, and Google Scholar.

As a limitation, we entirely relied on electronic databases to search relevant articles. We didn’t include locally available printed out records. We also applied limits for language. We excluded articles published other than English language. We believed we could get more relevant articles if we had access to records available in prints and if we include articles published other than English language. Furthermore, since the strategies are compiled from experiences of different countries (developed and least developed countries), there might be contextual differences like socio-economic, cultural, institutional and geographical challenges to adopt the identified strategies. There was also limited evidence for some articles, especially reports to rate their methodological quality. Readers should also note that our review might missed some important work in improving access to PHC services and the identified strategies are not the only strategies to improve access to PHC services. There might be other effective strategies which are not included in this review. In addition generalizability might be affected since some of the experiences only come from one or two countries. Moreover, this review focuses on access not quality of care delivered.

This review identified key strategies from international experiences to improve access to PHC services in rural communities. These strategies are effective to improve access to healthcare services in rural or remote communities. They can also play roles in achieving UHC and reducing disparities in health outcomes and increase access to rural communities to get healthcare when and where they want. Therefore, incorporating these key strategies suggested by this review in to the healthcare system is useful to enhance PHC services and to minimize impacts of health disparity in rural communities. However, the identified strategies may not be easy to implement. Increasing number and capacity of human resource for health; strengthening the healthcare financing system; improving medicine and supplies; working in different partners and communities; establishing monitoring and evaluation system; strong and committed leadership; and encouraging private initiatives must be considered to implement and maintain these strategies over time. Moreover, policy makers, program planners and implementers who want to utilize findings of this review should be aware that these are not the only effective strategies to improve access to primary healthcare services.

Availability of data and materials

All the extracted data are included in the manuscript.

Abbreviations

Community-based health insurance

Faith-based organizations

Family health program

Information communication technologies

Mixed methods appraisal tool

Non-governmental organizations

• Primary healthcare

Primary Health Care Performance Initiative

Population, phenomena of interest and context)

Traditional medicine

Universal health coverage

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Acknowledgements

The author would like to thank IPHC- E for funding this review.

This review was funded by International Institute for Primary Health Care- Ethiopia (IPHC- E).

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Supplementary Information

Additional file 1: .

Searchstrategy. MEDLINE (PubMed).

Additional file 2: Appendix 2: Table A1.

Description of full-text articles which discussed community health programs or community-directed interventions as a strategy to improve PHC service delivery in ruralcommunities.

Additional file 3:

Appendix 3: Table A2. Description of full-text articles which discussed school-based healthcareservices as a strategy to improve PHCservice delivery in rural communities.

Additional file 4:

Appendix 4: Table A3. Description of full-text articles which discussed student-led healthcareservices as a strategy to improve PHC service delivery in ruralcommunities.

Additional file 5: Appendix 5: Table A4

. Descriptionof full-text articles which discussed outreach services or mobile clinics as astrategy to improve PHC service delivery in ruralcommunities.

Additional file 6:

  Appendix 6: Table A5. Description of full-text articles which discussed family health program as astrategy to improve PHC service delivery in rural,communities.

Additional file 7:

  Appendix 7: Table A6. Description of full-text articles whichdiscussed empanelment as a strategy to improve PHC service delivery in ruralcommunities.

Additional file 8:

  Appendix 9: Table A8. Description of full-text articles which discussed telemedicine or mobile healthas a strategy to improve PHC service delivery in ruralcommunities.

Additional file 9:

  Appendix 8: Table A7. Description of full-text articles which discussed community health funding schemes as a strategy to improve PHC service delivery in ruralcommunities.

Additional file 10:

  Appendix 10: Table A9. Description of full-text articles which discussed promoting the role of workingwith traditional healers as a strategy toimprove PHC service delivery in rural communities.

Additional file 11:

  Appendix 11: Table A10. Description of full-text articles which discussed working with non-profitprivate sectors and non-governmental organizations as a strategy to improve PHC service delivery in rural communities.

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Gizaw, Z., Astale, T. & Kassie, G.M. What improves access to primary healthcare services in rural communities? A systematic review. BMC Prim. Care 23 , 313 (2022). https://doi.org/10.1186/s12875-022-01919-0

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A systematic review and multivariate meta-analysis of the physical and mental health benefits of touch interventions

• Julian Packheiser   ORCID: orcid.org/0000-0001-9805-6755 2   na1   nAff1 ,
• Helena Hartmann 2 , 3 , 4   na1 ,
• Kelly Fredriksen 2 ,
• Valeria Gazzola   ORCID: orcid.org/0000-0003-0324-0619 2 ,
• Christian Keysers   ORCID: orcid.org/0000-0002-2845-5467 2 &
• Frédéric Michon   ORCID: orcid.org/0000-0003-1289-2133 2  

Nature Human Behaviour ( 2024 ) Cite this article

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• Human behaviour
• Paediatric research
• Randomized controlled trials

Receiving touch is of critical importance, as many studies have shown that touch promotes mental and physical well-being. We conducted a pre-registered (PROSPERO: CRD42022304281) systematic review and multilevel meta-analysis encompassing 137 studies in the meta-analysis and 75 additional studies in the systematic review ( n  = 12,966 individuals, search via Google Scholar, PubMed and Web of Science until 1 October 2022) to identify critical factors moderating touch intervention efficacy. Included studies always featured a touch versus no touch control intervention with diverse health outcomes as dependent variables. Risk of bias was assessed via small study, randomization, sequencing, performance and attrition bias. Touch interventions were especially effective in regulating cortisol levels (Hedges’ g  = 0.78, 95% confidence interval (CI) 0.24 to 1.31) and increasing weight (0.65, 95% CI 0.37 to 0.94) in newborns as well as in reducing pain (0.69, 95% CI 0.48 to 0.89), feelings of depression (0.59, 95% CI 0.40 to 0.78) and state (0.64, 95% CI 0.44 to 0.84) or trait anxiety (0.59, 95% CI 0.40 to 0.77) for adults. Comparing touch interventions involving objects or robots resulted in similar physical (0.56, 95% CI 0.24 to 0.88 versus 0.51, 95% CI 0.38 to 0.64) but lower mental health benefits (0.34, 95% CI 0.19 to 0.49 versus 0.58, 95% CI 0.43 to 0.73). Adult clinical cohorts profited more strongly in mental health domains compared with healthy individuals (0.63, 95% CI 0.46 to 0.80 versus 0.37, 95% CI 0.20 to 0.55). We found no difference in health benefits in adults when comparing touch applied by a familiar person or a health care professional (0.51, 95% CI 0.29 to 0.73 versus 0.50, 95% CI 0.38 to 0.61), but parental touch was more beneficial in newborns (0.69, 95% CI 0.50 to 0.88 versus 0.39, 95% CI 0.18 to 0.61). Small but significant small study bias and the impossibility to blind experimental conditions need to be considered. Leveraging factors that influence touch intervention efficacy will help maximize the benefits of future interventions and focus research in this field.

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The sense of touch has immense importance for many aspects of our life. It is the first of all the senses to develop in newborns 1 and the most direct experience of contact with our physical and social environment 2 . Complementing our own touch experience, we also regularly receive touch from others around us, for example, through consensual hugs, kisses or massages 3 .

The recent coronavirus pandemic has raised awareness regarding the need to better understand the effects that touch—and its reduction during social distancing—can have on our mental and physical well-being. The most common touch interventions, for example, massage for adults or kangaroo care for newborns, have been shown to have a wide range of both mental and physical health benefits, from facilitating growth and development to buffering against anxiety and stress, over the lifespan of humans and animals alike 4 . Despite the substantial weight this literature gives to support the benefits of touch, it is also characterized by a large variability in, for example, studied cohorts (adults, children, newborns and animals), type and duration of applied touch (for example, one-time hug versus repeated 60-min massages), measured health outcomes (ranging from physical health outcomes such as sleep and blood pressure to mental health outcomes such as depression or mood) and who actually applies the touch (for example, partner versus stranger).

A meaningful tool to make sense of this vast amount of research is through meta-analysis. While previous meta-analyses on this topic exist, they were limited in scope, focusing only on particular types of touch, cohorts or specific health outcomes (for example, refs. 5 , 6 ). Furthermore, despite best efforts, meaningful variables that moderate the efficacy of touch interventions could not yet be identified. However, understanding these variables is critical to tailor touch interventions and guide future research to navigate this diverse field with the ultimate aim of promoting well-being in the population.

In this Article, we describe a pre-registered, large-scale systematic review and multilevel, multivariate meta-analysis to address this need with quantitative evidence for (1) the effect of touch interventions on physical and mental health and (2) which moderators influence the efficacy of the intervention. In particular, we ask whether and how strongly health outcomes depend on the dynamics of the touching dyad (for example, humans or robots/objects, familiarity and touch directionality), demographics (for example, clinical status, age or sex), delivery means (for example, type of touch intervention or touched body part) and procedure (for example, duration or number of sessions). We did so separately for newborns and for children and adults, as the health outcomes in newborns differed substantially from those in the other age groups. Despite the focus of the analysis being on humans, it is widely known that many animal species benefit from touch interactions and that engaging in touch promotes their well-being as well 7 . Since animal models are essential for the investigation of the mechanisms underlying biological processes and for the development of therapeutic approaches, we accordingly included health benefits of touch interventions in non-human animals as part of our systematic review. However, this search yielded only a small number of studies, suggesting a lack of research in this domain, and as such, was insufficient to be included in the meta-analysis. We evaluate the identified animal studies and their findings in the discussion.

Touch interventions have a medium-sized effect

The pre-registration can be found at ref. 8 . The flowchart for data collection and extraction is depicted in Fig. 1 .

Animal outcomes refer to outcomes measured in non-human species that were solely considered as part of a systematic review. Included languages were French, Dutch, German and English, but our search did not identify any articles in French, Dutch or German. MA, meta-analysis.

For adults, a total of n  = 2,841 and n  = 2,556 individuals in the touch and control groups, respectively, across 85 studies and 103 cohorts were included. The effect of touch overall was medium-sized ( t (102) = 9.74, P  < 0.001, Hedges’ g  = 0.52, 95% confidence interval (CI) 0.42 to 0.63; Fig. 2a ). For newborns, we could include 63 cohorts across 52 studies comprising a total of n  = 2,134 and n  = 2,086 newborns in the touch and control groups, respectively, with an overall effect almost identical to the older age group ( t (62) = 7.53, P  < 0.001, Hedges’ g  = 0.56, 95% CI 0.41 to 0.71; Fig. 2b ), suggesting that, despite distinct health outcomes, touch interventions show comparable effects across newborns and adults. Using these overall effect estimates, we conducted a power sensitivity analysis of all the included primary studies to investigate whether such effects could be reliably detected 9 . Sufficient power to detect such effect sizes was rare in individual studies, as investigated by firepower plots 10 (Supplementary Figs. 1 and 2 ). No individual effect size from either meta-analysis was overly influential (Cook’s D  < 0.06). The benefits were similar for mental and physical outcomes (mental versus physical; adults: t (101) = 0.79, P  = 0.432, Hedges’ g difference of −0.05, 95% CI −0.16 to 0.07, Fig. 2c ; newborns: t (61) = 1.08, P  = 0.284, Hedges’ g difference of −0.19, 95% CI −0.53 to 0.16, Fig. 2d ).

a , Orchard plot illustrating the overall benefits across all health outcomes for adults/children across 469 in part dependent effect sizes from 85 studies and 103 cohorts. b , The same as a but for newborns across 174 in part dependent effect sizes from 52 studies and 63 cohorts. c , The same as a but separating the results for physical versus mental health benefits across 469 in part dependent effect sizes from 85 studies and 103 cohorts. d , The same as b but separating the results for physical versus mental health benefits across 172 in part dependent effect sizes from 52 studies and 63 cohorts. Each dot reflects a measured effect, and the number of effects ( k ) included in the analysis is depicted in the bottom left. Mean effects and 95% CIs are presented in the bottom right and are indicated by the central black dot (mean effect) and its error bars (95% CI). The heterogeneity Q statistic is presented in the top left. Overall effects of moderator impact were assessed via an F test, and post hoc comparisons were done using t tests (two-sided test). Note that the P values above the mean effects indicate whether an effect differed significantly from a zero effect. P values were not corrected for multiple comparisons. The dot size reflects the precision of each individual effect (larger indicates higher precision). Small-study bias for the overall effect was significant ( F test, two-sided test) in the adult meta-analysis ( F (1, 101) = 21.24, P  < 0.001; Supplementary Fig. 3 ) as well as in the newborn meta-analysis ( F (1, 61) = 5.25, P  = 0.025; Supplementary Fig. 4 ).

