systematic review in healthcare research

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• v.2(1); Jan-Mar 2013

Systematic Reviews and Meta-analysis: Understanding the Best Evidence in Primary Healthcare

S. gopalakrishnan.

Department of Community Medicine, SRM Medical College, Hospital and Research Centre, Kattankulathur, Tamil Nadu, India

P. Ganeshkumar

Healthcare decisions for individual patients and for public health policies should be informed by the best available research evidence. The practice of evidence-based medicine is the integration of individual clinical expertise with the best available external clinical evidence from systematic research and patient's values and expectations. Primary care physicians need evidence for both clinical practice and for public health decision making. The evidence comes from good reviews which is a state-of-the-art synthesis of current evidence on a given research question. Given the explosion of medical literature, and the fact that time is always scarce, review articles play a vital role in decision making in evidence-based medical practice. Given that most clinicians and public health professionals do not have the time to track down all the original articles, critically read them, and obtain the evidence they need for their questions, systematic reviews and clinical practice guidelines may be their best source of evidence. Systematic reviews aim to identify, evaluate, and summarize the findings of all relevant individual studies over a health-related issue, thereby making the available evidence more accessible to decision makers. The objective of this article is to introduce the primary care physicians about the concept of systematic reviews and meta-analysis, outlining why they are important, describing their methods and terminologies used, and thereby helping them with the skills to recognize and understand a reliable review which will be helpful for their day-to-day clinical practice and research activities.

Introduction

Evidence-based healthcare is the integration of best research evidence with clinical expertise and patient values. Green denotes, “Using evidence from reliable research, to inform healthcare decisions, has the potential to ensure best practice and reduce variations in healthcare delivery.” However, incorporating research into practice is time consuming, and so we need methods of facilitating easy access to evidence for busy clinicians.[ 1 ] Ganeshkumar et al . mentioned that nearly half of the private practitioners in India were consulting more than 4 h per day in a locality,[ 2 ] which explains the difficulty of them in spending time in searching evidence during consultation. Ideally, clinical decision making ought to be based on the latest evidence available. However, to keep abreast with the continuously increasing number of publications in health research, a primary healthcare professional would need to read an insurmountable number of articles every day, covered in more than 13 million references and over 4800 biomedical and health journals in Medline alone. With the view to address this challenge, the systematic review method was developed. Systematic reviews aim to inform and facilitate this process through research synthesis of multiple studies, enabling increased and efficient access to evidence.[ 1 , 3 , 4 ]

Systematic reviews and meta-analyses have become increasingly important in healthcare settings. Clinicians read them to keep up-to-date with their field and they are often used as a starting point for developing clinical practice guidelines. Granting agencies may require a systematic review to ensure there is justification for further research and some healthcare journals are moving in this direction.[ 5 ]

This article is intended to provide an easy guide to understand the concept of systematic reviews and meta-analysis, which has been prepared with the aim of capacity building for general practitioners and other primary healthcare professionals in research methodology and day-to-day clinical practice.

The purpose of this article is to introduce readers to:

• The two approaches of evaluating all the available evidence on an issue i.e., systematic reviews and meta-analysis,
• Discuss the steps in doing a systematic review,
• Introduce the terms used in systematic reviews and meta-analysis,
• Interpret results of a meta-analysis, and
• The advantages and disadvantages of systematic review and meta-analysis.

Application

What is the effect of antiviral treatment in dengue fever? Most often a primary care physician needs to know convincing answers to questions like this in a primary care setting.

To find out the solutions or answers to a clinical question like this, one has to refer textbooks, ask a colleague, or search electronic database for reports of clinical trials. Doctors need reliable information on such problems and on the effectiveness of large number of therapeutic interventions, but the information sources are too many, i.e., nearly 20,000 journals publishing 2 million articles per year with unclear or confusing results. Because no study, regardless of its type, should be interpreted in isolation, a systematic review is generally the best form of evidence.[ 6 ] So, the preferred method is a good summary of research reports, i.e., systematic reviews and meta-analysis, which will give evidence-based answers to clinical situations.

There are two fundamental categories of research: Primary research and secondary research. Primary research is collecting data directly from patients or population, while secondary research is the analysis of data already collected through primary research. A review is an article that summarizes a number of primary studies and may draw conclusions on the topic of interest which can be traditional (unsystematic) or systematic.

Terminologies

Systematic review.

A systematic review is a summary of the medical literature that uses explicit and reproducible methods to systematically search, critically appraise, and synthesize on a specific issue. It synthesizes the results of multiple primary studies related to each other by using strategies that reduce biases and random errors.[ 7 ] To this end, systematic reviews may or may not include a statistical synthesis called meta-analysis, depending on whether the studies are similar enough so that combining their results is meaningful.[ 8 ] Systematic reviews are often called overviews.

The evidence-based practitioner, David Sackett, defines the following terminologies.[ 3 ]

• Review: The general term for all attempts to synthesize the results and conclusions of two or more publications on a given topic.
• Overview: When a review strives to comprehensively identify and track down all the literature on a given topic (also called “systematic literature review”).
• Meta-analysis: A specific statistical strategy for assembling the results of several studies into a single estimate.

Systematic reviews adhere to a strict scientific design based on explicit, pre-specified, and reproducible methods. Because of this, when carried out well, they provide reliable estimates about the effects of interventions so that conclusions are defensible. Systematic reviews can also demonstrate where knowledge is lacking. This can then be used to guide future research. Systematic reviews are usually carried out in the areas of clinical tests (diagnostic, screening, and prognostic), public health interventions, adverse (harm) effects, economic (cost) evaluations, and how and why interventions work.[ 9 ]

Cochrane reviews

Cochrane reviews are systematic reviews undertaken by members of the Cochrane Collaboration which is an international not-for-profit organization that aims to help people to make well-informed decisions about healthcare by preparing, maintaining, and promoting the accessibility of systematic reviews of the effects of healthcare interventions.

Cochrane Primary Health Care Field is a systematic review of primary healthcare research on prevention, treatment, rehabilitation, and diagnostic test accuracy. The overall aim and mission of the Primary Health Care Field is to promote the quality, quantity, dissemination, accessibility, applicability, and impact of Cochrane systematic reviews relevant to people who work in primary care and to ensure proper representation in the interests of primary care clinicians and consumers in Cochrane reviews and review groups, and in other entities. This field would serve to coordinate and promote the mission of the Cochrane Collaboration within the primary healthcare disciplines, as well as ensuring that primary care perspectives are adequately represented within the Collaboration.[ 10 ]

Meta-analysis

A meta-analysis is the combination of data from several independent primary studies that address the same question to produce a single estimate like the effect of treatment or risk factor. It is the statistical analysis of a large collection of analysis and results from individual studies for the purpose of integrating the findings.[ 11 ] The term meta-analysis has been used to denote the full range of quantitative methods for research reviews.[ 12 ] Meta-analyses are studies of studies.[ 13 ] Meta-analysis provides a logical framework to a research review where similar measures from comparable studies are listed systematically and the available effect measures are combined wherever possible.[ 14 ]

The fundamental rationale of meta-analysis is that it reduces the quantity of data by summarizing data from multiple resources and helps to plan research as well as to frame guidelines. It also helps to make efficient use of existing data, ensuring generalizability, helping to check consistency of relationships, explaining data inconsistency, and quantifies the data. It helps to improve the precision in estimating the risk by using explicit methods.

Therefore, “systematic review” will refer to the entire process of collecting, reviewing, and presenting all available evidence, while the term “meta-analysis” will refer to the statistical technique involved in extracting and combining data to produce a summary result.[ 15 ]

Steps in doing systematic reviews/meta-analysis

Following are the six fundamental essential steps while doing systematic review and meta-analysis.[ 16 ]

Define the question

This is the most important part of systematic reviews/meta-analysis. The research question for the systematic reviews may be related to a major public health problem or a controversial clinical situation which requires acceptable intervention as a possible solution to the present healthcare need of the community. This step is most important since the remaining steps will be based on this.

Reviewing the literature

This can be done by going through scientific resources such as electronic database, controlled clinical trials registers, other biomedical databases, non-English literatures, “gray literatures” (thesis, internal reports, non–peer-reviewed journals, pharmaceutical industry files), references listed in primary sources, raw data from published trials and other unpublished sources known to experts in the field. Among the available electronic scientific database, the popular ones are PUBMED, MEDLINE, and EMBASE.

Sift the studies to select relevant ones

To select the relevant studies from the searches, we need to sift through the studies thus identified. The first sift is pre-screening, i.e., to decide which studies to retrieve in full, and the second sift is selection which is to look again at these studies and decide which are to be included in the review. The next step is selecting the eligible studies based on similar study designs, year of publication, language, choice among multiple articles, sample size or follow-up issues, similarity of exposure, and or treatment and completeness of information.

It is necessary to ensure that the sifting includes all relevant studies like the unpublished studies (desk drawer problem), studies which came with negative conclusions or were published in non-English journals, and studies with small sample size.

Assess the quality of studies

The steps undertaken in evaluating the study quality are early definition of study quality and criteria, setting up a good scoring system, developing a standard form for assessment, calculating quality for each study, and finally using this for sensitivity analysis.

For example, the quality of a randomized controlled trial can be assessed by finding out the answers to the following questions:

• Was the assignment to the treatment groups really random?
• Was the treatment allocation concealed?
• Were the groups similar at baseline in terms of prognostic factors?
• Were the eligibility criteria specified?
• Were the assessors, the care provider, and the patient blinded?
• Were the point estimates and measure of variability presented for the primary outcome measure?
• Did the analyses include intention-to-treat analysis?

Calculate the outcome measures of each study and combine them

We need a standard measure of outcome which can be applied to each study on the basis of its effect size. Based on their type of outcome, following are the measures of outcome: Studies with binary outcomes (cured/not cured) have odds ratio, risk ratio; studies with continuous outcomes (blood pressure) have means, difference in means, standardized difference in means (effect sizes); and survival or time-to-event data have hazard ratios.

Combining studies

Homogeneity of different studies can be estimated at a glance from a forest plot (explained below). For example, if the lower confidence interval of every trial is below the upper of all the others, i.e., the lines all overlap to some extent, then the trials are homogeneous. If some lines do not overlap at all, these trials may be said to be heterogeneous.

The definitive test for assessing the heterogeneity of studies is a variant of Chi-square test (Mantel–Haenszel test). The final step is calculating the common estimate and its confidence interval with the original data or with the summary statistics from all the studies. The best estimate of treatment effect can be derived from the weighted summary statistics of all studies which will be based on weighting to sample size, standard errors, and other summary statistics. Log scale is used to combine the data to estimate the weighting.

Interpret results: Graph

The results of a meta-analysis are usually presented as a graph called forest plot because the typical forest plots appear as forest of lines. It provides a simple visual presentation of individual studies that went into the meta-analysis at a glance. It shows the variation between the studies and an estimate of the overall result of all the studies together.

Forest plot

Meta-analysis graphs can principally be divided into six columns [ Figure 1 ]. Individual study results are displayed in rows. The first column (“study”) lists the individual study IDs included in the meta-analysis; usually the first author and year are displayed. The second column relates to the intervention groups and the third column to the control groups. The fourth column visually displays the study results. The line in the middle is called “the line of no effect.” The weight (in %) in the fifth column indicates the weighting or influence of the study on the overall results of the meta-analysis of all included studies. The higher the percentage weight, the bigger the box, the more influence the study has on the overall results. The sixth column gives the numerical results for each study (e.g., odds ratio or relative risk and 95% confidence interval), which are identical to the graphical display in the fourth column. The diamond in the last row of the graph illustrates the overall result of the meta-analysis.[ 4 ]

Interpretation of meta-analysis[ 4 ]

Thus, the horizontal lines represent individual studies. Length of line is the confidence interval (usually 95%), squares on the line represent effect size (risk ratio) for the study, with area of the square being the study size (proportional to weight given) and position as point estimate (relative risk) of the study.[ 7 ]

For example, the forest plot of the effectiveness of dexamethasone compared with placebo in preventing the recurrence of acute severe migraine headache in adults is shown in Figure 2 .[ 17 ]

Forest plot of the effectiveness of dexamethasone compared with placebo in preventing the recurrence of acute severe migraine headache in adults[ 17 ]

The overall effect is shown as diamond where the position toward the center represents pooled point estimate, the width represents estimated 95% confidence interval for all studies, and the black plain line vertically in the middle of plot is the “line of no effect” (e.g., relative risk = 1).

Therefore, when examining the results of a systematic reviews/meta-analysis, the following questions should be kept in mind:

• Heterogeneity among studies may make any pooled estimate meaningless.
• The quality of a meta-analysis cannot be any better than the quality of the studies it is summarizing.
• An incomplete search of the literature can bias the findings of a meta-analysis.
• Make sure that the meta-analysis quantifies the size of the effect in units that you can understand.

Subgroup analysis and sensitivity analysis

Subgroup analysis looks at the results of different subgroups of trials, e.g., by considering trials on adults and children separately. This should be planned at the protocol stage itself which is based on good scientific reasoning and is to be kept to a minimum.

Sensitivity analysis is used to determine how results of a systematic review/meta-analysis change by fiddling with data, for example, what is the implication if the exclusion criteria or excluded unpublished studies or weightings are assigned differently. Thus, after the analysis, if changing makes little or no difference to the overall results, the reviewer's conclusions are robust. If the key findings disappear, then the conclusions need to be expressed more cautiously.

Advantages of Systematic Reviews

Systematic reviews have specific advantages because of using explicit methods which limit bias, draw reliable and accurate conclusions, easily deliver required information to healthcare providers, researchers, and policymakers, help to reduce the time delay in the research discoveries to implementation, improve the generalizability and consistency of results, generation of new hypotheses about subgroups of the study population, and overall they increase precision of the results.[ 18 ]

Limitations in Systematic Reviews/Meta-analysis

As with all research, the value of a systematic review depends on what was done, what was found, and the clarity of reporting. As with other publications, the reporting quality of systematic reviews varies, limiting readers’ ability to assess the strengths and weaknesses of those reviews.[ 5 ]

Even though systematic review and meta-analysis are considered the best evidence for getting a definitive answer to a research question, there are certain inherent flaws associated with it, such as the location and selection of studies, heterogeneity, loss of information on important outcomes, inappropriate subgroup analyses, conflict with new experimental data, and duplication of publication.

Publication Bias

Publication bias results in it being easier to find studies with a “positive” result.[ 19 ] This occurs particularly due to inappropriate sifting of the studies where there is always a tendency towards the studies with positive (significant) outcomes. This effect occurs more commonly in systematic reviews/meta-analysis which need to be eliminated.

The quality of reporting of systematic reviews is still not optimal. In a recent review of 300 systematic reviews, few authors reported assessing possible publication bias even though there is overwhelming evidence both for its existence and its impact on the results of systematic reviews. Even when the possibility of publication bias is assessed, there is no guarantee that systematic reviewers have assessed or interpreted it appropriately.[ 20 ]

To overcome certain limitations mentioned above, the Cochrane reviews are currently reported in a format where at the end of every review, findings are summarized in the author's point of view and also give an overall picture of the outcome by means of plain language summary. This is found to be much helpful to understand the existing evidence about the topic more easily by the reader.

A systematic review is an overview of primary studies which contains an explicit statement of objectives, materials, and methods, and has been conducted according to explicit and reproducible methodology. A meta-analysis is a mathematical synthesis of the results of two or more primary studies that addressed the same hypothesis in the same way. Although meta-analysis can increase the precision of a result, it is important to ensure that the methods used for the reviews were valid and reliable.

High-quality systematic reviews and meta-analyses take great care to find all relevant studies, critically assess each study, synthesize the findings from individual studies in an unbiased manner, and present balanced important summary of findings with due consideration of any flaws in the evidence. Systematic review and meta-analysis is a way of summarizing research evidence, which is generally the best form of evidence, and hence positioned at the top of the hierarchy of evidence.

Systematic reviews can be very useful decision-making tools for primary care/family physicians. They objectively summarize large amounts of information, identifying gaps in medical research, and identifying beneficial or harmful interventions which will be useful for clinicians, researchers, and even for public and policymakers.

Source of Support: Nil

Conflict of Interest: None declared.

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Carrying out systematic literature reviews: an introduction

Alan Davies

Lecturer in Health Data Science, School of Health Sciences, University of Manchester, Manchester

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Systematic reviews provide a synthesis of evidence for a specific topic of interest, summarising the results of multiple studies to aid in clinical decisions and resource allocation. They remain among the best forms of evidence, and reduce the bias inherent in other methods. A solid understanding of the systematic review process can be of benefit to nurses that carry out such reviews, and for those who make decisions based on them. An overview of the main steps involved in carrying out a systematic review is presented, including some of the common tools and frameworks utilised in this area. This should provide a good starting point for those that are considering embarking on such work, and to aid readers of such reviews in their understanding of the main review components, in order to appraise the quality of a review that may be used to inform subsequent clinical decision making.

Since their inception in the late 1970s, systematic reviews have gained influence in the health professions ( Hanley and Cutts, 2013 ). Systematic reviews and meta-analyses are considered to be the most credible and authoritative sources of evidence available ( Cognetti et al, 2015 ) and are regarded as the pinnacle of evidence in the various ‘hierarchies of evidence’. Reviews published in the Cochrane Library ( https://www.cochranelibrary.com) are widely considered to be the ‘gold’ standard. Since Guyatt et al (1995) presented a users' guide to medical literature for the Evidence-Based Medicine Working Group, various hierarchies of evidence have been proposed. Figure 1 illustrates an example.

Systematic reviews can be qualitative or quantitative. One of the criticisms levelled at hierarchies such as these is that qualitative research is often positioned towards or even is at the bottom of the pyramid, thus implying that it is of little evidential value. This may be because of traditional issues concerning the quality of some qualitative work, although it is now widely recognised that both quantitative and qualitative research methodologies have a valuable part to play in answering research questions, which is reflected by the National Institute for Health and Care Excellence (NICE) information concerning methods for developing public health guidance. The NICE (2012) guidance highlights how both qualitative and quantitative study designs can be used to answer different research questions. In a revised version of the hierarchy-of-evidence pyramid, the systematic review is considered as the lens through which the evidence is viewed, rather than being at the top of the pyramid ( Murad et al, 2016 ).

Both quantitative and qualitative research methodologies are sometimes combined in a single review. According to the Cochrane review handbook ( Higgins and Green, 2011 ), regardless of type, reviews should contain certain features, including:

• Clearly stated objectives
• Predefined eligibility criteria for inclusion or exclusion of studies in the review
• A reproducible and clearly stated methodology
• Validity assessment of included studies (eg quality, risk, bias etc).

The main stages of carrying out a systematic review are summarised in Box 1 .

Formulating the research question

Before undertaking a systemic review, a research question should first be formulated ( Bashir and Conlon, 2018 ). There are a number of tools/frameworks ( Table 1 ) to support this process, including the PICO/PICOS, PEO and SPIDER criteria ( Bowers et al, 2011 ). These frameworks are designed to help break down the question into relevant subcomponents and map them to concepts, in order to derive a formalised search criterion ( Methley et al, 2014 ). This stage is essential for finding literature relevant to the question ( Jahan et al, 2016 ).

It is advisable to first check that the review you plan to carry out has not already been undertaken. You can optionally register your review with an international register of prospective reviews called PROSPERO, although this is not essential for publication. This is done to help you and others to locate work and see what reviews have already been carried out in the same area. It also prevents needless duplication and instead encourages building on existing work ( Bashir and Conlon, 2018 ).

A study ( Methley et al, 2014 ) that compared PICO, PICOS and SPIDER in relation to sensitivity and specificity recommended that the PICO tool be used for a comprehensive search and the PICOS tool when time/resources are limited.

The use of the SPIDER tool was not recommended due to the risk of missing relevant papers. It was, however, found to increase specificity.

These tools/frameworks can help those carrying out reviews to structure research questions and define key concepts in order to efficiently identify relevant literature and summarise the main objective of the review ( Jahan et al, 2016 ). A possible research question could be: Is paracetamol of benefit to people who have just had an operation? The following examples highlight how using a framework may help to refine the question:

• What form of paracetamol? (eg, oral/intravenous/suppository)
• Is the dosage important?
• What is the patient population? (eg, children, adults, Europeans)
• What type of operation? (eg, tonsillectomy, appendectomy)
• What does benefit mean? (eg, reduce post-operative pyrexia, analgesia).

An example of a more refined research question could be: Is oral paracetamol effective in reducing pain following cardiac surgery for adult patients? A number of concepts for each element will need to be specified. There will also be a number of synonyms for these concepts ( Table 2 ).

Table 2 shows an example of concepts used to define a search strategy using the PICO statement. It is easy to see even with this dummy example that there are many concepts that require mapping and much thought required to capture ‘good’ search criteria. Consideration should be given to the various terms to describe the heart, such as cardiac, cardiothoracic, myocardial, myocardium, etc, and the different names used for drugs, such as the equivalent name used for paracetamol in other countries and regions, as well as the various brand names. Defining good search criteria is an important skill that requires a lot of practice. A high-quality review gives details of the search criteria that enables the reader to understand how the authors came up with the criteria. A specific, well-defined search criterion also aids in the reproducibility of a review.

Search criteria

Before the search for papers and other documents can begin it is important to explicitly define the eligibility criteria to determine whether a source is relevant to the review ( Hanley and Cutts, 2013 ). There are a number of database sources that are searched for medical/health literature including those shown in Table 3 .

The various databases can be searched using common Boolean operators to combine or exclude search terms (ie AND, OR, NOT) ( Figure 2 ).

Although most literature databases use similar operators, it is necessary to view the individual database guides, because there are key differences between some of them. Table 4 details some of the common operators and wildcards used in the databases for searching. When developing a search criteria, it is a good idea to check concepts against synonyms, as well as abbreviations, acronyms and plural and singular variations ( Cognetti et al, 2015 ). Reading some key papers in the area and paying attention to the key words they use and other terms used in the abstract, and looking through the reference lists/bibliographies of papers, can also help to ensure that you incorporate relevant terms. Medical Subject Headings (MeSH) that are used by the National Library of Medicine (NLM) ( https://www.nlm.nih.gov/mesh/meshhome.html) to provide hierarchical biomedical index terms for NLM databases (Medline and PubMed) should also be explored and included in relevant search strategies.

Searching the ‘grey literature’ is also an important factor in reducing publication bias. It is often the case that only studies with positive results and statistical significance are published. This creates a certain bias inherent in the published literature. This bias can, to some degree, be mitigated by the inclusion of results from the so-called grey literature, including unpublished work, abstracts, conference proceedings and PhD theses ( Higgins and Green, 2011 ; Bettany-Saltikov, 2012 ; Cognetti et al, 2015 ). Biases in a systematic review can lead to overestimating or underestimating the results ( Jahan et al, 2016 ).

An example search strategy from a published review looking at web use for the appraisal of physical health conditions can be seen in Box 2 . High-quality reviews usually detail which databases were searched and the number of items retrieved from each.

A balance between high recall and high precision is often required in order to produce the best results. An oversensitive search, or one prone to including too much noise, can mean missing important studies or producing too many search results ( Cognetti et al, 2015 ). Following a search, the exported citations can be added to citation management software (such as Mendeley or Endnote) and duplicates removed.

Title and abstract screening

Initial screening begins with the title and abstracts of articles being read and included or excluded from the review based on their relevance. This is usually carried out by at least two researchers to reduce bias ( Bashir and Conlon, 2018 ). After screening any discrepancies in agreement should be resolved by discussion, or by an additional researcher casting the deciding vote ( Bashir and Conlon, 2018 ). Statistics for inter-rater reliability exist and can be reported, such as percentage of agreement or Cohen's kappa ( Box 3 ) for two reviewers and Fleiss' kappa for more than two reviewers. Agreement can depend on the background and knowledge of the researchers and the clarity of the inclusion and exclusion criteria. This highlights the importance of providing clear, well-defined criteria for inclusion that are easy for other researchers to follow.

Full-text review

Following title and abstract screening, the remaining articles/sources are screened in the same way, but this time the full texts are read in their entirety and included or excluded based on their relevance. Reasons for exclusion are usually recorded and reported. Extraction of the specific details of the studies can begin once the final set of papers is determined.

Data extraction

At this stage, the full-text papers are read and compared against the inclusion criteria of the review. Data extraction sheets are forms that are created to extract specific data about a study (12 Jahan et al, 2016 ) and ensure that data are extracted in a uniform and structured manner. Extraction sheets can differ between quantitative and qualitative reviews. For quantitative reviews they normally include details of the study's population, design, sample size, intervention, comparisons and outcomes ( Bettany-Saltikov, 2012 ; Mueller et al, 2017 ).

Quality appraisal

The quality of the studies used in the review should also be appraised. Caldwell et al (2005) discussed the need for a health research evaluation framework that could be used to evaluate both qualitative and quantitative work. The framework produced uses features common to both research methodologies, as well as those that differ ( Caldwell et al, 2005 ; Dixon-Woods et al, 2006 ). Figure 3 details the research critique framework. Other quality appraisal methods do exist, such as those presented in Box 4 . Quality appraisal can also be used to weight the evidence from studies. For example, more emphasis can be placed on the results of large randomised controlled trials (RCT) than one with a small sample size. The quality of a review can also be used as a factor for exclusion and can be specified in inclusion/exclusion criteria. Quality appraisal is an important step that needs to be undertaken before conclusions about the body of evidence can be made ( Sambunjak and Franic, 2012 ). It is also important to note that there is a difference between the quality of the research carried out in the studies and the quality of how those studies were reported ( Sambunjak and Franic, 2012 ).

The quality appraisal is different for qualitative and quantitative studies. With quantitative studies this usually focuses on their internal and external validity, such as how well the study has been designed and analysed, and the generalisability of its findings. Qualitative work, on the other hand, is often evaluated in terms of trustworthiness and authenticity, as well as how transferable the findings may be ( Bettany-Saltikov, 2012 ; Bashir and Conlon, 2018 ; Siddaway et al, 2019 ).

Reporting a review (the PRISMA statement)

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) provides a reporting structure for systematic reviews/meta-analysis, and consists of a checklist and diagram ( Figure 4 ). The stages of identifying potential papers/sources, screening by title and abstract, determining eligibility and final inclusion are detailed with the number of articles included/excluded at each stage. PRISMA diagrams are often included in systematic reviews to detail the number of papers included at each of the four main stages (identification, screening, eligibility and inclusion) of the review.

