a review of the literature and meta analysis

Literature Review Research

• What is a Literature Review?
• Systematic Review
• Literature vs Systematic Review

Systematic reviews vs. Meta-Analysis

• Planning your Literature Review
• Finding information
• Helpful Tips
• Other Resources
• Citing your Sources

Systematic review or meta-analysis?

A  systematic review  answers a defined research question by collecting and summarizing all empirical evidence that fits pre-specified eligibility criteria.

A  meta-analysis  is the use of statistical methods to summarize the results of these studies.

Systematic reviews , just like other research articles, can be of varying quality. They are a significant piece of work (the Centre for Reviews and Dissemination at York estimates that a team will take 9-24 months), and to be useful to other researchers and practitioners they should have:

• clearly stated objectives with pre-defined eligibility criteria for studies
• explicit, reproducible methodology
• a systematic search that attempts to identify all studies
• assessment of the validity of the findings of the included studies (e.g. risk of bias)
• systematic presentation, and synthesis, of the characteristics and findings of the included studies

Not all systematic reviews contain meta-analysis. 

Meta-analysis  is the use of statistical methods to summarize the results of independent studies. By combining information from all relevant studies, meta-analysis can provide more precise estimates of the effects of health care than those derived from the individual studies included within a review.    More information on meta-analyses can be found in   Cochrane Handbook, Chapter 9 .

A  meta-analysis  goes beyond critique and integration and conducts secondary statistical analysis on the outcomes of similar studies.  It is a systematic review that uses quantitative methods to synthesize and summarize the results.

An advantage of a  meta-analysis  is the ability to be completely objective in evaluating research findings.  Not all topics, however, have sufficient research evidence to allow a meta-analysis to be conducted.  In that case, an integrative review is an appropriate strategy. 

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How to conduct a meta-analysis in eight steps: a practical guide

• Open Access
• Published: 30 November 2021
• volume  72 ,  pages 1–19 ( 2022 )

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• Christopher Hansen 1 ,
• Holger Steinmetz 2 &
• Jörn Block 3 , 4 , 5  

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1 Introduction

“Scientists have known for centuries that a single study will not resolve a major issue. Indeed, a small sample study will not even resolve a minor issue. Thus, the foundation of science is the cumulation of knowledge from the results of many studies.” (Hunter et al. 1982 , p. 10)

Meta-analysis is a central method for knowledge accumulation in many scientific fields (Aguinis et al. 2011c ; Kepes et al. 2013 ). Similar to a narrative review, it serves as a synopsis of a research question or field. However, going beyond a narrative summary of key findings, a meta-analysis adds value in providing a quantitative assessment of the relationship between two target variables or the effectiveness of an intervention (Gurevitch et al. 2018 ). Also, it can be used to test competing theoretical assumptions against each other or to identify important moderators where the results of different primary studies differ from each other (Aguinis et al. 2011b ; Bergh et al. 2016 ). Rooted in the synthesis of the effectiveness of medical and psychological interventions in the 1970s (Glass 2015 ; Gurevitch et al. 2018 ), meta-analysis is nowadays also an established method in management research and related fields.

The increasing importance of meta-analysis in management research has resulted in the publication of guidelines in recent years that discuss the merits and best practices in various fields, such as general management (Bergh et al. 2016 ; Combs et al. 2019 ; Gonzalez-Mulé and Aguinis 2018 ), international business (Steel et al. 2021 ), economics and finance (Geyer-Klingeberg et al. 2020 ; Havranek et al. 2020 ), marketing (Eisend 2017 ; Grewal et al. 2018 ), and organizational studies (DeSimone et al. 2020 ; Rudolph et al. 2020 ). These articles discuss existing and trending methods and propose solutions for often experienced problems. This editorial briefly summarizes the insights of these papers; provides a workflow of the essential steps in conducting a meta-analysis; suggests state-of-the art methodological procedures; and points to other articles for in-depth investigation. Thus, this article has two goals: (1) based on the findings of previous editorials and methodological articles, it defines methodological recommendations for meta-analyses submitted to Management Review Quarterly (MRQ); and (2) it serves as a practical guide for researchers who have little experience with meta-analysis as a method but plan to conduct one in the future.

2 Eight steps in conducting a meta-analysis

2.1 step 1: defining the research question.

The first step in conducting a meta-analysis, as with any other empirical study, is the definition of the research question. Most importantly, the research question determines the realm of constructs to be considered or the type of interventions whose effects shall be analyzed. When defining the research question, two hurdles might develop. First, when defining an adequate study scope, researchers must consider that the number of publications has grown exponentially in many fields of research in recent decades (Fortunato et al. 2018 ). On the one hand, a larger number of studies increases the potentially relevant literature basis and enables researchers to conduct meta-analyses. Conversely, scanning a large amount of studies that could be potentially relevant for the meta-analysis results in a perhaps unmanageable workload. Thus, Steel et al. ( 2021 ) highlight the importance of balancing manageability and relevance when defining the research question. Second, similar to the number of primary studies also the number of meta-analyses in management research has grown strongly in recent years (Geyer-Klingeberg et al. 2020 ; Rauch 2020 ; Schwab 2015 ). Therefore, it is likely that one or several meta-analyses for many topics of high scholarly interest already exist. However, this should not deter researchers from investigating their research questions. One possibility is to consider moderators or mediators of a relationship that have previously been ignored. For example, a meta-analysis about startup performance could investigate the impact of different ways to measure the performance construct (e.g., growth vs. profitability vs. survival time) or certain characteristics of the founders as moderators. Another possibility is to replicate previous meta-analyses and test whether their findings can be confirmed with an updated sample of primary studies or newly developed methods. Frequent replications and updates of meta-analyses are important contributions to cumulative science and are increasingly called for by the research community (Anderson & Kichkha 2017 ; Steel et al. 2021 ). Consistent with its focus on replication studies (Block and Kuckertz 2018 ), MRQ therefore also invites authors to submit replication meta-analyses.

2.2 Step 2: literature search

2.2.1 search strategies.

Similar to conducting a literature review, the search process of a meta-analysis should be systematic, reproducible, and transparent, resulting in a sample that includes all relevant studies (Fisch and Block 2018 ; Gusenbauer and Haddaway 2020 ). There are several identification strategies for relevant primary studies when compiling meta-analytical datasets (Harari et al. 2020 ). First, previous meta-analyses on the same or a related topic may provide lists of included studies that offer a good starting point to identify and become familiar with the relevant literature. This practice is also applicable to topic-related literature reviews, which often summarize the central findings of the reviewed articles in systematic tables. Both article types likely include the most prominent studies of a research field. The most common and important search strategy, however, is a keyword search in electronic databases (Harari et al. 2020 ). This strategy will probably yield the largest number of relevant studies, particularly so-called ‘grey literature’, which may not be considered by literature reviews. Gusenbauer and Haddaway ( 2020 ) provide a detailed overview of 34 scientific databases, of which 18 are multidisciplinary or have a focus on management sciences, along with their suitability for literature synthesis. To prevent biased results due to the scope or journal coverage of one database, researchers should use at least two different databases (DeSimone et al. 2020 ; Martín-Martín et al. 2021 ; Mongeon & Paul-Hus 2016 ). However, a database search can easily lead to an overload of potentially relevant studies. For example, key term searches in Google Scholar for “entrepreneurial intention” and “firm diversification” resulted in more than 660,000 and 810,000 hits, respectively. Footnote 1 Therefore, a precise research question and precise search terms using Boolean operators are advisable (Gusenbauer and Haddaway 2020 ). Addressing the challenge of identifying relevant articles in the growing number of database publications, (semi)automated approaches using text mining and machine learning (Bosco et al. 2017 ; O’Mara-Eves et al. 2015 ; Ouzzani et al. 2016 ; Thomas et al. 2017 ) can also be promising and time-saving search tools in the future. Also, some electronic databases offer the possibility to track forward citations of influential studies and thereby identify further relevant articles. Finally, collecting unpublished or undetected studies through conferences, personal contact with (leading) scholars, or listservs can be strategies to increase the study sample size (Grewal et al. 2018 ; Harari et al. 2020 ; Pigott and Polanin 2020 ).

2.2.2 Study inclusion criteria and sample composition

Next, researchers must decide which studies to include in the meta-analysis. Some guidelines for literature reviews recommend limiting the sample to studies published in renowned academic journals to ensure the quality of findings (e.g., Kraus et al. 2020 ). For meta-analysis, however, Steel et al. ( 2021 ) advocate for the inclusion of all available studies, including grey literature, to prevent selection biases based on availability, cost, familiarity, and language (Rothstein et al. 2005 ), or the “Matthew effect”, which denotes the phenomenon that highly cited articles are found faster than less cited articles (Merton 1968 ). Harrison et al. ( 2017 ) find that the effects of published studies in management are inflated on average by 30% compared to unpublished studies. This so-called publication bias or “file drawer problem” (Rosenthal 1979 ) results from the preference of academia to publish more statistically significant and less statistically insignificant study results. Owen and Li ( 2020 ) showed that publication bias is particularly severe when variables of interest are used as key variables rather than control variables. To consider the true effect size of a target variable or relationship, the inclusion of all types of research outputs is therefore recommended (Polanin et al. 2016 ). Different test procedures to identify publication bias are discussed subsequently in Step 7.

In addition to the decision of whether to include certain study types (i.e., published vs. unpublished studies), there can be other reasons to exclude studies that are identified in the search process. These reasons can be manifold and are primarily related to the specific research question and methodological peculiarities. For example, studies identified by keyword search might not qualify thematically after all, may use unsuitable variable measurements, or may not report usable effect sizes. Furthermore, there might be multiple studies by the same authors using similar datasets. If they do not differ sufficiently in terms of their sample characteristics or variables used, only one of these studies should be included to prevent bias from duplicates (Wood 2008 ; see this article for a detection heuristic).

In general, the screening process should be conducted stepwise, beginning with a removal of duplicate citations from different databases, followed by abstract screening to exclude clearly unsuitable studies and a final full-text screening of the remaining articles (Pigott and Polanin 2020 ). A graphical tool to systematically document the sample selection process is the PRISMA flow diagram (Moher et al. 2009 ). Page et al. ( 2021 ) recently presented an updated version of the PRISMA statement, including an extended item checklist and flow diagram to report the study process and findings.

2.3 Step 3: choice of the effect size measure

2.3.1 types of effect sizes.