Source data

On the basis of the overall effect of both meta-analyses as well as their median sample sizes, the minimum number of studies necessary for subgroup analyses to achieve 80% power was k  = 9 effects for adults and k  = 8 effects for newborns (Supplementary Figs. 5 and 6 ). Assessing specific health outcomes with sufficient power in more detail in adults (Fig. 3a ) revealed smaller benefits to sleep and heart rate parameters, moderate benefits to positive and negative affect, diastolic blood and systolic blood pressure, mobility and reductions of the stress hormone cortisol and larger benefits to trait and state anxiety, depression, fatigue and pain. Post hoc tests revealed stronger benefits for pain, state anxiety, depression and trait anxiety compared with respiratory, sleep and heart rate parameters (see Fig. 3 for all post hoc comparisons). Reductions in pain and state anxiety were increased compared with reductions in negative affect ( t (83) = 2.54, P  = 0.013, Hedges’ g difference of 0.31, 95% CI 0.07 to 0.55; t (83) = 2.31, P  = 0.024, Hedges’ g difference of 0.27, 95% CI 0.03 to 0.51). Benefits to pain symptoms were higher compared with benefits to positive affect ( t (83) = 2.22, P  = 0.030, Hedges’ g difference of 0.29, 95% CI 0.04 to 0.54). Finally, touch resulted in larger benefits to cortisol release compared with heart rate parameters ( t (83) = 2.30, P  = 0.024, Hedges’ g difference of 0.26, 95% CI 0.04–0.48).

a , b , Health outcomes in adults analysed across 405 in part dependent effect sizes from 79 studies and 97 cohorts ( a ) and in newborns analysed across 105 in part dependent effect sizes from 46 studies and 56 cohorts ( b ). The type of health outcomes measured differed between adults and newborns and were thus analysed separately. Numbers on the right represent the mean effect with its 95% CI in square brackets and the significance level estimating the likelihood that the effect is equal to zero. Overall effects of moderator impact were assessed via an F test, and post hoc comparisons were done using t tests (two-sided test). The F value in the top right represents a test of the hypothesis that all effects within the subpanel are equal. The Q statistic represents the heterogeneity. P values of post hoc tests are depicted whenever significant. P values above the horizontal whiskers indicate whether an effect differed significantly from a zero effect. Vertical lines indicate significant post hoc tests between moderator levels. P values were not corrected for multiple comparisons. Physical outcomes are marked in red. Mental outcomes are marked in blue.

In newborns, only physical health effects offered sufficient data for further analysis. We found no benefits for digestion and heart rate parameters. All other health outcomes (cortisol, liver enzymes, respiration, temperature regulation and weight gain) showed medium to large effects (Fig. 3b ). We found no significant differences among any specific health outcomes.

Non-human touch and skin-to-skin contact

In some situations, a fellow human is not readily available to provide affective touch, raising the question of the efficacy of touch delivered by objects and robots 11 . Overall, we found humans engaging in touch with other humans or objects to have medium-sized health benefits in adults, without significant differences ( t (99) = 1.05, P  = 0.295, Hedges’ g difference of 0.12, 95% CI −0.11 to 0.35; Fig. 4a ). However, differentiating physical versus mental health benefits revealed similar benefits for human and object touch on physical health outcomes, but larger benefits on mental outcomes when humans were touched by humans ( t (97) = 2.32, P  = 0.022, Hedges’ g difference of 0.24, 95% CI 0.04 to 0.44; Fig. 4b ). It must be noted that touching with an object still showed a significant effect (see Supplementary Fig. 7 for the corresponding orchard plot).

a , Forest plot comparing humans versus objects touching a human on health outcomes overall across 467 in part dependent effect sizes from 85 studies and 101 cohorts. b , The same as a but separately for mental versus physical health outcomes across 467 in part dependent effect sizes from 85 studies and 101 cohorts. c , Results with the removal of all object studies, leaving 406 in part dependent effect sizes from 71 studies and 88 cohorts to identify whether missing skin-to-skin contact is the relevant mediator of higher mental health effects in human–human interactions. Numbers on the right represent the mean effect with its 95% CI in square brackets and the significance level estimating the likelihood that the effect is equal to zero. Overall effects of moderator impact were assessed via an F test, and post hoc comparisons were done using t tests (two-sided test). The F value in the top right represents a test of the hypothesis that all effects within the subpanel are equal. The Q statistic represents the heterogeneity. P values of post hoc tests are depicted whenever significant. P values above the horizontal whiskers indicate whether an effect differed significantly from a zero effect. Vertical lines indicate significant post hoc tests between moderator levels. P values were not corrected for multiple comparisons. Physical outcomes are marked in red. Mental outcomes are marked in blue.

We considered the possibility that this effect was due to missing skin-to-skin contact in human–object interactions. Thus, we investigated human–human interactions with and without skin-to-skin contact (Fig. 4c ). In line with the hypothesis that skin-to-skin contact is highly relevant, we again found stronger mental health benefits in the presence of skin-to-skin contact that however did not achieve nominal significance ( t (69) = 1.95, P  = 0.055, Hedges’ g difference of 0.41, 95% CI −0.00 to 0.82), possibly because skin-to-skin contact was rarely absent in human–human interactions, leading to a decrease in power of this analysis. Results for skin-to-skin contact as an overall moderator can be found in Supplementary Fig. 8 .

Influences of type of touch

The large majority of touch interventions comprised massage therapy in adults and kangaroo care in newborns (see Supplementary Table 1 for a complete list of interventions across studies). However, comparing the different types of touch explored across studies did not reveal significant differences in effect sizes based on touch type, be it on overall health benefits (adults: t (101) = 0.11, P  = 0.916, Hedges’ g difference of 0.02, 95% CI −0.32 to 0.29; Fig. 5a ) or comparing different forms of touch separately for physical (massage therapy versus other forms: t (99) = 0.99, P  = 0.325, Hedges’ g difference 0.16, 95% CI −0.15 to 0.47) or for mental health benefits (massage therapy versus other forms: t (99) = 0.75, P  = 0.458, Hedges’ g difference of 0.13, 95% CI −0.22 to 0.48) in adults (Fig. 5c ; see Supplementary Fig. 9 for the corresponding orchard plot). A similar picture emerged for physical health effects in newborns (massage therapy versus kangaroo care: t (58) = 0.94, P  = 0.353, Hedges’ g difference of 0.15, 95% CI −0.17 to 0.47; massage therapy versus other forms: t (58) = 0.56, P  = 0.577, Hedges’ g difference of 0.13, 95% CI −0.34 to 0.60; kangaroo care versus other forms: t (58) = 0.07, P  = 0.947, Hedges’ g difference of 0.02, 95% CI −0.46 to 0.50; Fig. 5d ; see also Supplementary Fig. 10 for the corresponding orchard plot). This suggests that touch types may be flexibly adapted to the setting of every touch intervention.

a , Forest plot of health benefits comparing massage therapy versus other forms of touch in adult cohorts across 469 in part dependent effect sizes from 85 studies and 103 cohorts. b , Forest plot of health benefits comparing massage therapy, kangaroo care and other forms of touch for newborns across 174 in part dependent effect sizes from 52 studies and 63 cohorts. c , The same as a but separating mental and physical health benefits across 469 in part dependent effect sizes from 85 studies and 103 cohorts. d , The same as b but separating mental and physical health outcomes where possible across 164 in part dependent effect sizes from 51 studies and 62 cohorts. Note that an insufficient number of studies assessed mental health benefits of massage therapy or other forms of touch to be included. Numbers on the right represent the mean effect with its 95% CI in square brackets and the significance level estimating the likelihood that the effect is equal to zero. Overall effects of moderator impact were assessed via an F test, and post hoc comparisons were done using t tests (two-sided test). The F value in the top right represents a test of the hypothesis that all effects within the subpanel are equal. The Q statistic represents heterogeneity. P values of post hoc tests are depicted whenever significant. P values above the horizontal whiskers indicate whether an effect differed significantly from a zero effect. Vertical lines indicate significant post hoc tests between moderator levels. P values were not corrected for multiple comparisons. Physical outcomes are marked in red. Mental outcomes are marked in blue.

The role of clinical status

Most research on touch interventions has focused on clinical samples, but are benefits restricted to clinical cohorts? We found health benefits to be significant in clinical and healthy populations (Fig. 6 ), whether all outcomes are considered (Fig. 6a,b ) or physical and mental health outcomes are separated (Fig. 6c,d , see Supplementary Figs. 11 and 12 for the corresponding orchard plots). In adults, however, we found higher mental health benefits for clinical populations compared with healthy ones (Fig. 6c ; t (99) = 2.11, P  = 0.037, Hedges’ g difference of 0.25, 95% CI 0.01 to 0.49).

a , Health benefits for clinical cohorts of adults versus healthy cohorts of adults across 469 in part dependent effect sizes from 85 studies and 103 cohorts. b , The same as a but for newborn cohorts across 174 in part dependent effect sizes from 52 studies and 63 cohorts. c , The same as a but separating mental versus physical health benefits across 469 in part dependent effect sizes from 85 studies and 103 cohorts. d , The same as b but separating mental versus physical health benefits across 172 in part dependent effect sizes from 52 studies and 63 cohorts. Numbers on the right represent the mean effect with its 95% CI in square brackets and the significance level estimating the likelihood that the effect is equal to zero. Overall effects of moderator impact were assessed via an F test, and post hoc comparisons were done using t tests (two-sided test).The F value in the top right represents a test of the hypothesis that all effects within the subpanel are equal. The Q statistic represents the heterogeneity. P values of post hoc tests are depicted whenever significant. P values above the horizontal whiskers indicate whether an effect differed significantly from a zero effect. Vertical lines indicate significant post hoc tests between moderator levels. P values were not corrected for multiple comparisons. Physical outcomes are marked in red. Mental outcomes are marked in blue.

A more detailed analysis of specific clinical conditions in adults revealed positive mental and physical health benefits for almost all assessed clinical disorders. Differences between disorders were not found, with the exception of increased effectiveness of touch interventions in neurological disorders (Supplementary Fig. 13 ).