Data synthesis

The combined results of the screened studies can be analysed qualitatively by grouping them together under themes and subthemes, often referred to as meta-synthesis or meta-ethnography ( Siddaway et al, 2019 ). Sometimes this is not done and a summary of the literature found is presented instead. When the findings are synthesised, they are usually grouped into themes that were derived by noting commonality among the studies included. Inductive (bottom-up) thematic analysis is frequently used for such purposes and works by identifying themes (essentially repeating patterns) in the data, and can include a set of higher-level and related subthemes (Braun and Clarke, 2012). Thomas and Harden (2008) provide examples of the use of thematic synthesis in systematic reviews, and there is an excellent introduction to thematic analysis by Braun and Clarke (2012).

The results of the review should contain details on the search strategy used (including search terms), the databases searched (and the number of items retrieved), summaries of the studies included and an overall synthesis of the results ( Bettany-Saltikov, 2012 ). Finally, conclusions should be made about the results and the limitations of the studies included ( Jahan et al, 2016 ). Another method for synthesising data in a systematic review is a meta-analysis.

Limitations of systematic reviews

Apart from the many advantages and benefits to carrying out systematic reviews highlighted throughout this article, there remain a number of disadvantages. These include the fact that not all stages of the review process are followed rigorously or even at all in some cases. This can lead to poor quality reviews that are difficult or impossible to replicate. There also exist some barriers to the use of evidence produced by reviews, including ( Wallace et al, 2012 ):

• Lack of awareness and familiarity with reviews
• Lack of access
• Lack of direct usefulness/applicability.

Meta-analysis

When the methods used and the analysis are similar or the same, such as in some RCTs, the results can be synthesised using a statistical approach called meta-analysis and presented using summary visualisations such as forest plots (or blobbograms) ( Figure 5 ). This can be done only if the results can be combined in a meaningful way.

Meta-analysis can be carried out using common statistical and data science software, such as the cross-platform ‘R’ ( https://www.r-project.org), or by using standalone software, such as Review Manager (RevMan) produced by the Cochrane community ( https://tinyurl.com/revman-5), which is currently developing a cross-platform version RevMan Web.

Carrying out a systematic review is a time-consuming process, that on average takes between 6 and 18 months and requires skill from those involved. Ideally, several reviewers will work on a review to reduce bias. Experts such as librarians should be consulted and included where possible in review teams to leverage their expertise.

Systematic reviews should present the state of the art (most recent/up-to-date developments) concerning a specific topic and aim to be systematic and reproducible. Reproducibility is aided by transparent reporting of the various stages of a review using reporting frameworks such as PRISMA for standardisation. A high-quality review should present a summary of a specific topic to a high standard upon which other professionals can base subsequent care decisions that increase the quality of evidence-based clinical practice.

• Systematic reviews remain one of the most trusted sources of high-quality information from which to make clinical decisions
• Understanding the components of a review will help practitioners to better assess their quality
• Many formal frameworks exist to help structure and report reviews, the use of which is recommended for reproducibility
• Experts such as librarians can be included in the review team to help with the review process and improve its quality

CPD reflective questions

• Where should high-quality qualitative research sit regarding the hierarchies of evidence?
• What background and expertise should those conducting a systematic review have, and who should ideally be included in the team?
• Consider to what extent inter-rater agreement is important in the screening process

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A high-quality systematic review is described as the most reliable source of evidence to guide clinical practice. The purpose of a systematic review is to deliver a meticulous summary of all the available primary research in response to a research question. A systematic review uses all the existing research and is sometime called ‘secondary research’ (research on research). They are often required by research funders to establish the state of existing knowledge and are frequently used in guideline development. Systematic review findings are often used within the healthcare setting but may be applied elsewhere. For example, the Campbell Collaboration advocates the application of systematic reviews for policy-making in education, justice and social work.

Systematic reviews can be conducted on all types of primary research. Many are reviews of randomised trials (addressing questions of effectiveness), cross-sectional studies (addressing questions about prevalence or diagnostic accuracy, for example) or cohort studies (addressing questions about prognosis). When qualitative research is reviewed systematically, it may be described as a systematic review, but more often other terms such as meta-synthesis are used.

Systematic review methodology is explicit and precise and aims to minimise bias, thus enhancing the reliability of the conclusions drawn. 1 , 2 The features of a systematic review include:

■ clear aims with predetermined eligibility and relevance criteria for studies;

■ transparent, reproducible methods;

■ rigorous search designed to locate all eligible studies;

■ an assessment of the validity of the findings of the included studies and

■ a systematic presentation, and synthesis, of the included studies. 3

The first step in a systematic review is a meticulous search of all sources of evidence for relevant studies. The databases and citation indexes searched are listed in the methodology section of the review. Next, using predetermined reproducible criteria to screen for eligibility and relevance assessment of titles and the abstracts is completed. Each study is then assessed in terms of methodological quality.

Finally, the evidence is synthesised. This process may or may not include a meta-analysis. A meta-analysis is a statistical summary of the findings of independent studies. 4 Meta-analyses can potentially present more precise estimates of the effects of interventions than those derived from the individual studies alone. These strategies are used to limit bias and random error which may arise during this process. Without these safeguards, then, reviews can mislead, such that we gain an unreliable summary of the available knowledge.

The Cochrane Collaboration is a leader in the production of systematic reviews. Cochrane reviews are published on a monthly basis in the Cochrane Database of Systematic Reviews in The Cochrane Library (see: http://www.thecochranelibrary.com ).

• Antman EM ,
• Kupelnick B ,
• Higgins JPT ,

Competing interests None.

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• Published: 03 February 2011

Methodology in conducting a systematic review of systematic reviews of healthcare interventions

• Valerie Smith 1 ,
• Declan Devane 2 ,
• Cecily M Begley 1 &
• Mike Clarke 3  

BMC Medical Research Methodology volume  11 , Article number:  15 ( 2011 ) Cite this article

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Hundreds of studies of maternity care interventions have been published, too many for most people involved in providing maternity care to identify and consider when making decisions. It became apparent that systematic reviews of individual studies were required to appraise, summarise and bring together existing studies in a single place. However, decision makers are increasingly faced by a plethora of such reviews and these are likely to be of variable quality and scope, with more than one review of important topics. Systematic reviews (or overviews) of reviews are a logical and appropriate next step, allowing the findings of separate reviews to be compared and contrasted, providing clinical decision makers with the evidence they need.

The methods used to identify and appraise published and unpublished reviews systematically, drawing on our experiences and good practice in the conduct and reporting of systematic reviews are described. The process of identifying and appraising all published reviews allows researchers to describe the quality of this evidence base, summarise and compare the review's conclusions and discuss the strength of these conclusions.

Methodological challenges and possible solutions are described within the context of (i) sources, (ii) study selection, (iii) quality assessment (i.e. the extent of searching undertaken for the reviews, description of study selection and inclusion criteria, comparability of included studies, assessment of publication bias and assessment of heterogeneity), (iv) presentation of results, and (v) implications for practice and research.

Conducting a systematic review of reviews highlights the usefulness of bringing together a summary of reviews in one place, where there is more than one review on an important topic. The methods described here should help clinicians to review and appraise published reviews systematically, and aid evidence-based clinical decision-making.

Peer Review reports

The healthcare literature contains hundreds of thousands of studies of healthcare interventions, growing at tens of thousands per year [ 1 ]. In most areas of health care, there are too many studies for people involved in providing care to identify and consider when making decisions. Researchers have recognised this problem and many have accepted the challenge of preparing systematic reviews of individual studies in order to appraise, summarise and bring together existing studies in a single place. More recently, calls have been made for 'rapid reviews' to provide decision-makers with the evidence they need in a shorter time frame, but the possible limitations of such 'rapid reviews', compared to full systematic reviews, require further research [ 2 ]. There are now several organisations dedicated to the preparation of systematic reviews, including the National Institute of Health and Clinical Excellence (NICE) in the UK, the Evidence-based Practice Centre Program, funded by AHRQ in the USA, the Joanna Briggs Institute, and the international Campbell and Cochrane Collaborations, with the latter being the largest single producer of systematic reviews in health care, with more than 4200 published by the end of 2010 [ 3 ]. In recent years however, decision makers who were once overwhelmed by the number of individual studies have become faced by a plethora of reviews [ 4 , 5 ]. These reviews are likely to be of variable quality and scope, with more than one systematic review on important topics. For example, a comprehensive search of twelve health related citation databases (using database specific search strategies) identified over thirty reviews evaluating the effectiveness of nurse and midwife-led interventions on clinical outcomes, as part of an on-going study into the impact of the role of nurse and midwife specialist and advanced practitioners in Ireland. A logical and appropriate next step is to conduct a systematic review of reviews of the topic under consideration, allowing the findings of separate reviews to be compared and contrasted, thereby providing clinical decision makers with the evidence they need. We have been involved in several examples of systematic reviews (or overviews) of reviews [ 6 – 9 ] and The Cochrane Collaboration introduced a new type of Cochrane review in 2009 [ 10 ], the overview of Cochrane reviews, with two full overviews [ 11 , 12 ] and protocols for five more [ 13 – 17 ] published by October 2010. These reviews of reviews aims to provide a summary of evidence from more than one systematic review at a variety of different levels, including the combination of different interventions, different outcomes, different conditions, problems or populations, or the provision of a summary of evidence on the adverse effects of an intervention [ 10 ].

This paper describes the conduct and methods used to identify and appraise published and unpublished systematic reviews systematically. It draws on our experience of conducting several of these reviews of reviews in recent years. The purpose of such an overview, in identifying and appraising all published reviews is to describe their quality, summarise and compare their conclusions and discuss the strength of these conclusions, so that best evidence is made available to clinical decision-makers. During the review process a number of methodological challenges can arise. We describe these challenges and offer possible solutions to overcome them. We hope to provide a guide to clinicians and researchers who wish to conduct a systematic review of reviews and to share our experiences.

The objective and the reasons for conducting a systematic review of reviews should be made explicit at the start of the process, as this is likely to influence the methods used for the review. In formulating the scope for the review of reviews, the PICOS (participants, interventions, comparators, outcomes, and study design) structure may be helpful. This can help the reviewers to delineate clearly if they wish, for example, to compare and summarise systematic reviews that address the same treatment comparison or a particular intervention for a population or condition, or a range of interventions for people with a specific condition. Following this, the methods in conducting a systematic review of reviews require consideration of the following aspects, akin to the planning for a systematic review of individual studies: sources, review selection, quality assessment of reviews, presentation of results and implications for practice and research.

Sources and searching

Locating and retrieving relevant literature is challenging, yet crucial to the success of a systematic review. The material sourced provides the information from which evidence, conclusions and recommendations are drawn. For many, the literature search may appear overwhelming, given the sheer volume of material to check through. However, establishing a systematic search strategy, before commencing the literature search, is fundamental to appropriate and successful information retrieval. This planning assists in meeting the requirements of the systematic review and in answering the research question. In developing a search strategy, the scope of the search, its thoroughness and the time available to conduct it, all need to be considered. The aim is to ensure that the systematic review of reviews is comprehensive, thorough and objective.

The methods used in sourcing relevant literature to conduct a systematic review of reviews are similar to those adopted in conducting a systematic review of individual studies with some subtle differences described here. A realistic time-frame to conduct the systematic review of reviews should be established. It has been estimated that a typical systematic review would take between six and eighteen months [ 18 ] but this is very dependent on the research question and the staffing, funding and other resources available. The process might be faster for a systematic review of reviews if the time-frame to complete the literature search is significantly reduced through the ability to target the searching of articles most likely to be reports of a systematic review. In a systematic review of individual studies, the search should be as wide as possible to maximize the likelihood of capturing all relevant data and minimizing the effects of reporting biases. A search of a variety of electronic databases relevant to the topic of interest is recommended [ 18 ]. However, in a systematic review of reviews, it may be possible to limit the searches to databases specific to systematic reviews such as the Cochrane Database of Systematic Reviews and the Database of Abstracts of Reviews of Effects. Likewise, although the search for a review of individual studies might need to cover many decades [ 19 ], limiting the search to period from the early 1990 s onwards is likely to identify all but the very small minority of systematic reviews conducted before then [ 20 , 21 ]. Furthermore, researchers might find that identifying and highlighting a recent high quality systematic review will prove of most benefit to decision makers using their review or reviews. However, a summary of the earlier reviews can still prove helpful if these contain relevant information that is not included in the recent review. Applying language restrictions is not recommended; but, unavoidable constraints such as a lack of access to translation services or funds to pay for these may make it necessary to restrict the systematic review or reviews to English language publications. In such instances, this limitation should be acknowledged when reporting the review and it might be worthwhile reporting the difference between searches with and without language restrictions in order to estimate the amount of literature that might have been excluded.

The search terms used for the literature search should be clearly described, with information on their relevance to the research question. Furthermore, search terms should be focused so that they are broad enough in scope to capture all the relevant data yet narrow enough to minimize the capture of extraneous literature that may result in unnecessary time and effort being spent assessing irrelevant articles. In conducting a systematic review of reviews, systematic reviews rather than individual studies are of interest to the reviewer and several search strategies have been developed to identify this type of research [ 22 , 23 ] which could be combined with the terms for the relevant healthcare topic. In developing the search strategy for a systematic review of reviews, researchers might wish to consider the PRESS initiative, developed as a means for peer reviewing literature searches [ 24 ] to check that the various elements of the electronic search strategy have been considered. To minimize the risk of missing relevant reviews, a manual search of key journals and of the reference lists of reviews captured by the initial searches is also recommended. The literature search can also be complemented by contacting experts in the topic under review and by checking articles which cite individual studies that are known to be relevant to the topic. This may prove relevant in learning of published systematic reviews that are not indexed in the bibliographic databases searched, and of ongoing systematic reviews near completion. The development of a prospective register of systematic reviews should help further with this [ 25 ].

Review Selection

A major challenge to review selection is identifying all reviews relevant to the topic of interest, and of potential importance to answering the research question. During the planning phase, before commencing the systematic review of reviews, a review team should be established. The review team should include at least one person with methodological expertise in conducting systematic reviews and at least one person with expertise on the topic under review. The review team is responsible for developing a review selection strategy. An agreement of inclusion and exclusion criteria should be made before starting the review selection process. Aspects of this process might include decisions regarding the type of reviews that may be included in the systematic review. For example, in our review on interventions for preventing preterm birth [ 6 ], we restricted the inclusion criteria to reviews of randomized controlled trials. Another example of inclusion criteria might be to limit the systematic review of reviews to reviews of a particular type of participant (such as women having their first baby) or which assess a particular type of pain relief.

When a selection strategy has been developed, the selection process is carried out in a similar way to a review of individual studies:

Assess retrieved titles and abstracts for relevance and duplication.

Select those you wish to retrieve and appraise further.

Obtain full text copies of these potentially eligible reviews.

Assess these reviews for relevance and quality; ideally, using independent assessment by at least two members of the review team. This reduces bias in review selection and allows for appropriate discussion should uncertainty arise.

Quality Assessment of Reviews

The quality and strength of evidence presented in the individual, included reviews should influence the conclusions drawn in the systematic review of these. The quality and scope of published reviews varies widely. The strength of the conclusions and the ability to provide decision-makers with reliable information depends on the inclusion of reviews that meet a minimum standard of quality. When assessing the quality of the reviews, one should try to avoid being influenced by extraneous variables, such as authors, institutional affiliations and journal names; and should focus on the quality of the conduct of the review. Although the researchers will usually have to do this via an assessment of the quality of report, with the hope that initiatives such as PRISMA (formerly, QUOROM) which assist by facilitating adequate standards of reporting [ 26 ].

The AMSTAR tool [ 27 ], which became available after we started work on our review of reviews, is the only tool that we are aware of that has been validated as a means to assess the methodological quality of systematic reviews and could be used in the review of reviews to determine if the potentially eligible reviews meet minimum requirements based on quality. While the authors of the AMSTAR paper [ 27 ] recognise the need for further testing of the AMSTAR tool, important domains identified within the tool are: establishing the research question and inclusion criteria before the conduct of the review, data extraction by at least two independent data extractors, comprehensive literature review with searching of at least two databases, key word identification, expert consultation and limits applied, detailed list of included/excluded studies and study characteristics, quality assessment of included studies and consideration of quality assessments in analysis and conclusions, appropriate assessment of homogeneity, assessment of publication bias and a statement of any conflict of interest.

Although our review of reviews began before the publication of the AMSTAR tool, we used similar domains to assess review quality. Our assessment criteria are shown below and provide a structure that can be used to report the quality and comparability of the included reviews to help readers assess the strength of the evidence in the review of reviews:

▪ The extent of searching undertaken: Are the databases searched, years searched and restrictions applied in the original review clearly described? Information on the extent of searching should be clearly provided, to allow for a comprehensive assessment of the scope of the review.

▪ Description of review selection and inclusion criteria: Do the authors of the original review provide details of study selection and eligibility criteria and what are these details? This information should be clearly reported in the systematic review of reviews.

▪ Assessment of publication bias: Did the authors of the original review seek additional information from authors of the studies they included? Are there any details of statistical tests (such as funnel plot analysis) to assess for publication bias?

▪ Assessment of heterogeneity: Did the authors of the original review discuss or provide details of any tests of heterogeneity? In the presence of significant heterogeneity, were statistical tests used to address this?

▪ Comparability of included reviews: Are the reviews comparable in terms of eligibility criteria, study characteristics and primary outcome of interest? For example, in our review of reviews on fetal fibronectin and transvaginal cervical ultrasound for predicting preterm birth, [ 8 ] we included reviews that had incorporated studies among women who were both symptomatic and asymptomatic for preterm birth. As a means of addressing comparability of the included reviews, we provided details of the number of women in each group separately and reported the results for each group separately, where applicable.

Presentation of Results

When the results of a systematic review of reviews are presented, this should present the reader with the major conclusions of the review through the provision of answers to the research question, as well as the evidence on which these conclusions are based and an assessment of the quality of the evidence supporting each conclusion; for example, using the GRADE approach as adopted for the 'Summary of Findings' table in Cochrane reviews [ 28 ]. It is important to be specific in reporting the primary outcome of interest for the review, and this can reduce workload by limiting data extraction to only those results relevant to the topic of interest from reviews that report on several outcome measures. For example, some systematic reviews on antibiotic therapy for the prevention of preterm birth [ 29 , 30 ] report a variety of outcome measures other than preterm birth (e.g. neonatal outcomes). However, in our systematic reviews of reviews [ 6 , 8 ], our research focus on preterm birth meant that only results for the effects on preterm birth were extracted.

The use of summary tables and figures is helpful in presenting results in a structured and clear format that will enhance textual commentary. Table 1 is an example of the provision of details of the scope of the reviews included in a systematic review of reviews (3). Sources of evidence and some quality assessment criteria are included. The quality assessment is enhanced by a narrative discussion of heterogeneity and publication bias.

Table 2 provides an example of how summary results from each original review might be presented in the systematic review of reviews.

The use of a checklist or reporting tool may also guide the reviewer when reporting on a systematic review of reviews. Although we did not identify a tool specific to reporting of systematic reviews of reviews, the PRISMA statement provides a useful framework to follow [ 26 ]. This guidance, developed for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions, can be used to assess item inclusion in a systematic review of systematic reviews.

Implications for practice and research

One of the problems faced by decision makers who encounter multiple reviews of the same topic is inconsistency in the results or conclusions of these reviews. Jadad et al (1997) provide guidance on how to address discordant results from individual reviews [ 31 ] and conducting systematic reviews of reviews will help to address this issue further. A systematic review of reviews can provide reassurances that the conclusions of individual reviews are consistent, or not. The quality of individual reviews may be assessed, so that evidence from the best quality reviews can be highlighted and brought together in a single document, providing definitive summaries that could be used to inform clinical practice.

Meta-analyses in systematic reviews of reviews

A major challenge in conducting a systematic review of reviews is the creation of a 'meta-analysis' of the included reviews, which are themselves meta-analyses. In doing this, it is important that data from individual studies are not used more than once. This would give too much statistical power, with the risk that a misleading estimate will be produced and that this will be overly precise. Overcoming this challenge would require the unpicking of each of the included reviews and the subsequent combination of the results of the individual, included studies. This may prove to be a complex and time-consuming task and careful consideration should be given to its value when planning the systematic review of reviews, highlighting the importance of having clear reasons for conducting the review.

A systematic review of reviews allows the creation of a summary of reviews in a single document. In this paper, we have discussed the methods for conducting such a review. The methods we have described and discussed draw on our experiences, and should be useful to healthcare practitioners who wish to conduct a systematic review of reviews to enhance their evidence-based knowledge and to support well-informed clinical decision making. They should also be useful to practitioners who will find that the ideal starting point for knowledge from research will be a systematic review of reviews of the topic of interest to them.

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Valerie Smith & Cecily M Begley

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Declan Devane

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VS participated in the sequence content and drafted the manuscript. MC conceived and contributed to the rationale for the manuscript. VS, CB, DD and MC contributed to the design of the manuscript. CB, DD and MC read and critically revised the draft manuscript for important intellectual content. All authors read and approved the final manuscript.

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Smith, V., Devane, D., Begley, C.M. et al. Methodology in conducting a systematic review of systematic reviews of healthcare interventions. BMC Med Res Methodol 11 , 15 (2011). https://doi.org/10.1186/1471-2288-11-15

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Received : 04 June 2010

Accepted : 03 February 2011

Published : 03 February 2011

DOI : https://doi.org/10.1186/1471-2288-11-15

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• Published: 01 June 2024

Biomarkers for personalised prevention of chronic diseases: a common protocol for three rapid scoping reviews

• E Plans-Beriso   ORCID: orcid.org/0000-0002-9388-8744 1 , 2   na1 ,
• C Babb-de-Villiers 3   na1 ,
• D Petrova 2 , 4 , 5 ,
• C Barahona-López 1 , 2 ,
• P Diez-Echave 1 , 2 ,
• O R Hernández 1 , 2 ,
• N F Fernández-Martínez 2 , 4 , 5 ,
• H Turner 3 ,
• E García-Ovejero 1 ,
• O Craciun 1 ,
• P Fernández-Navarro 1 , 2 ,
• N Fernández-Larrea 1 , 2 ,
• E García-Esquinas 1 , 2 ,
• V Jiménez-Planet 7 ,
• V Moreno 2 , 8 , 9 ,
• F Rodríguez-Artalejo 2 , 10 , 11 ,
• M J Sánchez 2 , 4 , 5 ,
• M Pollan-Santamaria 1 , 2 ,
• L Blackburn 3 ,
• M Kroese 3   na2 &
• B Pérez-Gómez 1 , 2   na2  

Systematic Reviews volume  13 , Article number:  147 ( 2024 ) Cite this article

Metrics details

Introduction

Personalised prevention aims to delay or avoid disease occurrence, progression, and recurrence of disease through the adoption of targeted interventions that consider the individual biological, including genetic data, environmental and behavioural characteristics, as well as the socio-cultural context. This protocol summarises the main features of a rapid scoping review to show the research landscape on biomarkers or a combination of biomarkers that may help to better identify subgroups of individuals with different risks of developing specific diseases in which specific preventive strategies could have an impact on clinical outcomes.

This review is part of the “Personalised Prevention Roadmap for the future HEalThcare” (PROPHET) project, which seeks to highlight the gaps in current personalised preventive approaches, in order to develop a Strategic Research and Innovation Agenda for the European Union.

To systematically map and review the evidence of biomarkers that are available or under development in cancer, cardiovascular and neurodegenerative diseases that are or can be used for personalised prevention in the general population, in clinical or public health settings.

Three rapid scoping reviews are being conducted in parallel (February–June 2023), based on a common framework with some adjustments to suit each specific condition (cancer, cardiovascular or neurodegenerative diseases). Medline and Embase will be searched to identify publications between 2020 and 2023. To shorten the time frames, 10% of the papers will undergo screening by two reviewers and only English-language papers will be considered. The following information will be extracted by two reviewers from all the publications selected for inclusion: source type, citation details, country, inclusion/exclusion criteria (population, concept, context, type of evidence source), study methods, and key findings relevant to the review question/s. The selection criteria and the extraction sheet will be pre-tested. Relevant biomarkers for risk prediction and stratification will be recorded. Results will be presented graphically using an evidence map.

Inclusion criteria

Population: general adult populations or adults from specific pre-defined high-risk subgroups; concept: all studies focusing on molecular, cellular, physiological, or imaging biomarkers used for individualised primary or secondary prevention of the diseases of interest; context: clinical or public health settings.

Systematic review registration

https://doi.org/10.17605/OSF.IO/7JRWD (OSF registration DOI).

Peer Review reports

In recent years, innovative health research has moved quickly towards a new paradigm. The ability to analyse and process previously unseen sources and amounts of data, e.g. environmental, clinical, socio-demographic, epidemiological, and ‘omics-derived, has created opportunities in the understanding and prevention of chronic diseases, and in the development of targeted therapies that can cure them. This paradigm has come to be known as “personalised medicine”. According to the European Council Conclusion on personalised medicine for patients (2015/C 421/03), this term defines a medical model which involves characterisation of individuals’ genotypes, phenotypes and lifestyle and environmental exposures (e.g. molecular profiling, medical imaging, lifestyle and environmental data) for tailoring the right therapeutic strategy for the right person at the right time, and/or to determine the predisposition to disease and/or to deliver timely and targeted prevention [ 1 , 2 ]. In many cases, these personalised health strategies have been based on advances in fields such as molecular biology, genetic engineering, bioinformatics, diagnostic imaging and new’omics technologies, which have made it possible to identify biomarkers that have been used to design and adapt therapies to specific patients or groups of patients [ 2 ]. A biomarker is defined as a substance, structure, characteristic, or process that can be objectively quantified as an indicator of typical biological functions, disease processes, or biological reactions to exposure [ 3 , 4 ].

Adopting a public health perspective within this framework, one of the most relevant areas that would benefit from these new opportunities is the personalisation of disease prevention. Personalised prevention aims to delay or avoid the occurrence, progression and recurrence of disease by adopting targeted interventions that take into account biological information, environmental and behavioural characteristics, and the socio-economic and cultural context of individuals. These interventions should be timely, effective and equitable in order to maintain the best possible balance in lifetime health trajectory [ 5 ].