The two most common meta-analytical effect size measures in management studies are (z-transformed) correlation coefficients and standardized mean differences (Aguinis et al. 2011a ; Geyskens et al. 2009 ). However, meta-analyses in management science and related fields may not be limited to those two effect size measures but rather depend on the subfield of investigation (Borenstein 2009 ; Stanley and Doucouliagos 2012 ). In economics and finance, researchers are more interested in the examination of elasticities and marginal effects extracted from regression models than in pure bivariate correlations (Stanley and Doucouliagos 2012 ). Regression coefficients can also be converted to partial correlation coefficients based on their t-statistics to make regression results comparable across studies (Stanley and Doucouliagos 2012 ). Although some meta-analyses in management research have combined bivariate and partial correlations in their study samples, Aloe ( 2015 ) and Combs et al. ( 2019 ) advise researchers not to use this practice. Most importantly, they argue that the effect size strength of partial correlations depends on the other variables included in the regression model and is therefore incomparable to bivariate correlations (Schmidt and Hunter 2015 ), resulting in a possible bias of the meta-analytic results (Roth et al. 2018 ). We endorse this opinion. If at all, we recommend separate analyses for each measure. In addition to these measures, survival rates, risk ratios or odds ratios, which are common measures in medical research (Borenstein 2009 ), can be suitable effect sizes for specific management research questions, such as understanding the determinants of the survival of startup companies. To summarize, the choice of a suitable effect size is often taken away from the researcher because it is typically dependent on the investigated research question as well as the conventions of the specific research field (Cheung and Vijayakumar 2016 ).

2.3.2 Conversion of effect sizes to a common measure

After having defined the primary effect size measure for the meta-analysis, it might become necessary in the later coding process to convert study findings that are reported in effect sizes that are different from the chosen primary effect size. For example, a study might report only descriptive statistics for two study groups but no correlation coefficient, which is used as the primary effect size measure in the meta-analysis. Different effect size measures can be harmonized using conversion formulae, which are provided by standard method books such as Borenstein et al. ( 2009 ) or Lipsey and Wilson ( 2001 ). There also exist online effect size calculators for meta-analysis. Footnote 2

2.4 Step 4: choice of the analytical method used

Choosing which meta-analytical method to use is directly connected to the research question of the meta-analysis. Research questions in meta-analyses can address a relationship between constructs or an effect of an intervention in a general manner, or they can focus on moderating or mediating effects. There are four meta-analytical methods that are primarily used in contemporary management research (Combs et al. 2019 ; Geyer-Klingeberg et al. 2020 ), which allow the investigation of these different types of research questions: traditional univariate meta-analysis, meta-regression, meta-analytic structural equation modeling, and qualitative meta-analysis (Hoon 2013 ). While the first three are quantitative, the latter summarizes qualitative findings. Table 1 summarizes the key characteristics of the three quantitative methods.

2.4.1 Univariate meta-analysis

In its traditional form, a meta-analysis reports a weighted mean effect size for the relationship or intervention of investigation and provides information on the magnitude of variance among primary studies (Aguinis et al. 2011c ; Borenstein et al. 2009 ). Accordingly, it serves as a quantitative synthesis of a research field (Borenstein et al. 2009 ; Geyskens et al. 2009 ). Prominent traditional approaches have been developed, for example, by Hedges and Olkin ( 1985 ) or Hunter and Schmidt ( 1990 , 2004 ). However, going beyond its simple summary function, the traditional approach has limitations in explaining the observed variance among findings (Gonzalez-Mulé and Aguinis 2018 ). To identify moderators (or boundary conditions) of the relationship of interest, meta-analysts can create subgroups and investigate differences between those groups (Borenstein and Higgins 2013 ; Hunter and Schmidt 2004 ). Potential moderators can be study characteristics (e.g., whether a study is published vs. unpublished), sample characteristics (e.g., study country, industry focus, or type of survey/experiment participants), or measurement artifacts (e.g., different types of variable measurements). The univariate approach is thus suitable to identify the overall direction of a relationship and can serve as a good starting point for additional analyses. However, due to its limitations in examining boundary conditions and developing theory, the univariate approach on its own is currently oftentimes viewed as not sufficient (Rauch 2020 ; Shaw and Ertug 2017 ).

2.4.2 Meta-regression analysis

Meta-regression analysis (Hedges and Olkin 1985 ; Lipsey and Wilson 2001 ; Stanley and Jarrell 1989 ) aims to investigate the heterogeneity among observed effect sizes by testing multiple potential moderators simultaneously. In meta-regression, the coded effect size is used as the dependent variable and is regressed on a list of moderator variables. These moderator variables can be categorical variables as described previously in the traditional univariate approach or (semi)continuous variables such as country scores that are merged with the meta-analytical data. Thus, meta-regression analysis overcomes the disadvantages of the traditional approach, which only allows us to investigate moderators singularly using dichotomized subgroups (Combs et al. 2019 ; Gonzalez-Mulé and Aguinis 2018 ). These possibilities allow a more fine-grained analysis of research questions that are related to moderating effects. However, Schmidt ( 2017 ) critically notes that the number of effect sizes in the meta-analytical sample must be sufficiently large to produce reliable results when investigating multiple moderators simultaneously in a meta-regression. For further reading, Tipton et al. ( 2019 ) outline the technical, conceptual, and practical developments of meta-regression over the last decades. Gonzalez-Mulé and Aguinis ( 2018 ) provide an overview of methodological choices and develop evidence-based best practices for future meta-analyses in management using meta-regression.

2.4.3 Meta-analytic structural equation modeling (MASEM)

MASEM is a combination of meta-analysis and structural equation modeling and allows to simultaneously investigate the relationships among several constructs in a path model. Researchers can use MASEM to test several competing theoretical models against each other or to identify mediation mechanisms in a chain of relationships (Bergh et al. 2016 ). This method is typically performed in two steps (Cheung and Chan 2005 ): In Step 1, a pooled correlation matrix is derived, which includes the meta-analytical mean effect sizes for all variable combinations; Step 2 then uses this matrix to fit the path model. While MASEM was based primarily on traditional univariate meta-analysis to derive the pooled correlation matrix in its early years (Viswesvaran and Ones 1995 ), more advanced methods, such as the GLS approach (Becker 1992 , 1995 ) or the TSSEM approach (Cheung and Chan 2005 ), have been subsequently developed. Cheung ( 2015a ) and Jak ( 2015 ) provide an overview of these approaches in their books with exemplary code. For datasets with more complex data structures, Wilson et al. ( 2016 ) also developed a multilevel approach that is related to the TSSEM approach in the second step. Bergh et al. ( 2016 ) discuss nine decision points and develop best practices for MASEM studies.

2.4.4 Qualitative meta-analysis

While the approaches explained above focus on quantitative outcomes of empirical studies, qualitative meta-analysis aims to synthesize qualitative findings from case studies (Hoon 2013 ; Rauch et al. 2014 ). The distinctive feature of qualitative case studies is their potential to provide in-depth information about specific contextual factors or to shed light on reasons for certain phenomena that cannot usually be investigated by quantitative studies (Rauch 2020 ; Rauch et al. 2014 ). In a qualitative meta-analysis, the identified case studies are systematically coded in a meta-synthesis protocol, which is then used to identify influential variables or patterns and to derive a meta-causal network (Hoon 2013 ). Thus, the insights of contextualized and typically nongeneralizable single studies are aggregated to a larger, more generalizable picture (Habersang et al. 2019 ). Although still the exception, this method can thus provide important contributions for academics in terms of theory development (Combs et al., 2019 ; Hoon 2013 ) and for practitioners in terms of evidence-based management or entrepreneurship (Rauch et al. 2014 ). Levitt ( 2018 ) provides a guide and discusses conceptual issues for conducting qualitative meta-analysis in psychology, which is also useful for management researchers.

2.5 Step 5: choice of software

Software solutions to perform meta-analyses range from built-in functions or additional packages of statistical software to software purely focused on meta-analyses and from commercial to open-source solutions. However, in addition to personal preferences, the choice of the most suitable software depends on the complexity of the methods used and the dataset itself (Cheung and Vijayakumar 2016 ). Meta-analysts therefore must carefully check if their preferred software is capable of performing the intended analysis.

Among commercial software providers, Stata (from version 16 on) offers built-in functions to perform various meta-analytical analyses or to produce various plots (Palmer and Sterne 2016 ). For SPSS and SAS, there exist several macros for meta-analyses provided by scholars, such as David B. Wilson or Andy P. Field and Raphael Gillet (Field and Gillett 2010 ). Footnote 3 Footnote 4 For researchers using the open-source software R (R Core Team 2021 ), Polanin et al. ( 2017 ) provide an overview of 63 meta-analysis packages and their functionalities. For new users, they recommend the package metafor (Viechtbauer 2010 ), which includes most necessary functions and for which the author Wolfgang Viechtbauer provides tutorials on his project website. Footnote 5 Footnote 6 In addition to packages and macros for statistical software, templates for Microsoft Excel have also been developed to conduct simple meta-analyses, such as Meta-Essentials by Suurmond et al. ( 2017 ). Footnote 7 Finally, programs purely dedicated to meta-analysis also exist, such as Comprehensive Meta-Analysis (Borenstein et al. 2013 ) or RevMan by The Cochrane Collaboration ( 2020 ).

2.6 Step 6: coding of effect sizes

2.6.1 coding sheet.

The first step in the coding process is the design of the coding sheet. A universal template does not exist because the design of the coding sheet depends on the methods used, the respective software, and the complexity of the research design. For univariate meta-analysis or meta-regression, data are typically coded in wide format. In its simplest form, when investigating a correlational relationship between two variables using the univariate approach, the coding sheet would contain a column for the study name or identifier, the effect size coded from the primary study, and the study sample size. However, such simple relationships are unlikely in management research because the included studies are typically not identical but differ in several respects. With more complex data structures or moderator variables being investigated, additional columns are added to the coding sheet to reflect the data characteristics. These variables can be coded as dummy, factor, or (semi)continuous variables and later used to perform a subgroup analysis or meta regression. For MASEM, the required data input format can deviate depending on the method used (e.g., TSSEM requires a list of correlation matrices as data input). For qualitative meta-analysis, the coding scheme typically summarizes the key qualitative findings and important contextual and conceptual information (see Hoon ( 2013 ) for a coding scheme for qualitative meta-analysis). Figure  1 shows an exemplary coding scheme for a quantitative meta-analysis on the correlational relationship between top-management team diversity and profitability. In addition to effect and sample sizes, information about the study country, firm type, and variable operationalizations are coded. The list could be extended by further study and sample characteristics.