Familiarity in the touching dyad and intervention location

Touch interventions can be performed either by familiar touchers (partners, family members or friends) or by unfamiliar touchers (health care professionals). In adults, we did not find an impact of familiarity of the toucher ( t (99) = 0.12, P  = 0.905, Hedges’ g difference of 0.02, 95% CI −0.27 to 0.24; Fig. 7a ; see Supplementary Fig. 14 for the corresponding orchard plot). Similarly, investigating the impact on mental and physical health benefits specifically, no significant differences could be detected, suggesting that familiarity is irrelevant in adults. In contrast, touch applied to newborns by their parents (almost all studies only included touch by the mother) was significantly more beneficial compared with unfamiliar touch ( t (60) = 2.09, P  = 0.041, Hedges’ g difference of 0.30, 95% CI 0.01 to 0.59) (Fig. 7b ; see Supplementary Fig. 15 for the corresponding orchard plot). Investigating mental and physical health benefits specifically revealed no significant differences. Familiarity with the location in which the touch was applied (familiar being, for example, the participants’ home) did not influence the efficacy of touch interventions (Supplementary Fig. 16 ).

a , Health benefits for being touched by a familiar (for example, partner, family member or friend) versus unfamiliar toucher (health care professional) across 463 in part dependent effect sizes from 83 studies and 101 cohorts. b , The same as a but for newborn cohorts across 171 in part dependent effect sizes from 51 studies and 62 cohorts. c , The same as a but separating mental versus physical health benefits across 463 in part dependent effect sizes from 83 studies and 101 cohorts. d , The same as b but separating mental versus physical health benefits across 169 in part dependent effect sizes from 51 studies and 62 cohorts. Numbers on the right represent the mean effect with its 95% CI in square brackets and the significance level estimating the likelihood that the effect is equal to zero. Overall effects of moderator impact were assessed via an F test, and post hoc comparisons were done using t tests (two-sided test). The F value in the top right represents a test of the hypothesis that all effects within the subpanel are equal. The Q statistic represents the heterogeneity. P values of post hoc tests are depicted whenever significant. P values above the horizontal whiskers indicate whether an effect differed significantly from a zero effect. Vertical lines indicate significant post hoc tests between moderator levels. P values were not corrected for multiple comparisons. Physical outcomes are marked in red. Mental outcomes are marked in blue.

Frequency and duration of touch interventions

How often and for how long should touch be delivered? For adults, the median touch duration across studies was 20 min and the median number of touch interventions was four sessions with an average time interval of 2.3 days between each session. For newborns, the median touch duration across studies was 17.5 min and the median number of touch interventions was seven sessions with an average time interval of 1.3 days between each session.

Delivering more touch sessions increased benefits in adults, whether overall ( t (101) = 4.90, P  < 0.001, Hedges’ g  = 0.02, 95% CI 0.01 to 0.03), physical ( t (81) = 3.07, P  = 0.003, Hedges’ g  = 0.02, 95% CI 0.01–0.03) or mental benefits ( t (72) = 5.43, P  < 0.001, Hedges’ g  = 0.02, 95% CI 0.01–0.03) were measured (Fig. 8a ). A closer look at specific outcomes for which sufficient data were available revealed that positive associations between the number of sessions and outcomes were found for trait anxiety ( t (12) = 7.90, P  < 0.001, Hedges’ g  = 0.03, 95% CI 0.02–0.04), depression ( t (20) = 10.69, P  < 0.001, Hedges’ g  = 0.03, 95% CI 0.03–0.04) and pain ( t (37) = 3.65, P  < 0.001, Hedges’ g  = 0.03, 95% CI 0.02–0.05), indicating a need for repeated sessions to improve these adverse health outcomes. Neither increasing the number of sessions for newborns nor increasing the duration of touch per session in adults or newborns increased health benefits, be they physical or mental (Fig. 8b–d ). For continuous moderators in adults, we also looked at specific health outcomes as sufficient data were generally available for further analysis. Surprisingly, we found significant negative associations between touch duration and reductions of cortisol ( t (24) = 2.71, P  = 0.012, Hedges’ g  = −0.01, 95% CI −0.01 to −0.00) and heart rate parameters ( t (21) = 2.35, P  = 0.029, Hedges’ g  = −0.01, 95% CI −0.02 to −0.00).

a , Meta-regression analysis examining the association between the number of sessions applied and the effect size in adults, either on overall health benefits (left, 469 in part dependent effect sizes from 85 studies and 103 cohorts) or for physical (middle, 245 in part dependent effect sizes from 69 studies and 83 cohorts) or mental benefits (right, 224 in part dependent effect sizes from 60 studies and 74 cohorts) separately. b , The same as a for newborns (overall: 150 in part dependent effect sizes from 46 studies and 53 cohorts; physical health: 127 in part dependent effect sizes from 44 studies and 51 cohorts; mental health: 21 in part dependent effect sizes from 11 studies and 12 cohorts). c , d the same as a ( c ) and b ( d ) but for the duration of the individual sessions. For adults, 449 in part dependent effect sizes across 80 studies and 96 cohorts were included in the overall analysis. The analysis of physical health benefits included 240 in part dependent effect sizes across 67 studies and 80 cohorts, and the analysis of mental health benefits included 209 in part dependent effect sizes from 56 studies and 69 cohorts. For newborns, 145 in part dependent effect sizes across 45 studies and 52 cohorts were included in the overall analysis. The analysis of physical health benefits included 122 in part dependent effect sizes across 43 studies and 50 cohorts, and the analysis of mental health benefits included 21 in part dependent effect sizes from 11 studies and 12 cohorts. Each dot represents an effect size. Its size indicates the precision of the study (larger indicates better). Overall effects of moderator impact were assessed via an F test (two-sided test). The P values in each panel represent the result of a regression analysis testing the hypothesis that the slope of the relationship is equal to zero. P values are not corrected for multiple testing. The shaded area around the regression line represents the 95% CI.

Demographic influences of sex and age

We used the ratio between women and men in the single-study samples as a proxy for sex-specific effects. Sex ratios were heavily skewed towards larger numbers of women in each cohort (median 83% women), and we could not find significant associations between sex ratio and overall ( t (62) = 0.08, P  = 0.935, Hedges’ g  = 0.00, 95% CI −0.00 to 0.01), mental ( t (43) = 0.55, P  = 0.588, Hedges’ g  = 0.00, 95% CI −0.00 to 0.01) or physical health benefits ( t (51) = 0.15, P  = 0.882, Hedges’ g  = −0.00, 95% CI −0.01 to 0.01). For specific outcomes that could be further analysed, we found a significant positive association of sex ratio with reductions in cortisol secretion ( t (18) = 2.31, P  = 0.033, Hedges’ g  = 0.01, 95% CI 0.00 to 0.01) suggesting stronger benefits in women. In contrast to adults, sex ratios were balanced in samples of newborns (median 53% girls). For newborns, there was no significant association with overall ( t (36) = 0.77, P  = 0.447, Hedges’ g  = −0.01, 95% CI −0.02 to 0.01) and physical health benefits of touch ( t (35) = 0.93, P  = 0.359, Hedges’ g  = −0.01, 95% CI −0.02 to 0.01). Mental health benefits did not provide sufficient data for further analysis.

The median age in the adult meta-analysis was 42.6 years (s.d. 21.16 years, range 4.5–88.4 years). There was no association between age and the overall ( t (73) = 0.35, P  = 0.727, Hedges’ g = 0.00, 95% CI −0.01 to 0.01), mental ( t (53) = 0.94, P  = 0.353, Hedges’ g  = 0.01, 95% CI −0.01 to 0.02) and physical health benefits of touch ( t (60) = 0.16, P  = 0.870, Hedges’ g  = 0.00, 95% CI −0.01 to 0.01). Looking at specific health outcomes, we found significant positive associations between mean age and improved positive affect ( t (10) = 2.54, P  = 0.030, Hedges’ g  = 0.01, 95% CI 0.00 to 0.02) as well as systolic blood pressure ( t (11) = 2.39, P  = 0.036, Hedges’ g  = 0.02, 95% CI 0.00 to 0.04).

A list of touched body parts can be found in Supplementary Table 1 . For the touched body part, we found significantly higher health benefits for head touch compared with arm touch ( t (40) = 2.14, P  = 0.039, Hedges’ g difference of 0.78, 95% CI 0.07 to 1.49) and torso touch ( t (40) = 2.23, P  = 0.031; Hedges’ g difference of 0.84, 95% CI 0.10 to 1.58; Supplementary Fig. 17 ). Touching the arm resulted in lower mental health compared with physical health benefits ( t (37) = 2.29, P  = 0.028, Hedges’ g difference of −0.35, 95% CI −0.65 to −0.05). Furthermore, we found a significantly increased physical health benefit when the head was touched as opposed to the torso ( t (37) = 2.10, P  = 0.043, Hedges’ g difference of 0.96, 95% CI 0.06 to 1.86). Thus, head touch such as a face or scalp massage could be especially beneficial.

Directionality

In adults, we tested whether a uni- or bidirectional application of touch mattered. The large majority of touch was applied unidirectionally ( k  = 442 of 469 effects). Unidirectional touch had higher health benefits ( t (101) = 2.17, P  = 0.032, Hedges’ g difference of 0.30, 95% CI 0.03 to 0.58) than bidirectional touch. Specifically, mental health benefits were higher in unidirectional touch ( t (99) = 2.33, P  = 0.022, Hedges’ g difference of 0.46, 95% CI 0.06 to 0.66).

Study location

For adults, we found significantly stronger health benefits of touch in South American compared with North American cohorts ( t (95) = 2.03, P  = 0.046, Hedges’ g difference of 0.37, 95% CI 0.01 to 0.73) and European cohorts ( t (95) = 2.22, P  = 0.029, Hedges’ g difference of 0.36, 95% CI 0.04 to 0.68). For newborns, we found weaker effects in North American cohorts compared to Asian ( t (55) = 2.28, P  = 0.026, Hedges’ g difference of −0.37, 95% CI −0.69 to −0.05) and European cohorts ( t (55) = 2.36, P  = 0.022, Hedges’ g difference of −0.40, 95% CI −0.74 to −0.06). Investigating the interaction with mental and physical health benefits did not reveal any effects of study location in both meta-analyses (Supplementary Fig. 18 ).

Systematic review of studies without effect sizes

All studies where effect size data could not be obtained or that did not meet the meta-analysis inclusion criteria can be found on the OSF project 12 in the file ‘Study_lists_final_revised.xlsx’ (sheet ‘Studies_without_effect_sizes’). Specific reasons for exclusion are furthermore documented in Supplementary Table 2 . For human health outcomes assessed across 56 studies and n  = 2,438 individuals, interventions mostly comprised massage therapy ( k  = 86 health outcomes) and kangaroo care ( k  = 33 health outcomes). For datasets where no effect size could be computed, 90.0% of mental health and 84.3% of physical health parameters were positively impacted by touch. Positive impact of touch did not differ between types of touch interventions. These results match well with the observations of the meta-analysis of a highly positive benefit of touch overall, irrespective of whether a massage or any other intervention is applied.

We also assessed health outcomes in animals across 19 studies and n  = 911 subjects. Most research was conducted in rodents. Animals that received touch were rats (ten studies, k  = 16 health outcomes), mice (four studies, k  = 7 health outcomes), macaques (two studies, k  = 3 health outcomes), cats (one study, k  = 3 health outcomes), lambs (one study, k  = 2 health outcomes) and coral reef fish (one study, k  = 1 health outcome). Touch interventions mostly comprised stroking ( k  = 13 health outcomes) and tickling ( k  = 10 health outcomes). For animal studies, 71.4% of effects showed benefits to mental health-like parameters and 81.8% showed positive physical health effects. We thus found strong evidence that touch interventions, which were mostly conducted by humans (16 studies with human touch versus 3 studies with object touch), had positive health effects in animal species as well.