Among the main diseases that merit specific attention are chronic noncommunicable diseases, due to their incidence, their mortality or disability-adjusted life years [ 6 , 7 , 8 , 9 ]. Within the European Union (EU), in 2021, one-third of adults reported suffering from a chronic condition [ 10 ]. In addition, in 2019, the leading causes of mortality were cardiovascular disease (CVD) (35%), cancer (26%), respiratory disease (8%), and Alzheimer's disease (5%) [ 11 ]. For all of the above, in 2019, the PRECeDI consortium recommended the identification of biomarkers that could be used for the prevention of chronic diseases to integrate personalised medicine in the field of chronicity. This will support the goal of stratifying populations by indicating an individuals’ risk or resistance to disease and their potential response to drugs, guiding primary, secondary and tertiary preventive interventions [ 12 ]; understanding primary prevention as measures taken to prevent the occurrence of a disease before it occurs, secondary prevention as actions aimed at early detection, and tertiary prevention as interventions to prevent complications and improve quality of life in individuals already affected by a disease [ 4 ].

The “Personalised Prevention roadmap for the future HEalThcare” (PROPHET) project, funded by the European Union’s Horizon Europe research and innovation program and linked to ICPerMed, seeks to assess the effectiveness, clinical utility, and existing gaps in current personalised preventive approaches, as well as their potential to be implemented in healthcare settings. It also aims to develop a Strategy Research and Innovation Agenda (SRIA) for the European Union. This protocol corresponds to one of the first steps in the PROPHET, namely a review that aims to map the evidence and highlight the evidence gaps in research or the use of biomarkers in personalised prevention in the general adult population, as well as their integration with digital technologies, including wearable devices, accelerometers, and other appliances utilised for measuring physical and physiological functions. These biomarkers may be already available or currently under development in the fields of cancer, CVD, and neurodegenerative diseases.

There is already a significant body of knowledge about primary and secondary prevention strategies for these diseases. For example, hypercholesterolemia or dyslipidaemia, hypertension, smoking, diabetes mellitus and obesity or levels of physical activity are known risk factors for CVD [ 6 , 13 ] and neurodegenerative diseases [ 14 , 15 , 16 ]; for cancer, a summary of lifestyle preventive actions with good evidence is included in the European code against cancer [ 17 ]. The question is whether there is any biomarker or combination of biomarkers that can help to better identify subgroups of individuals with different risks of developing a particular disease, in which specific preventive strategies could have an impact on clinical outcomes. Our aim in this context is to show the available research in this field.

Given the context and time constraints, the rapid scoping review design is the most appropriate method for providing landscape knowledge [ 18 ] and provide summary maps, such as Campbell evidence and gap map [ 19 ]. Here, we present the protocol that will be used to elaborate three rapid scoping reviews and evidence maps of research on biomarkers investigated in relation to primary or secondary prevention of cancer, cardiovascular and neurodegenerative diseases, respectively. The results of these three rapid scoping reviews will contribute to inform the development of the PROPHET SRIA, which will guide the future policy for research in this field in the EU.

Review question

What biomarkers are being investigated in the context of personalised primary and secondary prevention of cancer, CVD and neurodegenerative diseases in the general adult population in clinical or public health settings?

Three rapid scoping reviews are being conducted between February and June 2023, in parallel, one for each disease group included (cancer, CVD and neurodegenerative diseases), using a common framework and specifying the adaptations to each disease group in search terms, data extraction and representation of results.

This research protocol, designed according to Joanna Briggs Institute (JBI) and Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist [ 20 , 21 , 22 ] was uploaded to the Open Science Framework for public consultation [ 23 ], with registration DOI https://doi.org/ https://doi.org/10.17605/OSF.IO/7JRWD . The protocol was also reviewed by experts in the field, after which modifications were incorporated.

Eligibility criteria

Following the PCC (population, concept and context) model [ 21 , 22 ], the included studies will meet the following eligibility criteria (Table  1 ):

Rationale for performing a rapid scoping review

As explained above, these scoping reviews are intended to be one of the first materials produced in the PROPHET project, so that they can inform the first draft of the SRIA. Therefore, according to the planned timetable, the reviews should be completed in only 4 months. Thus, following recommendations from the Cochrane Rapid Review Methods Group [ 24 ] and taking into account the large number of records expected to be assessed, according to the preliminary searches, and in order to meet these deadlines, specific restrictions were defined for the search—limited to a 3-year period (2020–2023), in English only, and using only MEDLINE and EMBASE as possible sources—and it was decided that the title-abstract and full-text screening phase would be carried out by a single reviewer, after an initial training phase with 10% of the records assessed by two reviewers to ensure concordance between team members. This percentage could be increased if necessary.

Rationale for population selection

These rapid scoping reviews are focused on the general adult population. In addition, they give attention to studies conducted among populations that present specific risk factors relevant to the selected diseases or that include these factors among those considered in the study.

For cancer, these risk (or preventive) factors include smoking [ 25 ], obesity [ 26 ], diabetes [ 27 , 28 , 29 ], Helicobacter pylori infection/colonisation [ 30 ], human papillomavirus (HPV) infection [ 30 ], human immunodeficiency virus (HIV) infection [ 30 ], alcohol consumption [ 31 ], liver cirrhosis and viral (HVB, HVC, HVD) hepatitis [ 32 ].

For CVD, we include hypercholesterolemia or dyslipidaemia, arterial hypertension, smoking, diabetes mellitus, chronic kidney disease, hyperglycaemia and obesity [ 6 , 13 ].

Risk groups for neurodegenerative diseases were defined based on the following risk factors: obesity [ 15 , 33 ], arterial hypertension [ 15 , 33 , 34 , 35 ], diabetes mellitus [ 15 , 33 , 34 , 35 ], dyslipidaemia [ 33 ], alcohol consumption [ 36 , 37 ] and smoking [ 15 , 16 , 33 , 34 ].

After the general search, only relevant and/or disease-specific subpopulations will be used for each specific disease. On the other hand, pregnancy is an exclusion criterion, as the very specific characteristics of this population group would require a specific review.

Rationale for disease selection

The search is limited to diseases with high morbidity and mortality within each of the three disease groups:

Cancer type

Due to time constraints, we only evaluate those malignant neoplasms with the greatest mortality and incidence rates in Europe, which according to the European Cancer Information System [ 38 ] are breast, prostate, colorectum, lung, bladder, pancreas, liver, stomach, kidney, and corpus uteri. Additionally, cervix uteri and liver cancers will also be included due to their preventable nature and/or the existence of public health screening programs [ 30 , 31 ].

We evaluate the following main causes of deaths: ischemic heart disease (49.2% of all CVD deaths), stroke (35.2%) (this includes ischemic stroke, intracerebral haemorrhage and subarachnoid haemorrhage), hypertensive heart disease (6.2%), cardiomyopathy and myocarditis (1.8%), atrial fibrillation and flutter (1.7%), rheumatic heart disease (1.6%), non-rheumatic valvular heart disease (0.9%), aortic aneurism (0.9%), peripheral artery disease (0.4%) and endocarditis (0.4%) [ 6 ].

In this scoping review, specifically in the context of CVD, rheumatic heart disease and endocarditis are not considered because of their infectious aetiology. Arterial hypertension is a risk factor for many cardiovascular diseases and for the purposes of this review is considered as an intermediary disease that leads to CVD.

• Neurodegenerative diseases

The leading noncommunicable neurodegenerative causes of death are Alzheimer’s disease or dementia (20%), Parkinson’s disease (2.5%), motor neuron diseases (0.4%) and multiple sclerosis (0.2%) [ 8 ]. Alzheimer’s disease, vascular dementia, frontotemporal dementia and Lewy body disease will be specifically searched, following the pattern of European dementia prevalence studies [ 39 ]. Additionally, because amyotrophic lateral sclerosis is the most common motor neuron disease, it is also included in the search [ 8 , 40 , 41 ].

Rationale for context

Public health and clinical settings from any geographical location are being considered. The searches will only consider the period between January 2020 and mid-February 2023 due to time constraints.

Rationale for type of evidence

Qualitative studies are not considered since they cannot answer the research question. Editorials and opinion pieces, protocols, and conference abstracts will also be excluded. Clinical practice guidelines are not included since the information they contain should be in the original studies and in reviews on which they are based.

Pilot study

We did a pilot study to test and refine the search strategies, selection criteria and data extraction sheet as well as to get used to the software—Covidence [ 42 ]. The pilot study consisted of selecting from the results of the preliminary search matrix 100 papers in order of best fit to the topic, and 100 papers at random. The team comprised 15 individual reviewers (both in the pilot and final reviews) who met daily to revise, enhance, and reach consensus on the search matrices, criteria, and data extraction sheets.

Regarding the selected databases and the platforms used, we conducted various tests, including PubMed/MEDLINE and Ovid/MEDLINE, as well as Ovid/Embase and Elsevier/Embase. Ultimately, we chose Ovid as the platform for accessing both MEDLINE and Embase, utilizing thesaurus Mesh and EmTrees. We manually translated these thesauri to ensure consistency between them. Given that the review team was spread across the UK and Spain, we centralised the search results within the UK team's access to the Ovid license to ensure consistency. Additionally, using Ovid exclusively for accessing both MEDLINE and Embase streamlined the process and allowed for easier access to preprints, which represent the latest research in this rapidly evolving field.

Identification of research

The searches are being conducted in MEDLINE via Ovid, Embase via Ovid and Embase preprints via Ovid. We also explored the feasibility of searching in CDC-Authored Genomics and Precision Health Publications Databases [ 43 ] . However, the lack of advanced tools to refine the search, as well as the unavailability of bulk downloading prevented the inclusion of this data source. Nevertheless, a search with 15 records for each disease group showed a full overlap with MEDLINE and/or Embase.

Search strategy definition

An initial limited search of MEDLINE via PubMed and Ovid was undertaken to identify relevant papers on the topic. In this step, we identified keytext words in their titles and abstracts, as well as thesaurus terms. The SR-Accelerator, Citationchaser, and Yale Mesh Analyzer tools were used to assist in the construction of the search matrix. With all this information, we developed a full search strategy adapted for each included database and information source, optimised by research librarians.

Study evidence selection

The complete search strategies are shown in Additional file 3. The three searches are being conducted in parallel. When performing the search, no limits to the type of study or setting are being applied.

Following each search, all identified citations will be collated and uploaded into Covidence (Veritas Health Innovation, Melbourne, Australia, available at www.covidence.org ) with the citation details, and duplicates will be removed.

In the title-abstract and full-text screening phase, the first 10% of the papers will be evaluated by two independent reviewers (accounting for 200 or more papers in absolute numbers in the title-abstract phase). Then, a meeting to discuss discrepancies will lead to adjusting inclusion and exclusion criteria and to acquire consistency between reviewers’ decisions. After that, the full screening of the search results will be performed by a single reviewer. Disagreements that arise between reviewers at each stage of the selection process will be resolved through discussion, or with additional reviewers. We maintain an active forum to facilitate permanent contact among reviewers.

The results of the searches and the study inclusion processes will be reported and presented in a flow diagram following the PRISMA-ScR recommendations [ 22 ].

Expert consultation

The protocol has been refined after consultation with experts in each field (cancer, CVD, and neurodegenerative diseases) who gave input on the scope of the reviews regarding the diverse biomarkers, risk factors, outcomes, and types of prevention relevant to their fields of expertise. In addition, the search strategies have been peer-reviewed by a network of librarians (PRESS-forum in pressforum.pbworks.com) who kindly provided useful feedback.

Data extraction

We have developed a draft data extraction sheet, which is included as Additional file 4, based on the JBI recommendations [ 21 ]. Data extraction will include citation details, study design, population type, biomarker information (name, type, subtype, clinical utility, use of AI technology), disease (group, specific disease), prevention (primary or secondary, lifestyle if primary prevention), and subjective reviewer observations. The data extraction for all papers will be performed by two reviewers to ensure consistency in the classification of data.

Data analysis and presentation

The descriptive information about the studies collected in the previous phase will be coded according to predefined categories to allow the elaboration of visual summary maps that can allow readers and researchers to have a quick overview of their main results. As in the previous phases, this process will be carried out with the aid of Covidence.

Therefore, a summary of the extracted data will be presented in tables as well as in static and, especially, through interactive evidence gap maps (EGM) created using EPPI-Mapper [ 44 ], an open-access web application developed in 2018 by the Evidence for Policy and Practice Information and Coordinating Centre (EPPI-Centre) and Digital Solution Foundry, in partnership with the Campbell Collaboration, which has become the standard software for producing visual evidence gap maps.

Tables and static maps will be made by using R Studio, which will also be used to clean and prepare the database for its use in EPPI-Mapper by generating two Excel files: one containing the EGM structure (i.e. what will be the columns and rows of the visual table) and coding sets, and another containing the bibliographic references and their codes that reviewers had added. Finally, we will use a Python script to produce a file in JSON format, making it ready for importation into EPPI-Reviewer.

The maps are matrixes with biomarker categories/subcategories defining the rows and diseases serving as columns. They define cells, which contain small squares, each one representing each paper included in it. We will use a code of colours to reflect the study design. There will be also a second sublevel in the columns, depending on the map. Thus, for each group of diseases, we will produce three interactive EGMs: two for primary prevention and one for secondary prevention. For primary prevention, the first map will stratify the data to show whether any or which lifestyle has been considered in each paper in combination with the studied biomarker. The second map for primary prevention and the map for secondary prevention will include, as a second sublevel, the subpopulations in which the biomarker has been used or evaluated, which are disease-specific (i.e. cirrhosis for hepatic cancer) researched. The maps will also include filters that allow users to select records based on additional features, such as the use of artificial intelligence in the content of the papers. Furthermore, the EGM, which will be freely available online, will enable users to view and export selected bibliographic references and their abstracts. An example of these interactive maps with dummy data is provided in Additional file 5.

Finally, we will elaborate on two scientific reports for PROPHET. The main report, which will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) recommendations, will summarise the results of the three scoping reviews, will provide a general and global interpretation of the results and will comment on their implication for the SRIA, and will discuss the limitations of the process. The second report will present the specific methodology for the dynamic maps.

This protocol summarises the procedure to carry out three parallel rapid scoping reviews to provide an overview of the available research and gaps in the literature on biomarkers for personalised primary and secondary prevention for the three most common chronic disease groups: cancer, CVD and neurodegenerative diseases. The result will be a common report for the three scoping reviews and the online publication of interactive evidence gap maps to facilitate data visualisation.

This work will be complemented, in a further step of the PROPHET project, by a subsequent mapping report on the scientific evidence for the clinical utility of biomarkers. Both reports are part of an overall mapping effort to characterise the current knowledge and environment around personalised preventive medicine. In this context, PROPHET will also map personalised prevention research programs, as well as bottlenecks and challenges in the adoption of personalised preventive approaches or in the involvement of citizens, patients, health professionals and policy-makers in personalised prevention. The overall results will contribute to the development of the SRIA concept paper, which will help define future priorities for personalised prevention research in the European Union.

In regard to this protocol, one of the strengths of this approach is that it can be applied in the three scoping reviews. This will improve the consistency and comparability of the results between them, allowing for better leveraging of efforts; it also will facilitate the coordination among the staff conducting the different reviews and will allow them to discuss them together, providing a more global perspective as needed for the SRIA. In addition, the collaboration of researchers with different backgrounds, the inclusion of librarians in the research team, and the specific software tools used have helped us to guarantee the quality of the work and have shortened the time invested in defining the final version of this protocol. Another strength is that we have conducted a pilot study to test and refine the search strategy, selection criteria and data extraction sheet. In addition, the selection of the platform of access to the bibliographic databases has been decided after a previous evaluation process (Ovid-MEDLINE versus PubMed MEDLINE, Ovid-Embase versus Elsevier-Embase, etc.).

Only 10% of the papers will undergo screening by two reviewers, and if time permits, we will conduct kappa statistics to assess reviewer agreement during the screening phases. Additionally, ongoing communication and the exchange and discussion of uncertainties will ensure a high level of consensus in the review process.

The main limitation of this work is the very broad field it covers: personalised prevention in all chronic diseases; however, we have tried to maintain decisions to limit it to the chronic diseases with the greatest impact on the population and in the last 3 years, making a rapid scoping review due to time constraints following recommendations from the Cochrane Rapid Review Methods Group [ 24 ]; however, as our aim is to identify gaps in the literature in an area of growing interest (personalisation and prevention), we believe that the records retrieved will provide a solid foundation for evaluating available literature. Additionally, systematic reviews, which may encompass studies predating 2020, have the potential to provide valuable insights beyond the temporal constraints of our search.

Thus, this protocol reflects the decisions set by the PROPHET's timetable, without losing the quality and rigour of the work. In addition, the data extraction phase will be done by two reviewers in 100% of the papers to ensure the consistency of the extracted data. Lastly, extending beyond these three scoping reviews, the primary challenge resides in amalgamating their findings with those from numerous other reviews within the project, ultimately producing a cohesive concept paper in the Strategy Research and Innovation Agenda (SRIA) for the European Union, firmly rooted in evidence-based conclusions.

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Acknowledgements

We are grateful for the library support received from Teresa Carretero (Instituto de Salud Carlos III, ISCIII) and, from Concepción Campos-Asensio (Hospital Universitario de Getafe, Comité ejecutivo BiblioMadSalud) for the seminar on the Scoping Reviews methodology and for their continuous teachings through their social networks.

Also, we would like to thank Dr. Héctor Bueno (Centro Nacional de Investigaciones Cardiovasculares (CNIC), Hospital Universitario 12 de Octubre) and Dr. Pascual Sánchez (Fundación Centro de Investigación de Enfermedades Neurológicas (CIEN)) for their advice in their fields of expertise.

The PROPHET project has received funding from the European Union’s Horizon Europe research and innovation program under grant agreement no. 101057721. UK participation in Horizon Europe Project PROPHET is supported by UKRI grant number 10040946 (Foundation for Genomics & Population Health).

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Plans-Beriso E and Babb-de-Villiers C contributed equally to this work.

Kroese M and Pérez-Gómez B contributed equally to this work.

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Department of Epidemiology of Chronic Diseases, National Centre for Epidemiology, Instituto de Salud Carlos III, Madrid, Spain

E Plans-Beriso, C Barahona-López, P Diez-Echave, O R Hernández, E García-Ovejero, O Craciun, P Fernández-Navarro, N Fernández-Larrea, E García-Esquinas, M Pollan-Santamaria & B Pérez-Gómez

CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain

E Plans-Beriso, D Petrova, C Barahona-López, P Diez-Echave, O R Hernández, N F Fernández-Martínez, P Fernández-Navarro, N Fernández-Larrea, E García-Esquinas, V Moreno, F Rodríguez-Artalejo, M J Sánchez, M Pollan-Santamaria & B Pérez-Gómez

PHG Foundation, University of Cambridge, Cambridge, UK

C Babb-de-Villiers, H Turner, L Blackburn & M Kroese

Instituto de Investigación Biosanitaria Ibs. GRANADA, Granada, Spain

D Petrova, N F Fernández-Martínez & M J Sánchez

Escuela Andaluza de Salud Pública (EASP), Granada, Spain

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National Library of Health Sciences, Instituto de Salud Carlos III, Madrid, Spain

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Oncology Data Analytics Program, Catalan Institute of Oncology (ICO), L’Hospitalet de Llobregat, Barcelona, 08908, Spain

Colorectal Cancer Group, ONCOBELL Program, Institut de Recerca Biomedica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Barcelona, 08908, Spain

Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid, Madrid, Spain

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IMDEA-Food Institute, CEI UAM+CSIC, Madrid, Spain

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Plans-Beriso, E., Babb-de-Villiers, C., Petrova, D. et al. Biomarkers for personalised prevention of chronic diseases: a common protocol for three rapid scoping reviews. Syst Rev 13 , 147 (2024). https://doi.org/10.1186/s13643-024-02554-9

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Leagility in the healthcare research: a systematic review

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• Volume 24 , article number  307 , ( 2024 )

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Expenditure of healthcare services has been growing over the past decades. Lean and agile are two popular paradigms that could potentially contain cost and improve proficiency of the healthcare system. However no systematic review was found on leagilty in the healthcare research. This study aims at synthesizing the extant literature of leagility in the healthcare area to consolidate its potential and identify research gaps for future study in the field.

A systematic literature review is conducted following the PRISMA checklist approach. Studies were searched in multiple databases. The selection of articles was executed by dual-scanning of two researchers to ensure quality of data and relevance to the topic. Scientific articles published between January 1999 and November 2023 concerning leagile healthcare are analysed using Microsoft Excel and VOSviewer (version 1.6.18).

Out of 270 articles identified from the inclusion and exclusion criteria, 24 were included in the review. A total of 11 target areas were identified in leagility applications in healthcare. Success and limiting factors of leagile healthcare were classified into macro and micro aspects and further categorized into six dimensions: policy, organization, human resources, marketing, operation management and technology. Moreover, four research gaps were revealed and suggestions were provided for future study.

Leagility in the healthcare context is still being in its infancy. Few empirical validation was found in leagile healthcare literature. Further exploration into the application of theory in various sectors under the scope of healthcare is appealed for. Standardization and modularization, leadership support, skillfulness of professionals and staff training are the factors most frequently mentioned for a successful implementation of leagility in the healthcare sector.

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Introduction.

Over the past few decades, the healthcare industry has been blooming global-wide and so does the expenditure of healthcare services [ 1 ]. According to the work of Shrank and his colleagues, the U.S. spends nearly 18% of the gross domestic product (GDP) in healthcare while approximately 30% of the budget may be considered waste [ 2 ]. While in China, national expenditure on health has been climbing up from 2016 to 2021, reaching over 10.8 trillion dollars in 2021 [ 3 ]. How to contain cost and in the meanwhile maintain high quality health service delivery, has been in the spotlight since the 1980s [ 1 , 4 , 5 ]. Due to the outbreak of COVID-19, economic burden of the disease becomes remarkably high [ 6 ] thus such attempt is an increasingly relevant topic.

While the healthcare industry is in pursuit of efficiency, quality and profitability gains, a number of management concepts have proved successful in the manufacturing industry [ 7 ]. Two popular paradigms among them are lean and agile [ 8 , 9 , 10 , 11 , 12 ]. Briefly speaking, lean is to reduce waste in order to increase value to customers [ 13 ] while agile aims at staying responsive to market demand [ 14 , 15 ]. However, each single approach has its specificities. In order to achieve greater excellency, it is proposed by scholars to combine lean and agility together as “leagility” to improve performance of the supply chain [ 10 ]. Nevertheless, leagility as a process improvement methodology addressing work redesign, it accelerates healthcare’s transition towards digital technology which tremendously expand the capacity of healthcare organizations [ 16 ]. Research and applications have been conducted to transfer the lean concept from manufacturing industry to the field of health care [ 1 , 15 , 17 , 18 ], but the discussion of leagility strategy in health care settings arose only more recently [ 1 , 4 , 7 , 19 ].

The research gap identified concerning leagile healthcare studies is that knowledge is dispersed and no systematic literature review about leagility specifically in the area of healthcare was found. Although there are several articles on leagility in healthcare, an integration of knowledge on the topic is still scarce. To cover the gap, this study aims at synthesizing knowledge on leagile healthcare and discuss its application to find out the important aspects during its implementation in the context of healthcare. Literatures reveal that the theory has potential to improve healthcare delivery service [ 20 , 21 , 22 ]. Thus this study is devoted to answer the following questions: 1) how and where can leagility be used in healthcare settings? 2) what are the factors facilitating or limiting a successful implementation of leagility strategy in healthcare?

This systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses ( PRISMA ) checklist approach [ 23 , 24 ].

Search strategy

Several electronic databases were considered for relevant articles to maximize the identification of relevant articles: B-on, Web of Science, ABI-inform, Scopus, CNKI, Wanfang and Pubmed. CNKI and Wanfang were considered to include Chinese literature. The search strings in titles, key words and abstracts used to trace studies of the field were “lean” AND “agile” AND “healthcare”, “lean” AND “agile” AND “health service”, “leagile” AND “healthcare”, “leagile” AND “health service”, “decoupling” AND “healthcare”. The search syntax is shown in Table  1 . No starting date was set for the retrieval of articles. The earliest retrieved article was published in 1999. A list of references published between 1999 up to November 2023 was generated. All selected articles were imported to Mendeley (version 1.19.8).

Inclusion and exclusion criteria

We included journal articles in English and Chinese that relate to leagile healthcare, in other words, decoupling point theory in the healthcare industry. In the screening stage, duplicates and articles that were not relevant to leagile healthcare were removed. Then the remaining studies were analysed for eligibility. In this phase, articles that focus merely on lean without involving agility, that were not about healthcare management, not on leagility or do not satisfy the quality appraisal were excluded. Articles not written in Chinese or English were also ruled out in the study. The flow diagram of screening and selection process is shown in Fig.  1 .

PRISMA flowchart of research selection process

Study selection, data extraction and synthesis

The search strategy was discussed between the two researchers until a consensus was reached. Data were scanned and extracted by two researchers, individual and separately. In this dual-scanning, firstly, the two researchers read the titles and abstracts of the retrieved articles. Secondly, different colors were used to mark whether the article should be included or not, independently by the two researchers. The independency in the screening of the articles aimed at reducing possible bias in the analysis. Included articles were marked in green, excluded ones were marked in red while articles that remained uncertain for classification were marked in yellow. Whenever an article was marked in yellow or in different colors by the researchers, the two researchers went to the full text to determine eligibility of the study by discussion. Evidence was pointed out by one researcher, and ask for agreement of the other. If the other does not agree, more details was provided to support the different opinion. This iterative process was repeated until both sides come to the same decision.

The results of the study consist of descriptive analysis and in-depth analysis. Descriptive data were synthesized according to the year of publication, country or region of the study, journals and their rankings and collaboration of authors among different studies. In-depth analysis includes different perception of leagility in healthcare, methods adopted in the studies, target areas and application of leagile healthcare, applicability of leagility in healthcare sector and what are the success and limiting factors of leagile application in health care. The softwares used in the analysis are Microsoft Excel and VOSviewer (version 1.6.18).

Quality appraisal of included studies

The quality appraisal of articles was performed by adopting an adjusted assessment checklist for systematic review [ 25 ]. The checklist consists of 11 questions related to methods, sampling, quality of data collected and interpretation. In this study, scoring was conducted in this way: articles were scored 1, 0.5, and 0 with a perfect, moderate, or poor quality accordingly.