Exemplary coding sheet for a meta-analysis on the relationship (correlation) between top-management team diversity and profitability

2.6.2 Inclusion of moderator or control variables

It is generally important to consider the intended research model and relevant nontarget variables before coding a meta-analytic dataset. For example, study characteristics can be important moderators or function as control variables in a meta-regression model. Similarly, control variables may be relevant in a MASEM approach to reduce confounding bias. Coding additional variables or constructs subsequently can be arduous if the sample of primary studies is large. However, the decision to include respective moderator or control variables, as in any empirical analysis, should always be based on strong (theoretical) rationales about how these variables can impact the investigated effect (Bernerth and Aguinis 2016 ; Bernerth et al. 2018 ; Thompson and Higgins 2002 ). While substantive moderators refer to theoretical constructs that act as buffers or enhancers of a supposed causal process, methodological moderators are features of the respective research designs that denote the methodological context of the observations and are important to control for systematic statistical particularities (Rudolph et al. 2020 ). Havranek et al. ( 2020 ) provide a list of recommended variables to code as potential moderators. While researchers may have clear expectations about the effects for some of these moderators, the concerns for other moderators may be tentative, and moderator analysis may be approached in a rather exploratory fashion. Thus, we argue that researchers should make full use of the meta-analytical design to obtain insights about potential context dependence that a primary study cannot achieve.

2.6.3 Treatment of multiple effect sizes in a study

A long-debated issue in conducting meta-analyses is whether to use only one or all available effect sizes for the same construct within a single primary study. For meta-analyses in management research, this question is fundamental because many empirical studies, particularly those relying on company databases, use multiple variables for the same construct to perform sensitivity analyses, resulting in multiple relevant effect sizes. In this case, researchers can either (randomly) select a single value, calculate a study average, or use the complete set of effect sizes (Bijmolt and Pieters 2001 ; López-López et al. 2018 ). Multiple effect sizes from the same study enrich the meta-analytic dataset and allow us to investigate the heterogeneity of the relationship of interest, such as different variable operationalizations (López-López et al. 2018 ; Moeyaert et al. 2017 ). However, including more than one effect size from the same study violates the independency assumption of observations (Cheung 2019 ; López-López et al. 2018 ), which can lead to biased results and erroneous conclusions (Gooty et al. 2021 ). We follow the recommendation of current best practice guides to take advantage of using all available effect size observations but to carefully consider interdependencies using appropriate methods such as multilevel models, panel regression models, or robust variance estimation (Cheung 2019 ; Geyer-Klingeberg et al. 2020 ; Gooty et al. 2021 ; López-López et al. 2018 ; Moeyaert et al. 2017 ).

2.7 Step 7: analysis

2.7.1 outlier analysis and tests for publication bias.

Before conducting the primary analysis, some preliminary sensitivity analyses might be necessary, which should ensure the robustness of the meta-analytical findings (Rudolph et al. 2020 ). First, influential outlier observations could potentially bias the observed results, particularly if the number of total effect sizes is small. Several statistical methods can be used to identify outliers in meta-analytical datasets (Aguinis et al. 2013 ; Viechtbauer and Cheung 2010 ). However, there is a debate about whether to keep or omit these observations. Anyhow, relevant studies should be closely inspected to infer an explanation about their deviating results. As in any other primary study, outliers can be a valid representation, albeit representing a different population, measure, construct, design or procedure. Thus, inferences about outliers can provide the basis to infer potential moderators (Aguinis et al. 2013 ; Steel et al. 2021 ). On the other hand, outliers can indicate invalid research, for instance, when unrealistically strong correlations are due to construct overlap (i.e., lack of a clear demarcation between independent and dependent variables), invalid measures, or simply typing errors when coding effect sizes. An advisable step is therefore to compare the results both with and without outliers and base the decision on whether to exclude outlier observations with careful consideration (Geyskens et al. 2009 ; Grewal et al. 2018 ; Kepes et al. 2013 ). However, instead of simply focusing on the size of the outlier, its leverage should be considered. Thus, Viechtbauer and Cheung ( 2010 ) propose considering a combination of standardized deviation and a study’s leverage.

Second, as mentioned in the context of a literature search, potential publication bias may be an issue. Publication bias can be examined in multiple ways (Rothstein et al. 2005 ). First, the funnel plot is a simple graphical tool that can provide an overview of the effect size distribution and help to detect publication bias (Stanley and Doucouliagos 2010 ). A funnel plot can also support in identifying potential outliers. As mentioned above, a graphical display of deviation (e.g., studentized residuals) and leverage (Cook’s distance) can help detect the presence of outliers and evaluate their influence (Viechtbauer and Cheung 2010 ). Moreover, several statistical procedures can be used to test for publication bias (Harrison et al. 2017 ; Kepes et al. 2012 ), including subgroup comparisons between published and unpublished studies, Begg and Mazumdar’s ( 1994 ) rank correlation test, cumulative meta-analysis (Borenstein et al. 2009 ), the trim and fill method (Duval and Tweedie 2000a , b ), Egger et al.’s ( 1997 ) regression test, failsafe N (Rosenthal 1979 ), or selection models (Hedges and Vevea 2005 ; Vevea and Woods 2005 ). In examining potential publication bias, Kepes et al. ( 2012 ) and Harrison et al. ( 2017 ) both recommend not relying only on a single test but rather using multiple conceptionally different test procedures (i.e., the so-called “triangulation approach”).

2.7.2 Model choice

After controlling and correcting for the potential presence of impactful outliers or publication bias, the next step in meta-analysis is the primary analysis, where meta-analysts must decide between two different types of models that are based on different assumptions: fixed-effects and random-effects (Borenstein et al. 2010 ). Fixed-effects models assume that all observations share a common mean effect size, which means that differences are only due to sampling error, while random-effects models assume heterogeneity and allow for a variation of the true effect sizes across studies (Borenstein et al. 2010 ; Cheung and Vijayakumar 2016 ; Hunter and Schmidt 2004 ). Both models are explained in detail in standard textbooks (e.g., Borenstein et al. 2009 ; Hunter and Schmidt 2004 ; Lipsey and Wilson 2001 ).

In general, the presence of heterogeneity is likely in management meta-analyses because most studies do not have identical empirical settings, which can yield different effect size strengths or directions for the same investigated phenomenon. For example, the identified studies have been conducted in different countries with different institutional settings, or the type of study participants varies (e.g., students vs. employees, blue-collar vs. white-collar workers, or manufacturing vs. service firms). Thus, the vast majority of meta-analyses in management research and related fields use random-effects models (Aguinis et al. 2011a ). In a meta-regression, the random-effects model turns into a so-called mixed-effects model because moderator variables are added as fixed effects to explain the impact of observed study characteristics on effect size variations (Raudenbush 2009 ).

2.8 Step 8: reporting results

2.8.1 reporting in the article.

The final step in performing a meta-analysis is reporting its results. Most importantly, all steps and methodological decisions should be comprehensible to the reader. DeSimone et al. ( 2020 ) provide an extensive checklist for journal reviewers of meta-analytical studies. This checklist can also be used by authors when performing their analyses and reporting their results to ensure that all important aspects have been addressed. Alternative checklists are provided, for example, by Appelbaum et al. ( 2018 ) or Page et al. ( 2021 ). Similarly, Levitt et al. ( 2018 ) provide a detailed guide for qualitative meta-analysis reporting standards.

For quantitative meta-analyses, tables reporting results should include all important information and test statistics, including mean effect sizes; standard errors and confidence intervals; the number of observations and study samples included; and heterogeneity measures. If the meta-analytic sample is rather small, a forest plot provides a good overview of the different findings and their accuracy. However, this figure will be less feasible for meta-analyses with several hundred effect sizes included. Also, results displayed in the tables and figures must be explained verbally in the results and discussion sections. Most importantly, authors must answer the primary research question, i.e., whether there is a positive, negative, or no relationship between the variables of interest, or whether the examined intervention has a certain effect. These results should be interpreted with regard to their magnitude (or significance), both economically and statistically. However, when discussing meta-analytical results, authors must describe the complexity of the results, including the identified heterogeneity and important moderators, future research directions, and theoretical relevance (DeSimone et al. 2019 ). In particular, the discussion of identified heterogeneity and underlying moderator effects is critical; not including this information can lead to false conclusions among readers, who interpret the reported mean effect size as universal for all included primary studies and ignore the variability of findings when citing the meta-analytic results in their research (Aytug et al. 2012 ; DeSimone et al. 2019 ).

2.8.2 Open-science practices

Another increasingly important topic is the public provision of meta-analytical datasets and statistical codes via open-source repositories. Open-science practices allow for results validation and for the use of coded data in subsequent meta-analyses ( Polanin et al. 2020 ), contributing to the development of cumulative science. Steel et al. ( 2021 ) refer to open science meta-analyses as a step towards “living systematic reviews” (Elliott et al. 2017 ) with continuous updates in real time. MRQ supports this development and encourages authors to make their datasets publicly available. Moreau and Gamble ( 2020 ), for example, provide various templates and video tutorials to conduct open science meta-analyses. There exist several open science repositories, such as the Open Science Foundation (OSF; for a tutorial, see Soderberg 2018 ), to preregister and make documents publicly available. Furthermore, several initiatives in the social sciences have been established to develop dynamic meta-analyses, such as metaBUS (Bosco et al. 2015 , 2017 ), MetaLab (Bergmann et al. 2018 ), or PsychOpen CAMA (Burgard et al. 2021 ).

3 Conclusion

This editorial provides a comprehensive overview of the essential steps in conducting and reporting a meta-analysis with references to more in-depth methodological articles. It also serves as a guide for meta-analyses submitted to MRQ and other management journals. MRQ welcomes all types of meta-analyses from all subfields and disciplines of management research.

Gusenbauer and Haddaway ( 2020 ), however, point out that Google Scholar is not appropriate as a primary search engine due to a lack of reproducibility of search results.

One effect size calculator by David B. Wilson is accessible via: https://www.campbellcollaboration.org/escalc/html/EffectSizeCalculator-Home.php .

The macros of David B. Wilson can be downloaded from: http://mason.gmu.edu/~dwilsonb/ .

The macros of Field and Gillet ( 2010 ) can be downloaded from: https://www.discoveringstatistics.com/repository/fieldgillett/how_to_do_a_meta_analysis.html .

The tutorials can be found via: https://www.metafor-project.org/doku.php .

Metafor does currently not provide functions to conduct MASEM. For MASEM, users can, for instance, use the package metaSEM (Cheung 2015b ).

The workbooks can be downloaded from: https://www.erim.eur.nl/research-support/meta-essentials/ .

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Literature Review, Systematic Review and Meta-analysis

Literature reviews can be a good way to narrow down theoretical interests; refine a research question; understand contemporary debates; and orientate a particular research project. It is very common for PhD theses to contain some element of reviewing the literature around a particular topic. It’s typical to have an entire chapter devoted to reporting the result of this task, identifying gaps in the literature and framing the collection of additional data.

Systematic review is a type of literature review that uses systematic methods to collect secondary data, critically appraise research studies, and synthesise findings. Systematic reviews are designed to provide a comprehensive, exhaustive summary of current theories and/or evidence and published research (Siddaway, Wood & Hedges, 2019) and may be qualitative or qualitative. Relevant studies and literature are identified through a research question, summarised and synthesized into a discrete set of findings or a description of the state-of-the-art. This might result in a ‘literature review’ chapter in a doctoral thesis, but can also be the basis of an entire research project.