The key aim of the present study was twofold: (1) to provide an estimate of the effect size of touch interventions and (2) to disambiguate moderating factors to potentially tailor future interventions more precisely. Overall, touch interventions were beneficial for both physical and mental health, with a medium effect size. Our work illustrates that touch interventions are best suited for reducing pain, depression and anxiety in adults and children as well as for increasing weight gain in newborns. These findings are in line with previous meta-analyses on this topic, supporting their conclusions and their robustness to the addition of more datasets. One limitation of previous meta-analyses is that they focused on specific health outcomes or populations, despite primary studies often reporting effects on multiple health parameters simultaneously (for example, ref. 13 focusing on neck and shoulder pain and ref. 14 focusing on massage therapy in preterms). To our knowledge, only ref. 5 provides a multivariate picture for a large number of dependent variables. However, this study analysed their data in separate random effects models that did not account for multivariate reporting nor for the multilevel structure of the data, as such approaches have only become available recently. Thus, in addition to adding a substantial amount of new data, our statistical approach provides a more accurate depiction of effect size estimates. Additionally, our study investigated a variety of moderating effects that did not reach significance (for example, sex ratio, mean age or intervention duration) or were not considered (for example, the benefits of robot or object touch) in previous meta-analyses in relation to touch intervention efficacy 5 , probably because of the small number of studies with information on these moderators in the past. Owing to our large-scale approach, we reached high statistical power for many moderator analyses. Finally, previous meta-analyses on this topic exclusively focused on massage therapy in adults or kangaroo care in newborns 15 , leaving out a large number of interventions that are being carried out in research as well as in everyday life to improve well-being. Incorporating these studies into our study, we found that, in general, both massages and other types of touch, such as gentle touch, stroking or kangaroo care, showed similar health benefits.

While it seems to be less critical which touch intervention is applied, the frequency of interventions seems to matter. More sessions were positively associated with the improvement of trait outcomes such as depression and anxiety but also pain reductions in adults. In contrast to session number, increasing the duration of individual sessions did not improve health effects. In fact, we found some indications of negative relationships in adults for cortisol and blood pressure. This could be due to habituating effects of touch on the sympathetic nervous system and hypothalamic–pituitary–adrenal axis, ultimately resulting in diminished effects with longer exposure, or decreased pleasantness ratings of affective touch with increasing duration 16 . For newborns, we could not support previous notions that the duration of the touch intervention is linked to benefits in weight gain 17 . Thus, an ideal intervention protocol does not seem to have to be excessively long. It should be noted that very few interventions lasted less than 5 min, and it therefore remains unclear whether very short interventions have the same effect.

A critical issue highlighted in the pandemic was the lack of touch due to social restrictions 18 . To accommodate the need for touch in individuals with small social networks (for example, institutionalized or isolated individuals), touch interventions using objects/robots have been explored in the past (for a review, see ref. 11 ). We show here that touch interactions outside of the human–human domain are beneficial for mental and physical health outcomes. Importantly, object/robot touch was not as effective in improving mental health as human-applied touch. A sub-analysis of missing skin-to-skin contact among humans indicated that mental health effects of touch might be mediated by the presence of skin-to-skin contact. Thus, it seems profitable to include skin-to-skin contact in future touch interventions, in line with previous findings in newborns 19 . In robots, recent advancements in synthetic skin 20 should be investigated further in this regard. It should be noted that, although we did not observe significant differences in physical health benefits between human–human and human–object touch, the variability of effect sizes was higher in human–object touch. The conditions enabling object or robot interactions to improve well-being should therefore be explored in more detail in the future.

Touch was beneficial for both healthy and clinical cohorts. These data are critical as most previous meta-analytic research has focused on individuals diagnosed with clinical disorders (for example, ref. 6 ). For mental health outcomes, we found larger effects in clinical cohorts. A possible reason could relate to increased touch wanting 21 in patients. For example, loneliness often co-occurs with chronic illnesses 22 , which are linked to depressed mood and feelings of anxiety 23 . Touch can be used to counteract this negative development 24 , 25 . In adults and children, knowing the toucher did not influence health benefits. In contrast, familiarity affected overall health benefits in newborns, with parental touch being more beneficial than touch applied by medical staff. Previous studies have suggested that early skin-to-skin contact and exposure to maternal odour is critical for a newborn’s ability to adapt to a new environment 26 , supporting the notion that parental care is difficult to substitute in this time period.

With respect to age-related effects, our data further suggest that increasing age was associated with a higher benefit through touch for systolic blood pressure. These findings could potentially be attributed to higher basal blood pressure 27 with increasing age, allowing for a stronger modulation of this parameter. For sex differences, our study provides some evidence that there are differences between women and men with respect to health benefits of touch. Overall, research on sex differences in touch processing is relatively sparse (but see refs. 28 , 29 ). Our results suggest that buffering effects against physiological stress are stronger in women. This is in line with increased buffering effects of hugs in women compared with men 30 . The female-biased primary research in adults, however, begs for more research in men or non-binary individuals. Unfortunately, our study could not dive deeper into this topic as health benefits broken down by sex or gender were almost never provided. Recent research has demonstrated that sensory pleasantness is affected by sex and that this also interacts with the familiarity of the other person in the touching dyad 29 , 31 . In general, contextual factors such as sex and gender or the relationship of the touching dyad, differences in cultural background or internal states such as stress have been demonstrated to be highly influential in the perception of affective touch and are thus relevant to maximizing the pleasantness and ultimately the health benefits of touch interactions 32 , 33 , 34 . As a positive personal relationship within the touching dyad is paramount to induce positive health effects, future research applying robot touch to promote well-being should therefore not only explore synthetic skin options but also focus on improving robots as social agents that form a close relationship with the person receiving the touch 35 .

As part of the systematic review, we also assessed the effects of touch interventions in non-human animals. Mimicking the results of the meta-analysis in humans, beneficial effects of touch in animals were comparably strong for mental health-like and physical health outcomes. This may inform interventions to promote animal welfare in the context of animal experiments 36 , farming 37 and pets 38 . While most studies investigated effects in rodents, which are mostly used as laboratory animals, these results probably transfer to livestock and common pets as well. Indeed, touch was beneficial in lambs, fish and cats 39 , 40 , 41 . The positive impact of human touch in rodents also allows for future mechanistic studies in animal models to investigate how interventions such as tickling or stroking modulate hormonal and neuronal responses to touch in the brain. Furthermore, the commonly proposed oxytocin hypothesis can be causally investigated in these animal models through, for example, optogenetic or chemogenetic techniques 42 . We believe that such translational approaches will further help in optimizing future interventions in humans by uncovering the underlying mechanisms and brain circuits involved in touch.

Our results offer many promising avenues to improve future touch interventions, but they also need to be discussed in light of their limitations. While the majority of findings showed robust health benefits of touch interventions across moderators when compared with a null effect, post hoc tests of, for example, familiarity effects in newborns or mental health benefit differences between human and object touch only barely reached significance. Since we computed a large number of statistical tests in the present study, there is a risk that these results are false positives. We hope that researchers in this field are stimulated by these intriguing results and target these questions by primary research through controlled experimental designs within a well-powered study. Furthermore, the presence of small-study bias in both meta-analyses is indicative that the effect size estimates presented here might be overestimated as null results are often unpublished. We want to stress however that this bias is probably reduced by the multivariate reporting of primary studies. Most studies that reported on multiple health outcomes only showed significant findings for one or two among many. Thus, the multivariate nature of primary research in this field allowed us to include many non-significant findings in the present study. Another limitation pertains to the fact that we only included articles in languages mostly spoken in Western countries. As a large body of evidence comes from Asian countries, it could be that primary research was published in languages other than specified in the inclusion criteria. Thus, despite the large and inclusive nature of our study, some studies could have been missed regardless. Another factor that could not be accounted for in our meta-analysis was that an important prerequisite for touch to be beneficial is its perceived pleasantness. The level of pleasantness associated with being touched is modulated by several parameters 34 including cultural acceptability 43 , perceived humanness 44 or a need for touch 45 , which could explain the observed differences for certain moderators, such as human–human versus robot–human interaction. Moreover, the fact that secondary categorical moderators could not be investigated with respect to specific health outcomes, owing to the lack of data points, limits the specificity of our conclusions in this regard. It thus remains unclear whether, for example, a decreased mental health benefit in the absence of skin-to-skin contact is linked mostly to decreased anxiolytic effects, changes in positive/negative affect or something else. Since these health outcomes are however highly correlated 46 , it is likely that such effects are driven by multiple health outcomes. Similarly, it is important to note that our conclusions mainly refer to outcomes measured close to the touch intervention as we did not include long-term outcomes. Finally, it needs to be noted that blinding towards the experimental condition is essentially impossible in touch interventions. Although we compared the touch intervention with other interventions, such as relaxation therapy, as control whenever possible, contributions of placebo effects cannot be ruled out.

In conclusion, we show clear evidence that touch interventions are beneficial across a large number of both physical and mental health outcomes, for both healthy and clinical cohorts, and for all ages. These benefits, while influenced in their magnitude by study cohorts and intervention characteristics, were robustly present, promoting the conclusion that touch interventions can be systematically employed across the population to preserve and improve our health.

Open science practices

All data and code are accessible in the corresponding OSF project 12 . The systematic review was registered on PROSPERO (CRD42022304281) before the start of data collection. We deviated from the pre-registered plan as follows:

Deviation 1: During our initial screening for the systematic review, we were confronted with a large number of potential health outcomes to look at. This observation of multivariate outcomes led us to register an amendment during data collection (but before any effect size or moderator screening). In doing so, we aimed to additionally extract meta-analytic effects for a more quantitative assessment of our review question that can account for multivariate data reporting and dependencies of effects within the same study. Furthermore, as we noted a severe lack of studies with respect to health outcomes for animals during the inclusion assessment for the systematic review, we decided that the meta-analysis would only focus on outcomes that could be meaningfully analysed on the meta-analytic level and therefore only included health outcomes of human participants.

Deviation 2: In the pre-registration, we did not explicitly exclude non-randomized trials. Since an explicit use of non-randomization for group allocation significantly increases the risk of bias, we decided to exclude them a posteriori from data analysis.

Deviation 3: In the pre-registration, we outlined a tertiary moderator level, namely benefits of touch application versus touch reception. This level was ignored since no included study specifically investigated the benefits of touch application by itself.

Deviation 4: In the pre-registration, we suggested using the RoBMA function 47 to provide a Bayesian framework that allows for a more accurate assessment of publication bias beyond small-study bias. Unfortunately, neither multilevel nor multivariate data structures are supported by the RoBMA function, to our knowledge. For this reason, we did not further pursue this analysis, as the hierarchical nature of the data would not be accounted for.

Deviation 5: Beyond the pre-registered inclusion and exclusion criteria, we also excluded dissertations owing to their lack of peer review.

Deviation 6: In the pre-registration, we stated to investigate the impact of sex of the person applying the touch. This moderator was not further analysed, as this information was rarely given and the individuals applying the touch were almost exclusively women (7 males, 24 mixed and 85 females in studies on adults/children; 3 males, 17 mixed and 80 females in studied on newborns).

Deviation 7: The time span of the touch intervention as assessed by subtracting the final day of the intervention from the first day was not investigated further owing to its very high correlation with the number of sessions ( r (461) = 0.81 in the adult meta-analysis, r (145) = 0.84 in the newborn meta-analysis).