Screening results

A total of 270 articles are identified from searched databases. Eighty-one duplicates are removed and 189 articles remain for further distinction by dual-scanning of two researchers. After analysing the abstracts, 141 articles were ruled out from the study by agreement of both researchers, as they are out of research range of leagility in the healthcare area. The full text of the remaining 48 articles were further screened for eligibility. In this step, 24 articles are excluded as these studies focused only on one aspect of leagile healthcare management but not on the holistic concept. Finally, 24 articles were selected for the systematic review. The PRISMA flow of articles selection is shown in Fig. 1 .

Results of quality appraisal

There are 21 studies recognized as good quality (score of 8 and above), one as medium quality (score between 5.5–8) and one as poor quality (score of 5.5 and below). Generally, all the included studies were fine designed and with clear structure, providing certain insights into the research topic. The report of quality appraisal was attached in Annex .

Article distribution across reviewed timeframe

A consecutive growth of number of articles focusing on leagility over the reviewed timeframe can be observed in Fig.  2 . Articles are published between 1999 and 2023. Among the first decade, ranging from 1999 to 2009, publication on healthcare leagility was very modest, but in the following decade, a boost of publications took place and the growth in number of articles become more stable and continuous. This growth reveals that leagile healthcare is getting more and more attention, which may also result from a recognition of its positive impact on healthcare organizations and settings.

Article distribution across reviewed timeframe ( n  = 24)

Geographical distribution

The published papers report results of research that was carried out in four continents and 15 countries or regions (Fig.  3 ), showing that the attention given to the topic is not very concentrated. Over half of the research is taken in Europe, while 7 out of 24 studies are embedded in Asia, 3 are conducted in North America and 1 in Africa. The UK and India have more publications on the topic than other countries. This spread of geographical applications show that the impact of using an agility approach in healthcare is not limited to cultural issues. However, research in the topic is yet to be launched in Oceania, Latin America and Africa. It is also observed that leagility in healthcare still remains to be explored on the landscape of China.

Geographical distribution of selected articles

With the increase of attention in healthcare in more developed countries, the topic still awaits to be further explored and calls for more in-depth study.

Journals and rankings

Over half of the articles are published in journals of the first and second quartile, which reflects that studies included in the systematic review are of relatively high quality and recognized impact. The journals that accept more papers concerning leagile healthcare are Supply Chain Management and Production Planning and Control, both of which are ranked in the first quartile. Figure  4 presents the distribution of articles among different journal quartiles.

Articles distribution among different journal quartiles

Research collaboration in the study of leagility in healthcare

It was previously seen that there is dispersion of geographical application or origin of the publication in the researched topics. This leads to an expectation of a not very high level of collaboration between researchers. This expectation was confirmed. In fact, there are two publications in the pool of articles considered that are by Guimarães and de Carvalho [ 26 , 27 ] and then only Aronsson [ 7 , 28 ] published more than one article by working with different partners. Besides these cases, all other publications are by isolated researchers. This limited interaction between research teams is revealed in Fig.  5 . This might be the consequence of leagility in the healthcare context still being in its infancy, and eventually with a higher level of recognition of the benefits of the use of a leagile approach in healthcare setting, the collaboration between researchers may increase.

Author collaboration in selected studies

Perception of leagility in healthcare

The appearance of the concept of leagility can be traced back to as early as 1999 when Naylor and his colleagues proposed the integration of lean and agile paradigms in the total supply chain [ 10 ]. Being the combination of two strategies, leagility is also addressed as “hybrid strategy” [ 7 , 20 , 26 , 29 , 30 ]. In a leagile supply chain, the lean strategy is adopted upstream to reduce waste for maximum productivity and efficiency, while agile strategy serves downstream to satisfy volatile market demand ensuring system responsiveness [ 1 , 7 , 28 , 29 , 31 ]. The two paradigms are separated by a strategic stocking point called “decoupling point” or “customer order decoupling point” (CODP) where the shift from lean to agile is done at [ 7 , 20 , 26 , 30 , 32 , 33 ]. Sometimes the shift is gradual and the decoupling point can also be a transition point from lean to agile [ 34 ].

Nabelsi and Gagnon [ 35 ] developed the concept of lean and agile into “patient-oriented, lean and agile”, strengthening the importance of being patient-centered, integrating patient needs within optimized healthcare supply chain. Ni and his colleagues [ 36 ] extended the concept into a lean and agile multi-dimensional (LAMP) process, an early health technology assessments framework for evidence generation in commercial decision-making. Furthermore, a lean, agile, resilient and green (LARG) management paradigm has been put forward and attracting increased attention for achieving sustained competitive advantage [ 37 , 38 , 39 ]. Claimed to be contested that Leanness is a prerequisite for agility and vice versa [ 26 ], it was stated with more certainty later in 2019 that agility is the next step after leaness and agility is best to be achieved when a system is lean [ 20 ]. The evolution of the perception of leagility in healthcare in literature is shown in Table  2 .

Applied methods

It was found that 19 out of 24 studies adopted a qualitative methodology, as seen in Table  3 . Only two articles adopted quantitative methods. Four studies selected mixed methods. The main use of qualitative approaches is also evidence of case applications and research in a topic that is still in its infancy, requiring further attention to be able to expand the knowledge in the topic and its impact in the healthcare care area. It is indicated that the majority of included articles use indirect and secondary data while empirical practice of leagility in the healthcare sector is still scarce.

Target area and application

Table  4 explores the area of application of the different considered studies. Almost half of the selected studies on leagile healthcare hold a system-wide or hospital-wide view towards the topic. The second heated application of leagility focus on patient flow. While implementation of leagility in other areas such as pharmacy, medical equipment and clinical laboratory is limited and documented only in recent decade. This show that the recognition of the usability and positive impact of leagility in the healthcare area is becoming more sustained, with overall approaches guiding the application in more detailed areas. Nonetheless, many healthcare areas are still unexplored.

Applicability of leagility in the healthcare sector

According to the Global Supply Chain Matrix proposed by Christopher et al., a leagile strategy is best to adopt when a product is of unpredictable demand and long lead time [ 15 ]. The applicability of leagility was further analysed by Mishra et al., adding three additional variables: criticality, cost and perishability of the product. It was found that leagile strategy suits best when the product is of relatively low criticality, low cost and highly perishable [ 20 ].

In the healthcare area, based on the selected articles and the cases they explore, it is undeniable that the level of demand is unpredictable, mainly if one considers emergency areas [ 22 ]. As a service, healthcare capacity is highly perishable, requiring the need to explore the capacity of the resources available and their competencies in the most effective way to, simultaneously, assure the best quality possible in delivery and controlled costs.

Success and limiting factors of leagile application in health care

The identified success and limiting factors of leagility in the context of healthcare are shown in Table  5 . These factors were first divided in macro and micro level and then further categorized into different dimensions according to their nature. For macro aspects, policy assurance in leagility application in healthcare is reported to be important for adequate financial support and political commitment [ 32 , 43 ]. For micro aspects, factors are classified into five dimensions: organizational, human resources, marketing, operation management and technology. At organizational level, success factors of leagile healthcare that appear more in literature include top-down decision [ 21 , 26 , 27 ], well-established control machanism and monitoring results [ 40 , 47 ], and understanding of need for better planning and control [ 21 , 28 ]. But if an organization lacks system-wide strategy and stays only at a tools-and-techniques level, actions are taken to solve local problems only and this limits the maximized impact of leagility implementation [ 26 ]. Concerning human resources dimension, professionalism level, staff traning and employers’ engagement pose themselves as more frequently mentioned success ingredients of leagile healthcare. While lack of skillful and experienced professionals hinders the application of leagile strategy [ 32 , 33 ]. High level of market sensitivity and staying customer focus facilitate the strategy as well [ 29 ]. In the aspect of operation management, standardization [ 7 , 27 , 34 , 45 ] and modularization of processes are the two elements mostly emphasized in studies to implement leagility in healthcare [ 7 , 33 , 34 , 42 , 44 , 45 ]. What follows is short product life cycles for timely delivery [ 29 , 47 ] and sufficient use of shared resources [ 22 , 40 ]. However, out of the difficulty to control and monitor performance, outsourcing might introduce potential risk during implementation of leagility [ 26 ]. Moreover, it is worth paying attention to information technology as it has significant impact on an organization’s capability to manage demand and stay responsive as well as flexible in a volatile environment [ 16 , 41 , 47 ].

Theoretical contribution

There is no evidence showing the existence of systematic literature review on lean and agile operation in healthcare management. Dixit and his colleagues [ 1 ] conducted a systematic literature review of healthcare supply chain (HSC), but the review just mentioned lean and agile operation as one of the many important aspects of the area. This study fills the gap by providing consolidated knowledge on the topic, allowing more in-depth understanding of the theory and explore potential gaps for future research.

By presenting different perceptions of leagility in the healthcare sector, this study reveals the evolution of the concept across researched timeframe and indicates how it could fit into the healthcare context. As empirical validation of leagility is still scarce, consolidating its manifold perceptions and interpretation in the healthcare sector is vital to construct a more holistic conceptual framework for leagile healthcare. This allows in-depth understanding of the concept and thus better guides leagility implementation in the healthcare context. And vice versa, the practice of leagile healthcare provides more evidence on its potential benefits to the healthcare system.

Practical contribution

The contribution to practice of this study is threefold.

First, 11 target areas in current study are listed, including hospital-wide [ 26 , 27 , 29 , 40 , 42 , 44 , 46 ], overall health system [ 1 , 30 ], patient flow [ 7 , 22 , 28 , 32 , 33 , 34 ], pharmacy [ 20 , 35 ], equipments [ 35 ], clinical laboratory [ 21 ], healthcare technology [ 36 ], point-of-care (POC) diagnosis [ 43 ], communication process [ 41 ], operating room (OR) cleaning [ 45 ] and vaccine supply chain [ 31 ]. This provides guidance for practitioners to apply leagility theory in respective sectors. Moreover, it leaves a hint for future research to explore areas that has not been mentioned yet, such as intensive care unit (ICU), organ transplant centers, mental health units and other departments within a hospital. Nevertheless, primary healthcare, elderly care centers and many other services across the healthcare industry also await for further study.

Second, the applicability of leagility in healthcare area is identified [ 15 , 20 ], which enables practitioners to make decisions whether and where the leagile strategy could be adopted to improve organizational efficiency and effectiveness. By adopting leagility principles at the right place, it is more likely to achieve best quality healthcare services at a controlled price [ 20 ].

Third, success and limiting factors of leagility application in healthcare are classified by macro and micro aspects and further categorized into six dimensions: policy, organizational, human resources, marketing, operation management and technology. At macro political level, it is essential to design refined financial regimes to ensure reseasonable financial support for making the best decision at the decoupling point [ 32 ]. In the case of Uslu and her colleagues [ 32 ], the difference in reimbursement of laparoscopic and open surgery led to the dilemma of choosing a clinical decision better for the patient or the organization. Imperfect financial regimes may cause unnecessary suffering to the patient even though the decision may bring more benefits to the healthcare organization. It is also implied that instead of considering merely organizational efficiency, the lean and agile approach should rather be patient oriented. In organizational aspects, it is most vital to gain leadership support to carry out a top-down leagile reform [ 21 , 26 , 27 ]. A system-wide strategy is essential for leagility to achieve greater influence throughout the organization [ 7 , 26 , 28 ]. In the dimension of human resources, as lack of skillful and experienced professionals constructs one of the constraints of successful implementation of leagile strategy [ 32 , 33 ], training and education as well as better human resources management is indispensable to have and retain qualified labor force. Employee’s engagement refers to trust and empower instead of control and going over into details [ 29 ]. An agile team is highly autonomous [ 46 ], thus high level surveillance and perfectionism from supervisors might need to be avoided during execution of the strategy. From the angle of operation management, standardization and modularization of processes gain the highest rate of exposure beyond any other factors. Modularization was observed in managing patient flow [ 7 , 27 , 33 , 34 ], material logistics [ 44 ] and pharmacy [ 47 ]. Standardization was found to be utilized in patient treatment process [ 7 , 34 ], operating room cleaning [ 45 ] and staff training [ 27 ]. Both of them serve to streamline processes and improve efficiency of the system. Additionally, monitor and risk management is required for outsourcing activities [ 26 ]. Concerning technological issues of leagility implementation, it is also mentioned by researchers to consider the risk related to end-users and vendors, such as privacy problems when adopting a new technology [ 35 ]. This categorization helps practitioners identify what to promote and reinforce in field work as well as what should be averted for a positive outcome while implementing leagility in the healthcare sector.

Research gaps and indication for future study

In general, leagility in healthcare settings is a rather “young” concept that awaits for further development [ 1 , 7 , 29 ]. Due to its being in an early stage, limited cooperation between different authors was observed in current studies. Thus more collaboration among scholars is appealed for further exploration on this concept, as well as healthcare situations that are available to benefit from its potential.

Although there is a consecutive growth of published articles concerning leagile healthcare, most of them are theoretical and lack empirical validation. To fill this gap, first-hand data collected from real field could be used to analyze the applicability of leagility in healthcare and how the concept affects performance of the system. Additionally, proposed models and conceptual framework in existing knowledge could be applied in healthcare organizations of different levels and scales [ 7 , 42 ], identifying and exploring the healthcare scenarios and cases that require specific adjustments.

Over 50% of the presented studies were conducted in Europe while the remaining half are distributed sparsely in other countries. Research is not yet spotted in many countries or regions such as China, Australia, Africa and South America. Several of these regions and some parts of these countries are not very advanced in terms of their healthcare offerings and could benefit from a more structured service if leagile principles are considered. This indicates a geographical gap to be filled in future studies, allowing the identification of eventual regional or system structural particularities in the adoption of the leagile principle.

Moreover, scholars mostly hold a system-wide view towards leagile healthcare or focus mainly on patient flow in healthcare services. Application of leagility in a specific sub-sector under the healthcare setting appears only after 2015 [ 20 , 26 , 28 , 36 , 45 , 46 , 47 ]. It is worth exploring the adoption of leagility in various sectors across a healthcare organization, such as research and clinical trials, medical education and training management and surgical operation management to improve performance in more areas under healthcare settings.

The fact that non-English written articles are not included in the study might pose as a limitation to the study since it may lead to bias or miss of information on the concept. Nonetheless, Chinese language was considered, and with it a potential wide range of articles, as the Chinese Government is focusing heavily on the reorganization of its system [ 48 , 49 , 50 ]. Additionally, this research constructed points of view based merely on ideas or results presented by other scholars without considering the views of filed practitioners or incorporating primary data. But with such early development of the topic and the fact that the research aimed at performing a systematic literature review, such inclusion would not have been appropriate.

Leagility in the healthcare context is still being in its infancy with potential to improve healthcare services. To the best of our knowledge, this is the first systematic literature review consolidating knowledge on leagile healthcare. The 11 target areas of leagility application in the healthcare sector include hospital-wide implementation, patient flow, overall healthcare system, pharmacy, equipments, clinical laboratory, healthcare technology, point-of-care (POC) diagnostics, communication process, operating room (OR) cleaning and vaccine supply chain. Many healthcare areas are still unexplored and call for empirical validation of benefits brought from leagility. Moreover, success and limiting factors of leagility in healthcare were classified by macro and micro aspects and further categorized into six dimensions: policy, organization, human resources, marketing, operation management and technology. A majority of influencing factors fall within the category of organization and operation management. Standardization and modularization are the two most frequently mentioned factors for a successful leagility application in healthcare. Besides, leadership support, a system-wide strategy, better planning and control and skillfulness of employees are also vital elements to consider while adopting the leagility approach. This finding helps field practitioners better understand what should be facilitated or averted when using leagility to improve the performance of a healthcare system. Lastly, Four research gaps are identified and indication for future research is proposed.

Availability of data and materials

No datasets were generated or analysed during the current study.

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Acknowledgements

The authors are grateful to comments and suggestions received by the editors of the journal and referees. The authors would like to thank Business Research Unit of ISCTE-IUL and FCT foundation.

This research was supported by Business Research Unit (BRU-IUL) and Fundação para a Ciência e a Tecnologia, grant UIDB/00315/2020.

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Li, X., Martins, A.L. Leagility in the healthcare research: a systematic review. BMC Health Serv Res 24 , 307 (2024). https://doi.org/10.1186/s12913-024-10771-0

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Differential Outcomes of Placebo Treatment Across 9 Psychiatric Disorders : A Systematic Review and Meta-Analysis

• 1 Department of Psychiatry and Psychotherapy, University Hospital, Technical University of Dresden, Dresden, Germany
• 2 Federal Joint Committee (G-BA), Berlin, Germany
• 3 Social Psychiatric Service, Berlin district of Reinickendorf, Berlin, Germany
• 4 Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
• 5 Department of Psychiatry and Psychotherapy, Faculty of Medicine, University of Cologne, Cologne, Germany
• 6 Government Commission for Modern and Needs-Based Hospital Care, Berlin, Germany

Question   Which psychiatric disorder exhibits the strongest improvement associated with placebo treatment in randomized clinical trials (RCTs)?

Findings   This systematic review and meta-analysis of 90 high-quality RCTs with 9985 participants found significant improvement under placebo treatment for all 9 disorders, but the degree of improvement varied significantly among diagnoses. Patients with major depressive disorder experienced the greatest improvement, followed by those with generalized anxiety disorder, panic disorder, attention-deficit/hyperactivity disorder, posttraumatic stress disorder, social phobia, mania, and OCD, while patients with schizophrenia benefited the least.

Meaning   These findings may inform planning of RCTs, interpreting of uncontrolled studies, and advising patients for or against a specific treatment.

Importance   Placebo is the only substance systematically evaluated across common psychiatric diagnoses, but comprehensive cross-diagnostic comparisons are lacking.

Objective   To compare changes in placebo groups in recent high-quality randomized clinical trials (RCTs) across a broad spectrum of psychiatric disorders in adult patients.

Data Sources   MEDLINE and the Cochrane Database of Systematic Reviews were systematically searched in March 2022 for the latest systematic reviews meeting predetermined high-quality criteria for 9 major psychiatric diagnoses.

Study Selection   Using these reviews, the top 10 highest-quality (ie, lowest risk of bias, according to the Cochrane Risk of Bias tool) and most recent placebo-controlled RCTs per diagnosis (totaling 90 RCTs) were selected, adhering to predetermined inclusion and exclusion criteria.

Data Extraction and Synthesis   Following the Cochrane Handbook, 2 authors independently carried out the study search, selection, and data extraction. Cross-diagnosis comparisons were based on standardized pre-post effect sizes (mean change divided by its SD) for each placebo group. This study is reported following the Meta-analysis of Observational Studies in Epidemiology (MOOSE) reporting guideline.

Main Outcome and Measure   The primary outcome, pooled pre-post placebo effect sizes ( d av ) with 95% CIs per diagnosis, was determined using random-effects meta-analyses. A Q test assessed statistical significance of differences across diagnoses. Heterogeneity and small-study effects were evaluated as appropriate.

Results   A total of 90 RCTs with 9985 placebo-treated participants were included. Symptom severity improved with placebo in all diagnoses. Pooled pre-post placebo effect sizes differed across diagnoses ( Q  = 88.5; df  = 8; P  < .001), with major depressive disorder ( d av  = 1.40; 95% CI, 1.24-1.56) and generalized anxiety disorder ( d av  = 1.23; 95% CI, 1.06-1.41) exhibiting the largest d av . Panic disorder, attention-deficit/hyperactivity disorder, posttraumatic stress disorder, social phobia, and mania showed d av between 0.68 and 0.92, followed by OCD ( d av  = 0.65; 95% CI, 0.51-0.78) and schizophrenia ( d av  = 0.59; 95% CI, 0.41-0.76).

Conclusion and Relevance   This systematic review and meta-analysis found that symptom improvement with placebo treatment was substantial in all conditions but varied across the 9 included diagnoses. These findings may help in assessing the necessity and ethical justification of placebo controls, in evaluating treatment effects in uncontrolled studies, and in guiding patients in treatment decisions. These findings likely encompass the true placebo effect, natural disease course, and nonspecific effects.

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Bschor T , Nagel L , Unger J , Schwarzer G , Baethge C. Differential Outcomes of Placebo Treatment Across 9 Psychiatric Disorders : A Systematic Review and Meta-Analysis . JAMA Psychiatry. Published online May 29, 2024. doi:10.1001/jamapsychiatry.2024.0994

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• Open access
• Published: 28 May 2024

Social support as a coping resource for psychosocial conditions in postpartum period: a systematic review and logic framework

• Khadijeh Khademi 1 &
• Mohammad Hossein Kaveh 2  

BMC Psychology volume  12 , Article number:  301 ( 2024 ) Cite this article

123 Accesses

Metrics details

This review seeks to examine the current state of postpartum social support and psychosocial conditions among women around the world, as well as explore the relationship between these factors. Additionally, it aims to propose a logical framework for enhancing postpartum social support and psychosocial conditions in this population.

Following the development of a search strategy, two databases, PubMed and Science Direct, were searched for studies published between January 2019 and May 2023. The search was conducted throughout the entire month of May 2023. The risk of bias in the included cross-sectional studies was assessed using the Newcastle–Ottawa Quality Assessment Scale, which was adapted for this specific study design. To determine if the main objective of the cross-sectional studies was to investigate the relationship between social support and postpartum psychosocial conditions, a review was conducted based on the AMSTAR checklist, PRISMA checklist and PRISMA flow diagram. Data extraction was performed with the consensus of two authors, and a narrative synthesis approach was chosen for data synthesis, following the guidelines provided by the Centre for Reviews and Dissemination (CRD).

Eleven cross-sectional studies were included in the final analysis. Our findings revealed that all reviewed studies provided evidence of a positive association between social support and healthy psychosocial conditions in postpartum period. However, due to the absence of standardized measurement indicators to identify and compare the outcomes of various studies, there was a need to develop a conceptual framework that could enhance our understanding of the postpartum psychosocial condition including anxiety, depression, unfavorable quality of life and social support status up to 24 month after child birth. This framework aimed to incorporate childbirth and motherhood as "stressful events," while considering social support as a crucial "coping resource." Furthermore, it acknowledged empowerment, help-seeking behavior, and peer support as important "coping actions," alongside implementing client-centered interventions. Lastly, it recognized postpartum mental health and optimal quality of life as significant "effects" of these factors.

Conclusions

The proposed conceptual framework could define postpartum women’s health as “the ability to adapt and self-manage.”

Peer Review reports

Introduction

Birth and motherhood are considered neuro-psycho-social events, and the first year postpartum, although a pleasant time for a family, is a crucial developmental life stage for women [ 1 , 2 ]. During this transitional period, women face a dual challenge: Firstly, they must adapt to the changes in their physical appearance and the added expectations of new responsibilities. Secondly, they experience physical discomforts resulting from pregnancy and childbirth, potential marital discord, and negative social interactions such as conflict, insensitivity and interference, especially with their husbands [ 2 , 3 , 4 ]. These changes and problems can be challenging and far-reaching, resulting in undesirable psychosocial well-being or psychosocial problems [ 5 , 6 , 7 ].

Psychosocial well-being is a superordinate construct that includes emotional or psychological well-being, as well as social and collective well-being [ 5 ]. So, postpartum psychosocial problems are defined as anxiety, depression, other mental disorders, unfavorable quality of life and increasing the incidence of suicidal ideation and behavior [ 1 , 5 , 6 , 7 ]. Postpartum depression (PPD) is a type of major depressive episode that occurs during pregnancy or within 4 weeks following delivery [ 8 ]. Another related illness is postpartum post-traumatic stress disorder (PP-PTSD), which is an anxiety disorder that can develop as a result of a difficult or traumatic birth experience. It's important to note that women may experience PP-PTSD even after a successful birth [ 9 ]. Both PPD and anxiety disorder are serious psychosocial problems that require proper diagnosis and treatment [ 8 , 9 ]. Notably, postpartum psychosocial problems can impede successful adjustment to the maternal role, impact the entire family, and impose significant economic costs on the healthcare system [ 10 , 11 , 12 ].

However, current postpartum care, which is often standardized in terms of content and structure, is associated with low satisfaction rates among mothers [ 13 ]. Furthermore, most studies focusing on mothers’ health outcomes in the postpartum period have centered on measures such as breastfeeding rates, hospital admissions, and physical health indicators of mothers and infants [ 14 , 15 , 16 , 17 ]. While these outcomes are undoubtedly important, mothers have also indicated that maternal functioning and mental health are essential for health [ 14 , 18 , 19 ]. To aid in coping with the stress of motherhood and promote maternal well-being, effective social support can be instrumental in facilitating a successful transition to motherhood [ 20 , 21 , 22 ].

Theoretical frameworks suggest that social support, which refers to the availability of others to provide emotional, psychological, and material resources, can serve as a coping resource that impacts health [ 23 ]. In addition, social support is also recognized as a protective factor against stress, anxiety, depression, and other mental disorders that can negatively impact the quality of life [ 24 , 25 , 26 ]. Negative postpartum health outcomes highlight the critical need for increased support and resources [ 14 ].

Further investigation is necessary to deepen our understanding of the status of social support after childbirth and how it can contribute to maternal psychosocial well-being during the transition to motherhood [ 20 ]. Although psychosocial conditions are crucial, because of persistent mother’s mental disorders up to 24 months after childbirth, they are often not the primary focus of research [ 24 , 25 ]. Mothers’ low satisfaction rates with standardized postpartum care also highlight the need for a client-centered approach [ 13 ]. Ultimately, by identifying evidence-based factors that affect women’s psychosocial conditions and the necessity for plans in this area, postpartum can be one of life’s most pleasant experiences, and the challenges confronting them can be an opportunity for personal growth and skill enhancement [ 11 ].

In fact, the majority of current studies on postpartum women primarily focus on physical issues such as postpartum bleeding or pain, as well as psychological problems like breastfeeding difficulties and PPD [ 15 , 16 , 17 ]. Unfortunately, other psycho-social conditions that arise after childbirth are often overlooked and receive little attention [ 14 , 24 , 25 ]. To enhance the psycho-social well-being of women following childbirth, it is crucial to gain a comprehensive understanding of these conditions and assess the factors that influence them [ 11 , 18 ]. Among these factors, social support plays a significant role and warrants further investigation to determine its importance during the postpartum period [ 20 , 26 ].

Based on the background above, the current review aims to achieve the following objectives: 1) to explore evidence for the status of women’s social support in postpartum period (up to 24 month after child birth), 2) to assess the evidence for the status of women’s psychosocial problems including anxiety, PPD and unfavorable quality of life up to 24 month after child birth, 3) to evaluate the evidence for associations between social support and psychosocial problems in postpartum period, and 4) to propose a logical framework for enhancing postpartum social support and psychosocial conditions.