Meta-analysis is a specialised type of systematic review which is quantitative and rigorous, often comparing data and results across multiple similar studies. This is a common approach in medical research where several papers might report the results of trials of a particular treatment, for instance. The meta-analysis then statistical techniques to synthesize these into one summary. This can have a high statistical power but care must be taken not to introduce bias in the selection and filtering of evidence.

Whichever type of review is employed, the process is similarly linear. The first step is to frame a question which can guide the review. This is used to identify relevant literature, often through searching subject-specific scientific databases. From these results the most relevant will be identified. Filtering is important here as there will be time constraints that prevent the researcher considering every possible piece of evidence or theoretical viewpoint. Once a concrete evidence base has been identified, the researcher extracts relevant data before reporting the synthesized results in an extended piece of writing.

Literature Review: GO-GN Insights

Sarah Lambert used a systematic review of literature with both qualitative and quantitative phases to investigate the question “How can open education programs be reconceptualised as acts of social justice to improve the access, participation and success of those who are traditionally excluded from higher education knowledge and skills?”

“My PhD research used systematic review, qualitative synthesis, case study and discourse analysis techniques, each was underpinned and made coherent by a consistent critical inquiry methodology and an overarching research question. “Systematic reviews are becoming increasingly popular as a way to collect evidence of what works across multiple contexts and can be said to address some of the weaknesses of case study designs which provide detail about a particular context – but which is often not replicable in other socio-cultural contexts (such as other countries or states.) Publication of systematic reviews that are done according to well defined methods are quite likely to be published in high-ranking journals – my PhD supervisors were keen on this from the outset and I was encouraged along this path. “Previously I had explored social realist authors and a social realist approach to systematic reviews (Pawson on realist reviews) but they did not sufficiently embrace social relations, issues of power, inclusion/exclusion. My supervisors had pushed me to explain what kind of realist review I intended to undertake, and I found out there was a branch of critical realism which was briefly of interest. By getting deeply into theory and trying out ways of combining theory I also feel that I have developed a deeper understanding of conceptual working and the different ways theories can be used at all stagesof research and even how to come up with novel conceptual frameworks.”

Useful references for Systematic Review & Meta-Analysis: Finfgeld-Connett (2014); Lambert (2020); Siddaway, Wood & Hedges (2019)

Research Methods Handbook Copyright © 2020 by Rob Farrow; Francisco Iniesto; Martin Weller; and Rebecca Pitt is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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Expert Commentary

The literature review and meta-analysis: 2 journalism tools you should use

Reporters can get up to date on a public policy issue quickly by reading a research literature review or meta-analysis. This article from the Education Writers Association explains how to find and use them.

Republish this article

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License .

by Denise-Marie Ordway, The Journalist's Resource June 20, 2019

This <a target="_blank" href="https://journalistsresource.org/media/meta-analysis-literature-review/">article</a> first appeared on <a target="_blank" href="https://journalistsresource.org">The Journalist's Resource</a> and is republished here under a Creative Commons license.<img src="https://journalistsresource.org/wp-content/uploads/2020/11/cropped-jr-favicon-150x150.png" style="width:1em;height:1em;margin-left:10px;">

We’re republishing this article on research literature reviews and meta-analyses with permission from the Education Writers Association , which hired Journalist’s Resource’s managing editor, Denise-Marie Ordway, late last year to write it in her free time. Ordway is a veteran education reporter who joined the EWA’s board of directors in May.  

This piece was first published on the EWA’s website . It has been slightly edited to reflect Journalist’s Resource’s editorial style.

It’s important to note that while the examples used in this piece come from the education beat, the information applies to literature reviews and meta-analyses across academic fields.

———–

When journalists want to learn what’s known about a certain subject, they look for research. Scholars are continually conducting studies on education topics ranging from kindergarten readiness and teacher pay to public university funding and Ivy League admissions.

One of the best ways for a reporter to get up to date quickly, though, is to read a study of studies, which come in two forms: a literature review and a meta-analysis.

A literature review is what it sounds like — a review of all the academic literature that exists on a specific issue or research question. If your school district or state is considering a new policy or approach, there’s no better way to educate yourself on what’s already been learned. Your news coverage also benefits from literature reviews: Rather than hunting down studies on your own and then worrying whether you found the right ones, you can, instead, share the results of a literature review that already has done that legwork for you.

Literature reviews examine both quantitative research, which is based on numerical data, and qualitative research, based on observations and other information that isn’t in numerical form. When scholars conduct a literature review, they summarize and synthesize multiple research studies and their findings, highlighting gaps in knowledge and the studies that are the strongest or most pertinent.

In addition, literature reviews often point out and explain disagreements between studies — why the results of one study seem to contradict the results of another.

For instance, a literature review might explain that the results of Study A and Study B differ because the two pieces of research focus on different populations or examine slightly different interventions. By relying on literature reviews, journalists also will be able to provide the context audiences need to make sense of the cumulative body of knowledge on a topic.

A meta-analysis also can be helpful to journalists, but for different reasons. To conduct a meta-analysis, scholars focus on quantitative research studies that generally aim to answer a research question — for example, whether there is a link between student suspension rates and academic achievement or whether a certain type of program reduces binge drinking among college students.

After pulling together the quantitative research that exists on the topic, scholars perform a systematic analysis of the numerical data and draw their own conclusions. The findings of a meta-analysis are statistically stronger than those reached in a single study, partly because pooling data from multiple, similar studies creates a larger sample.

The results of a meta-analysis are summarized as a single number or set of numbers that represent an average outcome for all the studies included in the review. A meta-analysis might tell us, for example, how many children, on average, are bullied in middle school, or the average number of points SAT scores rise after students complete a specific type of tutoring program.

It’s important to note that a meta-analysis is vulnerable to misinterpretation because its results can be deceptively simple: Just as you can’t learn everything about students from viewing their credit ratings or graduation rates, you can miss out on important nuances when you attempt to synthesize an entire body of research with a single number or set of numbers generated by a meta-analysis.

For journalists, literature reviews and meta-analyses are important tools for investigating public policy issues and fact-checking claims made by elected leaders, campus administrators and others. But to use them, reporters first need to know how to find them. And, as with any source of information, reporters also should be aware of the potential flaws and biases of these research overviews.

Finding research

The best place to find literature reviews and meta-analyses are in peer-reviewed academic journals such as the Review of Educational Research , Social Problems  and PNAS (short for Proceedings of the National Academy of Sciences of the United States of America ). While publication in a journal does not guarantee quality, the peer-review process is designed for quality control. Typically, papers appearing in top-tier journals have survived detailed critiques by scholars with expertise in the field. Thus, academic journals are an important source of reliable, evidence-based knowledge.

An easy way to find journal articles is by using Google Scholar, a free search engine that indexes published and unpublished research. Another option is to go directly to journal websites. Although  many academic journals keep their research behind paywalls, some provide journalists with free subscriptions or special access codes. Other ways to get around journal paywalls are outlined in a tip sheet that Journalist’s Resource , a project of Harvard’s Shorenstein Center on Media, Politics and Public Policy, created specifically for reporters.

Another thing to keep in mind: Literature reviews and meta-analyses do not exist on every education topic. If you have trouble finding one, reach out to an education professor or research organization such as the American Educational Research Association for guidance.

Sources of bias

Because literature reviews and meta-analyses are based on an examination of multiple studies, the strength of their findings relies heavily on three factors:

• the quality of each included study,
• ​the completeness of researchers’ search for scholarship on the topic of interest, and
• ​researchers’ decisions about which studies to include and leave out.

In fact, many of the choices researchers make during each step of designing and carrying out a meta-analysis can create biases that might influence their results.

Knowing these things can help journalists gauge the quality of a literature review or meta-analysis and ask better questions about them. This comes in handy for reporters wanting to take a critical lens to their coverage of these two forms of research, especially those claiming to have made a groundbreaking discovery.

That said, vetting a review or meta-analysis can be time-consuming. Remember that journalists are not expected to be experts in research methods. When in doubt, contact education researchers for guidance and insights. Also, be sure to interview authors about their studies’ strengths, weaknesses, limitations and real-world implications.

Study quality, appropriateness

If scholars perform a meta-analysis using biased data or data from studies that are too dissimilar, the findings might be misleading — or outright incorrect. One of the biggest potential flaws of meta-analyses is the pooling of data from studies that should not be combined. For example, even if two individual studies focus on school meals, the authors might be looking at different populations, using different definitions and collecting data differently.

Perhaps the authors of the first study consider a school meal to be a hot lunch prepared by a public school cafeteria in Oklahoma, while the research team for the second study defines a school meal as any food an adult or child eats at college preparatory schools throughout Europe. What if the first study relies on data collected from school records over a decade and the second relies on data extracted from a brief online survey of students? Researchers performing a meta-analysis would need to make a judgment call about the appropriateness of merging information from these two studies, conducted in different parts of the world.

Search completeness

Researchers should explain how hard they worked to find all the research that exists on the topic they examined. Small differences in search strategies can lead to substantial differences in search results. If, for instance, search terms are too vague or specific, scholars might miss some compelling studies. Likewise, results may vary according to the databases, websites and search engines used.

Decisions about what to include

Scholars are not supposed to cherry-pick the research they include in literature reviews and meta-analyses. But decisions researchers make about which kinds of scholarship make the cut can influence conclusions.

Should they include unpublished research, such as working papers and papers presented at academic conferences? Does it make sense to exclude studies written in foreign languages? What about doctoral dissertations? Should researchers only include studies that have been published in journals, which tend to favor research with positive findings? Some scholars argue that meta-analyses that rely solely on published research offer misleading findings.

Other factors to consider

As journalists consider how the process of conducting literature reviews and meta-analyses affects results, they also should look for indicators of quality among the individual research studies examined. For example:

• Sample sizes: Bigger samples tend to provide more accurate results than smaller ones.
• ​Study duration: Data collected over several years generally offer a more complete picture than data gathered over a few weeks.
• ​Study age: In some cases, an older study might not be reliable anymore. If a study appears to be too old, ask yourself if there is a reason to expect that conditions have changed substantially since its publication or release.
• ​Researcher credentials: A scholar’s education, work experience and publication history often reflect their level of expertise.

About The Author

Denise-Marie Ordway

Main Navigation Menu

Systematic reviews.

• Getting Started with Systematic Reviews

What is a Systematic Review and Meta-Analysis

Differences between systematic and literature reviews.