Inclusion and exclusion criteria

To be included in the systematic review, studies had to investigate the relationship between at least one health outcome (physical and/or mental) in humans or animals and a touch intervention, include explicit physical touch by another human, animal or object as part of an intervention and include an experimental and control condition/group that are differentiated by touch alone. Of note, as a result of this selection process, no animal-to-animal touch intervention study was included, as they never featured a proper no-touch control. Human touch was always explicit touch by a human (that is, no brushes or other tools), either with or without skin-to-skin contact. Regarding the included health outcomes, we aimed to be as broad as possible but excluded parameters such as neurophysiological responses or pleasantness ratings after touch application as they do not reflect health outcomes. All included studies in the meta-analysis and systematic review 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 , 162 , 163 , 164 , 165 , 166 , 167 , 168 , 169 , 170 , 171 , 172 , 173 , 174 , 175 , 176 , 177 , 178 , 179 , 180 , 181 , 182 , 183 , 184 , 185 , 186 , 187 , 188 , 189 , 190 , 191 , 192 , 193 , 194 , 195 , 196 , 197 , 198 , 199 , 200 , 201 , 202 , 203 , 204 , 205 , 206 , 207 , 208 , 209 , 210 , 211 , 212 , 213 , 214 , 215 , 216 , 217 , 218 , 219 , 220 , 221 , 222 , 223 , 224 , 225 , 226 , 227 , 228 , 229 , 230 , 231 , 232 , 233 , 234 , 235 , 236 , 237 , 238 , 239 , 240 , 241 , 242 , 243 , 244 , 245 , 246 , 247 , 248 , 249 , 250 , 251 , 252 , 253 , 254 , 255 , 256 , 257 , 258 , 259 , 260 , 261 , 262 , 263 are listed in Supplementary Table 2 . All excluded studies are listed in Supplementary Table 3 , together with a reason for exclusion. We then applied a two-step process: First, we identified all potential health outcomes and extracted qualitative information on those outcomes (for example, direction of effect). Second, we extracted quantitative information from all possible outcomes (for example, effect sizes). The meta-analysis additionally required a between-subjects design (to clearly distinguish touch from no-touch effects and owing to missing information about the correlation between repeated measurements 264 ). Studies that explicitly did not apply a randomized protocol were excluded before further analysis to reduce risk of bias. The full study lists for excluded and included studies can be found in the OSF project 12 in the file ‘Study_lists_final_revised.xlsx’. In terms of the time frame, we conducted an open-start search of studies until 2022 and identified studies conducted between 1965 and 2022.

Data collection

We used Google Scholar, PubMed and Web of Science for our literature search, with no limitations regarding the publication date and using pre-specified search queries (see Supplementary Information for the exact keywords used). All procedures were in accordance with the updated Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines 265 . Articles were assessed in French, Dutch, German or English. The above databases were searched from 2 December 2021 until 1 October 2022. Two independent coders evaluated each paper against the inclusion and exclusion criteria. Inconsistencies between coders were checked and resolved by J.P. and H.H. Studies excluded/included for the review and meta-analysis can be found on the OSF project.

Search queries

We used the following keywords to search the chosen databases. Agents (human versus animal versus object versus robot) and touch outcome (physical versus mental) were searched separately together with keywords searching for touch.

TOUCH: Touch OR Social OR Affective OR Contact OR Tactile interaction OR Hug OR Massage OR Embrace OR Kiss OR Cradling OR Stroking OR Haptic interaction OR tickling

AGENT: Object OR Robot OR human OR animal OR rodent OR primate

MENTAL OUTCOME: Health OR mood OR Depression OR Loneliness OR happiness OR life satisfaction OR Mental Disorder OR well-being OR welfare OR dementia OR psychological OR psychiatric OR anxiety OR Distress

PHYSICAL OUTCOME: Health OR Stress OR Pain OR cardiovascular health OR infection risk OR immune response OR blood pressure OR heart rate

Data extraction and preparation

Data extraction began on 10 October 2022 and was concluded on 25 February 2023. J.P. and H.H. oversaw the data collection process, and checked and resolved all inconsistencies between coders.

Health benefits of touch were always coded by positive summary effects, whereas adverse health effects of touch were represented by negative summary effects. If multiple time points were measured for the same outcome on the same day after a single touch intervention, we extracted the peak effect size (in either the positive or negative direction). If the touch intervention occurred multiple times and health outcomes were assessed for each time point, we extracted data points separately. However, we only extracted immediate effects, as long-term effects not controlled through the experimental conditions could be due to influences other than the initial touch intervention. Measurements assessing long-term effects without explicit touch sessions in the breaks were excluded for the same reason. Common control groups for touch interventions comprised active (for example, relaxation therapy) as well as passive control groups (for example, standard medical care). In the case of multiple control groups, we always contrasted the touch group to the group that most closely matched the touch condition (for example, relaxation therapy was preferred over standard medical care). We extracted information from all moderators listed in the pre-registration (Supplementary Table 4 ). A list of included and excluded health outcomes is presented in Supplementary Table 5 . Authors of studies with possible effects but missing information to calculate those effects were contacted via email and asked to provide the missing data (response rate 35.7%).

After finalizing the list of included studies for the systematic review, we added columns for moderators and the coding schema for our meta-analysis per our updated registration. Then, each study was assessed for its eligibility in the meta-analysis by two independent coders (J.P., H.H., K.F. or F.M.). To this end, all coders followed an a priori specified procedure: First, the PDF was skimmed for possible effects to extract, and the study was excluded if no PDF was available or the study was in a language different from the ones specified in ‘ Data collection ’. Effects from studies that met the inclusion criteria were extracted from all studies listing descriptive values or statistical parameters to calculate effect sizes. A website 266 was used to convert descriptive and statistical values available in the included studies (means and standard deviations/standard errors/confidence intervals, sample sizes, F values, t values, t test P values or frequencies) into Cohen’s d , which were then converted in Hedges’ g . If only P value thresholds were reported (for example, P  < 0.01), we used this, most conservative, value as the P value to calculate the effect size (for example, P  = 0.01). If only the total sample size was given but that number was even and the participants were randomly assigned to each group, we assumed equal sample sizes for each group. If delta change scores (for example, pre- to post-touch intervention) were reported, we used those over post-touch only scores. In case frequencies were 0 when frequency tables were used to determine effect sizes, we used a value of 0.5 as a substitute to calculate the effect (the default setting in the ‘metafor’ function 267 ). From these data, Hedges’ g and its variance could be derived. Effect sizes were always computed between the experimental and the control group.

Statistical analysis and risk of bias assessment

Owing to the lack of identified studies, health benefits to animals were not included as part of the statistical analysis. One meta-analysis was performed for adults, adolescents and children, as outcomes were highly comparable. We refer to this meta-analysis as the adult meta-analysis, as children/adolescent cohorts were only targeted in a minority of studies. A separate meta-analysis was performed for newborns, as their health outcomes differed substantially from any other age group.

Data were analysed using R (version 4.2.2) with the ‘rma.mv’ function from the ‘metafor’ package 267 in a multistep, multivariate and multilevel fashion.

We calculated an overall effect of touch interventions across all studies, cohorts and health outcomes. To account for the hierarchical structure of the data, we used a multilevel structure with random effects at the study, cohort and effects level. Furthermore, we calculated the variance–covariance matrix of all data points to account for the dependencies of measured effects within each individual cohort and study. The variance–covariance matrix was calculated by default with an assumed correlation of effect sizes within each cohort of ρ  = 0.6. As ρ needed to be assumed, sensitivity analyses for all computed effect estimates were conducted using correlations between effects of 0, 0.2, 0.4 and 0.8. The results of these sensitivity analyses can be found in ref. 12 . No conclusion drawn in the present manuscript was altered by changing the level of ρ . The sensitivity analyses, however, showed that higher assumed correlations lead to more conservative effect size estimates (see Supplementary Figs. 19 and 20 for the adult and newborn meta-analyses, respectively), reducing the type I error risk in general 268 . In addition to these procedures, we used robust variance estimation with cluster-robust inference at the cohort level. This step is recommended to more accurately determine the confidence intervals in complex multivariate models 269 . The data distribution was assumed to be normal, but this was not formally tested.

To determine whether individual effects had a strong influence on our results, we calculated Cook’s distance D . Here, a threshold of D  > 0.5 was used to qualify a study as influential 270 . Heterogeneity in the present study was assessed using Cochran’s Q , which determines whether the extracted effect sizes estimate a common population effect size. Although the Q statistic in the ‘rma.mv’ function accounts for the hierarchical nature of the data, we also quantified the heterogeneity estimator σ ² for each random-effects level to provide a comprehensive overview of heterogeneity indicators. These indicators for all models can be found on the OSF project 12 in the Table ‘Model estimates’. To assess small study bias, we visually inspected the funnel plot and used the standard error as a moderator in the overarching meta-analyses.

Before any sub-group analysis, the overall effect size was used as input for power calculations. While such post hoc power calculations might be limited, we believe that a minimum number of effects to be included in subgroup analyses was necessary to allow for meaningful conclusions. Such medium effect sizes would also probably be the minimum effect sizes of interest for researchers as well as clinical practitioners. Power calculation for random-effects models further requires a sample size for each individual effect as well as an approximation of the expected heterogeneity between studies. For the sample size input, we used the median sample size in each of our studies. For heterogeneity, we assumed a value between medium and high levels of heterogeneity ( I ² = 62.5% 271 ), as moderator analyses typically aim at reducing heterogeneity overall. Subgroups were only further investigated if the number of observed effects achieved ~80% power under these circumstances, to allow for a more robust interpretation of the observed effects (see Supplementary Figs. 5 and 6 for the adult and newborn meta-analysis, respectively). In a next step, we investigated all pre-registered moderators for which sufficient power was detected. We first looked at our primary moderators (mental versus physical health) and how the effect sizes systematically varied as a function of our secondary moderators (for example, human–human or human–object touch, duration, skin-to-skin presence, etc.). We always included random slopes to allow for our moderators to vary with the random effects at our clustering variable, which is recommended in multilevel models to reduce false positives 272 . All statistical tests were performed two-sided. Significance of moderators was determined using omnibus F tests. Effect size differences between moderator levels and their confidence intervals were assessed via t tests.

Post hoc t tests were performed comparing mental and physical health benefits within each interacting moderator (for example, mental versus physical health benefits in cancer patients) and mental or physical health benefits across levels of the interacting moderator (for example, mental health benefits in cancer versus pain patients). The post hoc tests were not pre-registered. Data were visualized using forest plots and orchard plots 273 for categorical moderators and scatter plots for continuous moderators.

For a broad overview of prior work and their biases, risk of bias was assessed for all studies included in both meta-analyses and the systematic review. We assessed the risk of bias for the following parameters:

Bias from randomization, including whether a randomization procedure was performed, whether it was a between- or within-participant design and whether there were any baseline differences for demographic or dependent variables.

Sequence bias resulting from a lack of counterbalancing in within-subject designs.

Performance bias resulting from the participants or experiments not being blinded to the experimental conditions.

Attrition bias resulting from different dropout rates between experimental groups.