Materials and methods

The present study utilized a systematic review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) [ 27 ] checklist, We chose two databases based on recommendations from the PRISMA group paper, which suggests searching at least one database, and the Assessing the Methodological Quality of Systematic Reviews (AMSTAR) checklist, which recommends searching at least two databases [ 28 , 29 ]. Our search included well-known databases PubMed and Science Direct, and we used the following search strategy: keywords for each search term (Table  1 ), Field “Title/Abstract,” free full-text (access to some scientific articles is limited for Iranian universities due to debt, not having a subscription, etc.). Our investigation covered a period of five years, from January 2019 to May 2023. This timeframe was chosen to ensure that our evidence syntheses were as up-to-date as possible when published, as this is often neglected by authors of overviews [ 30 ].

Study criteria

The inclusion criteria for the studies consisted of four key factors: (1) the participation of postpartum mothers up to 24 months, as research has shown that mothers can continue to experience mental disorders for up to 24 months after giving birth. This extended timeframe highlights the need for ongoing support and care for postpartum mothers beyond the traditional 12-month postpartum period [ 25 ]; (2) the use of self-administered questionnaires or scales to assess social support; (3) publication in full-text English; and (4) a descriptive or cross-sectional designs. Since, according to the Oxford Center's table of Evidence-Based Medicine 2011 and Dehkordi AH et al. review study, a review of descriptive or cross-sectional studies is necessary to examine the status of a medical or health condition and its relationship with other conditions [ 31 , 32 ].

Exclusion criteria included studies that were: (1) clinical/controlled trials, qualitative, longitudinal, or non-original articles; (2) solely for psychometric purposes; and (3) targeted specific groups of postpartum women.

A total of 991 articles were initially identified in various databases and imported into EndNote X7 software [ 33 ], with duplicates removed. Out of the 956 articles, 19 papers were selected for inclusion after being assessed for relevance by two independent reviewers who achieved consensus on which studies to include [ 27 ]. Eight full-text studies were excluded due to failure to report intended results ( n  = 2) and no intended design ( n  = 6). Finally, 11 papers were reviewed. The study search and selection process are illustrated in Fig.  1 .

Study search and selection process

Risk of bias in included studies

The Newcastle–Ottawa Quality Assessment Scale (adapted for cross-sectional studies) [ 34 ] was used to determine the risk of bias. Five studies (45%) were determined to have a low risk of bias, 6 of them (55%) were a medium risk of bias, and no study (0%) was assessed as having a high risk of bias. Figure  2 presents the details of the risk-of-bias items separately for each article.

Summary of risk of bias; authors' assessment of the risk of bias for each study

Data synthesis

A meta-analysis is often not feasible due to the presence of significant heterogeneity in quantitative indices or measurement tools. In such cases, a narrative approach to synthesis may be more appropriate and effective [ 32 , 35 ]. So, in present study a narrative and deductive approach to synthesis was selected, following the steps outlined in the Centre for Reviews and Dissemination (CRD). These steps included developing a preliminary synthesis of the results of included studies, exploring relationships in the data, and considering the robustness of the synthesis [ 36 ].

Description of studies

Eleven cross-sectional studies were included in the final analysis, and the majority of studies ( N  = 8) took place in Asian nations. Only one study was conducted in Europe, while two were conducted in Africa. The maximum time after childbirth was 18 months. The characteristics of the studies are shown in Table  2 .

Aim 1: Status of Postpartum Social support

Five studies used the Multidimensional Scale of Perceived Social Support (MSPSS) to assess social support. In comparison, two studies utilized the Maternity Social Support Scale (MSSS), and the remaining employed different questionnaires (see Tables 2 and 3 ).

In two studies, the majority of women reported their postpartum social support level as medium (56.1% and 53%) [ 42 , 46 ]. In three other studies, most women reported high-level social support (ranging from 39.5% to 66.6%) [ 8 , 40 , 43 ]. However, one study found that 73.3% of participants had low social support [ 44 ]. Additionally, in two studies, the authors interpreted the level of postpartum social support based on its mean score as moderate and high [ 37 , 39 ]. It is important to note that the scoring for social support varied across these studies, as shown in Table  3 .

Aim 2: Status of postpartum psychosocial conditions

The Edinburgh Postnatal Depression Scale (EPDS) was utilized in all, but one of the studies [ 39 ]. The prevalence of Postpartum Depression (PPD) with a score of ≥ 13 was reported as 22%- 29.08% in four of the studies [ 8 , 40 , 41 , 44 ]. Meanwhile, three studies reported the prevalence of PPD with a score of ≥ 10 as 21.3%- 41.49% [ 41 , 42 , 43 , 45 ]. Furthermore, one study reported the prevalence of PPD with a score of ≥ 8.5 as 23.7% [ 46 ] (Table  3 ).

The prevalence of anxiety was assessed using the Perinatal Post-Traumatic Stress Questionnaire (PPQ) with a score of ≥ 19 and the State-Trait Anxiety Inventory (STAI) with a score of ≥ 75 percentile, reported rates of 6.1% and 27.80%, respectively [ 8 , 45 ] (Table  3 ). The PPQ is a self-rating scale to identify women suffering from PTSD symptoms (i.e. re-experiencing, avoidance- numbing, and hyperarousal) at 1–18 months postpartum [ 8 ].

The level of mental health was assessed using the Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS) in a study, with authors interpreting the mean score as low [ 38 ] (refer to Table  3 for details).

Only three studies explored the postpartum quality of life using the World Health Organization Quality of Life Assessment-BREF (WHOQOL-BREF), Spiritual Wellbeing Scale (SWBS), and Postpartum Quality of Life (PQOL). In a study, the level of PQOL was interpreted as medium based on its mean score [ 39 ]. Additionally, findings from a separate study showed that 72.43% of non-depressive women had a high score (100–120) on SWB [ 44 ] (Table  3 ).

Aim 3: Association between postpartum social support and psychosocial conditions

Ten studies were identified that investigated the association between social support and postpartum depression (PPD), with results showing that social support was a statistically significant factor in the development of PPD [ 8 , 37 , 38 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ]. Only three studies, however, evaluated the link between women’s social support and mental health disorders such as anxiety and PTSD in postpartum period. These studies suggested that low levels of social support were a contributing risk factor for postpartum anxiety and other mental illnesses [ 8 , 38 , 45 ] (the statistical tests used are given in Table  2 ).

Moreover, three studies specifically examined the association between social support and quality of life in the postpartum period, where an association was confirmed [ 37 , 39 , 41 , 44 ]. Furthermore, two of these studies found that this relationship was reciprocal [ 39 , 44 ] (the statistical tests used are given in Table  2 ).

Figure  3 summarizes the studies, analyses, and syntheses pertaining to the relationship between social support and psychosocial conditions in the postpartum period.

Relationship between social support and psychosocial conditions in postpartum period

In this study, we systematically reviewed cross-sectional reports on the relationships between social support and psychosocial conditions in postpartum period. This review pursued four aims: 1) to explore evidence for social support status in postpartum period, 2) to assess the evidence for psychosocial conditions status in postpartum period, 3) to evaluate the evidence for associations between social support and psychosocial conditions in postpartum period, and 4) to propose a logic framework for improving postpartum social support and psychosocial conditions.

Regarding aim 1, our review found that the social support status of the majority of women in postpartum period was at a moderate to high level. There was a sufficient level of social support, as the majority of evidence came from Asia, where the appropriate level of support for postpartum women is associated with socio-cultural norms. For example, in Saudi culture, it is common for a mother to spend the puerperium period, especially the first forty days, at her mother's house to receive the necessary support until she recovers [ 37 ]. However, more research is needed to fully understand mothers’ social support in the postpartum period, as this is crucial in developing strategies to improve maternal health [ 47 ].

Concerning aim 2, our review found that the prevalence of PPD (EPDS score ≥ 13) was 22- 29.08%, but there was insufficient evidence to determine the prevalence of other mental disorders. Similar to our findings, the aggregate data meta-analyses (AGMAs) results of the systematic review studies revealed a prevalence of 17.22% to 27% for PPD [ 21 , 48 , 49 , 50 , 51 ]. PPD is a major mental health issue that impacts about 1 in 8 women, as the transition to motherhood is not always smooth and can be overwhelming [ 52 ]. During this transitional period, women encounter numerous challenges including changes in their physical appearance, increased expectations of new responsibilities, physical discomforts from pregnancy and childbirth, and potential marital discord leading to psychosocial issues, particularly PPD [ 2 , 3 , 4 ]. Furthermore, PPD is a widespread social health concern that not only affects the mother and her newborn, but also has repercussions for other family members and various aspects of their lives [ 48 , 49 ]. Consequently, there is a need to implement routine postpartum screening for maternal mental health to ensure early detection and treatment of PPD [ 53 ].

Regarding aim 3, our systematic review indicated that low social support is a significant predictor of self- reported PPD and anxiety symptoms. Furthermore, our findings demonstrated that social support and postpartum quality of life were mutually dependent. These results are consistent with previous studies, including review or meta-analysis studies with random- effects model, which have identified a lack of social support as a major risk factor for PPD [ 49 , 50 , 51 , 54 , 55 ]. Riem et al.’s review study also supports our results, as it found that low social support is associated with self- reported mental disorders symptoms, such as stress and anxiety, during postpartum [ 7 ]. Postpartum stress and anxiety are crucial to address as they have been linked to negative health behaviors in women, such as unhealthy diet, smoking relapse, and postpartum weight retention. Additionally, they are key factors associated with PPD, which can develop into self- reported major depression and pose significant risks to morbidity and mortality if left underdiagnosed [ 56 ]. It is important to recognize and address these issues in order to support the overall well-being of new mothers [ 52 ]. Social support is essential in reducing the risk of postpartum psychosocial problems by providing a protective effect. This includes feeling understood, accepted, and respected, which can help alleviate individual psychological pressure, inhibit negative emotions, and provide positive emotional experiences. Additionally, social support can aid in bonding and coping by improving self-evaluation, helping to form a positive self-image, and promoting self-esteem. Furthermore, social support can act as a buffer against the negative effects of stressors during the postpartum period [ 52 , 56 ]. As such, providing adequate social and psychological support from family members, providing reassurance, conducting appropriate educational interventions, and regularly assessing the psychological state of women by healthcare providers can help them adapt to postpartum changes, improve their quality of life, and enhance their overall health [ 57 ].

Aim 4: A proposed logic framework for improving postpartum social support and psychosocial conditions

Social support was protective against all postpartum psychosocial disorders; therefore, these findings provide a foundation for developing and tailoring interventions and strategies to improve mental health outcomes [ 58 , 59 ]. The major components of our proposed logic framework are depicted in Fig.  4 and described below.

Proposed logic framework for improving postpartum social support and psychosocial conditions

In the logic framework, stressful events are associated with childbirth and motherhood [ 1 , 2 , 3 , 4 ]. Social support is the coping resource in this framework [ 22 ]. According to this coping resource, during the coping action stage, researchers and healthcare providers should attempt to improve perceived social support by encouraging and empowering women to be actively involved in adapting to the physical and psychosocial changes occurring, acquiring the necessary knowledge, engaging in help-seeking behavior, and developing novel social roles throughout the postpartum period [ 18 , 60 , 61 , 62 ]. In addition, health policymakers should be aware that flexible education-care-support planning is a promising tool for facilitating more client-centered care during the postpartum care period. In other words, it is crucial to transition from narrow-minded to comprehensive plans that integrate care, education, and support, as well as from uniformity to customization based on individual conditions, resources, and requirements. This shift entails prioritizing clients' personal needs and preferences over organizational constraints, which can help address challenges like escalating healthcare expenses and staffing deficiencies in care facilities. Also, it is consistent with the proposed positive definition of health, which shifts from total well-being to the “ability to adapt and self-manage.” As a result, health professionals encourage patients to participate in their own care processes more than ever before [ 13 , 47 ].

Finally, the effects of this framework are optimal postpartum mental health and quality of life [ 58 , 59 ].

The present systematic review is limited by its focus on English-language publications of the included studies. Additionally, a meta-analysis was not conducted due to shortcomings in quantitative indices and varying measuring tools. Nonetheless, this review provides a valuable and broad geographic overview of social support for postpartum psychosocial conditions. The novel contribution of this study is the development of a conceptual framework that offers insights into designing programs for postpartum mental health and quality of life. We recommend using standard protocols for designing, implementing, and evaluating interventions to facilitate comparison in systematic review and meta-analysis studies. Our proposed logic framework can be tested as a guiding framework in intervention design. We also recommend conducting a systematic review that focuses on specific types of action, such as empowerment. Client-tailored and risk-based maternity cares are two important strategies that empower postpartum women [ 63 ]. These interventions are designed to address the physical and psychosocial changes that women experience during this time, and they encourage women to actively participate in adapting to these changes [ 18 ]. By tailoring care to each individual's needs and addressing potential risks, women can feel more supported and empowered as they navigate the postpartum period.

In conclusion, this systematic review indicates a positive association between social support and postpartum psychosocial conditions. Social support is viewed as a coping mechanism during the postpartum period, which can result in improved quality of life and mental health. This is achieved by empowering women, promoting help-seeking behaviors, and providing client-centered care. As such, the “ability to adapt and self-manage” defines postpartum women’s health.

Availability of data and materials

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

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Research Article

Factors influencing the participation of pregnant and lactating women in clinical trials: A mixed-methods systematic review

Contributed equally to this work with: Mridula Shankar, Alya Hazfiarini

Roles Data curation, Formal analysis, Methodology, Project administration, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Gender and Women’s Health Unit, Nossal Institute for Global Health, School of Population and Global Health, University of Melbourne, Carlton, Victoria, Australia

Roles Formal analysis, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing

Roles Formal analysis, Methodology, Writing – review & editing

Roles Methodology, Writing – review & editing

Affiliation Maternal, Child and Adolescent Health Program, Burnet Institute, Melbourne, Victoria, Australia

Roles Data curation, Methodology, Writing – review & editing

Affiliation University Library, University of Melbourne, Carlton, Victoria, Australia

Affiliation Women’s and Children’s Health Research Unit, KLE Academy of Higher Education and Research, Jawaharlal Nehru Medical College, Belagavi, Karnataka, India

Affiliation Concept Foundation, Geneva, Switzerland/Bangkok, Thailand

Roles Conceptualization, Funding acquisition, Methodology, Writing – review & editing

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Supervision, Validation, Writing – original draft, Writing – review & editing

• Mridula Shankar, 
• Alya Hazfiarini, 
• Rana Islamiah Zahroh, 
• Joshua P. Vogel, 
• Annie R. A. McDougall, 
• Patrick Condron, 
• Shivaprasad S. Goudar, 
• Yeshita V. Pujar, 
• Manjunath S. Somannavar, 

• Published: May 30, 2024
• https://doi.org/10.1371/journal.pmed.1004405
• Peer Review
• Reader Comments

Poor representation of pregnant and lactating women and people in clinical trials has marginalised their health concerns and denied the maternal–fetal/infant dyad benefits of innovation in therapeutic research and development. This mixed-methods systematic review synthesised factors affecting the participation of pregnant and lactating women in clinical trials, across all levels of the research ecosystem.

Methods and findings

We searched 8 databases from inception to 14 February 2024 to identify qualitative, quantitative, and mixed-methods studies that described factors affecting participation of pregnant and lactating women in vaccine and therapeutic clinical trials in any setting. We used thematic synthesis to analyse the qualitative literature and assessed confidence in each qualitative review finding using the GRADE-CERQual approach. We compared quantitative data against the thematic synthesis findings to assess areas of convergence or divergence. We mapped review findings to the Theoretical Domains Framework (TDF) and Capability, Opportunity, and Motivation Model of Behaviour (COM-B) to inform future development of behaviour change strategies.

We included 60 papers from 27 countries. We grouped 24 review findings under 5 overarching themes: (a) interplay between perceived risks and benefits of participation in women’s decision-making; (b) engagement between women and the medical and research ecosystems; (c) gender norms and decision-making autonomy; (d) factors affecting clinical trial recruitment; and (e) upstream factors in the research ecosystem. Women’s willingness to participate in trials was affected by: perceived risk of the health condition weighed against an intervention’s risks and benefits, therapeutic optimism, intervention acceptability, expectations of receiving higher quality care in a trial, altruistic motivations, intimate relationship dynamics, and power and trust in medicine and research. Health workers supported women’s participation in trials when they perceived clinical equipoise, had hope for novel therapeutic applications, and were convinced an intervention was safe. For research staff, developing reciprocal relationships with health workers, having access to resources for trial implementation, ensuring the trial was visible to potential participants and health workers, implementing a woman-centred approach when communicating with potential participants, and emotional orientations towards the trial were factors perceived to affect recruitment. For study investigators and ethics committees, the complexities and subjectivities in risk assessments and trial design, and limited funding of such trials contributed to their reluctance in leading and approving such trials. All included studies focused on factors affecting participation of cisgender pregnant women in clinical trials; future research should consider other pregnancy-capable populations, including transgender and nonbinary people.

Conclusions

This systematic review highlights diverse factors across multiple levels and stakeholders affecting the participation of pregnant and lactating women in clinical trials. By linking identified factors to frameworks of behaviour change, we have developed theoretically informed strategies that can help optimise pregnant and lactating women’s engagement, participation, and trust in such trials.

Author summary

Why was this study done.

• Pregnant and lactating women and people are routinely excluded from participating in drug and vaccine clinical trials, resulting in limited options for prevention and treatment of medical conditions.
• Challenges to including pregnant and lactating women and people in clinical research have been identified at multiple levels of the research and health systems, but the full range of barriers and facilitators to participation are not well known.

What did the researchers do and find?

• We conducted a mixed-methods systematic review and identified 60 research articles from 27 countries on the views and experiences of pregnant and lactating women’s participation in clinical research, from the perspectives of cisgender women, family and community members, health workers, and people involved in the conduct of clinical research.
• Using a thematic synthesis approach, we identified barriers affecting participation including women having a limited appetite for risk during pregnancy and lactation, concerns about women’s bodily autonomy during pregnancy, and challenges in obtaining ethical approval for clinical research with pregnant women.
• We also identified facilitators of participation including the potential for personal health benefits, expectations of higher quality care, trust in the medical and research systems, and strong teamwork between researchers and health workers.

What do these findings mean?

• Our findings demonstrate the need for multipronged strategies to address barriers and reinforce facilitators across the various levels of the research and health systems.
• The actions that are needed to overcome these barriers and reinforce facilitators must be discussed, prioritised, and adapted to specific contexts.
• All included studies focused on factors affecting participation of cisgender pregnant women in clinical trials; future research should consider other pregnancy-capable populations, including transgender and nonbinary people.

Citation: Shankar M, Hazfiarini A, Zahroh RI, Vogel JP, McDougall ARA, Condron P, et al. (2024) Factors influencing the participation of pregnant and lactating women in clinical trials: A mixed-methods systematic review. PLoS Med 21(5): e1004405. https://doi.org/10.1371/journal.pmed.1004405

Received: December 20, 2023; Accepted: April 19, 2024; Published: May 30, 2024

Copyright: © 2024 Shankar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The research in this publication was supported by funding from MSD (grant MFM-22-159697 to Concept Foundation), through its MSD for Mothers initiative ( https://www.msdformothers.com/ ) and is the sole responsibility of the authors. MSD for Mothers is an initiative of Merck & Co., Inc., Rahway, NJ, U.S.A. MAB’s time is supported by an Australian Research Council Discovery Early Career Researcher Award (DE200100264) and a Dame Kate Campbell Fellowship (University of Melbourne Faculty of Medicine, Dentistry and Health Sciences). JPV is supported by an Australian National Health and Medical Research Council (NHMRC) Investigator grant (GNT1194248). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations: BCW, Behaviour Change Wheel; COM-B, Capability, Opportunity, and Motivation Model of Behaviour; MMAT, Mixed Methods Appraisal Tool; TDF, Theoretical Domains Framework

Introduction

Clinical trials are the foundation for knowledge on the efficacy and safety of biomedical interventions to protect health and treat illness. The fundamental questions of who participates and whose data contributes to trials have implications for understanding the risks and benefits of interventions, and the societal value of such interventions to specific populations. Pregnant and lactating women and people have long been underrepresented or excluded entirely from participating in therapeutic and vaccine clinical trials [ 1 ]. Notwithstanding valid concerns regarding fetal and infant safety, an outright exclusionary response to this complex issue has denied the maternal–fetal/infant dyad the health benefits of biomedical innovation, despite demonstrated public health need [ 2 , 3 ]. As a recent example, during the COVID-19 pandemic, pregnant women and people were excluded from early therapeutic and vaccine trials despite greater severity of infection-related illness [ 4 – 9 ].

Including pregnant and lactating women and people as research participants is vital: pregnancy is a unique physiological state where the body undergoes adaptations that can lead to pregnancy-specific disorders or worsen preexisting conditions [ 10 ]. These changes can influence how effective a drug is, whether and how the body responds to the drug, and the dosages at which the drug is optimally effective and minimally harmful. Most pregnant women take at least 1 medication during pregnancy [ 11 ], yet many of these medications are provided with limited information on efficacy, appropriate dosing, and safety in these populations [ 1 ]. Pregnant and lactating women with preexisting illnesses may also be advised to discontinue medications to minimise potential harms, without full appreciation of the possible consequences of unmedicated disease progression [ 12 ].

The current state of maternal health and the limited therapeutic options available for pregnant and lactating populations illustrates the consequences of these evidence gaps. Each year, complications of pregnancy and childbirth result in approximately 287,000 maternal deaths [ 13 ], 1.9 million stillbirths [ 14 ], and 2.3 million neonatal deaths [ 15 ]. Most of these deaths occur from preventable or treatable obstetric causes (e.g., postpartum haemorrhage, preeclampsia/eclampsia, sepsis) that are generally treated using repurposed medications that were originally developed and approved for use in other non-obstetric conditions [ 16 ]. Over the past 3 decades, only 2 drugs have been registered to specifically treat pregnancy-related complications: Atosiban—a tocolytic to prevent preterm birth, and Carbetocin—an oxytocin analogue for managing postpartum haemorrhage [ 17 ]. Pregnancy-specific medicines rarely progress through the research and development pipeline due to a multitude of factors, including the absence of public stewardship, chronic underinvestment, and regulatory and market barriers [ 18 , 19 ]. Maternal mortality rates have largely remained static in the Sustainable Development Goal era: progress has halted or reversed in 150 countries [ 13 ]. Without significant investments in pharmaceutical development, the 2030 target of a global maternal mortality ratio less than 70 maternal deaths per 100,000 live births [ 20 ] is unlikely to be achieved.

Poor representation of pregnant and lactating women and people in clinical research, and the absence of a pregnancy-focused research and development agenda violates fundamental ethical principles of justice and equity [ 12 , 21 ]. Challenges to equitable inclusion operate across all research stages: “upstream” barriers include a lack of appropriate animal models, pharmaceutical industry risk aversion, and clinical trials and liability insurance challenges [ 12 , 18 , 22 , 23 ]. “Downstream” barriers include perceptions that pregnant and lactating women do not want to take part in clinical trials, or that their inclusion makes research activities too risky or onerous [ 23 ]. Overall, there is a lack of a comprehensive understanding of the full range of these factors from the perspectives of key stakeholder groups. This mixed-methods systematic review seeks to address this gap by synthesising current research evidence on factors (i.e., barriers and facilitators) affecting the participation of pregnant and lactating women in vaccine and therapeutic clinical trials. We use behavioural [ 24 , 25 ] frameworks to provide a theory-informed basis for the development and implementation of appropriate behaviour change intervention strategies to promote their meaningful inclusion.

This review is reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines ( S1 Appendix ), Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) statement ( S2 Appendix ), and based on guidance from the Cochrane Effective Practice and Organisation of Care group [ 26 ]. The protocol has been registered (PROSPERO: CRD42023462449).

Types of studies

We included primary qualitative, quantitative, and mixed-methods studies. There were no limitations on publication date, language, or country.

We excluded publications that were not primary research, including conceptual scholarship on the ethics of inclusion/exclusion, case reports, reviews, commentaries, short communications, editorials, news articles, letters to the editor, conference abstracts, workshop summaries, theses or dissertations, book chapters, book reviews, and regulatory or committee guidance or decisions.

Topic of interest

This review focuses on systematically identifying the factors, including barriers and facilitators, influencing the participation of pregnant and lactating women in drug or vaccine trials (i.e., therapeutic or prophylactic trials). We recognise that people who are capable of pregnancy have diverse gender identities. We use the terminology “pregnant and lactating women,” acknowledging that empirical literature on this topic has been focused on the experiences of cisgender women. Extrapolating these data to apply to people with other gender identities may lead to inaccurate or incomplete conclusions.

We included studies that described the attitudes, perspectives, and experiences of multiple stakeholders: women who participated and declined participation in clinical trials during pregnancy and lactation, partners or husbands, family members, community leaders, health workers, research staff, study investigators, ethics committee members, regulators, funders, pharmaceutical representatives, policy makers, and other relevant stakeholders.

We excluded the following types of interventions from this review: (a) lifestyle or behavioural interventions; (b) trials of diagnostics or medical devices; (b) workforce interventions to improve clinical care outcomes; (c) alternative or complementary medicine; (d) trials evaluating health policies or clinical protocols; (e) fetal tissue research, bio-banking, and genetic testing; (f) facilitators and barriers to engaging pregnant women in observational research; (g) supports to clinicians or pregnant or lactating women regarding decision-making on medication; and (h) research solely focused on substance use prevention and treatment, due to the particularly distinct barriers and facilitators given overlapping vulnerabilities among substance-using pregnant women, and unique considerations in relation to fetal health such as in utero exposure to alcohol and other substances. We also excluded clinical trial protocols and publications of randomised controlled trials that did not contain data related to facilitators or barriers to trial participation.

Search methods for identification of relevant studies

We searched 8 databases from inception to 14 February 2024: MEDLINE (Ovid), CINAHL Complete, Family & Society Studies Worldwide, SocINDEX, Scopus, Web of Science Core Collection, Embase (Ovid), and Global Health (Ovid). PC, an Information Specialist developed the final search strategy ( S3 Appendix ), using a combination of terms relevant to pregnant and lactating women, and perspectives and experiences of stakeholders regarding their inclusion/exclusion and participation in drug or vaccine clinical trials. No restrictions were placed on publication year, language, or geographical setting.