• Finding and Evaluating Existing Systematic Reviews
• Steps in a Systematic Review
• Step 1: Developing a Question
• Step 2: Selecting Databases
• Step 3: Grey Literature
• Step 4: Registering a Systematic Review Protocol
• Step 5: Translate Search Strategies
• Step 6: Citation Management Tools
• Step 7: Article Screening
• Other Resources
• Interlibrary Loan (ILL)

A systematic review collects and analyzes all evidence that answers a specific research question. In a systematic review, a question needs to be clearly defined and have inclusion and exclusion criteria. In general, specific and systematic methods selected are intended to minimize bias. This is followed by an extensive search of the literature and a critical analysis of the search results. The reason why a systematic review is conducted is to provide a current evidence-based answer to a specific question that in turn helps to inform decision making. Check out the Centers for Disease Control and Prevention and Cochrane Reviews links to learn more about Systematic Reviews.

A systematic review can be combined with a meta-analysis. A meta-analysis is the use of statistical methods to summarize the results of a systematic review. Not every systematic review contains a meta-analysis. A meta-analysis may not be appropriate if the designs of the studies are too different, if there are concerns about the quality of studies, if the outcomes measured are not sufficiently similar for the result across the studies to be meaningful.

Centers for Disease Control and Prevention. (n.d.).  Systematic Reviews . Retrieved from  https://www.cdc.gov/library/researchguides/sytemsaticreviews.html

Cochrane Library. (n.d.).  About Cochrane Reviews . Retrieved from  https://www.cochranelibrary.com/about/about-cochrane-reviews

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

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• Next: Finding and Evaluating Existing Systematic Reviews >>
• Last Updated: Jun 30, 2023 1:07 PM
• URL: https://guides.library.ucmo.edu/c.php?g=1017739

Systematic Reviews and Meta Analysis

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

Cochrane Handbook

The Cochrane Handbook isn't set down to be a standard, but it has become the de facto standard for planning and carrying out a systematic review. Chapter 6, Searching for Studies, is most helpful in planning your review.

Scoping Reviews, JBI Manual for Evidence Synthesis

The Joanna Briggs Institute provides extensive guidance for their authors in producing both systematic and scoping reviews. Their chapter on scoping reviews provides a succinct overview of the scoping review process. JBI maintains a page with other materials for scoping reviewers.

Methods Guide for Effectiveness and Comparative Effectiveness Reviews

Very good chapters on conducting a review, most of which were published as articles in the Journal of Clincal Epidemiology.

Institutes of Medicine Standards for Systematic Reviews

The IOM standards promote objective, transparent, and scientifically valid systematic reviews. They address the entire systematic review process, from locating, screening, and selecting studies for the review, to synthesizing the findings (including meta-analysis) and assessing the overall quality of the body of evidence, to producing the final review report.

Systematic Reviews: CRD's Guidance for Undertaking Reviews in Health Care

Provides a succinct outline for carrying out systematic reviews and well as details about constructing a protocol, testing for bias, and other aspects of the review process. Includes examples.

Systematic reviews to support evidence-based medicine how to review and apply findings of healthcare research

Khan, K., & Royal Society of Medicine. 2nd ed,  2013. London [England]: Hodder Annold. [Harvard ID required]

Systematic reviews to answer health care questions

Nelson, H. (2014). Philadelphia: Wolters Kluwer Health/Lippincott Williams & Wilkins. [Harvard ID required]

Systematic Review Toolbox

Not a guide or standard but a clearinghouse for all things systematic review. Check here for templates, reporting standards, screening tools, risk of bias assessment, etc.

Reporting Standards: PRISMA and MOOSE

You will improve the quality of your review by adhering to the standards below. Using the approriate standard can reassure editors and reviewers that you have conscienciously carried out your review.

http://www.prisma-statement.org/ The Preferred Reporting Items for Systematic Reviews and Meta-Analyses is an evidence-based minimum set of items for reporting in systematic reviews and meta-analyses. A 27-item checklist,  PRISMA  focuses on randomized trials but can also be used as a basis for reporting systematic reviews of other types of research, particularly evaluations of interventions. PRISMA may also be useful for critical appraisal of published systematic reviews, although it is not a quality assessment instrument to gauge the quality of a systematic review.

Consider using PRISMA-P when completing your protocol. PRISMA-P is a 17-item checklist for elements considered essential in protocol for a systematic review or meta-analysis. The documentation contains an excellent rationale for completing a protocol, too.

Use PRISMA-ScR, a 20-item checklist, for reporting scoping reviews. The documentation provides a clear overview of scoping reviews.

Further Reading:

Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009 Jul 21;6(7):e1000097. Epub 2009 Jul 21. PubMed PMID: 19621072 .  

Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, Clarke M, Devereaux PJ, Kleijnen J, Moher D. The PRISMA statement for reporting  systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. 2009 Jul 21;6(7):e1000100. Epub 2009 Jul 21. PubMed PMID: 19621070 . 

Shamseer L, Moher D, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA; PRISMA-P Group. Preferred reporting items for systematic review andmeta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ. 2015 Jan 2;349:g7647. doi: 10.1136/bmj.g7647. PubMed PMID: 25555855 .

Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA; PRISMA-P Group. Preferred reporting items for systematic review andmeta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. 2015 Jan 1;4:1. doi: 10.1186/2046-4053-4-1. PubMed PMID: 25554246 .

Tricco AC, Lillie E, Zarin W, O'Brien KK, Colquhoun H, Levac D, Moher D, Peters MDJ, Horsley T, Weeks L, Hempel S, Akl EA, Chang C, McGowan J, Stewart L, Hartling L, Aldcroft A, Wilson MG, Garritty C, Lewin S, Godfrey CM, Macdonald MT, Langlois EV, Soares-Weiser K, Moriarty J, Clifford T, Tunçalp Ö, Straus SE. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann Intern Med. 2018 Oct 2;169(7):467-473. doi: 10.7326/M18-0850. Epub 2018 Sep 4. PMID: 30178033 .

Also published in the Annals of Internal Medicine, BMJ, and the Journal of Clinical Epidemiology.

MOOSE Guidelines

http://www.consort-statement.org/Media/Default/Downloads/Other%20Instruments/MOOSE%20Statement%202000.pdf Meta-analysis of Observational Studies in Epidemiology checklist contains specifications for reporting of meta-analyses of observational studies in epidemiology. Editors will expect you to follow and cite this checklist.  It refers to the  Newcastle-Ottawa Scale for assessing the quality of non-randomized studies, a method of rating each observational study in your meta-analysis.

Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, Moher D, Becker BJ, Sipe TA, Thacker SB. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000 Apr 19;283(15):2008-12. PubMed PMID:  10789670 .

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• Next: Review Protocols >>
• Last Updated: Jul 20, 2023 8:23 AM
• URL: https://guides.library.harvard.edu/meta-analysis

• Manuscript Review

Systematic Review VS Meta-Analysis

• 3 minute read
• 41.6K views

Table of Contents

How you organize your research is incredibly important; whether you’re preparing a report, research review, thesis or an article to be published. What methodology you choose can make or break your work getting out into the world, so let’s take a look at two main types: systematic review and meta-analysis.

Let’s start with what they have in common – essentially, they are both based on high-quality filtered evidence related to a specific research topic. They’re both highly regarded as generally resulting in reliable findings, though there are differences, which we’ll discuss below. Additionally, they both support conclusions based on expert reviews, case-controlled studies, data analysis, etc., versus mere opinions and musings.

What is a Systematic Review?

A systematic review is a form of research done collecting, appraising and synthesizing evidence to answer a particular question, in a very transparent and systematic way. Data (or evidence) used in systematic reviews have their origin in scholarly literature – published or unpublished. So, findings are typically very reliable. In addition, they are normally collated and appraised by an independent panel of experts in the field. Unlike traditional reviews, systematic reviews are very comprehensive and don’t rely on a single author’s point of view, thus avoiding bias.

Systematic reviews are especially important in the medical field, where health practitioners need to be constantly up-to-date with new, high-quality information to lead their daily decisions. Since systematic reviews, by definition, collect information from previous research, the pitfalls of new primary studies is avoided. They often, in fact, identify lack of evidence or knowledge limitations, and consequently recommend further study, if needed.

Why are systematic reviews important?

• They combine and synthesize various studies and their findings.
• Systematic reviews appraise the validity of the results and findings of the collected studies in an impartial way.
• They define clear objectives and reproducible methodologies.

What is a Meta-analysis?

This form of research relies on combining statistical results from two or more existing studies. When multiple studies are addressing the same problem or question, it’s to be expected that there will be some potential for error. Most studies account for this within their results. A meta-analysis can help iron out any inconsistencies in data, as long as the studies are similar.

For instance, if your research is about the influence of the Mediterranean diet on diabetic people, between the ages of 30 and 45, but you only find a study about the Mediterranean diet in healthy people and another about the Mediterranean diet in diabetic teenagers. In this case, undertaking a meta-analysis would probably be a poor choice. You can either pursue the idea of comparing such different material, at the risk of findings that don’t really answer the review question. Or, you can decide to explore a different research method (perhaps more qualitative).

Why is meta-analysis important?

• They help improve precision about evidence since many studies are too small to provide convincing data.
• Meta-analyses can settle divergences between conflicting studies. By formally assessing the conflicting study results, it is possible to eventually reach new hypotheses and explore the reasons for controversy.
• They can also answer questions with a broader influence than individual studies. For example, the effect of a disease on several populations across the world, by comparing other modest research studies completed in specific countries or continents.

Undertaking research approaches, like systematic reviews and/or meta-analysis, involve great responsibility. They provide reliable information that has a real impact on society. Elsevier offers a number of services that aim to help researchers achieve excellence in written text, suggesting the necessary amendments to fit them into a targeted format. A perfectly written text, whether translated or edited from a manuscript, is the key to being respected within the scientific community, leading to more and more important positions like, let’s say…being part of an expert panel leading a systematic review or a widely acknowledged meta-analysis.

Check why it’s important to manage research data .

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Systematic Reviews and Meta-Analyses

Lindsay s. uman.

1 Clinical Psychologist, IWK Health Centre, Halifax, Nova Scotia

With an ever-increasing plethora of studies being published in the health sciences, it is challenging if not impossible for busy clinicians and researchers alike to keep up with the literature. Reviews summarizing the outcomes of various intervention trials are therefore an extremely efficient method for obtaining the “bottom line” about what works and what doesn’t.