Note that four studies in the adult meta-analysis did not explicitly mention randomization as part of their protocol. However, since these studies never showed any baseline differences in all relevant variables (see ‘Risk of Bias’ table on the OSF project ) , we assumed that randomization was performed but not mentioned. Sequence bias was of no concern for studies for the meta-analysis since cross-over designs were excluded. It was, however, assessed for studies within the scope of the systematic review. Importantly, performance bias was always high in the adult/children meta-analysis, as blinding of the participants and experimenters to the experimental conditions was not possible owing to the nature of the intervention (touch versus no touch). For studies with newborns and animals, we assessed the performance bias as medium since neither newborns or animals are likely to be aware of being part of an experiment or specific group. An overview of the results is presented in Supplementary Fig. 21 , and the precise assessment for each study can be found on the OSF project 12 in the ‘Risk of Bias’ table.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

All data are available via Open Science Framework at https://doi.org/10.17605/OSF.IO/C8RVW (ref. 12 ). Source data are provided with this paper.

Code availability

All code is available via Open Science Framework at https://doi.org/10.17605/OSF.IO/C8RVW (ref. 12 ).

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Acknowledgements

We thank A. Frick and E. Chris for supporting the initial literature search and coding. We also thank A. Dreisoerner, T. Field, S. Koole, C. Kuhn, M. Henricson, L. Frey Law, J. Fraser, M. Cumella Reddan, and J. Stringer, who kindly responded to our data requests and provided additional information or data with respect to single studies. J.P. was supported by the German National Academy of Sciences Leopoldina (LPDS 2021-05). H.H. was supported by the Marietta-Blau scholarship of the Austrian Agency for Education and Internationalisation (OeAD) and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, project ID 422744262 – TRR 289). C.K. received funding from OCENW.XL21.XL21.069 and V.G. from the European Research Council (ERC) under European Union’s Horizon 2020 research and innovation programme, grant ‘HelpUS’ (758703) and from the Dutch Research Council (NWO) grant OCENW.XL21.XL21.069. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Open access funding provided by Ruhr-Universität Bochum.

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Julian Packheiser

Present address: Social Neuroscience, Faculty of Medicine, Ruhr University Bochum, Bochum, Germany

These authors contributed equally: Julian Packheiser, Helena Hartmann.

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Social Brain Lab, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Art and Sciences, Amsterdam, the Netherlands

Julian Packheiser, Helena Hartmann, Kelly Fredriksen, Valeria Gazzola, Christian Keysers & Frédéric Michon

Center for Translational and Behavioral Neuroscience, University Hospital Essen, Essen, Germany

Helena Hartmann

Clinical Neurosciences, Department for Neurology, University Hospital Essen, Essen, Germany

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Source Data Fig. 2

Effect size/error (columns ‘Hedges_g’ and ‘variance’) information for each study/cohort/effect included in the analysis. Source Data Fig. 3 Effect size/error (columns ‘Hedges_g’ and ‘variance’) together with moderator data (column ‘Outcome’) for each study/cohort/effect included in the analysis. Source Data Fig. 4 Effect size/error (columns ‘Hedges_g’ and ‘variance’) together with moderator data (columns ‘dyad_type’ and ‘skin_to_skin’) for each study/cohort/effect included in the analysis. Source Data Fig. 5 Effect size/error (columns ‘Hedges_g’ and ‘variance’) together with moderator data (column ‘touch_type’) for each study/cohort/effect included in the analysis. Source Data Fig. 6 Effect size/error (columns ‘Hedges_g’ and ‘variance’) together with moderator data (column ‘clin_sample’) for each study/cohort/effect included in the analysis. Source Data Fig. 7 Effect size/error (columns ‘Hedges_g’ and ‘variance’) together with moderator data (column ‘familiarity’) for each study/cohort/effect included in the analysis. Source Data Fig. 7 Effect size/error (columns ‘Hedges_g’ and ‘variance’) together with moderator data (columns ‘touch_duration’ and ‘sessions’) for each study/cohort/effect included in the analysis.

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Packheiser, J., Hartmann, H., Fredriksen, K. et al. A systematic review and multivariate meta-analysis of the physical and mental health benefits of touch interventions. Nat Hum Behav (2024). https://doi.org/10.1038/s41562-024-01841-8

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• Published: 23 August 2022

Prognostic risk factors for moderate-to-severe exacerbations in patients with chronic obstructive pulmonary disease: a systematic literature review

• John R. Hurst 1 ,
• MeiLan K. Han 2 ,
• Barinder Singh 3 ,
• Sakshi Sharma 4 ,
• Gagandeep Kaur 3 ,
• Enrico de Nigris 5 ,
• Ulf Holmgren 6 &
• Mohd Kashif Siddiqui 3  

Respiratory Research volume  23 , Article number:  213 ( 2022 ) Cite this article

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Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. COPD exacerbations are associated with a worsening of lung function, increased disease burden, and mortality, and, therefore, preventing their occurrence is an important goal of COPD management. This review was conducted to identify the evidence base regarding risk factors and predictors of moderate-to-severe exacerbations in patients with COPD.

A literature review was performed in Embase, MEDLINE, MEDLINE In-Process, and the Cochrane Central Register of Controlled Trials (CENTRAL). Searches were conducted from January 2015 to July 2019. Eligible publications were peer-reviewed journal articles, published in English, that reported risk factors or predictors for the occurrence of moderate-to-severe exacerbations in adults age ≥ 40 years with a diagnosis of COPD.

The literature review identified 5112 references, of which 113 publications (reporting results for 76 studies) met the eligibility criteria and were included in the review. Among the 76 studies included, 61 were observational and 15 were randomized controlled clinical trials. Exacerbation history was the strongest predictor of future exacerbations, with 34 studies reporting a significant association between history of exacerbations and risk of future moderate or severe exacerbations. Other significant risk factors identified in multiple studies included disease severity or bronchodilator reversibility (39 studies), comorbidities (34 studies), higher symptom burden (17 studies), and higher blood eosinophil count (16 studies).

Conclusions

This systematic literature review identified several demographic and clinical characteristics that predict the future risk of COPD exacerbations. Prior exacerbation history was confirmed as the most important predictor of future exacerbations. These prognostic factors may help clinicians identify patients at high risk of exacerbations, which are a major driver of the global burden of COPD, including morbidity and mortality.

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide [ 1 ]. Based upon disability-adjusted life-years, COPD ranked sixth out of 369 causes of global disease burden in 2019 [ 2 ]. COPD exacerbations are associated with a worsening of lung function, and increased disease burden and mortality (of those patients hospitalized for the first time with an exacerbation, > 20% die within 1 year of being discharged) [ 3 ]. Furthermore, patients with COPD consider exacerbations or hospitalization due to exacerbations to be the most important disease outcome, having a large impact on their lives [ 4 ]. Therefore, reducing the future risk of COPD exacerbations is a key goal of COPD management [ 5 ].

Being able to predict the level of risk for each patient allows clinicians to adapt treatment and patients to adjust their lifestyle (e.g., through a smoking cessation program) to prevent exacerbations [ 3 ]. As such, identifying high-risk patients using measurable risk factors and predictors that correlate with exacerbations is critical to reduce the burden of disease and prevent a cycle of decline encompassing irreversible lung damage, worsening quality of life (QoL), increasing disease burden, high healthcare costs, and early death.

Prior history of exacerbations is generally thought to be the best predictor of future exacerbations; however, there is a growing body of evidence suggesting other demographic and clinical characteristics, including symptom burden, airflow obstruction, comorbidities, and inflammatory biomarkers, also influence risk [ 6 , 7 , 8 , 9 ]. For example, in the prospective ECLIPSE observational study, the likelihood of patients experiencing an exacerbation within 1 year of follow-up increased significantly depending upon several factors, including prior exacerbation history, forced expiratory volume in 1 s (FEV 1 ), St. George’s Respiratory Questionnaire (SGRQ) score, gastroesophageal reflux, and white blood cell count [ 9 ].

Many studies have assessed predictors of COPD exacerbations across a variety of countries and patient populations. This systematic literature review (SLR) was conducted to identify and compile the evidence base regarding risk factors and predictors of moderate-to-severe exacerbations in patients with COPD.

• Systematic literature review

A comprehensive search strategy was designed to identify English-language studies published in peer-reviewed journals providing data on risk factors or predictors of moderate or severe exacerbations in adults aged ≥ 40 years with a diagnosis of COPD (sample size ≥ 100). The protocol is summarized in Table 1 and the search strategy is listed in Additional file 1 : Table S1. Key biomedical electronic literature databases were searched from January 2015 until July 2019. Other sources were identified via bibliographic searching of relevant systematic reviews.

Study selection process

Implementation and reporting followed the recommendations and standards of the Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) statement [ 10 ]. An independent reviewer conducted the first screening based on titles and abstracts, and a second reviewer performed a quality check of the excluded evidence. A single independent reviewer also conducted the second screening based on full-text articles, with a quality check of excluded evidence performed by a second reviewer. Likewise, data tables of the included studies were generated by one reviewer, and another reviewer performed a quality check of extracted data. Where more than one publication was identified describing a single study or trial, data were compiled into a single entry in the data-extraction table to avoid double counting of patients and studies. One publication was designated as the ‘primary publication’ for the purposes of the SLR, based on the following criteria: most recently published evidence and/or the article that presented the majority of data (e.g., journal articles were preferred over conference abstracts; articles that reported results for the full population were preferred over later articles providing results of subpopulations). Other publications reporting results from the same study were designated as ‘linked publications’; any additional data in the linked publications that were not included in the primary publication were captured in the SLR. Conference abstracts were excluded from the SLR unless they were a ‘linked publication.’

Included studies

A total of 5112 references (Fig.  1 ) were identified from the database searches. In total, 76 studies from 113 publications were included in the review. Primary publications and ‘linked publications’ for each study are detailed in Additional file 1 : Table S2, and study characteristics are shown in Additional file 1 : Table S3. The studies included clinical trials, registry studies, cross-sectional studies, cohort studies, database studies, and case–control studies. All 76 included studies were published in peer-reviewed journals. Regarding study design, 61 of the studies were observational (34 retrospective observational studies, 19 prospective observational studies, four cross-sectional studies, two studies with both retrospective and prospective cohort data, one case–control study, and one with cross-sectional and longitudinal data) and 15 were randomized controlled clinical trials.

PRISMA flow diagram of studies through the systematic review process. CA conference abstract, CENTRAL Cochrane Central Register of Controlled Trials, PRISMA  Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Of the 76 studies, 16 were conducted in North America (13 studies in the USA, two in Canada, and one in Mexico); 26 were conducted in Europe (seven studies in Spain, four in the UK, three in Denmark, two studies each in Bulgaria, the Netherlands, and Switzerland, and one study each in Sweden, Serbia, Portugal, Greece, Germany, and France) and 17 were conducted in Asia (six studies in South Korea, four in China, three in Taiwan, two in Japan, and one study each in Singapore and Israel). One study each was conducted in Turkey and Australia. Fifteen studies were conducted across multiple countries.

The majority of the studies (n = 54) were conducted in a multicenter setting, while 22 studies were conducted in a single-center setting. The sample size among the included studies varied from 118 to 339,389 patients.

Patient characteristics

A total of 75 studies reported patient characteristics (Additional file 1 : Table S4). The mean age was reported in 65 studies and ranged from 58.0 to 75.2 years. The proportion of male patients ranged from 39.7 to 97.6%. The majority of included studies (85.3%) had a higher proportion of males than females.

Exacerbation history (as defined per each study) was reported in 18 of 76 included studies. The proportion of patients with no prior exacerbation was reported in ten studies (range, 0.1–79.5% of patients), one or fewer prior exacerbation in ten studies (range, 46–100%), one or more prior exacerbation in eight studies (range, 18.4–100%), and two or more prior exacerbations in 12 studies (range, 6.1–55.0%).

Prognostic factors of exacerbations

A summary of the risk factors and predictors reported across the included studies is provided in Tables 2 and 3 . The overall findings of the SLR are summarized in Figs. 2 and 3 .