Selection of studies

We imported the search results into Covidence [ 27 ] and removed duplicates. Five review authors (MS, AH, MAB, AM, and AA) independently screened titles and abstracts. Titles and abstracts of non-English publications were screened with the assistance of Google Translate. Three reviewers (MS, AH, and AM) independently reviewed full texts. One French publication that met the inclusion criteria was translated to English using ChatGPT [ 28 ], and translation accuracy was subsequently verified with a native French speaker in our research network. At each screening stage, differences in decisions regarding record inclusion were resolved through discussion and final decisions were made through consensus with a third review author (MAB).

Data extraction and assessing methodological limitations

Two review authors (MS and AH) extracted relevant data, including study aims, methodological characteristics, geographical settings, population of interest (pregnant women, lactating women, or both), intervention type (therapy or vaccine), specific areas of research, and study findings (author-generated themes, supporting explanations, participant quotes, survey results, and relevant tables and figures). We developed a data extraction form and refined it by extracting data from a subset of 6 studies. All extracted data was cross-checked for accuracy and completeness, and differences resolved via consensus.

Two reviewers (MS and AH) independently assessed the methodological limitations of each study using an adapted Mixed Methods Appraisal Tool (MMAT) [ 29 ]. For qualitative studies, evaluative criteria included alignment of methodology and data collection with research aims, rigour in data analysis and reporting of study findings, ethical considerations, and researcher reflexivity. We assessed quantitative studies based on the suitability of sampling strategy, reporting on sample representativeness, use of appropriate measures, level of nonresponse bias, ethical considerations, and relevance of statistical analyses conducted. In addition to the aforementioned criteria, we assessed mixed-methods studies to determine whether authors demonstrated sufficient rationale for the use of a mixed-methods approach, effectiveness of integration of study components and outputs, and discussion of data triangulation. All differences in assessments between the 2 review authors were resolved through discussion. The assessment of methodological limitations did not affect the inclusion or exclusion of studies but rather served as a mechanism for determining confidence in the evidence.

Data analysis and synthesis

We used a thematic synthesis approach to analyse qualitative data [ 30 ]. After selecting 6 data-rich studies, 2 reviewers (MS and AH) independently applied line-by-line coding to the textual data to create summative codes. Codes were discussed for consistency in meaning and refined if necessary. The remaining studies were each coded by one of the 2 reviewers, and new codes were added as necessary. Through discussion, we subsumed codes of similar meaning under broader categories, gradually developing “summary layers” in a hierarchical grouping structure. We applied the gender domains of the gender analysis matrix [ 31 ] as a lens to our findings to understand how our data on factors influencing participation were shaped by aspects such as distribution of labour and roles, gender norms and beliefs, access to resources, decision-making power, and institutional policies. We consolidated our results into a set of 5 overarching themes and 24 review findings through an iterative process of identifying, comparing, and discussing conceptual boundaries between and among thematic data outputs.

Two review authors (MS and AH) used the GRADE-CERQual (Confidence in the Evidence from Reviews of Qualitative research) approach [ 32 , 33 ] to assess our confidence in each of the 24 qualitative review findings. GRADE-CERQual assesses confidence in the evidence, based on the following 4 key components [ 26 ]:

• methodological limitations of included studies [ 34 ];
• coherence of the review finding [ 35 ];
• adequacy of the data contributing to the review finding [ 36 ]; and
• relevance of the included studies to the review question [ 37 ].

After assessing each component, we made a judgement via consensus about the overall confidence—rated as high, moderate, low, or very low—in the evidence supporting the review finding [ 32 ]. Detailed descriptions of the GRADE-CERQual assessments are in S4 Appendix .

We then mapped data from the quantitative studies onto the findings of the qualitative evidence synthesis, and determined areas of convergence or divergence, and whether any additional factors arose that had previously not been discussed. We regarded the quantitative data as (a) “supporting” of a qualitative evidence synthesis finding if the information synthesised from the contributory quantitative studies were similar to the finding; (b) “extending” if the data offered additional details in line with a review finding; and (c) “contradictory” if the data conflicted with a review finding. Summaries of the quantitative findings are presented in S5 Appendix .

Finally, we mapped our review findings to the Theoretical Domains Framework (TDF) [ 24 ] and the Capability, Opportunity, and Motivation (COM-B) [ 25 ] models of behavioural determinants and the Behaviour Change Wheel (BCW) to identify and provide a rational basis for the development and implementation of appropriate behaviour change strategies.

Review team and reflexivity

The review author team has diverse personal backgrounds, including gender, personal experiences of pregnancy, countries of origin and residence, and linguistic traditions. Our professional and academic backgrounds and experiences are varied, and include the social, behavioural, and biomedical sciences, medicine, clinical epidemiology, and public health. Some review authors have led and implemented trials in maternal and perinatal health. As an interdisciplinary team with diverse social and professional backgrounds, we maintained a reflexive stance through all stages of the review process by engaging in multiple reflective dialogues to interrogate and interpret the data and findings. Through this process, we named and critiqued assumptions that underpinned the analysis and challenged disciplinary biases. In doing so, we aimed to develop review findings that were inclusive of different disciplinary lenses.

Sixty papers from 53 studies met the inclusion criteria [ 38 – 97 ]. Fig 1 presents the PRISMA flowchart. Table 1 reports the summary characteristics of included papers and S6 Appendix includes more detailed individual characteristics of the included papers.

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• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pmed.1004405.g001

https://doi.org/10.1371/journal.pmed.1004405.t001

Description of papers

Thirty-nine papers used qualitative methodologies [ 39 , 40 , 42 – 48 , 53 , 54 , 56 – 66 , 69 , 70 , 72 – 74 , 78 , 81 , 82 , 84 – 87 , 89 – 92 , 96 ], 18 papers used quantitative methodologies [ 38 , 41 , 50 – 52 , 67 , 68 , 71 , 75 – 77 , 79 , 80 , 88 , 93 – 95 , 97 ], and 3 papers used mixed-methods study designs [ 49 , 55 , 83 ].

The 60 papers present data from 27 countries and 4 geographic regions: 13 countries in Africa [ 44 – 47 , 65 , 73 , 78 , 84 , 85 ], 8 countries in Europe [ 38 , 39 , 41 , 48 – 50 , 53 – 56 , 58 , 59 , 61 , 62 , 64 , 67 – 69 , 72 , 74 , 80 – 83 , 86 , 89 , 90 , 92 , 94 , 96 ], 3 countries in the Americas [ 42 , 43 , 51 , 52 , 57 , 60 , 63 , 66 , 70 , 71 , 75 , 77 , 79 , 85 , 88 , 91 , 93 , 95 ], and 3 countries in the Western Pacific [ 40 , 76 , 87 , 97 ].

Fifty-one papers focused on pregnant women only [ 38 – 41 , 44 , 47 – 50 , 52 , 53 , 55 – 70 , 72 – 94 , 97 ], 2 papers focused on lactating women only [ 46 , 96 ], and 7 papers focused on pregnant and lactating women [ 42 , 43 , 45 , 51 , 54 , 71 , 95 ]. Thirty-seven papers addressed a therapeutic drug-related intervention [ 38 , 40 , 41 , 44 – 49 , 53 , 56 , 59 – 62 , 66 , 69 , 70 , 72 , 73 , 77 , 79 – 90 , 92 , 93 , 96 , 97 ], 11 papers focused on a vaccine-related intervention [ 50 , 51 , 55 , 57 , 58 , 63 , 64 , 67 , 68 , 78 , 94 ], and 12 papers were about pregnant and/or lactating women’s participation in interventional clinical trials generally [ 39 , 42 , 43 , 52 , 54 , 65 , 71 , 74 – 76 , 91 , 95 ].

Twenty-five papers included perspectives of pregnant women [ 38 , 45 , 47 , 48 , 51 , 57 , 58 , 60 , 61 , 64 , 65 , 67 , 71 – 75 , 77 , 85 , 89 – 91 , 94 , 95 , 97 ], 28 papers included perspectives of postpartum women [ 39 – 41 , 44 – 46 , 49 , 51 , 56 , 57 , 59 , 62 , 63 , 69 – 71 , 74 , 79 – 87 , 92 , 95 ], and 14 papers included health workers’ perspectives [ 44 , 47 , 50 , 52 – 54 , 61 , 64 , 65 , 67 , 87 , 88 , 91 , 94 ]. For other stakeholder groups, please refer to Table 1 .

Methodological limitations of included studies

Assessments of methodological limitations of the included studies are available in S7 Appendix . Across qualitative studies, the most common methodological limitations concerned recruitment approaches and strategies, descriptions of analytical methods, ethical considerations, specifically steps or precautions taken to protect from loss of privacy and confidentiality, data security and integrity, and most studies did not include a reflexivity statement. Across quantitative studies, authors rarely reported on indicators of sample representativeness of the target population, most did not report on or were judged at high risk of nonresponse bias, and ethical considerations pertaining to data security and integrity were frequently missing. For the 3 mixed-methods studies, limitations were identified at the level of integrating methodological approaches at the methods, interpretation, and reporting levels.

Themes and findings from the qualitative and quantitative evidence synthesis

We developed 5 overarching themes and 24 review findings in the qualitative evidence synthesis ( Table 2 ):

• interplay between perceived risks and benefits of participation in women’s decision-making (9 review findings);
• engagement between women and the medical and research ecosystems (2 review findings);
• gender norms and decision-making autonomy (3 review findings);
• factors affecting clinical trial recruitment (7 review findings); and
• upstream factors in the research ecosystem (3 review findings).

https://doi.org/10.1371/journal.pmed.1004405.t002

We graded 6 review findings as high confidence, 11 as moderate confidence, and 7 as low confidence. An explanation for each GRADE-CERQual assessment is presented in the evidence profile ( S4 Appendix ).

Interplay between perceived risks and benefits of participation in women’s decision-making

Findings 1 to 9 are categorised under this theme with 48 studies exploring women’s perspectives on clinical trial participation and factors influencing their decision-making. These factors include balancing risks and benefits, experiences and expectations of high quality care, understanding of study design features, acceptability and stigma associated with the intervention, altruistic motivations and financial incentives.

Finding 1 : Women have a limited appetite and higher perception of risk during pregnancy or lactation . Perception of risks influenced pregnant and lactating women’s willingness to participate in trials, which varied based on their individual levels of risk tolerance, previous trial experiences, observations of others’ experiences, stage of pregnancy or lactation, existing health conditions, and a sense of responsibility for their health and that of the fetus/infant. Women were more likely to decline participation if the experimental intervention was previously untested and were more confident to participate when convinced of no harm (high confidence) [ 39 , 40 , 47 , 48 , 57 , 58 , 60 , 63 – 65 , 69 , 72 , 74 , 83 , 84 , 87 , 89 , 91 , 92 , 96 ].

The most salient factors affecting perceptions of risk were concerns of potential harm to the fetus or baby, including in the longer term, and fears of side-effects [ 39 , 48 , 57 , 58 , 60 , 63 , 69 , 72 , 74 , 83 , 84 , 87 , 89 , 91 , 92 , 96 ]. The uncertainty of these negative outcomes contributed to women’s reluctance to take medications [ 48 , 64 , 69 , 72 ] or participate in experimental interventions, with some likening the experience to being treated as “guinea pigs” [ 39 , 56 , 58 , 69 , 90 ]. Women willing to consider participation wanted proof of safety from previous research evidence [ 57 , 58 , 84 ], online resources [ 96 ], discussions with research staff and health workers [ 96 ], and knowing the experiences of others who had taken the intervention [ 47 , 96 ].

Quantitative evidence supported the qualitative findings that women were apprehensive about taking an experimental product during pregnancy or lactation [ 79 ] primarily due to concerns of fetal or infant harm [ 38 , 51 , 67 , 71 , 75 , 83 , 94 , 95 ], side-effects [ 77 , 80 ], and the possibility of unknown longer-term negative sequelae [ 67 , 75 , 77 ]. Prior knowledge of the health condition [ 68 ], information about drug safety in pregnant and nonpregnant populations [ 51 ], and information that large numbers of pregnant women had already enrolled in the trial [ 67 ] were factors that increased willingness to participate.

Finding 2 : Making trade-offs between risk and severity of the condition and risk-benefit ratio of intervention . Before participating, women weighed the risk of their medical condition and its impact, especially on the baby, against the risks of an intervention and its potential benefits. Women were less likely to participate if they felt healthy or perceived themselves at low risk of experiencing or being negatively affected by the condition, believed they had nothing to gain from participating, or felt concerned that the intervention risks were too high (moderate confidence) [ 39 , 48 , 57 – 60 , 63 , 64 , 69 , 72 , 74 , 87 , 91 , 96 ].

Women were more willing to participate when they had concerns about their risk factors [ 70 ], had previously experienced the condition [ 48 , 70 ], or personally knew someone who had [ 48 ], were anxious about the baby suffering health problems [ 57 – 60 ], or perceived the intervention to be helpful based on past use [ 87 ], or the only course of action to avoid (further) ill-health [ 57 – 59 , 63 , 91 ]. For some women with preconceived notions that research entailed significant risks, their perceptions did not change in the presence of information, including about intervention safety [ 48 ].

Quantitative evidence supported the qualitative findings that, when coupled with risks that were considered minimal or manageable [ 83 ], women with greater knowledge about [ 83 ] or direct exposure to the condition [ 94 ] were more likely to participate in a vaccine or therapeutic trial. However, prior exposure to the medical condition did not consistently lead to higher participation in trials [ 51 ].

Finding 3 : Benefits to health arising from participation . A key motivating factor for pregnant and lactating women to participate in trials was the expectation of personal health benefits, such as improved knowledge about how the condition affected them, protecting their fetus or infant from harm, and reducing mother-to-child disease transmission. When women saw the potential for these benefits, deciding not to participate was viewed as potentially putting the baby’s life at risk (high confidence) [ 40 , 47 , 55 , 60 , 61 , 63 , 64 , 70 , 73 , 83 , 84 , 87 , 90 – 92 , 96 ].

Quantitative evidence supported this finding that women were more willing to participate in a trial when they were convinced about the potential short and longer-term benefits of the intervention for the health of the fetus [ 38 , 51 , 75 , 77 , 80 ], and their own health [ 38 , 41 , 51 , 75 , 80 , 95 ] and education [ 41 , 95 ].

Finding 4 : Experiences and expectations of high-quality care motivate participation . Pregnant and lactating women were motivated to participate as a token of appreciation to health workers who provided good quality care. Additionally, women were more likely to participate when they perceived that it would result in higher quality clinical care or access to vaccines or therapeutic products that had previously been denied or were otherwise not accessible outside the context of a trial (high confidence) [ 39 , 48 , 49 , 60 , 63 , 70 , 72 , 83 , 84 , 86 , 87 , 92 , 96 ].

In addition to free medications and vaccines, women’s perceptions of higher quality care were linked to greater frequency of diagnostic and monitoring tests [ 72 , 83 , 84 , 92 ], detailed information regarding care provided [ 63 ], and closer and continuous clinical observation [ 49 , 63 , 70 , 92 ]. Occasionally, women perceived care associated with a trial as lower quality due to the “experimental” nature of the intervention [ 39 ].

Quantitative evidence supported the qualitative finding that women expected trial participation to engender more and better quality care through enhanced monitoring [ 38 , 41 , 67 , 68 , 80 ], more tests [ 67 ], better therapeutic treatment [ 38 , 49 ], and the general feeling of being provided a high standard of medical care [ 51 , 75 , 80 ].

Finding 5 : Knowledge of the rationale for study design features . The rationale behind certain trial design features such as randomisation, blinding or inclusion of a placebo arm could be a source of confusion, concern, or reassurance for potential participants, impacting their decisions to participate. These features could be viewed as preferential treatment of one group over another, adding burden with little opportunity for personal benefit, a mechanism to reduce bias or conversely for researchers to avoid accountability for an adverse outcome (moderate confidence) [ 39 , 40 , 45 , 59 , 62 , 63 , 69 , 72 , 74 , 87 , 91 , 92 ].

Quantitative evidence extended understanding of women’s views about participation in placebo-controlled trials. Some women expressed reluctance to participate due to the possibility of being assigned to the control or placebo group [ 67 , 77 , 79 , 83 ]. However, others expressed that the uncertainty of assignment would not affect their decision, and for a minority, the possibility of assignment to the control condition motivated their participation as it could minimise risk but still provide ancillary benefits [ 67 ]. Women were keen to be unblinded regarding the arm to which they were assigned, once the trial was complete [ 80 ].

Finding 6 : Acceptability of the intervention is key to pregnant and lactating women’s willingness to participate in a trial and for research staff to recruit for a trial . Interventions that were most acceptable to women and research staff were those that simplified intervention delivery, were less onerous or painful than usual care, had negligible risk, were noninvasive, placed limited demands on time, did not involve invasive procedures, and where prior knowledge about the condition intersected with positive attitudes towards the therapeutic product (high confidence) [ 40 , 45 , 48 , 53 , 54 , 61 , 64 , 65 , 72 , 73 , 81 , 83 , 86 , 87 , 90 – 92 , 96 ].

For health workers involved in recruitment and trial operations, acceptability of the intervention was closely linked to their perceptions of the safety of the experimental therapy, derived from previous positive experiences administering the drug in a different clinical setting [ 53 ].

Quantitative evidence supported this qualitative finding that some women might be more willing to participate in a trial when they were less likely to be inconvenienced by or experience discomfort from trial procedures, additional and lengthy study visits [ 38 , 41 , 80 ]. Decliners cited blood tests, additional scans, and availability of suitable noninvasive alternatives as reasons for nonparticipation [ 51 , 83 ]. In the case of vaccine trials, quantitative data extended this qualitative finding by suggesting that women indicated greater acceptability of inactivated virus vaccines compared to live-attenuated virus vaccines [ 51 ].

Finding 7 : Fears around data sharing and use . Some women feared that trial participation, including provision of blood samples, could expose them to stigmatisation and judgement due to unwanted diagnoses and disclosure of disease status, data sharing regarding sensitive behaviours, and the threat of their data being used in ways that would compromise confidentiality and safety (low confidence) [ 65 , 85 , 86 ]. In the context of HIV trials, some women discussed concerns that an HIV diagnosis would lead to abandonment by their husbands [ 85 ].

No quantitative evidence was identified in this domain.

Finding 8 : Altruistic motivations . Pregnant women expressed willingness to participate in trials for the purpose of contributing to societal benefits of research, including the potential to improve health and healthcare for pregnant women in the future. Altruistic motivations could act as a stand-alone stimulus, secondary to or alongside beliefs around personal benefit, or conditional on no additional risk for participation (moderate confidence) [ 39 , 40 , 47 , 48 , 55 – 61 , 63 , 64 , 70 , 72 – 74 , 83 , 86 , 87 , 89 , 91 , 92 ].

In addition to helping other women, altruistic sentiments were linked to perceptions that the research effort was worthy [ 48 , 59 , 61 ], well-intentioned [ 61 ], filled an important scientific gap [ 58 , 70 , 72 ], and addressed a pressing need [ 48 , 63 , 73 , 91 ].

Quantitative evidence supported the qualitative finding that altruistic motivations influenced willingness to participate in trials, alongside personal benefits [ 38 , 41 , 49 , 51 , 67 , 77 , 80 , 95 ]. Women expressed having a sense of fulfilment that participation would have a positive impact on women’s health in the future.

Finding 9 : Financial incentives . Pregnant and lactating women had mixed attitudes to financial incentives for research participation. Some viewed financial incentives as acceptable, with higher remuneration as an appropriate strategy to encourage participation, whereas others viewed financial incentives as potentially coercive, especially in the context of poverty. Some women felt that financial reimbursements did not play a substantial role in women’s decision-making (low confidence) [ 39 , 55 , 65 , 83 , 96 ].

Negative views on renumeration arose from concerns that financial incentives would entice women to enrol multiple times [ 65 ], or make it challenging for them to withdraw from the study [ 39 ].

Quantitative evidence extended this qualitative finding by suggesting that attitudes to financial compensation differed based on levels of education attainment [ 97 ]. In one study, less than 1 in 10 women discussed that financial incentives would increase their likelihood of participation in medication or vaccine-based research [ 75 ], whereas in another, 4 in 10 women agreed that they volunteered to participate due to financial compensation [ 41 ].

Engagement between women and the medical and research ecosystems

Findings 10 and 11 are categorised under this theme, with 34 contributing studies examining factors operating at the intersection of women and the medical and research ecosystems. The factors include women’s reliance on health workers’ clinical opinions to assist decision-making, and the role of therapeutic hope and optimism in women’s decisions to participate and health worker and research staffs’ motivations to administer trials.

Finding 10 : Roles of trust and power in the medical and research ecosystem . Pregnant and lactating women’s willingness to participate in trials was driven by trust, confidence, and faith in medicine and research, and women relied on the opinions of the health workers that they consulted with regarding the efficacy and safety of the intervention. Simultaneously, power imbalances between women and health workers, coupled with women’s therapeutic misconceptions, could lead to coercion in participation. This ethical dilemma was recognised by study investigators, ethics committee members, and women, especially in the context of the dual roles of clinician-researchers; however, power and credibility when combined with good rapport and clear communication generated trust to participate or comfort to decline. While rare, some women had larger concerns about the vested interests of pharmaceutical companies (high confidence) [ 39 , 40 , 42 – 45 , 47 – 49 , 56 – 61 , 65 , 69 , 70 , 72 – 74 , 81 , 82 , 86 , 87 , 89 , 91 , 92 ].

Quantitative data supported the qualitative finding that trust (or lack thereof) in health workers, research teams, and pharmaceutical companies affected participation [ 38 , 51 , 75 , 95 ]. Some women felt pressured to participate by health workers and were disappointed by the lack of an individualised approach to recruitment [ 80 ]. Among decliners of a vaccine trial, some noted that recommendations from a health worker could motivate a change of mind [ 51 ].

Finding 11 : The role of therapeutic hope and optimism . Therapeutic hope and optimism played a critical role for health workers and research staff to administer trials, and for pregnant and lactating women to participate in trials. Prior knowledge about and experience with using the intervention, observation of potential beneficial effects, and trust in health workers shaped feelings of therapeutic hope and optimism. However, for some women, a lack of understanding of the differences between research and clinical care when combined with therapeutic hope led to therapeutic misconceptions and unmet expectations about the personal benefits arising from trial participation (moderate confidence) [ 42 , 45 , 47 , 53 , 65 , 70 , 74 , 81 , 82 , 87 ].

Health workers expressed the importance of women and themselves comprehending the differences between research and clinical care to minimise participation arising from therapeutic misconceptions [ 47 ].

Gender norms and decision-making autonomy

Findings 12 to 14 are categorised under this theme with 24 contributing studies discussing women’s roles as mothers and caregivers, mixed perceptions of women’s autonomous decision-making, and intimate male partner involvement in decision-making.

Finding 12 : Expectations of women’s roles as mothers and caregivers . Pregnant and lactating women’s decisions to participate in clinical trials were often influenced by their strong sense of responsibility towards the health and care of their fetus or infant, themselves, and their families. This sense of responsibility was endorsed and reinforced by familial and societal expectations of what it means to be a good mother (low confidence) [ 60 , 61 , 64 , 91 , 96 ].

For some women, this responsibility to protect their baby translated to not engaging in any actions that might risk jeopardising the baby’s health [ 91 ].

Finding 13 : Role of bodily autonomy in decision-making . Some women, health workers, ethics committee members, and regulators perceived that pregnant women might not be able to make decisions by themselves about trial participation due to fetal involvement, inability to make rational choices during pregnancy, hormones, the stressful context of hospitalisation and financial inducements. However, research staff and some women believed in the right to bodily autonomy to make decisions by themselves despite having discussions with partners, family members, support persons, or health workers. Women viewed other people making decisions regarding their participation as a violation of this right, though some women declined participation due to pressure from family members (moderate confidence) [ 39 , 40 , 43 , 47 , 54 , 56 , 72 , 74 , 81 , 82 , 85 , 87 , 90 , 92 ].

Women also believed that research could be an avenue through which women demanded their rights in the healthcare [ 65 ].

Quantitative evidence supported qualitative findings that women believed in their capability to make decisions regarding trial participation, with some doing so autonomously and others receiving support from family members [ 38 , 83 ].

Finding 14 : Relationship dynamics , gender roles , and norms are key to women’s attitudes to partner involvement and paternal consent . Pregnant women often discussed the benefits and risks of trial participation with their partners—especially in the context of fetal involvement—and their final decision may or may not have been influenced by their partners’ own attitudes. In some settings, pregnant women’s trial participation was contingent on partners’ buy-in, and the formality justified in the context of gender norms and roles. These could be the partner being the household head, to allay men’s suspicions about women’s whereabouts and interactions, and to minimise any misunderstanding related to positive tests or disease status that might cast doubt on women’s fidelity to their husbands (moderate confidence) [ 39 , 40 , 42 , 43 , 47 , 60 , 64 , 65 , 69 , 72 , 74 , 81 , 83 , 85 , 87 , 90 , 91 ].

Partner involvement was not preferred when that partner was abusive or uninvolved, or when a woman was unmarried, or the pregnancy had occurred in the context of rape [ 85 ]. Furthermore, imposing a paternal consent rule in these circumstances was a serious barrier to participation [ 85 ]. When research participation violated gender roles and norms, it sometimes resulted in partner violence, marital breakdown, or rejection of the baby [ 85 ].

Factors affecting clinical trial recruitment

Findings 15 through 21 are categorised under this theme with 41 contributing studies exploring the importance of cultural acceptability and safety of intervention procedures, development of reciprocal relationships between research staff and health workers, the importance of resource availability, trial visibility and emotional orientations, and woman-centred approach to recruitment.

Finding 15 : Developing trusting and reciprocal relationships with the community as part of the research process . Designing and embedding research within communities required engaging with community norms, beliefs, and practices. Some community members expressed how they viewed research negatively in the context of historical and ongoing oppressions that people experience due to colonisation, corruption, extractive practices, and civil and political conflict. Central to the acceptability and cultural safety of the research were investments in developing trusting relationships with community representatives and leaders (moderate confidence) [ 44 , 45 , 60 , 65 , 66 , 74 , 78 , 83 , 90 , 92 ].