Key Terms Defined

Systematic reviews differ from traditional narrative reviews in several ways. Narrative reviews tend to be mainly descriptive, do not involve a systematic search of the literature, and thereby often focus on a subset of studies in an area chosen based on availability or author selection. Thus narrative reviews while informative, can often include an element of selection bias. They can also be confusing at times, particularly if similar studies have diverging results and conclusions. Systematic reviews, as the name implies, typically involve a detailed and comprehensive plan and search strategy derived a priori, with the goal of reducing bias by identifying, appraising, and synthesizing all relevant studies on a particular topic. Often, systematic reviews include a meta-analysis component which involves using statistical techniques to synthesize the data from several studies into a single quantitative estimate or summary effect size (Petticrew & Roberts, 2006). In contrast to traditional hypothesis testing which can give us information about statistical significance (i.e., did the intervention group differ from the control group) but not necessarily clinical significance (i.e., was this difference clinically meaningful or large), effect sizes measure the strength of the relationship between two variables, thereby providing information about the magnitude of the intervention effect (i.e., small, medium, or large). The type of effect size calculated generally depends on the type of outcome and intervention being examined as well as the data available from the published trials; however, some common examples include odds ratios (OR), weighted/standardized mean differences (WMD, SMD), and relative risk or risk ratios (RR). Although systematic reviews are published in academic forums, there are also organizations and databases specifically developed to promote and disseminate them. For example, the Cochrane Collaboration ( www.cochrane.org ) is a widely recognized and respected international and not-for-profit organization that promotes, supports, and disseminates systematic reviews and meta-analyses on the efficacy of interventions in the health care field.

8 Stages of a Systematic Review and Meta Analysis

1. formulate the review question.

The first stage involves defining the review question, forming hypotheses, and developing a review title. It is often best to keep titles as short and descriptive as possible, by using the following formula: Intervention for population with condition (e.g., Dialectical behavior therapy for adolescent females with borderline personality disorder). Reviews published with the Cochrane Collaboration do not need to be identified as such, but reviews published in other sources should also indicate in the title that they represent a systematic review and/or meta-analysis. If authors chose to conduct their review through the Cochrane Collaboration, they will also be required to register their title to the appropriate review group, which in essence “saves their spot” for this topic and provides access to further Cochrane support (e.g., assistance running search strategies).

2. Define inclusion and exclusion criteria

The Cochrane acronym PICO (or PICOC) which stands for population, intervention, comparison, outcomes (and context) can be useful to ensure that one decides on all key components prior to starting the review. For example, authors need to decide a priori on their population age range, conditions, outcomes, and type(s) of interventions and control groups. It is also critical to operationally define what types of studies to include and exclude (e.g., randomized controlled trials-RCTs only, RCTs and quasi-experimental designs, qualitative research), the minimum number of participants in each group, published versus unpublished studies, and language restrictions. For Cochrane Reviews, this information gets prepared, peer-reviewed, and published in a Protocol format first, which is then replaced with the full Review once it is completed.

3. Develop search strategy and locate studies

This is the stage where a reference librarian can be extremely helpful in terms of helping to develop and run electronic searches. Generally, it is important to come up with a comprehensive list of key terms (i.e., “MeSH” terms) related to each component of PICOC to be able to identify all relevant trials in an area. For example, if the age range is 13–18 year old females, search terms may need to include any of the following: adolescents, teenagers, youth, female, women, girls, etc. The key in developing an optimal search strategy is to balance sensitivity (retrieving a high proportion of relevant studies) with specificity (retrieving a low proportion of irrelevant studies). Searches generally include several relevant electronic databases but can also include checking article reference lists, hand-searching key journals, posting requests on listservs, and personal communication with experts or key researchers in the field.

4. Select studies

Once a comprehensive list of abstracts has been retrieved and reviewed, any studies appearing to meet inclusion criteria would then be obtained and reviewed in full. This process of review is generally done by at least two reviewers to establish inter-rater reliability. It is recommended that authors keep a log of all reviewed studies with reasons for inclusion or exclusion, and it may be necessary to contract study authors to obtain missing information needed for data pooling (e.g., means, standard deviations). Translations may also be required.

5. Extract data

It can be helpful to create and use a simple data extraction form or table to organize the information extracted from each reviewed study (e.g., authors, publication year, number of participants, age range, study design, outcomes, included/excluded). Data extraction by at least two reviewers is important again for establishing inter-rater reliability and avoiding data entry errors.

6. Assess study quality

There has been a movement in recent years to better assess the quality of each RCT included in systematic reviews. Although there are brief check-lists available such as the 5-point Oxford Quality Rating Scale ( Jadad et al., 1996 ) commonly used in Cochrane reviews, this measure is heavily influenced by double-blinding which is appropriate for drug trials but generally not for psychological or non-pharmacological interventions. There are other more comprehensive recommended guidelines and standards available such as the Consolidated Standards of Reporting Trials (CONSORT Statement; http://www.consort-statement.org/ ), as well as articles providing recommendations for improving quality in RCTs and meta-analyses for psychological interventions (e.g., Uman et al., 2010 ).

7. Analyze and interpret results

There are various statistical programs available to calculate effects sizes for meta-analyses, such as the Review Manager (RevMan) program endorsed by the Cochrane Collaboration. Effect sizes are stated along with a 95 % confidence interval (CI) range, and presented in both quantitative format and graphical representation (e.g., forest plots). Forest plots visually depict each trial as a horizontal diamond shape with the middle representing the effect size (e.g., SMD) and the end points representing both ends of the CI. These diamonds are presented on a graph with a centre line representing the zero mark. Often the left side of the graph (< zero) represents the side favoring treatment, while the right side (> zero) represents the side favouring the control condition. At the bottom of the graph is a summary effect size or diamond representing all of the individual studies pooled together. Ideally, we would like to see this entire diamond (effect size and both anchors of the CI) falling below zero, indicating that the intervention is favoured over the control. In addition, most programs also calculate a heterogeneity value to indicate whether the individual studies are similar enough to compare. In this case, it is preferable to have non-significant findings for heterogeneity. It is still possible to pool studies when significant heterogeneity exists, although these results should be interpreted with caution or reasons for the heterogeneity should be explored. As with all papers, the last step in the writing process involves summarize the findings, and providing recommendations for clinical work (e.g., which interventions are efficacious, for whom, and under what conditions) and research (e.g., what areas/topics/interventions require further research.

8. Disseminate findings

Although reviews conducted through the Cochrane Collaboration get published in the online Cochrane Database of Systematic Reviews, they are often quite lengthy and detailed. Thus, it is also possible and encouraged to publish abbreviated versions of the review in other relevant academic journals, as long as they are clearly indicated as such (e.g., Uman et al., 2008 ). Plain language summaries for families and patients are also commonly provided, and there is an expectation that reviews should be regularly updated to ensure they are always up-to-date and relevant. Indeed, participating in a review update or joining a well-established review team, can be a helpful way of getting involved in the systematic review process.

• Jadad AR, Moore RA, Carroll D, Jenkinson C, Reynolds DJM, Gavaghan DJ, et al. Assessing the quality of reports of randomized clinical trials: Is blinding necessary? Controlled Clinical Trials. 1996; 17 :1–12. [ PubMed ] [ Google Scholar ]
• Petticrew M, Roberts H. Systematic reviews in the social sciences: A practical guide. Malden, MA: Blackwell Publishing; year. [ Google Scholar ]
• Uman LS, Chambers CT, McGrath PJ, Kisely S. Assessing the quality of randomized controlled trials examining psychological interventions for pediatric procedural pain: Recommendations for quality improvement. Journal of Pediatric Psychology. 2010; 35 :693–703. [ PubMed ] [ Google Scholar ]
• Uman LS, Chambers CT, McGrath PJ, Kisely S. A systematic review of randomized controlled trials examining psychological interventions for needle-related procedural pain and distress in children and adolescents: An abbreviated Cochrane review. Journal of Pediatric Psychology. 2008; 33 :842–854. [ PMC free article ] [ PubMed ] [ Google Scholar ]

Assessment of correlation between conventional anthropometric and imaging-derived measures of body fat composition: a systematic literature review and meta-analysis of observational studies

Affiliations.

• 1 Cancer Epidemiology Unit, Richard Doll Building, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
• 2 MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Big Data Institute, Old Road Campus, Oxford, OX3 7LF, UK.
• 3 Cancer Epidemiology Unit, Richard Doll Building, Nuffield Department of Population Health, University of Oxford, Oxford, UK. [email protected].
• 4 MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Big Data Institute, Old Road Campus, Oxford, OX3 7LF, UK. [email protected].
• PMID: 37710156
• PMCID: PMC10503139
• DOI: 10.1186/s12880-023-01063-w

Background: In studies of the association of adiposity with disease risk, widely used anthropometric measures of adiposity (e.g. body-mass-index [BMI], waist circumference [WC], waist-hip ratio [WHR]) are simple and inexpensive to implement at scale. In contrast, imaging-based techniques (e.g. magnetic resonance imaging [MRI] and dual x-ray absorptiometry [DXA]) are expensive and labour intensive, but can provide more accurate quantification of body fat composition. There is, however, limited evidence about the relationship between conventional and imaging-derived measures of adiposity.

Methods: We searched Scopus and Web of Science for published reports in English of conventional versus imaging-derived measurements of adiposity. We identified 42 articles (MRI = 22; DXA = 20) that met selection criteria, involving 42,556 (MRI = 15,130; DXA = 27,426) individuals recruited from community or hospital settings. Study-specific correlation coefficients (r) were transformed using Fisher's Z transformation, and meta-analysed to yield weighted average correlations, both overall and by ancestry, sex and age, where feasible. Publication bias was investigated using funnel plots and Egger's test.

Results: Overall, 98% of participants were 18 + years old, 85% male and 95% White. BMI and WC were most strongly correlated with imaging-derived total abdominal (MRI-derived: r = 0.88-; DXA-derived: 0.50-0.86) and subcutaneous abdominal fat (MRI-derived: 0.83-0.85), but were less strongly correlated with visceral abdominal fat (MRI-derived: 0.76-0.79; DXA-derived: 0.80) and with DXA-derived %body fat (0.76). WHR was, at best, strongly correlated with imaging-derived total abdominal (MRI-derived: 0.60; DXA-derived: 0.13), and visceral abdominal fat (MRI-derived: 0.67; DXA-derived: 0.65), and moderately with subcutaneous abdominal (MRI-derived: 0.54), and with DXA-derived %body fat (0.58). All conventional adiposity measures were at best moderately correlated with hepatic fat (MRI-derived: 0.36-0.43). In general, correlations were stronger in women than in men, in Whites than in non-Whites, and in those aged 18 + years.

Conclusions: In this meta-analysis, BMI and WC, but not WHR, were very strongly correlated with imaging-derived total and subcutaneous abdominal fat. By comparison, all three measures were moderately or strongly correlated with imaging-based visceral abdominal fat, with WC showing the greatest correlation. No anthropometric measure was substantially correlated with hepatic fat. Further larger studies are needed to compare these measures within the same study population, and to assess their relevance for disease risks in diverse populations.

Keywords: Adiposity; Anthropometric; Correlation; DXA; Imaging; MRI; meta-analysis.

© 2023. BioMed Central Ltd., part of Springer Nature.

Publication types

• Meta-Analysis
• Systematic Review
• Research Support, Non-U.S. Gov't
• Adipose Tissue* / diagnostic imaging
• Anthropometry
• Body Composition*
• Body Mass Index
• Diagnostic Imaging

Grants and funding

• CRUK_/Cancer Research UK/United Kingdom

• Open supplemental data
• Reference Manager
• Simple TEXT file

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Systematic review article, anti-inflammatory and antioxidant activity of ursolic acid: a systematic review and meta-analysis.