Risk factors for moderate-to-severe exacerbations in patients with COPD. Factors with > 30 supporting studies shown as large circles; factors with ≤ 30 supporting studies shown as small circles and should be interpreted cautiously. BDR bronchodilator reversibility, BMI body mass index, COPD chronic obstructive pulmonary disease, EOS eosinophil, QoL quality of life

Summary of risk factors for exacerbation events. a Treatment impact studies removed. BDR bronchodilator reversibility, BMI body mass index, COPD chronic obstructive pulmonary disease, EOS eosinophil, QoL quality of life

Exacerbation history within the past 12 months was the strongest predictor of future exacerbations. Across the studies assessing this predictor, 34 out of 35 studies (97.1%) reported a significant association between history of exacerbations and risk of future moderate-to-severe exacerbations (Table 3 ). Specifically, two or more exacerbations in the previous year or at least one hospitalization for COPD in the previous year were identified as reliable predictors of future moderate or severe exacerbations. Even one moderate exacerbation increased the risk of a future exacerbation, with the risk increasing further with each subsequent exacerbation (Fig.  4 ). A severe exacerbation was also found to increase the risk of subsequent exacerbation and hospitalization (Fig.  5 ). Patients experiencing one or more severe exacerbations were more likely to experience further severe exacerbations than moderate exacerbations [ 11 , 12 ]. In contrast, patients with a history of one or more moderate exacerbations were more likely to experience further moderate exacerbations than severe exacerbations [ 11 , 12 ].

Exacerbation history as a risk factor for moderate-to-severe exacerbations. Yun 2018 included two studies; the study from which data were extracted (COPDGene or ECLIPSE) is listed in parentheses. CI confidence interval, ES effect size

Exacerbation history as a risk factor for severe exacerbations. Where data have been extracted from a linked publication rather than the primary publication, the linked publication is listed in parentheses. CI confidence interval, ES , effect size

Overall, 35 studies assessed the association of comorbidities with the risk of exacerbation. All studies except one (97.1%) reported a positive association between comorbidities and the occurrence of moderate-to-severe exacerbations (Table 3 ). In addition to the presence of any comorbidity, specific comorbidities that were found to significantly increase the risk of moderate-to-severe exacerbations included anxiety and depression, cardiovascular comorbidities, gastroesophageal reflux disease/dyspepsia, and respiratory comorbidities (Fig.  6 ). Comorbidities that were significant risk factors for severe exacerbations included cardiovascular, musculoskeletal, and respiratory comorbidities, diabetes, and malignancy (Fig.  7 ). Overall, the strongest association between comorbidities and COPD readmissions in the emergency department was with cardiovascular disease. The degree of risk for both moderate-to-severe and severe exacerbations also increased with the number of comorbidities. A Dutch cohort study found that 88% of patients with COPD had at least one comorbidity, with hypertension (35%) and coronary heart disease (19%) being the most prevalent. In this cohort, the comorbidities with the greatest risk of frequent exacerbations were pulmonary cancer (odds ratio [OR] 1.85) and heart failure (OR 1.72) [ 7 ].

Comorbidities as risk factors for moderate-to-severe exacerbations. Yun 2018 included two studies; the study from which data were extracted (COPDGene or ECLIPSE) is listed in parentheses. Where data have been extracted from a linked publication rather than the primary publication, the linked publication is listed in parentheses. CI confidence interval, ES effect size, GERD gastroesophageal disease

Comorbidities as risk factors for severe exacerbations. Where data have been extracted from a linked publication rather than the primary publication, the linked publication is listed in parentheses. CI confidence interval, CKD , chronic kidney disease, ES effect size

The majority of studies assessing disease severity or bronchodilator reversibility (39/41; 95.1%) indicated a significant positive relation between risk of future exacerbations and greater disease severity, as assessed by greater lung function impairment (in terms of lower FEV 1 , FEV 1 /forced vital capacity ratio, or forced expiratory flow [25–75]/forced vital capacity ratio) or more severe Global Initiative for Chronic Obstructive Lung Disease (GOLD) class A − D, and a positive relationship between risk of future exacerbations and lack of bronchodilator reversibility (Table 3 , Figs. 8 and 9 ).

Disease severity as a risk factor for moderate-to-severe exacerbations. Yun 2018 included two studies; the study from which data were extracted (COPDGene or ECLIPSE) is listed in parentheses. Where data have been extracted from a linked publication rather than the primary publication, the linked publication is listed in parentheses. CI confidence interval, ES effect size, FEV 1 f orced expiratory volume in 1 s, FVC , forced vital capacity, GOLD Global Initiative for Obstructive Lung Disease, HR hazard ratio, OR odds ratio

Disease severity and BDR as risk factors for severe exacerbations. ACCP American College of Chest Physicians, ACOS Asthma-COPD overlap syndrome, ATS  American Thoracic Society, BDR bronchodilator reversibility, CI confidence interval, ERS  European Respiratory Society, ES effect size, FEV 1 forced expiratory volume in 1 s, FVC  forced vital capacity, GINA Global Initiative for Asthma, GOLD Global Initiative for Obstructive Lung Disease

Of 21 studies assessing the relationship between blood eosinophil count and exacerbations (Table 3 ), 16 reported estimates for the risk of moderate or severe exacerbations by eosinophil count. A positive association was observed between higher eosinophil count and a higher risk of moderate or severe exacerbations, particularly in patients not treated with an inhaled corticosteroid (ICS); however, five studies reported a significant positive association irrespective of intervention effects. The risk of moderate-to-severe exacerbations was observed to be positively associated with various definitions of higher eosinophil levels (absolute counts: ≥ 200, ≥ 300, ≥ 340, ≥ 400, and ≥ 500 cells/mm 3 ; % of blood eosinophil count: ≥ 2%, ≥ 3%, ≥ 4%, and ≥ 5%). Of note, one study found reduced efficacy of ICS in lowering moderate-to-severe exacerbation rates for current smokers versus former smokers at all eosinophil levels [ 13 ].

Of 12 studies assessing QoL scales, 11 (91.7%) studies reported a significant association between the worsening of QoL scores and the risk of future exacerbations (Table 3 ). Baseline SGRQ [ 14 , 15 ], Center for Epidemiologic Studies Depression Scale (for which increased scores may indicate impaired QoL) [ 16 ], and Clinical COPD Questionnaire [ 17 , 18 ] scores were found to be associated with future risk of moderate and/or severe COPD exacerbations. For symptom scores, six out of eight studies assessing the association between moderate-to-severe or severe exacerbations with COPD Assessment Test (CAT) scores reported a significant and positive relationship. Furthermore, the risk of moderate-to-severe exacerbations was found to be significantly higher in patients with higher CAT scores (≥ 10) [ 15 , 19 , 20 , 21 ], with one study demonstrating that a CAT score of 15 increased predictive ability for exacerbations compared with a score of 10 or more [ 18 ]. Among 15 studies that assessed the association of modified Medical Research Council (mMRC) scores with the risk of moderate-to-severe or severe exacerbation, 11 found that the risk of moderate-to-severe or severe exacerbations was significantly associated with higher mMRC scores (≥ 2) versus lower scores. Furthermore, morning and night symptoms (measured by Clinical COPD Questionnaire) were associated with poor health status and predicted future exacerbations [ 17 ].

Of 36 studies reporting the relationship between smoking status and moderate-to-severe or severe exacerbations, 22 studies (61.1%) reported a significant positive association (Table 3 ). Passive smoking was also significantly associated with an increased risk of severe exacerbations (OR 1.49) [ 20 ]. Of note, three studies reported a significantly lower rate of moderate-to-severe exacerbations in current smokers compared with former smokers [ 22 , 23 , 24 ].

A total of 14 studies assessed the association of body mass index (BMI) with the occurrence of frequent moderate-to-severe exacerbations in patients with COPD. Six out of 14 studies (42.9%) reported a significant negative association between exacerbations and BMI (Table 3 ). The risk of moderate and/or severe COPD exacerbations was highest among underweight patients compared with normal and overweight patients [ 23 , 25 , 26 , 27 , 28 ].

In the 29 studies reporting an association between age and moderate or severe exacerbations, more than half found an association of older age with an increased risk of moderate-to-severe exacerbations (58.6%; Table 3 ). Four of these studies noted a significant increase in the risk of moderate-to-severe or severe exacerbations for every 10-year increase in age [ 25 , 26 , 29 , 30 ]. However, 12 studies reported no significant association between age and moderate-to-severe or severe exacerbation risk.

Sixteen out of 33 studies investigating the impact of sex on exacerbation risk found a significant association (48.5%; Table 3 ). Among these, ten studies reported that female sex was associated with an increased risk of moderate-to-severe exacerbations, while six studies showed a higher exacerbation risk in males compared with females. There was some variation in findings by geographic location and exacerbation severity (Additional file 2 : Figs. S1 and S2). Notably, when assessing the risk of severe exacerbations, more studies found an association with male sex compared with female sex (6/13 studies vs 1/13 studies, respectively).

Both studies evaluating associations between exacerbations and environmental factors reported that colder temperature and exposure to major air pollution (NO 2 , O 3 , CO, and/or particulate matter ≤ 10 μm in diameter) increased hospital admissions due to severe exacerbations and moderate-to-severe exacerbation rates [ 31 , 32 ].

Four studies assessed the association of 6-min walk distance with the occurrence of frequent moderate-to-severe exacerbations (Table 3 ). One study (25.0%) found that shorter 6-min walk distance (representing low physical activity) was significantly associated with a shortened time to severe exacerbation, but the effect size was small (hazard ratio 0.99) [ 33 ].

Five out of six studies assessing the relationship between race or ethnicity and exacerbation risk reported significant associations (Table 3 ). Additionally, one study reported an association between geographic location in the US and exacerbations, with living in the Northeast region being the strongest predictor of severe COPD exacerbations versus living in the Midwest and South regions [ 34 ].

Overall, seven studies assessed the association of biomarkers with risk of future exacerbations (Table 3 ), with the majority identifying significant associations between inflammatory biomarkers and increased exacerbation risk, including higher C-reactive protein levels [ 8 , 35 ], fibrinogen levels [ 8 , 30 ], and white blood cell count [ 8 , 15 , 16 ].

This SLR has identified several demographic and clinical characteristics that predict the future risk of COPD exacerbations. Key factors associated with an increased risk of future moderate-to-severe exacerbations included a history of prior exacerbations, worse disease severity and bronchodilator reversibility, the presence of comorbidities, a higher eosinophil count, and older age (Fig.  2 ). These prognostic factors may help clinicians identify patients at high risk of exacerbations, which are a major driver of the burden of COPD, including morbidity and mortality [ 36 ].

Findings from this review summarize the existing evidence, validating the previously published literature [ 6 , 9 , 23 ] and suggesting that the best predictor of future exacerbations is a history of exacerbations in the prior year [ 8 , 11 , 12 , 13 , 14 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 26 , 29 , 34 , 35 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 ]. In addition, the effect size generally increased with the number of prior exacerbations, with a stronger effect observed with prior severe versus moderate exacerbations. This effect was observed across regions, including in Europe and North America, and in several global studies. This relationship represents a vicious circle, whereby one exacerbation predisposes a patient to experience future exacerbations and leading to an ever-increasing disease burden, and emphasizes the importance of preventing the first exacerbation event through early, proactive exacerbation prevention. The finding that prior exacerbations tended to be associated with future exacerbations of the same severity suggests that the severity of the underlying disease may influence exacerbation severity. However, the validity of the traditional classification of exacerbation severity has recently been challenged [ 61 ], and further work is required to understand relationships with objective assessments of exacerbation severity.