This was achieved through dialogue and engagement starting at research conceptualisation, collaborating with community representatives and previous research participants to develop communication and mobilisation strategies, providing accurate information about study procedures, and ensuring alignment of these procedures with community norms, beliefs, and practices.

Finding 16 : Increasing visibility and awareness of the trial . Increasing visibility and awareness of the trial to potential participants, health workers, and community representatives influenced trial recruitment. Recommended strategies included paper and electronic promotional materials, regular physical presence of research staff in the areas where recruitment was taking place, and reminders to health workers about recruitment pathways and trial protocols through trainings (low confidence) [ 54 , 62 , 65 , 74 , 87 ].

Quantitative evidence extended the qualitative finding that women preferred to have information about trials through their health workers [ 67 ].

Finding 17 : Inadequate resources . Inadequate physical infrastructure, time, finances, and insufficient quantity and quality of human resources were barriers for research staff to recruit women for clinical trials. For health workers specifically, heavy workloads made it challenging to incorporate trial recruitment into clinical workflows, and the added burden and sometimes insufficient compensation, contributed to poor morale (low confidence) [ 44 , 54 , 55 , 62 , 87 , 89 ].

In terms of competency of human resources, research staff shared that their recruiting capability was built through practice and working alongside more experienced colleagues [ 54 ]. A key limiting factor in the recruitment of women from non-English speaking backgrounds was the unavailability of interpreters [ 87 ].

Quantitative evidence similarly reported that lack of infrastructure and limited time due to heavy workloads for health workers were barriers to including pregnant women in trials [ 50 , 67 , 88 ].

Finding 18 : Engaging health workers in trials . Research staff perceived the importance of building reciprocal and collaborative relationships with health workers because some acted as gatekeepers. Some health workers, however, were reluctant to engage women in clinical trials due to a lack of knowledge about trial design and the research value, varying levels of acceptability of risk, perceived obligation to protect women, and a lack of trust in the research team. Health workers supported inclusion when trial protocols included close monitoring of risks and when there was clinical equipoise alongside therapeutic hope in the trial intervention. These factors were informed by their clinical knowledge, previous clinical experiences using the intervention, and observed outcomes in the current trial (high confidence) [ 47 , 53 – 55 , 60 , 62 , 64 , 65 , 87 , 89 – 91 ].

Quantitative evidence supported qualitative findings that knowledge of the relevance, feasibility, and ethical obligations to include pregnant and lactating women in trials, perceptions that pregnant women were a vulnerable population, lack of interest in trials, and preferences for noninvasive treatment were factors influencing whether health workers encouraged pregnant women’s clinical trial participation [ 50 , 52 , 67 , 88 , 94 , 95 ].

Finding 19 : Research staff’s emotional orientations towards clinical trials . Having a sense of trial ownership, supportive teamwork, a shared sense of team achievement and motivation to achieve recruitment targets could support successful trial recruitment. However, feeling pressured by the recruitment process, seeing it as a procedural activity and needing to implement complex study designs impacted research staffs’ ability to recruit women, leading to frustration and lower enthusiasm (low confidence) [ 53 , 54 , 62 ].

Finding 20 : Women-centred approach encourages participation . Women valued an individualised, humanised, and transparent approach to communication, and adequate time during trial recruitment to discuss details and concerns related to the trial. These helped ensure they had sufficient capacity and opportunity to make informed decisions. Similarly, research staff found that approaching potential participants at the “right time” and in an appropriate manner by considering their physical and mental state, providing adequate information and engaging in discussions increased recruitment success (moderate confidence) [ 39 , 40 , 54 , 56 , 62 , 66 , 69 , 70 , 72 , 74 , 86 , 87 , 92 ].

To support an individualised recruitment approach, research staff reviewed obstetric information from women’s charts [ 54 , 86 ] and had discussions with health workers [ 86 ] to tailor the recruitment information to women’s personal situations. They also discussed using intuition to determine when and whom to approach for trial participation [ 54 ], considering the extent to which women looked sick or unwell at the time of recruitment [ 86 ].

Quantitative data supported this qualitative finding of women noting the significance of having detailed and well-explained trial information, including about risks and benefits, and adequate time to make decisions regarding participation [ 80 , 95 ]. Some women expressed disappointment when they felt they had been ill-informed about study procedures by research staff [ 80 ].

Finding 21 : Recruitment for intrapartum research . Pain, intensity, and duration of labour motivated pregnant women to participate in intrapartum clinical trials. However, women, their partners, and research staff recognised the challenges in ensure women make informed decisions during this sensitive time, as decisions had to be made quickly, and partners were reluctant to make decisions on women’s behalf, even during emergencies, due to fears of negative outcomes. To optimise women making informed decisions, research staff provided information clearly and succinctly during the intrapartum period and tried to offer adequate time for decision-making. Most women recommended having trial information provided in the antenatal period, and revisiting trial details, including having a de-briefing about one’s own experience, prior to discharge (moderate confidence) [ 43 , 49 , 56 , 59 , 61 , 62 , 81 , 82 , 86 , 91 ].

Quantitative data extended this qualitative finding with most ethics committee members considering consent in-labour as ethical. Factors that ethics committee members considered when approving labour trials, included the level of risk involved and women’s ability to provide informed consent [ 76 ]. Most ethics committee members also supported the involvement of partners in the consent process [ 76 ]. Aligned with the qualitative data, women expressed a preference to be approached for a labour trial earlier to have adequate time for discussion and an informed decision [ 79 , 80 ].

Upstream factors affecting the research ecosystem

Findings 22 to 24 are categorised under this theme with 13 studies discussing factors operating at the level of study investigators, ethics committees, and funders. The factors include study investigators’ personal and professional motivations to pursue research with pregnant women, complexities in obtaining ethical approval, and limited interest of funders to support clinical trials with pregnant and lactating women.

Finding 22 : Factors affecting motivation of study investigators . The underlying factors that motivated many study investigators to conduct research with pregnant women were ethical responsibility, passion towards equity, and dedication to improving women’s health status and care, and filling scientific gaps. Additionally, lived experience of being pregnant, having mentors in this area in early careers, and previous research experiences with pregnant women contributed to study investigators’ motivations. However, concerns about risks of teratogenicity demotivated some investigators (moderate confidence) [ 42 , 43 , 66 , 78 , 89 , 91 ].

Finding 23 : Challenges in gaining ethical approvals for trials with pregnant women . While some regulators, ethics committee members, and study investigators strongly support inclusion of pregnant women in clinical trials, most stakeholders start from a presumption of minimal risk to the fetus. This results in women’s exclusion, especially in the context of poor public stewardship, ambiguous guidelines, insufficient data on intervention safety, complexities and subjectivities in risk assessment, poor agreement on appropriate trial design, time-consuming ethical processes, and concerns about reputation (moderate confidence) [ 42 , 43 , 66 , 78 , 82 , 89 – 91 ].

Study investigators and ethics committee members reported that these challenges could be overcome through shared institutional commitment to pregnant women’s inclusion, close collaboration between investigators and ethics committee members from protocol inception, mutual understanding about each other roles, responsibilities, and intentions, development and implementation of practical guidance for consistency in regulatory interpretation and risk assessment, safety monitoring during implementation, and safeguards for injury compensation [ 42 , 66 , 78 , 89 , 91 ].

Quantitative evidence supported qualitative findings that obtaining regulatory approval for clinical trials that include pregnant women was challenging [ 88 ] due to ethics committees’ preference for observational studies over trials [ 93 ], and varied opinions on the inclusion of pregnant women and what constituted minimal risk [ 76 , 93 ]. Most ethics committee members were also aware that they did not have adequate policy or guidance to inform their decisions to ensure equitable subject selection [ 76 , 93 ].

Finding 24 : Role of funders . Limited interest of public and private funders and pharmaceutical companies to financially invest in trials due to the ethical complexities, potential for adverse events, liability, and possibility of political fallout was a barrier to conduct trials with pregnant and lactating women. When funding was available, funders’ requests might facilitate the inclusion of pregnant women or create ethical challenges in conducting trials (low confidence) [ 54 , 62 , 66 , 78 ].

Mapping review findings to TDF, COM-B, and potential implementation strategies

Table 3 presents the mapping of review findings to the applicable TDF [ 24 ] and COM-B model domains [ 25 ], and the BCW intervention types to inform proposed strategies that address these factors. The strategies that we have identified are designed to provide a theoretically informed guide to the types of actions that can be taken to address barriers at various levels associated with different stakeholder groups. Which actions are appropriate for a given context should therefore be discussed, prioritised, and adapted to a particular setting.

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Some of these strategies may already be in place as part of ethical conduct for trial recruitment, for example, sharing information transparently with potential participants about safety, risks, benefits, and side effects of the trial intervention (BCW intervention type: education). Given pregnant and lactating women’s concerns around risks of the intervention, such strategies can be enhanced through personalised discussions about how the intervention relates to women’s personal and clinical circumstances, for example, using a decision-aid tool (BCW intervention type: enablement). Developing clear and context-specific ways to explain study design features in plain language, and involvement of trusted sources (such as health workers), to communicate trial information can aid the decision-making process. Engaging with patient advocates and women’s groups and conducting formative research with potential participants to receive feedback on acceptability of trial components can streamline trial procedures and enhance acceptability and contextual alignment. Considerations should include how societal and gender norms, and gender roles impact various aspects of participation.

Given potential concerns among health workers regarding safety of interventions during pregnancy, providing access to credible resources on the risks, benefits and potential side-effects of the product being trialled, and elaborating on the trial rationale, potential benefits, and where the trial fits into existing evidence can help address fear and uncertainty regarding intervention safety (BCW intervention type: education, training).

At the health systems-level, strategies include creating a research-friendly environment within health facilities. In addition to promoting buy-in from hospital leadership, this would include infrastructural enhancements such as creating research spaces within health facilities (e.g., offices, meeting rooms, labs, data storage, research information systems), and hiring and training research support staff (e.g., research midwives), among other aspects.

Strategies to promote alignment between study investigators and ethics committee members include: educating ethics committee members about the health consequences of excluding pregnant women from research, and useful approaches for monitoring and managing risks associated with trial inclusion (BCW intervention type: education); developing a shared institutional commitment to inclusion of pregnant women research as the standard, and developing a common understanding of regulatory guidelines and associated documentation such as standard operating procedures, worksheets, and checklists to facilitate consistency in guideline application by institutional ethics committees and researchers.

This review provides a comprehensive overview of the range of factors affecting the participation of pregnant and lactating women in clinical trials across the research ecosystem. At the upstream levels, we identified barriers arising from limited interest of funders to invest in clinical trials with pregnant and lactating women, and reluctance of ethics committees to approve protocols due to potential for risks, particularly to fetal health. Factors at the interface between health systems and communities included developing trusting and reciprocal relationships among community members, research staff, and healthcare workers, and taking a woman-centred approach to recruitment. For women, determining the risk-benefit ratio of participation, trust (or lack thereof) in medicine and research, the potential to access high-quality care through trial participation, and altruistic motivations were key factors. Incorporating a gender lens to the data, we found that participation was impacted by gender relations of power sustained by gender norms, gender role expectations of women as mothers and caregivers, and mixed opinions regarding bodily and decisional autonomy during pregnancy.

Our findings on factors influencing pregnant women’s decisions regarding participation are aligned with those identified by Van der Zande and colleagues [ 98 ] who found that the potential for personal benefits alongside altruistic motivations were crucial drivers, while participation burdens, risks, and mistrust in research were key barriers to participation. Some of these findings, such as the role of altruism and potential for personal benefit, concerns about randomisation and other study design features, burdensome trial procedures, fears associated with taking an experimental therapy, and health worker attitudes towards trials are also consistent with the broader literature on factors associated with trial participation [ 99 – 101 ]. Across the findings, women and research staff emphasised the importance of a woman-centred approach to trial recruitment, with careful consideration of women’s individual clinical and personal circumstances, transparency in information, and support for informed and unhurried decision-making. These aspects were found to be challenging to navigate in intrapartum trials, given the timing of recruitment coinciding with birth, often in the context of impending or ongoing complications. For example, a recent analysis of uterotonic trials for prevention of postpartum haemorrhage found considerable variability between trials in the timing of informed consent—most obtained consent during labour, with a minority in the antenatal period [ 102 ]. Our findings suggest that women prefer consent in the antenatal period to optimise informed and unhurried decision-making. However, there are ethical concerns about seeking antenatal consent as it may exclude participation of women who do not regularly access antenatal care [ 102 ]. Indeed, the informed consent process in intrapartum trials is an issue of current debate and ethical interest [ 103 ], and more empirical work is needed to understand women’s preferences and needs to optimise informed decision-making.

We found that healthcare workers’ engagement was crucial in recruiting women as they play a vital role in bridging communication between potential participants and research staff. Many studies reported that women relied on health workers advice in making decisions about participation. Health workers in turn encouraged or discouraged participation based on their own attitudes towards clinical research in pregnancy and knowledge about or personal experience using the therapy under investigation. Given the roles of trust and power in women’s decision-making processes, it is important to promote transparent and open communication between women and health workers regarding trials, and their associated risks and benefits [ 104 , 105 ]. It is also important to clarify differences between clinical trial and regular clinical care to minimise the potential for therapeutic misconceptions, the consequences of which could lead to the eroding of trust in the medical system, affecting future health-seeking behaviour.

The complicated issue of autonomy in decision-making during pregnancy was raised by multiple stakeholders. Many women discussed trial participation with their partners and other family members but considered the final decision to be their own. In some settings, usually in the context of rigid gender norms, women required partners’ permission to participate; if violated, this could result in the threat of violence or marital discord. Separately, the imposition of a paternal consent requirement was viewed as a significant barrier for women who were in unstable relationships, unmarried, or wanted to exercise fully autonomous decision-making. Widmer and colleagues [ 102 ] argue that it is the role of research staff to guarantee and protect women’s autonomy. We found that women’s decisional autonomy was impacted by intimate partner relationship dynamics, and wider sociocultural and gender norms that required nuanced understandings of the context and multistakeholder engagement to create an enabling environment for women to exercise choice.

We also identified barriers experienced by researchers, ethics committees, and funders of clinical trials. Study investigators had trouble obtaining ethical approval as ethics committees have mixed perspectives on the inclusion of pregnant and lactating women in trials, particularly in the absence of clear guidelines. In line with previously reported upstream barriers [ 16 , 23 ], limited interest in funding clinical trials with pregnant and lactating women due to potential risks, high liability, and reputational consequences also inhibits the implementation of trials. These findings demonstrate a need to develop holistic strategies addressing barriers experienced by stakeholders operating at the upstream levels of clinical research.

The TDF and COM-B mapping in our review (Table 3) can be used by study investigators, research staff, health workers, ethics committees, and funders to inform the development of implementation strategies to address barriers to pregnant and lactating women’s participation in clinical trials. Formative research to identify specific barriers and facilitators in specific settings and contexts is a recommended starting point before developing appropriate strategies.

A limitation is that we did not include grey literature, which may have expanded the types of evidence and/or contexts of the review. However, our search strategies yielded high coverage of published literature. The studies included in the review had good coverage of countries from the African region, but sparse representation of countries from Latin America, and no representation of countries in the Eastern Mediterranean or South-East Asian regions. A growing number of trials addressing maternal and perinatal health are being implemented in these settings [ 106 ], calling for significantly greater focus in formative and process evaluation research with pregnant and lactating women and people, family members, health workers, local researchers, and ethics committee members to understand context-specific motivations for and concerns regarding conduct of and participation in research during pregnancy and lactation. The AIM-Gender project [ 107 ] aims to address this limitation through qualitative research on the topic in India and Nigeria—2 countries that together account for 37% of global maternal deaths [ 13 ]. Future work must also consider inclusion of pregnancy-capable transgender and nonbinary people, as knowledge gaps regarding factors affecting their participation in pregnancy and lactation clinical research are particularly pronounced. We also draw attention to 2 relevant reviews on factors affecting participation of racial and ethnically marginalised populations in pregnancy and lactation research, a related topic that was beyond the scope of this review [ 108 , 109 ].

Our review builds on previous work [ 98 ] by examining the full range of factors and perspectives of multiple stakeholders operating at the upstream and downstream levels of the research ecosystem. We optimised the available data by including qualitative, quantitative, and mixed-methods primary research. We applied the GRADE-CERQual approach to assess confidence in each finding, i.e., the extent to which the finding adequately represented the phenomenon of interest [ 32 , 33 ]. These assessments have important practical implications for increasing the applicability and usability of these findings by stakeholders seeking to enhance research and development in maternal health. This review additionally integrates the use of behavioural frameworks [ 24 , 25 ] to propose a theory-informed set of behaviour change interventions to address factors affecting clinical trial participation among pregnant and lactating women.

Supporting information

S1 appendix. preferred reporting items for systematic reviews and meta-analyses (prisma) reporting checklist..

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S2 Appendix. Enhancing transparency in reporting the synthesis of qualitative research (ENTREQ) reporting checklist.

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S3 Appendix. Search strategies.

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S4 Appendix. GRADE-CERQual evidence profile.

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S5 Appendix. Summaries of quantitative findings.

https://doi.org/10.1371/journal.pmed.1004405.s005

S6 Appendix. Characteristics of included papers.

https://doi.org/10.1371/journal.pmed.1004405.s006

S7 Appendix. Critical appraisal.

https://doi.org/10.1371/journal.pmed.1004405.s007

Acknowledgments

We are grateful to Alessandra Fleurent at Concept Foundation for her assistance with verifying the accuracy of the translated French paper included in this review.

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• Systematic Review
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• Published: 24 May 2024

Epidemiologic profile of inflammatory bowel disease in Eastern Mediterranean Region (EMRO) countries: a systematic review and meta-analysis

• Zahra Momayez Sanat 1 , 2   na1 ,
• Homayoon Vahedi 2   na1 ,
• Reza Malekzadeh 2 &
• Zeinab Fanni 1  

BMC Public Health volume  24 , Article number:  1395 ( 2024 ) Cite this article

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Inflammatory bowel disease (IBD) consists of two main types: Crohn’s disease (CD) and ulcerative colitis (UC). The epidemiology of IBD patients has not been comprehensively studied in EMRO countries; therefore, we conducted this meta-analysis to study the epidemiology of this disease in these countries.

We searched four international databases, namely Scopus, Web of Knowledge (ISI), Medline/PubMed, and ProQuest, from inception up to the end of May 2023. The Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guideline was used to carry out this systematic review and meta-analysis investigation. Using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist, the quality of the selected papers was assessed.

Based on the results of this study, the incidence of UC in EMRO countries was 2.65 per 100,000 (95% CI: 1.39–3.90), and the incidence of CD was 1.16 per 100,000 (95% CI: 0.73–1.59). The most commonly involved intestinal segment in CD was the terminal ileum (44.7%, 95% CI: 34.7–55.2), followed by the ileum (29.8%, 95% CI: 22.2–38.6), and colon (18.7%, 95% CI: 10.8–30.4). However, in UC patients, extensive colitis was the most common finding (32.3%, 95% CI: 26.4–38.8), followed by proctosigmoiditis (27.9%, 95% CI: 21.1–35.8), left-sided colitis (27.4%, 95% CI: 22.7–32.7), and proctitis (22.6%, 95% CI: 17.5–28.5).

As a result, we were able to establish the traits of IBD patients in EMRO nations. UC patients had a higher incidence than CD patients. The most common regions of involvement in CD and UC patients, respectively, were the colon and pancolitis. Compared to UC patients, CD patients had a higher history of appendectomy.

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Introduction

Inflammatory bowel disease (IBD) has two main subtypes contains ulcerative colitis (UC) and Crohn’s disease (CD). This disease is becoming a global concern with increasing prevalence and incidence worldwide [ 1 ]. Like other Gastrointestinal diseases, IBD has imposed considerable burden globally along with significant population suffering from this condition [ 2 , 3 ].

Almost 6.8 million cases of IBD were recognized in 2017 globally with the prevalence rate and death rate of 84.3 and 0.51 respectively [ 4 ]. It is estimated 2.5 million people in US and 1 million people in Europe suffering from IBD [ 2 ]. According to Global Burden of Disease (GBD) statements, North America and Caribbean were the countries with the highest and lowest prevalence of IBD respectively [ 4 ]. A study in the UK revealed that the prevalence of IBD has raised 33.8% between 2006 and 2016 [ 5 ]. A time-trend analysis has shown that 75% of CD surveys and 60% of UC studies demonstrated a statistically significant growing incidence [ 6 ]. In addition, in a study conducted by Caviglia et al., the incidence of IBD was increased from 200 per 100,000 in 2006 to 321.2 per 100,000 in 2021 presenting an increased rate of 46 percent [ 7 ].

IBD may occur as a result of the uncontrolled immune system response, which can originate from genetic or environmental determinants [ 8 ]. Environmental factors and hereditary susceptibility are the most important cause of the IBD and its course. These two factors arouse the immune system to act over­active and impaired [ 9 , 10 ]. Smoking, low physical activity, hygiene status, surgeries, and antibiotic consumption are some environmental factors associated with IBD [ 11 ]. Based on the epidemiological models, environmental factors can affect individuals based on a person’s genetic characteristics, including age, gender, personality, and physical state, causing IBD susceptibility [ 10 , 12 ].

Eastern Mediterranean Regional Office (EMRO) includes 22 countries which is one of the World Health Organization regional classifications [ 13 ]. The epidemiology of IBD was studies in the EMRO countries separately but a comprehensive study to assess IBD epidemiology was lacking hence we performed a comprehensive meta-analysis study to investigated epidemiological status of IBD in this region.

Materials and methods

The goal of the present research project is to determine the epidemiology of IBD in the EMRO nations by a systematic review and meta-analysis. The Systematic Review and Meta-analysis (PRISMA) protocol was used for executing the study [ 14 ].

Search strategy

We searched four international databases, namely Scopus, Web of Knowledge (ISI), Medline/PubMed, and ProQuest, from inception up to the end of May 2023. The search strategy and keywords are presented in Table 1 .

Inclusion and exclusion criteria

Case–control, cross-sectional, and cohort studies assessing IBD, CD, or UC individuals in the EMRO countries' population with the following criteria were eligible to be included in our study: IBD diagnosis confirmed by clinical characteristics of the individuals and endoscopy or colonoscopy confirmation. At least one of the following outcomes reported: The smoking rate in patients, family history, sites of involvement, risk factors of patients, incidence rate. Studies in English. Available full text. Studies which didn’t fulfill the inclusion criteria were excluded. Two researchers independently selected the studies, and any disagreements were resolved by the third researcher.

Quality assessment

Using The Joanna Briggs Institute (JBI) Critical Appraisal Checklist, two independent researchers conducted the quality assessment of included cross-sectional, case–control, and cohort articles. Any disagreements were finalized by face-to-face consultation and the contribution of a third researcher. The JBI checklist scores of included studies are shown in Table 2 .

Data extraction

Included papers were carefully studied by two researchers. The following outcomes were extracted: Name of the first author, year of publication, region of study, duration of study, sample size of study, mean age of participants. The features of included studies are shown in Table 2 .

Statistical analysis

Version 2 of the statistical software for comprehensive meta-analysis (CMA) was employed for this investigation. When three trials were available for a particular outcome, the data were pooled. To ascertain the amount of result heterogeneity, Cochran's test (where the significance level was deemed less than 0.1) and I2 statistics (where the significant level was deemed greater than 50%) were obtained. When heterogeneity was significant, the random-effects model was utilized; otherwise, the fixed-effects model was used.

A total of 1671 studies were found in the initial search. After omitting the duplications, 1485 studies underwent screening. Two researchers independently screened the title, abstract, and, when necessary, the full text of the articles. A total of 1416 articles were deleted, and 69 papers underwent full-text revision. Finally, 34 studies that met our inclusion criteria were selected for our study (Fig. 1 ).

Flowchart of the included eligible studies in systematic review

Description of studies

The basic characteristics of the included studies are presented in Table 2 [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 ]. Based on the geographical location of the 34 included studies, 14 studies were conducted in Iran, 9 in Saudi Arabia, 3 in Kuwait, 1 in Qatar, 1 in Bahrain, 1 in the UAE, 1 in Lebanon, 1 in Oman, 1 in Pakistan, 1 in Tunisia, and 1 in Egypt. The summary characteristics of the studies are shown in Table 2 .

Incidence of IBD patients

According to the results of the meta-analysis, the incidence of UC in EMRO countries was 2.6 per 100,000 (95% CI: 1.3–3.9), and the incidence of CD was 1.16 per 100,000 (95% CI: 0.7–1.5) (Fig. 2 A and B).

A Incidence of UC in EMRO countries, B Incidence of UC in EMRO countries, C Prevalence of Ulcerative Colitis among men, D Prevalence of Crohn Disease among men, E Mean Age at diagnosis for Ulcerative Colitis, F Mean Age at diagnosis for Crohn Disease, G Terminal ileum involvement in CD, H Ileal involvement in CD, I Colon involvement in CD

Prevalence of IBD among men and women

Based on our meta-analysis, 46% of Ulcerative Colitis diagnoses in EMRO are from men. However, this number is 55% for Crohn Disease (Fig. 2 C and D).

Age at diagnosis

The mean age at diagnosis for Ulcerative Colitis is 32.7 (95% CI: 30.3 to 35.1). In addition, the mean age at diagnosis is 30.9 (95% CI: 27.1 to 34.7) for Crohn Disease (Fig. 2 E and F).

Sites of involvement

The distribution of patients with Crohn's disease (CD) and ulcerative colitis (UC) based on the area of intestinal involvement is depicted in Fig. 2 G to I and Fig. 3 A to D. In CD patients, the terminal ileum was the most frequently affected intestinal segment (44.7%, 95% CI: 34.7–55.2), followed by the ileum (29.8%, 95% CI: 22.2–38.6), and the colon (18.7%, 95% CI: 10.8–30.4). Regarding UC patients, extensive colitis was the most prevalent finding (32.3%, 95% CI: 26.4–38.8), followed by proctosigmoiditis (27.9%, 95% CI: 21.1–35.8), left-sided colitis (27.4%, 95% CI: 22.7–32.7), and proctitis (22.6%, 95% CI: 17.5–28.5).

A Extensive colitis involvement in UC, B Proctosigmoiditis involvement in UC, C Left sided colitis involvement in UC patients, D Proctitis involvement in UC, E Prevalence of smoking in CD patients, F Prevalence of smoking in UC patients, G Prevalence of positive family history in UC patients, H Prevalence of positive family history in CD patients, I (Upper figure): History of appendectomy in CD patients, J (Lower figure): History of appendectomy in UC patients

The prevalence of smoking in CD patients (12.2%, 95% CI: 8.2–17.7) was higher than in UC patients (11.0%, 95% CI: 7.8–15.4) (Fig. 3 E and F).