• 1 College of Animal Science and Technology, Hebei Agricultural University, Baoding, China
• 2 Hebei Research Institute of Microbiology Co., Ltd., Baoding, China

Introduction: There is currently evidence suggesting that ursolic acid may exert a favorable influence on both anti-inflammatory and antioxidant impact. Nevertheless, the anti-inflammatory and antioxidant activities of ursolic acid have not been systematically evaluated. Consequently, this study aims to conduct a systematic review and meta-analysis regarding the impact of ursolic acid on markers of inflammatory and antioxidant activity in both animal models and in vitro systems.

Methods: The search encompassed databases such as PubMed, Web of Science, Google Scholar, and ScienceDirect, up until May 2023. All eligible articles in English were included in the analysis. Standard mean difference (SMD) was pooled using a random-effects model, and the included studies underwent a thorough assessment for potential bias.

Results: The final review comprised 31 articles. In disease-model related studies, animal experiments have consistently shown that ursolic acid significantly reduced the levels of inflammatory parameters IL-1β, IL-6 and TNF-α in mouse tissues. In vitro studies have similarly showed that ursolic acid significantly reduced the levels of inflammatory parameters IL-1β, IL-6, IL-8 and TNF-α. Our results showed that ursolic acid could significantly elevate SOD and GSH levels, while significantly reducing MDA levels in animal tissues. The results of in vitro studies shown that ursolic acid significantly increased the level of GSH and decreased the level of MDA.

Discussion: Findings from both animal and in vitro studies suggest that ursolic acid decreases inflammatory cytokine levels, elevates antioxidant enzyme levels, and reduces oxidative stress levels (graphical abstract). This meta-analysis furnishes compelling evidence for the anti-inflammatory and antioxidant properties of ursolic acid.

1 Introduction

Inflammation and oxidative stress play pivotal roles in the pathophysiology of numerous prevalent diseases, including diabetes, cardiovascular diseases, metabolic disorders, and cancer ( Valko et al., 2007 ; Sarapultsev et al., 2015 ; Nakamura and Smyth, 2017 ; Burgos-Morón et al., 2019 ). In recent years, research focused on natural extracts and their bioactive constituents to mitigate inflammatory damage and ameliorate oxidative stress has gradually increased. These investigations consistently underscore the significant research and practical implications of natural extracts in mitigating the detrimental effects of inflammation and oxidative stress and reducing disease incidence ( Liu et al., 2016 ; Moudgil and Venkatesha, 2022 ).

Triterpenoids are widely distributed throughout the plant kingdom, existing either as free acids or saponins in the form of sapogenins. They belong to a group of compounds long recognized for their diverse biological effects ( Máñez et al., 1997 ). Ursolic acid, a naturally occurring pentacyclic triterpene carboxylic acid, is predominantly found in various plants, including rosemary, chasteberry, hawthorn, cranberry, and loquat leaves ( Kashyap et al., 2016 ). Despite once being considered biologically inactive, it has garnered increasing interest in recent years due to its pharmacological potential ( Kim et al., 2015 ; Kashyap et al., 2016 ; López-Hortas et al., 2018 ). Studies have demonstrated that ursolic acid has a broad spectrum of biological activities, including its ability to combat tumor cells and modulate lipid metabolism ( Woźniak et al., 2015 ). Several studies have collectively affirmed the anti-inflammatory and antioxidant properties of ursolic acid ( Lin et al., 2017 ; Li et al., 2018a ). However, while several narrative review studies have explored the pharmacological effects of ursolic acid, they have not undertaken quantitative synthesis and have solely incorporated published findings ( Habtemariam, 2019 ; Nguyen et al., 2021 ; Luan et al., 2022 ; Namdeo et al., 2023 ). In addition, a review of the anti-inflammatory effect of ursolic acid showed that the effects of ursolic acid on normal cells and tissues are occasionally pro-inflammatory, portraying it as a double-edged sword with both positive and negative consequences ( Ikeda et al., 2008 ). Collectively, these studies underscore the need for a comprehensive assessment of the anti-inflammatory and antioxidant effects of ursolic acid, as well as its performance across different health conditions within the body. Systematic reviews and meta-analyses are aimed at reducing the bias of narrative reviews by identifying, appraising, and synthesizing all relevant literature, following a transparent and reproducible methodology to obtain the most reliable evidence.

Therefore, we conducted a comprehensive systematic review and meta-analysis encompassing all relevant in vitro and in vivo studies. We examined the influence of ursolic acid on the body’s health status and its role in chronic inflammatory and oxidative stress-related pathological conditions. Our objective was to ascertain whether ursolic acid possesses the capability to modulate inflammatory responses and oxidative stress.

2.1 Literature search strategy and selection criteria

This meta-analysis strictly followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) ( Moher et al., 2015 ).

Three researchers independently searched PubMed, Web of Science, Google Scholar and ScienceDirect (before 6 May 2023). We restricted the language to English. The MeSH term “ursolic acid, or any name of ursolic acid, in combination with “antioxidants” or “anti-inflammatory” to identify eligible studies.

2.2 Inclusion and exclusion criteria

The search results from the four databases (PubMed, Web of Science, Google Scholar and ScienceDirect) were pooled in EndNote (Version X9). Duplicate publications ( n = 1,407) were subsequently removed. For inclusion in our meta-analysis, studies had to meet the following criteria: 1) manuscripts published in English in peer-reviewed journals, 2) experimental trials and randomized control trials (RCTs), 3) studies including ursolic acid treatment and negative control groups and use of ursolic acid to treat chronic inflammatory and oxidative stress system lesions versus intervention control group, and 4) reporting of anti-inflammatory or antioxidant activity.

The exclusion criteria were defined as follows: 1) the major content of the supplement was not ursolic acid, 2) studies lacking data on anti-inflammatory or antioxidant activity, and 3) studies that were not of RCTs. Following these criteria, we conducted a selective screening of eligible studies for inclusion in the analysis.

2.3 Data extraction

The information extracted from the included studies was as follows: first author, year, country, experimental subject, sample, sample size, intervention, dosage, duration, and primary outcomes. Primary outcomes include: interleukin-1beta (IL-1β), tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-8 (IL-8), interleukin-10 (IL-10), glutathione (GSH), glutathione peroxidase (GPx), catalase (CAT), superoxide dismutase (SOD), malondialdehyde (MDA). When results were available only in graphical format, data were extracted using Origin (Version 2022).

2.4 Study quality assessment

Two investigators (M.Z. and F.Y.W.) performed independent study quality assessment according to the criteria provided in the Consolidated Standards of Reporting Trials statement ( Moher et al., 2015 ) and the Cochrane Collaboration’s tool for assessing risk of bias ( Higgins et al., 2011 ). The assessment items included random sequence generation (selection bias), allocation concealment (selection bias), blinding of participants and personnel (performance bias), blinding of outcome assessment (detection bias), incomplete outcome data (attrition bias), selective reporting (reporting bias), and other bias. The divergences were resolved by the third investigator (Z.H.T.).

2.5 Statistical analysis

2.5.1 meta-analysis.

The statistical analysis was performed with R 4.1.2 in the meta package ( Balduzzi et al., 2019 ). The random-effects model was used to estimate the effect size and 95% confidence interval (CI) for each trait ( Riley et al., 2011 ; Eng et al., 2014 ). The effect size of ursolic acid was expressed as standard mean difference (SMD). We used the I 2 statistic to quantitatively measure the heterogeneity in our analysis. Heterogeneity between-study variability was assessed using the I 2 : no heterogeneity, I 2 ≤ 25%; low heterogeneity, 25% < I 2 ≤ 50%; moderate heterogeneity, 50% < I 2 ≤ 75%; and high heterogeneity, I 2 > 75% ( Higgins et al., 2003 ).

2.5.2 Meta-regression analysis

We conducted meta-regression analyses to elucidate significant heterogeneity ( p < 0.05) or beyond a moderate level ( I 2 > 50%) ( Higgins et al., 2003 ). To avoid a false positive result, the regression analysis was applied only to groups with more than 10 records. Meta-regression analyses were conducted using effect sizes (SMD) for each outcome ( P SMD <0.05, I 2 > 50%, n ≥ 10) as the dependent variable to examine heterogeneity sources of meta-analysis.

2.5.3 Subgroup categorization and analysis

We conducted subgroup analyses to elucidate significant heterogeneity ( p < 0.05) or beyond a moderate level ( I 2 > 50%) ( Higgins et al., 2003 ). The sub-groups were divided based on the original categories and practical implications where necessary.

2.5.4 Publication bias

Publication bias was evaluated using Egger’s tests ( n ≥ 5), for which the significance level was defined at p < 0.05 ( Egger et al., 1997 ).

3.1 Selection of studies

The process and results of the publication search and selection are shown in Figure 1 . A total of 2,942 articles were identified, with 695 from PubMed, 1,859 from Web of Science, 94 from Google Scholar, and 294 from ScienceDirect. After removing duplicate articles, we proceeded to read the remaining 1,535 titles and abstracts. After excluding published in non-English, reviews, letters and those whose theme did not match the criteria of this study, 103 articles remained. An additional 72 articles were excluded after a full-text review based on previous protocols. Finally, 31 articles were included in this meta-analysis. The main characteristics of the 31 studies are provided in Supplementary Tables S1, S2 . The bias risks for each study and overall are shown in Figure 2 , Figure 3 .

FIGURE 1 . The flowchart of the search strategy and selection of eligible studies.

FIGURE 2 . Risk of bias summary depicting authors’ judgements about each risk of bias item for each included study.

FIGURE 3 . Risk of bias graph depicting review authors’ judgements about each risk of bias item presented as percentages across all included studies.

3.2 Animal studies

3.2.1 the effect of use of ursolic acid to treat chronic inflammatory and oxidative stress system lesions.

In animal studies, we analyzed the effect of the use of ursolic acid to treat chronic inflammatory and oxidative stress system lesions on inflammatory markers. As shown in Figure 4 , ursolic acid significantly reduced the content of IL-1β (SMD = −4.07, 95%CI: −5.59 to −2.54, P SMD < 0.0001, I 2 = 79%), IL-6 (SMD = −4.53, 95%CI: −6.83 to −2.23, P SMD < 0.0001, I 2 = 86%) and TNF-α (SMD = −2.65, 95%CI: −3.67 to −1.63, P SMD < 0.0001, I 2 = 75%).

FIGURE 4 . Characteristic of animal studies regarding the effect of use of ursolic acid to treat chronic inflammatory and oxidative stress system lesions on inflammatory markers. Interleukin-1beta (IL-1β) (A) , Interleukin-6 (IL-6) (B) and (Tumor necrosis factor-alpha) TNF-α (C) .