In addition to exacerbation history, disease severity and bronchodilator reversibility were also strong predictors for future exacerbations [ 8 , 14 , 16 , 18 , 19 , 20 , 22 , 23 , 24 , 26 , 28 , 29 , 33 , 37 , 40 , 43 , 44 , 45 , 46 , 48 , 50 , 51 , 52 , 56 , 59 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 ]. The association with disease severity was noted in studies that used GOLD disease stages 1–4 and those that used FEV 1 percent predicted and other lung function assessments as continuous variables. Again, this risk factor is self-perpetuating, as evidence shows that even a single moderate or severe exacerbation may almost double the rate of lung function decline [ 79 ]. Accordingly, disease severity and exacerbation history may be correlated. Margüello et al. concluded that the severity of COPD could be associated with a higher risk of exacerbations, but this effect was partly determined by the exacerbations suffered in the previous year [ 23 ]. It should be noted that FEV 1 is not recommended by GOLD for use as a predictor of exacerbation risk or mortality alone due to insufficient precision when used at the individual patient level [ 5 ].

Another factor that should be considered when assessing individual exacerbation risk is the presence of comorbidities [ 7 , 14 , 16 , 18 , 19 , 20 , 21 , 22 , 24 , 25 , 26 , 27 , 28 , 30 , 33 , 34 , 35 , 40 , 41 , 44 , 45 , 46 , 47 , 48 , 51 , 52 , 53 , 54 , 56 , 58 , 59 , 63 , 64 , 73 , 74 , 76 , 77 , 80 , 81 , 82 , 83 , 84 , 85 ]. Comorbidities are common in COPD, in part due to common risk factors (e.g., age, smoking, lifestyle factors) that also increase the risk of other chronic diseases [ 7 ]. Significant associations were observed between exacerbation risk and comorbidities, such as anxiety and depression, cardiovascular disease, diabetes, and respiratory comorbidities. As with prior exacerbations, the strength of the association increased with the number of comorbidities. Some comorbidities that were found to be associated with COPD exacerbations share a common biological mechanism of systemic inflammation, such as cardiovascular disease, diabetes, and depression [ 86 ]. Furthermore, other respiratory comorbidities, including asthma and bronchiectasis, involve inflammation of the airways [ 87 ]. In these patients, optimal management of comorbidities may reduce the risk of future COPD exacerbations (and improve QoL), although further research is needed to confirm the efficacy of this approach to exacerbation prevention. As cardiovascular conditions, including hypertension and coronary heart disease, are the most common comorbidities in people with COPD [ 7 ], reducing cardiovascular risk may be a key goal in reducing the occurrence of exacerbations. For other comorbidities, the mechanism for the association with exacerbation risk may be related to non-biological factors. For example, in depression, it has been suggested that the mechanism may relate to greater sensitivity to symptom changes or more frequent physician visits [ 88 ].

There is now a growing body of evidence reporting the relationship between blood eosinophil count and exacerbation risk [ 8 , 13 , 14 , 20 , 37 , 48 , 52 , 56 , 59 , 60 , 62 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 ]. Data from many large clinical trials (SUNSET [ 89 ], FLAME [ 96 ], WISDOM [ 98 ], IMPACT [ 13 ], TRISTAN [ 99 ], INSPIRE [ 99 ], KRONOS [ 91 ], TRIBUTE [ 48 ], TRILOGY [ 52 ], TRINITY [ 56 ]) have also shown relationships between treatment, eosinophil count, and exacerbation rates. Evidence shows that eosinophil count, along with other effect modifiers (e.g., exacerbation history), can be used to predict reductions in exacerbations with ICS treatment. Identifying patients most likely to respond to ICS should contribute to personalized medicine approaches to treat COPD. One challenge in drawing a strong conclusion from eosinophil counts is the choice of a cut-off value, with a variety of absolute and percentage values observed to be positively associated with the risk of moderate-to-severe exacerbations. The use of absolute counts may be more practical, as these are not affected by variations in other immune cell numbers; however, there is a lack of consensus on this point [ 100 ].

Across the studies examined, associations between sex and the risk of moderate and/or severe exacerbations were variable [ 14 , 16 , 18 , 20 , 21 , 22 , 23 , 24 , 26 , 27 , 28 , 29 , 37 , 40 , 42 , 44 , 45 , 46 , 47 , 48 , 51 , 52 , 56 , 58 , 59 , 63 , 73 , 74 , 77 , 80 , 83 , 84 , 85 ]. A greater number of studies showed an increased risk of exacerbations in females compared with males. In contrast, some studies failed to detect a relationship, suggesting that country-specific or cultural factors may play a role. A majority of the included studies evaluated more male patients than female patients; to further elucidate the relationship between sex and exacerbations, more studies in female patients are warranted. Over half of the studies that assessed the relationship between age and exacerbation risk found an association between increasing age and increasing risk of moderate-to-severe COPD exacerbations [ 14 , 16 , 18 , 20 , 21 , 22 , 23 , 24 , 26 , 27 , 28 , 29 , 33 , 40 , 42 , 44 , 45 , 47 , 51 , 52 , 54 , 56 , 63 , 73 , 74 , 77 , 80 , 83 , 85 ].

Our findings also suggested that patients with low BMI have greater risk of moderate and/or severe exacerbations. The mechanism underlying this increased risk in underweight patients is poorly understood; however, loss of lean body mass in patients with COPD may be related to ongoing systemic inflammation that impacts skeletal muscle mass [ 101 , 102 , 103 ].

A limitation of this SLR, that may have resulted in some studies with valid results being missed, was the exclusion of non-English-language studies and the limitation by date; however, the search strategy was otherwise broad, resulting in the review of a large number of studies. The majority of studies captured in this SLR were from Europe, North America, and Asia. The findings may therefore be less generalizable to patients in other regions, such as Africa or South America. Given that one study reported an association between geographic location within different regions of the US and exacerbations [ 34 ], it is plausible that risk of exacerbations may be impacted by global location. As no formal meta-analysis was planned, the assessments are based on a qualitative synthesis of studies. A majority of the included studies looked at exposures of certain factors (e.g., history of exacerbations) at baseline; however, some of these factors change over time, calling into question whether a more sophisticated statistical analysis should have been conducted in some cases to consider time-varying covariates. Our results can only inform on associations, not causation, and there are likely bidirectional relationships between many factors and exacerbation risk (e.g., health status). Finally, while our review of the literature captured a large number of prognostic factors, other variables such as genetic factors, lung microbiome composition, and changes in therapy over time have not been widely studied to date, but might also influence exacerbation frequency [ 104 ]. Further research is needed to assess the contribution of these factors to exacerbation risk.

This SLR captured publications up to July 2019. However, further studies have since been published that further support the prognostic factors identified here. For example, recent studies have reported an increased risk of exacerbations in patients with a history of exacerbations [ 105 ], comorbidities [ 106 ], poorer lung function (GOLD stage) [ 105 ], higher symptomatic burden [ 107 ], female sex [ 105 ], and lower BMI [ 106 , 108 ].

In summary, the literature assessing risk factors for moderate-to-severe COPD exacerbations shows that there are associations between several demographic and disease characteristics with COPD exacerbations, potentially allowing clinicians to identify patients most at risk of future exacerbations. Exacerbation history, comorbidities, and disease severity or bronchodilator reversibility were the factors most strongly associated with exacerbation risk, and should be considered in future research efforts to develop prognostic tools to estimate the likelihood of exacerbation occurrence. Importantly, many prognostic factors for exacerbations, such as symptom burden, QoL, and comorbidities, are modifiable with optimal pharmacologic and non-pharmacologic treatments or lifestyle modifications. Overall, the evidence suggests that, taken together, predicting and reducing exacerbation risk is an achievable goal in COPD.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Body mass index

COPD Assessment Test

Chronic obstructive pulmonary disease

Forced expiratory volume in 1 s

Global Initiative for Chronic Obstructive Lung Disease

Inhaled corticosteroid

Modified Medical Research Council

Quality of life

St. George’s Respiratory Questionnaire

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Acknowledgements

Medical writing support, under the direction of the authors, was provided by Julia King, PhD, and Sarah Piggott, MChem, CMC Connect, McCann Health Medical Communications, funded by AstraZeneca in accordance with Good Publication Practice (GPP3) guidelines [ 109 ].

This study was supported by AstraZeneca.

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UCL Respiratory, University College London, London, WC1E 6BT, UK

John R. Hurst

Division of Pulmonary and Critical Care, University of Michigan, Ann Arbor, MI, USA

MeiLan K. Han

Formerly of Parexel International, Mohali, India

Barinder Singh, Gagandeep Kaur & Mohd Kashif Siddiqui

Parexel International, Mohali, India

Sakshi Sharma

Formerly of AstraZeneca, Cambridge, UK

Enrico de Nigris

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The authors have made the following declaration about their contributions. JRH and MKH made substantial contributions to the interpretation of data; BS, SS, GK, and MKS made substantial contributions to the acquisition, analysis, and interpretation of data; EdN and UH made substantial contributions to the conception and design of the work and the interpretation of data. All authors contributed to drafting or critically revising the article, have approved the submitted version, and agree to be personally accountable for their own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. All authors read and approved the final manuscript.

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Correspondence to John R. Hurst .

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Competing interests.

JRH reports consulting fees from AstraZeneca; speaker fees from AstraZeneca, Chiesi, Pfizer, and Takeda; and travel support from GlaxoSmithKline and AstraZeneca. MKH reports assistance with conduction of this research and publication from AstraZeneca; personal fees from Aerogen, Altesa Biopharma, AstraZeneca, Boehringer Ingelheim, Chiesi, Cipla, DevPro, GlaxoSmithKline, Integrity, Medscape, Merck, Mylan, NACE, Novartis, Polarean, Pulmonx, Regeneron, Sanofi, Teva, Verona, United Therapeutics, and UpToDate; either in kind research support or funds paid to the institution from the American Lung Association, AstraZeneca, Biodesix, Boehringer Ingelheim, the COPD Foundation, Gala Therapeutics, the NIH, Novartis, Nuvaira, Sanofi, and Sunovion; participation in Data Safety Monitoring Boards for Novartis and Medtronic with funds paid to the institution; and stock options from Altesa Biopharma and Meissa Vaccines. BS, GK, and MKS are former employees of Parexel International. SS is an employee of Parexel International, which was funded by AstraZeneca to conduct this analysis. EdN is a former employee of AstraZeneca and previously held stock and/or stock options in the company. UH is an employee of AstraZeneca and holds stock and/or stock options in the company.

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Supplementary Information

Additional file1: table s1..

Search strategies. Table S2. List of included studies with linked publications. Table S3. Study characteristics across the 76 included studies. Table S4. Clinical characteristics of the patients assessed across the included studies.

Additional file 2: Fig. S1.

Sex (male vs female) as a risk factor for moderate-to-severe exacerbations. Fig. S2. Sex (male vs female) as a risk factor for severe exacerbations.

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Hurst, J.R., Han, M.K., Singh, B. et al. Prognostic risk factors for moderate-to-severe exacerbations in patients with chronic obstructive pulmonary disease: a systematic literature review. Respir Res 23 , 213 (2022). https://doi.org/10.1186/s12931-022-02123-5

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Received : 02 March 2022

Accepted : 20 July 2022

Published : 23 August 2022

DOI : https://doi.org/10.1186/s12931-022-02123-5

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