Family history

The prevalence of a positive family history in UC and CD was 11.7% (95% CI: 9.2–14.7) and 11.3% (95% CI: 8.6–14.6), respectively (Fig. 3 G and H).

History of appendectomy

The history of appendectomy was higher in CD patients (15.5%, 95% CI: 12.9–18.5) compared to UC (4.8%, 95% CI: 2.9–8) (Fig. 3 I and J).

Result of heterogeneity assessment

As we used random effect model for our main analyses, we presented the detailed information about possible heterogeneity for each outcome in the Table 3 . We also evaluated the distribution of true effect using prediction interval (See supplementary material).

In this study we surveyed the epidemiology of IBD in the EMRO countries. We assessed the incidence of IBD, sites of involvement in GI tract and risk factors.

According to the findings of our study, the incidence rates for UC and CD in the EMRO region were 2.65 and 1.16, respectively. Different nations have distinct rates of incidence and prevalence for IBD and its subtypes. The highest frequency of IBD was found in Europe and North America, according to a comprehensive review and meta-analysis by Ng et al. The incidence of IBD in North America and Europe appeared to be steady or declining based on the findings of this study [ 1 ]. The annual incidence rate of CD was reported to be 0.5 per 100,000 in Japan and 20.2 per 100,000 in Canada. In Japan, there were 5.8 UC patients per 100,000 people, compared to 319 UC patients per 100,000 people in Canada [ 49 , 50 ]. The incidence and prevalence of UC were reported to be 0.3 and 7.6 per 100,000 people in South Korea, respectively [ 51 ]. In the United States, prior research places the incidence of UC and CD, respectively, at 10.1 to 12 and 6.3 to 7.9 per 100,000 people [ 52 ]. By comparing the findings of our study with those of other studies, we have come to the conclusion that the incidence of UC and CD is higher in the EMRO region than in eastern nations like Japan and South Korea, and lower than in eastern nations. We believe this variation is caused by varying genetic vulnerability, environmental circumstances, and lifestyle choices.

With regard to the findings of our study, CD patients had slightly higher incident rate of smoking (12.2%) than UC patients (11%). In a cohort study conducted by Lunney et al., CD patients had a greater prevalence of smoking than UC patients [ 53 ]. Smoking is a difficult component in IBD. Even though it increases the risk of CD, patients with UC benefited from it [ 54 , 55 , 56 ]. Smoking’s impact on IBD patients was shown to follow a dosage response pattern [ 45 ]. Smoking’s effects on IBD patients can be influenced by genetic and ethnic factors [ 57 , 58 ].

Positive family history is one of the major risk factors for IBD patients [ 59 ]. A person’s genetic and environmental susceptibilities that they inherited from their parents are reflected in their positive family history in IBD patients [ 60 ]. First degree relatives and monozygotic twins have a higher incidence of IBD, which supports the hereditary component to IBD [ 61 ]. In this study, we demonstrated that UC (11.7%) and CD (11.3%) have slightly higher positive family history rates. Family members of UC patients were much more numerous than CD patients in a meta-analysis research by Childres et al. [ 62 ]. Asian, African American, Hispanic, and White populations all had higher rates of positive family history, ranging from 26 to 33%, 9% to 18%, 9% to 16%, and 5.9%, respectively [ 63 , 64 , 65 , 66 , 67 ].

Based to the results obtained in our study, CD patients were more likely to undergo an appendectomy (15.5%) than UC patients (4.8%). Appendectomy's impact on the course of IBD is debatable. According to research by Andersson et al., appendectomy for inflammatory diseases such appendicitis reduces the incidence of UC [ 68 ]. Higher risk of CD and UC after appendectomy was found in a different cohort research by Chung et al. [ 69 ]. Five years after surgery, an appendectomy significantly reduced the risk of UC in another trial [ 70 ].

CD can affect any part of the gastrointestinal tract in a discontinuous manner, whereas UC is limited to the rectum and colon [ 71 ]. In this study, we observed that the most common pattern of GI tract involvement in UC patients is extensive colitis (32.3%), followed by proctosigmoiditis (27.9%). For CD patients, the most frequent pattern of involvement was coloileal, followed by the ileum. Previous studies have reported that proctitis and proctosigmoiditis occur in 46% of UC patients, while left-sided colitis and extensive colitis affect 17% and 37% of UC individuals, respectively [ 72 ].

Our research had some limitations. First, some of the EMRO region's nations lacked the appropriate literature for our analysis. Second, we do not have adequate data to conduct subgroup analyses based on gender, age, and marital status. Third, we do not have enough information about how many years each patient with IBD has had the disease.

Conclusions

In conclusion, our study identified the characteristics of patients with inflammatory bowel disease (IBD) in EMRO countries. We observed a higher incidence of ulcerative colitis (UC) compared to Crohn's disease (CD) patients. Coloileal involvement was the most common site of disease in CD patients, whereas extensive colitis was the predominant pattern in UC patients. Additionally, a history of appendectomy was more frequent among CD patients than UC patients.

Availability of data and materials

No datasets were generated or analysed during the current study.

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Sanat, Z.M., Vahedi, H., Malekzadeh, R. et al. Epidemiologic profile of inflammatory bowel disease in Eastern Mediterranean Region (EMRO) countries: a systematic review and meta-analysis. BMC Public Health 24 , 1395 (2024). https://doi.org/10.1186/s12889-024-18816-z

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• Systematic Review
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• Published: 24 May 2024

Turnover intention and its associated factors among nurses in Ethiopia: a systematic review and meta-analysis

• Eshetu Elfios 1 ,
• Israel Asale 1 ,
• Merid Merkine 1 ,
• Temesgen Geta 1 ,
• Kidist Ashager 1 ,
• Getachew Nigussie 1 ,
• Ayele Agena 1 ,
• Bizuayehu Atinafu 1 ,
• Eskindir Israel 2 &
• Teketel Tesfaye 3  

BMC Health Services Research volume  24 , Article number:  662 ( 2024 ) Cite this article

303 Accesses

Metrics details

Nurses turnover intention, representing the extent to which nurses express a desire to leave their current positions, is a critical global public health challenge. This issue significantly affects the healthcare workforce, contributing to disruptions in healthcare delivery and organizational stability. In Ethiopia, a country facing its own unique set of healthcare challenges, understanding and mitigating nursing turnover are of paramount importance. Hence, the objectives of this systematic review and meta-analysis were to determine the pooled proportion ofturnover intention among nurses and to identify factors associated to it in Ethiopia.

A comprehensive search carried out for studies with full document and written in English language through an electronic web-based search strategy from databases including PubMed, CINAHL, Cochrane Library, Embase, Google Scholar and Ethiopian University Repository online. Checklist from the Joanna Briggs Institute (JBI) was used to assess the studies’ quality. STATA version 17 software was used for statistical analyses. Meta-analysis was done using a random-effects method. Heterogeneity between the primary studies was assessed by Cochran Q and I-square tests. Subgroup and sensitivity analyses were carried out to clarify the source of heterogeneity.

This systematic review and meta-analysis incorporated 8 articles, involving 3033 nurses in the analysis. The pooled proportion of turnover intention among nurses in Ethiopia was 53.35% (95% CI (41.64, 65.05%)), with significant heterogeneity between studies (I 2  = 97.9, P  = 0.001). Significant association of turnover intention among nurses was found with autonomous decision-making (OR: 0.28, CI: 0.14, 0.70) and promotion/development (OR: 0.67, C.I: 0.46, 0.89).

Conclusion and recommendation

Our meta-analysis on turnover intention among Ethiopian nurses highlights a significant challenge, with a pooled proportion of 53.35%. Regional variations, such as the highest turnover in Addis Ababa and the lowest in Sidama, underscore the need for tailored interventions. The findings reveal a strong link between turnover intention and factors like autonomous decision-making and promotion/development. Recommendations for stakeholders and concerned bodies involve formulating targeted retention strategies, addressing regional variations, collaborating for nurse welfare advocacy, prioritizing career advancement, reviewing policies for nurse retention improvement.

Peer Review reports

Turnover intention pertaining to employment, often referred to as the intention to leave, is characterized by an employee’s contemplation of voluntarily transitioning to a different job or company [ 1 ]. Nurse turnover intention, representing the extent to which nurses express a desire to leave their current positions, is a critical global public health challenge. This issue significantly affects the healthcare workforce, contributing to disruptions in healthcare delivery and organizational stability [ 2 ].

The global shortage of healthcare professionals, including nurses, is an ongoing challenge that significantly impacts the capacity of healthcare systems to provide quality services [ 3 ]. Nurses, as frontline healthcare providers, play a central role in patient care, making their retention crucial for maintaining the functionality and effectiveness of healthcare delivery. However, the phenomenon of turnover intention, reflecting a nurse’s contemplation of leaving their profession, poses a serious threat to workforce stability [ 4 ].

Studies conducted globally shows that high turnover rates among nurses in several regions, with notable figures reported in Alexandria (68%), China (63.88%), and Jordan (60.9%) [ 5 , 6 , 7 ]. In contrast, Israel has a remarkably low turnover rate of9% [ 8 ], while Brazil reports 21.1% [ 9 ], and Saudi hospitals26% [ 10 ]. These diverse turnover rates highlight the global nature of the nurse turnover phenomenon, indicating varying degrees of workforce mobility in different regions.

The magnitude and severity of turnover intention among nurses worldwide underscore the urgency of addressing this issue. High turnover rates not only disrupt healthcare services but also result in a loss of valuable skills and expertise within the nursing workforce. This, in turn, compromises the continuity and quality of patient care, with potential implications for patient outcomes and overall health service delivery [ 11 ]. Extensive research conducted worldwide has identified a range of factors contributing to turnover intention among nurses [ 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. These factors encompass both individual and organizational aspects, such as high workload, inadequate support, limited career advancement opportunities, job satisfaction, conflict, payment or reward, burnout sense of belongingness to their work environment. The complex interplay of these factors makes addressing turnover intention a multifaceted challenge that requires targeted interventions.

In Ethiopia, a country facing its own unique set of healthcare challenges, understanding and mitigating nursing turnover are of paramount importance. The healthcare system in Ethiopia grapples with issues like resource constraints, infrastructural limitations, and disparities in healthcare access [ 18 ]. Consequently, the factors influencing nursing turnover in Ethiopia may differ from those in other regions. Previous studies conducted in the Ethiopian context have started to unravel some of these factors, emphasizing the need for a more comprehensive examination [ 18 , 19 ].

Although many cross-sectional studies have been conducted on turnover intention among nurses in Ethiopia, the results exhibit variations. The reported turnover intention rates range from a minimum of 30.6% to a maximum of 80.6%. In light of these disparities, this systematic review and meta-analysis was undertaken to ascertain the aggregated prevalence of turnover intention among nurses in Ethiopia. By systematically analyzing findings from various studies, we aimed to provide a nuanced understanding of the factors influencing turnover intention specific to the Ethiopian healthcare context. Therefore, this systematic review and meta-analysis aimed to answer the following research questions.

What is the pooled prevalence of turnover intention among nurses in Ethiopia?

What are the factors associated with turnover intention among nurses in Ethiopia?

The primary objective of this review was to assess the pooled proportion of turnover intention among nurses in Ethiopia. The secondary objective was identifying the factors associated to turnover intention among nurses in Ethiopia.

Study design and search strategy

A comprehensive systematic review and meta-analysis was conducted, examining observational studies on turnover intention among nurses in Ethiopia. The procedure for this systematic review and meta-analysis was developed in accordance with the Preferred Reporting Items for Systematic review and Meta-analysis Protocols (PRISMA-P) statement [ 20 ]. PRISMA-2015 statement was used to report the findings [ 21 , 22 ]. This systematic review and meta-analysis were registered on PROSPERO with the registration number of CRD42024499119.

We conducted systematic and an extensive search across multiple databases, including PubMed, CINAHL, Cochrane Library, Embase, Google Scholar and Ethiopian University Repository online to identify studies reporting turnover intention among nurses in Ethiopia. We reviewed the database available at http://www.library.ucsf.edu and the Cochrane Library to ensure that the intended task had not been previously undertaken, preventing any duplication. Furthermore, we screened the reference lists to retrieve relevant articles. The process involved utilizing EndNote (version X8) software for downloading, organizing, reviewing, and citing articles. Additionally, a manual search for cross-references was performed to discover any relevant studies not captured through the initial database search. The search employed a comprehensive set of the following search terms:“prevalence”, “turnover intention”, “intention to leave”, “attrition”, “employee attrition”, “nursing staff turnover”, “Ethiopian nurses”, “nurses”, and “Ethiopia”. These terms were combined using Boolean operators (AND, OR) to conduct a thorough and systematic search across the specified databases.

Eligibility criteria

Inclusion criteria.

The established inclusion criteria for this meta-analysis and systematic review are as follows to guide the selection of articles for inclusion in this review.

Population: Nurses working in Ethiopia.

Study period: studies conducted or published until 23November 2023.

Study design: All observational study designs, such as cross-sectional, longitudinal, and cohort studies, were considered.

Setting: Only studies conducted in Ethiopia were included.

Outcome; turnover intention.

Study: All studies, whether published or unpublished, in the form of journal articles, master’s theses, and dissertations, were included up to the final date of data analysis.

Language: This study exclusively considered studies in the English language.

Exclusion criteria

Excluded were studies lacking full text or Studies with a Newcastle–Ottawa Quality Assessment Scale (NOS) score of 6 or less. Studies failing to provide information on turnover intention among nurses or studies for which necessary details could not be obtained were excluded. Three authors (E.E., T.G., K.A) independently assessed the eligibility of retrieved studies, other two authors (E.I & M.M) input sought for consensus on potential in- or exclusion.

Quality assessment and data extraction

Two authors (E.E, A.A, G.N) independently conducted a critical appraisal of the included studies. Joanna Briggs Institute (JBI) checklists of prevalence study was used to assess the quality of the studies. Studies with a Newcastle–Ottawa Quality Assessment Scale (NOS) score of seven or more were considered acceptable [ 23 ]. The tool has nine parameters, which have yes, no, unclear, and not applicable options [ 24 ]. Two reviewers (I.A, B.A) were involved when necessary, during the critical appraisal process. Accordingly, all studies were included in our review. ( Table  1 ) Questions to evaluate the methodological quality of studies on turnover intention among nurses and its associated factors in Ethiopia are the followings:

Q1 = was the sample frame appropriate to address the target population?

Q2. Were study participants sampled appropriately.

Q3. Was the sample size adequate?

Q4. Were the study subjects and the setting described in detail?

Q5. Was the data analysis conducted with sufficient coverage of the identified sample?

Q6. Were the valid methods used for the identification of the condition?

Q7. Was the condition measured in a standard, reliable way for all participants?

Q8. Was there appropriate statistical analysis?

Q9. Was the response rate adequate, and if not, was the low response rate.

managed appropriately?

Data was extracted and recorded in a Microsoft Excel as guided by the Joanna Briggs Institute (JBI) data extraction form for observational studies. Three authors (E.E, M.G, T.T) independently conducted data extraction. Recorded data included the first author’s last name, publication year, study setting or country, region, study design, study period, sample size, response rate, population, type of management, proportion of turnover intention, and associated factors. Discrepancies in data extraction were resolved through discussion between extractors.

Data processing and analysis

Data analysis procedures involved importing the extracted data into STATA 14 statistical software for conducting a pooled proportion of turnover intention among nurses. To evaluate potential publication bias and small study effects, both funnel plots and Egger’s test were employed [ 25 , 26 ]. We used statistical tests such as the I statistic to quantify heterogeneity and explore potential sources of variability. Additionally, subgroup analyses were conducted to investigate the impact of specific study characteristics on the overall results. I 2 values of 0%, 25%, 50%, and 75% were interpreted as indicating no, low, medium, and high heterogeneity, respectively [ 27 ].

To assess publication bias, we employed several methods, including funnel plots and Egger’s test. These techniques allowed us to visually inspect asymmetry in the distribution of study results and statistically evaluate the presence of publication bias. Furthermore, we conducted sensitivity analyses to assess the robustness of our findings to potential publication bias and other sources of bias.

Utilizing a random-effects method, a meta-analysis was performed to assess turnover intention among nurses, employing this method to account for observed variability [ 28 ]. Subgroup analyses were conducted to compare the pooled magnitude of turnover intention among nurses and associated factors across different regions. The results of the pooled prevalence were visually presented in a forest plot format with a 95% confidence interval.

Study selection

After conducting the initial comprehensive search concerning turnover intention among nurses through Medline, Cochran Library, Web of Science, Embase, Ajol, Google Scholar, and other sources, a total of 1343 articles were retrieved. Of which 575 were removed due to duplication. Five hundred ninety-three articles were removed from the remaining 768 articles by title and abstract. Following theses, 44 articles which cannot be retrieved were removed. Finally, from the remaining 131 articles, 8 articles with a total 3033 nurses were included in the systematic review and meta-analysis (Fig.  1 ).

PRISMA flow diagram of the selection process of studies on turnover intention among nurses in Ethiopia, 2024

Study characteristics

All included 8 studies had a cross-sectional design and of which, 2 were from Tigray region, 2 were from Addis Ababa(Capital), 1 from south region, 1 from Amhara region, 1 from Sidama region, and 1 was multiregional and Nationwide. The prevalence of turnover intention among nurses ‘ranges from 30.6 to 80.6%. Table  2 .

Pooled prevalence of turnover intention among nurses in Ethiopia

Our comprehensive meta-analysis revealed a notable turnover intention rate of 53.35% (95% CI: 41.64, 65.05%) among Ethiopian nurses, accompanied by substantial heterogeneity between studies (I 2  = 97.9, P  = 0.000) as depicted in Fig.  2 . Given the observed variability, we employed a random-effects model to analyze the data, ensuring a robust adjustment for the significant heterogeneity across the included studies.

Forest plot showing the pooled proportion of turnover intention among nurses in Ethiopia, 2024

Subgroup analysis of turnover intention among nurses in Ethiopia

To address the observed heterogeneity, we conducted a subgroup analysis based on regions. The results of the subgroup analysis highlighted considerable variations, with the highest level of turnover intention identified in Addis Ababa at 69.10% (95% CI: 46.47, 91.74%) and substantial heterogeneity (I 2  = 98.1%). Conversely, the Sidama region exhibited the lowest level of turnover intention among nurses at 30.6% (95% CI: 25.18, 36.02%), accompanied by considerable heterogeneity (I 2  = 100.0%) ( Fig.  3 ).

Subgroup analysis of systematic review and meta-analysis by region of turnover intention among nurses in Ethiopia, 2024

Publication bias of turnover intention among nurses in Ethiopia

The Egger’s test result ( p  = 0.64) is not statistically significant, indicating no evidence of publication bias in the meta-analysis (Table  3 ). Additionally, the symmetrical distribution of included studies in the funnel plot (Fig.  4 ) confirms the absence of publication bias across studies.

Funnel plot of systematic review and meta-analysis on turnover intention among nurses in Ethiopia, 2024

Sensitivity analysis

The leave-out-one sensitivity analysis served as a meticulous evaluation of the influence of individual studies on the comprehensive pooled prevalence of turnover intention within the context of Ethiopian nurses. In this systematic process, each study was methodically excluded from the analysis one at a time. The outcomes of this meticulous examination indicated that the exclusion of any particular study did not lead to a noteworthy or statistically significant alteration in the overall pooled estimate of turnover intention among nurses in Ethiopia. The findings are visually represented in Fig.  5 , illustrating the stability and robustness of the overall pooled estimate even with the removal of specific studies from the analysis.

Sensitivity analysis of pooled prevalence for each study being removed at a time for systematic review and meta-analysis of turnover intention among nurses in Ethiopia

Factors associated with turnover intention among nurses in Ethiopia

In our meta-analysis, we comprehensively reviewed and conducted a meta-analysis on the determinants of turnover intention among nurses in Ethiopia by examining eight relevant studies [ 6 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ]. We identified a significant association between turnover intention with autonomous decision-making (OR: 0.28, CI: 0.14, 0.70) (Fig.  6 ) and promotion/development (OR: 0.67, CI: 0.46, 0.89) (Fig.  7 ). In both instances, the odds ratios suggest a negative association, signifying that increased levels of autonomous decision-making and promotion/development were linked to reduced odds of turnover intention.

Forest plot of the association between autonomous decision making with turnover intention among nurses in Ethiopia2024

Forest plot of the association between promotion/developpment with turnover intention among nurses in Ethiopia, 2024

In our comprehensive meta-analysis exploring turnover intention among nurses in Ethiopia, our findings revealed a pooled proportion of turnover intention at 53.35%. This significant proportion warrants a comparative analysis with turnover rates reported in other global regions. Distinct variations emerge when compared with turnover rates in Alexandria (68%), China (63.88%), and Jordan (60.9%) [ 5 , 6 , 7 ]. This comparison highlights that the multifaceted nature of turnover intention, influenced by diverse contextual, cultural, and organizational factors. Conversely, Ethiopia’s turnover rate among nurses contrasts with substantially lower figures reported in Israel (9%) [ 8 ], Brazil (21.1%) [ 9 ], and Saudi hospitals (26%) [ 10 ]. Challenges such as work overload, economic constraints, limited promotional opportunities, lack of recognition, and low job rewards are more prevalent among nurses in Ethiopia, contributing to higher turnover intention compared to their counterparts [ 7 , 29 , 36 ].

The highest turnover intention was observed in Addis Ababa, while Sidama region displayed the lowest turnover intention among nurses, These differences highlight the complexity of turnover intention among Ethiopian nurses, showing the importance of specific interventions in each region to address unique factors and improve nurses’ retention.

Our systematic review and meta-analysis in the Ethiopian nursing context revealed a significant inverse association between turnover intention and autonomous decision-making. The odd of turnover intention is approximately reduced by 72% in employees with autonomous decision-making compared to those without autonomous decision-making. This finding was supported by other similar studies conducted in South Africa, Tanzania, Kenya, and Turkey [ 37 , 38 , 39 , 40 ].

The significant association of turnover intention with promotion/development in our study underscores the crucial role of career advancement opportunities in alleviating turnover intention among nurses. Specifically, our analysis revealed that individuals with promotion/development had approximately 33% lower odds of turnover intention compared to those without such opportunities. These results emphasize the pivotal influence of organizational support in shaping the professional environment for nurses, providing substantive insights for the formulation of evidence-based strategies targeted at enhancing workforce retention. This finding is in line with former researches conducted in Taiwan, Philippines and Italy [ 41 , 42 , 43 ].

Our meta-analysis on turnover intention among Ethiopian nurses reveals a considerable challenge, with a pooled proportion of 53.35%. Regional variations highlight the necessity for region-specific strategies, with Addis Ababa displaying the highest turnover intention and Sidama region the lowest. A significant inverse association was found between turnover intention with autonomous decision-making and promotion/development. These insights support the formulation of evidence-based strategies and policies to enhance nurse retention, contributing to the overall stability of the Ethiopian healthcare system.

Recommendations

Federal ministry of health (fmoh).

The FMoH should consider the regional variations in turnover intention and formulate targeted retention strategies. Investment in professional development opportunities and initiatives to enhance autonomy can be integral components of these strategies.

Ethiopian nurses association (ENA)

ENA plays a pivotal role in advocating for the welfare of nurses. The association is encouraged to collaborate with healthcare institutions to promote autonomy, create mentorship programs, and advocate for improved working conditions to mitigate turnover intention.

Healthcare institutions

Hospitals and healthcare facilities should prioritize the provision of career advancement opportunities and recognize the value of professional autonomy in retaining nursing staff. Tailored interventions based on regional variations should be considered.

Policy makers

Policymakers should review existing healthcare policies to identify areas for improvement in nurse retention. Policy changes that address challenges such as work overload, limited promotional opportunities, and economic constraints can positively impact turnover rates.

Future research initiatives

Further research exploring the specific factors contributing to turnover intention in different regions of Ethiopia is recommended. Understanding the nuanced challenges faced by nurses in various settings will inform the development of more targeted interventions.

Strength and limitations

Our systematic review and meta-analysis on nurse turnover intention in Ethiopia present several strengths. The comprehensive inclusion of diverse studies provides a holistic view of the issue, enhancing the generalizability of our findings. The use of a random-effects model accounts for potential heterogeneity, ensuring a more robust and reliable synthesis of data.

However, limitations should be acknowledged. The heterogeneity observed across studies, despite the use of a random-effects model, may impact the precision of the pooled estimate. These considerations should be taken into account when interpreting and applying the results of our analysis.

Data availability

Data set used on this analysis will available from corresponding author upon reasonable request.

Abbreviations

Ethiopian Nurses Association

Federal Ministry of Health

Joanna Briggs Institute

Preferred Reporting Items for Systematic review and Meta-analysis Protocols

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School of Nursing, College of Health Science and Medicine, Wolaita Sodo University, Wolaita Sodo, Ethiopia

Eshetu Elfios, Israel Asale, Merid Merkine, Temesgen Geta, Kidist Ashager, Getachew Nigussie, Ayele Agena & Bizuayehu Atinafu

Department of Midwifery, College of Health Science and Medicine, Wolaita Sodo University, Wolaita Sodo, Ethiopia

Eskindir Israel

Department of Midwifery, College of Health Science and Medicine, Wachamo University, Hossana, Ethiopia

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E.E. conceptualized the study, designed the research, performed statistical analysis, and led the manuscript writing. I.A, T.G, M.M contributed to the study design and provided critical revisions. K.A., G.N, B.A., E.I., and T.T. participated in data extraction and quality assessment. M.M. and T.G. K.A. and G.N. contributed to the literature review. I.A, A.A. and B.A. assisted in data interpretation. E.I. and T.T. provided critical revisions to the manuscript. All authors read and approved the final version.

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Correspondence to Eshetu Elfios .

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Elfios, E., Asale, I., Merkine, M. et al. Turnover intention and its associated factors among nurses in Ethiopia: a systematic review and meta-analysis. BMC Health Serv Res 24 , 662 (2024). https://doi.org/10.1186/s12913-024-11122-9

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Received : 20 January 2024

Accepted : 20 May 2024

Published : 24 May 2024

DOI : https://doi.org/10.1186/s12913-024-11122-9

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