We analyzed the effects of the use of ursolic acid to treat chronic inflammatory and oxidative stress system lesions on oxidative stress markers. As shown in Figure 5 , ursolic acid significantly increased the content of SOD (SMD = 3.62, 95%CI: 1.97 to 5.26, P SMD < 0.0001, I 2 = 86%) and GSH (SMD = 8.01, 95%CI: 4.41 to 11.61, P SMD < 0.0001, I 2 = 86%). Ursolic acid significantly reduced the content of MDA (SMD = −2.28, 95%CI: −2.91 to −1.66, P SMD < 0.0001, I 2 = 71%).

FIGURE 5 . Characteristic of animal studies regarding the effect of use of ursolic acid to treat chronic inflammatory and oxidative stress system lesions on antioxidant markers. Malondialdehyde (MDA) (A) and Superoxide dismutase (SOD) (B) and Glutathione (GSH) (C) .

We conducted meta-regression analyses, incorporating covariates such as dosage (mg/kg), duration (d) and intervention. The results showed that dosage had a significant impact on IL-1β ( p = 0.026), while duration significantly influenced SOD ( p = 0.002) ( Table 1 ). However, the intervention had no significant effect on IL-1β, MDA TNF-α and SOD ( p > 0.05). Furthermore, we conducted a sub-group analysis based on dosage categories (Low: <25 mg/kg; Middle: 25–50 mg/kg; High: > 50 mg/kg) and duration (Short (≤ 14 days); Long: >14 days). The sub-group analysis indicated that all three dosage groups of ursolic acid had significant effects on IL-1β ( P SMD < 0.05), and there was a significant difference among the three subgroups (Q = 12.05, p = 0.002), the low-dosage group had the best effect (SMD = −5.91, 95%CI: −8.17 to −3.65, P SMD < 0.0001) ( Table 2 ). Moderate heterogeneity was observed in the low-dosage group ( I 2 = 68%, p < 0.05), high heterogeneity was observed in the middle-dosage group ( I 2 = 77%, p < 0.05), and no heterogeneity was observed in the high-dosage group ( I 2 = 0%, p = 0.51). All two duration groups of ursolic acid had significant effects on SOD ( P SMD < 0.05), but there was no significant difference between the two subgroups ( p = 0.26). No heterogeneity was observed in the short-duration group ( I 2 = 49%, p = 0.16), and high heterogeneity was observed in the long-duration group ( I 2 = 86%, p < 0.05). Additionally, the results of Egger’s test indicated some evidence of publication bias in IL-1β, IL-6, MDA, SOD, TNF-α and GSH( p < 0.05) ( Table 3 ).

TABLE 1 . The summary of the meta-regression analysis.

TABLE 2 . The summary of the sub-group analysis.

TABLE 3 . The summary of Egger’s tests.

3.3 In vitro studies

3.3.1 the effect of ursolic acid on anti-inflammatory and antioxidant parameters.

As shown in Figure 6 , ursolic acid did not significantly affect IL-1β, IL-6, SOD, GSH, GPx and CAT in healthy cells ( P SMD > 0.05). The Egger’s test results indicated no evidence of publication bias in IL-1β and IL-6 ( p > 0.05).

FIGURE 6 . Characteristic of in vitro studies regarding the effect of ursolic acid on inflammatory and antioxidant markers. Interleukin-1beta (IL-1β) (A) , Interleukin-6 (IL-6) (B) , Superoxide dismutase (SOD) (C) , Glutathione (GSH) (D) , Glutathione peroxidase (GPx) (E) and Catalase (CAT) (F) .

3.3.2 The effect of use of ursolic acid to treat chronic inflammatory and oxidative stress system lesions

We conducted an analysis to evaluate the impact of ursolic acid in treating chronic inflammatory and oxidative stress system lesions on inflammatory markers within cells. As shown in Figure 7 , ursolic acid significantly reduced the content of IL-1β (SMD = −5.89, 95%CI: −8.24 to −3.54, P SMD < 0.0001, I 2 = 60%), IL-6 (SMD = −4.64, 95%CI: −6.14 to −3.14, P SMD < 0.0001, I 2 = 59%), IL-8 (SMD = −6.43, 95%CI: −8.91 to −3.94, P SMD < 0.0001, I 2 = 53%) and TNF-α (SMD = −2.46, 95%CI: −3.26 to −1.67, P SMD < 0.0001, I 2 = 45%).

FIGURE 7 . Characteristic of in vitro studies regarding the effect of use of ursolic acid to treat chronic inflammatory and oxidative stress system lesions on inflammatory markers. Interleukin-1beta (IL-1β) (A) , Interleukin-6 (IL-6) (B) , Interleukin-8 (IL-8) (C) and Tumor necrosis factor-alpha (TNF-α) (D) .

We analyzed the effects of the use of ursolic acid to treat chronic inflammatory and oxidative stress system lesions on oxidative stress markers in cells. As shown in Figure 8 , ursolic acid did not significantly affect withers SOD, GPx and CAT ( P SMD > 0.05). Ursolic acid significantly reduced the content of MDA (SMD = −7.16, 95%CI: −9.04 to −5.29, P SMD < 0.0001, I 2 = 6%). Ursolic acid significantly increased the content of GSH (SMD = 2.85, 95%CI: 2.02 to 3.69, P SMD < 0.0001, I 2 = 27%).

FIGURE 8 . Characteristic of in vitro studies regarding the effect of use of ursolic acid to treat chronic inflammatory and oxidative stress system lesions on antioxidant markers. Superoxide dismutase (SOD) (A) , Malondialdehyde (MDA) (B) , Glutathione (GSH) (C) , Glutathione peroxidase (GPx) (D) and Catalase (CAT) (E) .

We performed meta-regression analyses, including two covariates: dosage (μM) and duration (h). The results revealed that dosage had a significant effect on IL-8 ( p = 0.004) but no significant effect on IL-1β, IL-6 and TNF-α ( p > 0.05). On the other hand, duration had a significant effect on IL-1β ( p < 0.0001) but no significant effect on IL-6, IL-8 and TNF-α ( p > 0.05) ( Table 1 ). Subsequently, we conducted sub-group analyses for these two covariates, with dosage categorized as Low: <10 μM, Middle: 10–19 μM, High: >19 μM; and duration as Short: <20 h, Middle: 20–40 h, Long: >40 h). Sub-group analysis indicated that all three duration groups of ursolic acid had significant effects on IL-1β ( P SMD <0.05), Notably, there was a significant difference among the three subgroups (Q = 18.56, p < 0.0001), with the long-duration group demonstrating the most favorable effect (SMD = −10.28, 95%CI: −15.80 to −4.76, P SMD < 0.0001) ( Table 2 ). No heterogeneity was observed in three duration groups (Short: I 2 = 45%, Middle: I 2 = 0%, Long: I 2 = 0%; p > 0.05). Furthermore, the sub-group analysis indicated that all three dosage groups of ursolic acid had significant effects on IL-8 ( P SMD <0.05), Similarly, there was a significant difference among the three subgroups (Q = 6.09, p = 0.048), with the high dosage group had the best effect (SMD = −14.00, 95%CI: −21.15 to −6.86, P SMD = 0.0001) ( Table 2 ). No heterogeneity was observed in three dosage groups (Short: I 2 = 48%, Middle: I 2 = 0%, Long: I 2 = 38%; p > 0.05). Finally, the results of Egger’s test indicated some evidence of publication bias in IL-1β, IL-6, IL-8, IL-10, MDA and TNF-α ( p < 0.05) ( Table 3 ), while no evidence of publication bias was found in SOD, GSH, GPx and CAT ( p > 0.05).

4 Discussion

This meta-analysis aims to comprehensively evaluate the impact of ursolic acid on enhancing anti-inflammatory and antioxidant functions while identifying potential influencing factors on effect size. The findings hold substantial potential for optimizing the application of ursolic acid, which carries significant implications for preventing and treating diseases related to inflammatory and oxidative stress systems. Distinguished from previous studies, our systematic review encompassed multiple databases and, as far as possible, conducted quantitative syntheses. To the best of our knowledge, this is currently a rare comprehensive meta-analysis of this issue. This systematic review and meta-analysis of 31 trials suggests that ursolic acid has a significant beneficial effect in the treatment of inflammatory and oxidative stress system diseases.

In the context of an inflammatory response, there is a noticeable increase in the expression and release of pro-inflammatory cytokines. The excessive production of these inflammatory factors stands as a primary driver of tissue damage. Among the key pro-inflammatory cytokines, IL-1 and TNF-α occupy prominent roles. TNF-α, as the initiating cytokine in the inflammatory process, triggers cascading effects that stimulate the upregulation of other inflammatory factors such as IL-1 and IL-6, thereby amplifying the overall inflammatory response ( Dinarello, 2005 ; Hovhannisyan et al., 2011 ; Bent et al., 2018 ; Pandolfi et al., 2020 ; Bernhard et al., 2021 ; van Loo and Bertrand, 2023 ). In disease-model-related studies, animal experiments have consistently shown that ursolic acid significantly reduced the levels of inflammatory parameters IL-1β, IL-6 and TNF-α in mouse tissues. In vitro studies have similarly showed that ursolic acid significantly reduced the levels of inflammatory parameters IL-1β, IL-6, IL-8 and TNF-α. These findings collectively support the notion that ursolic acid significantly inhibits inflammatory processes. In addition, it is plausible to assert that cells and animals experiencing inflammatory responses may benefit more from ursolic acid compared to healthy states. This observation might also be attributed to the frequent inclusion of ursolic acid in studies aimed at preventing and treating inflammatory diseases. In addition, the high consistency of results from animal and cellular studies further supports the anti-inflammatory activity of ursolic acid.

Antioxidant defense systems exist in most organisms, effectively scavenging free radicals and ROS. The redox dynamic balance is determined by the balance between the production of free radicals and ROS and their elimination by various antioxidants. Key enzymatic antioxidants in animals include SOD, GSH, GPx, and CAT ( Fang et al., 2002 ). When there is an increased production of oxygen radicals or oxidizing substances in the body beyond the antioxidant defense mechanism of the cells, it results in cellular oxidative stress ( Sarapultsev et al., 2015 ). MDA a byproduct of lipid peroxidation, serves as an indicator of cellular damage and a biomarker for oxidative stress severity ( Tangvarasittichai, 2015 ). Several natural extracts, including vitamin C, vitamin E, flavonoids and polyphenols have demonstrated their ability to bolster the body’s innate defense system and maintain redox homeostasis ( Rubió et al., 2013 ). Our results showed that ursolic acid could significantly elevate SOD and GSH levels, while significantly reducing MDA levels in animal tissues. The results of in vitro studies shown that ursolic acid significantly increased the level of GSH and decreased the level of MDA. Hence, it is plausible to consider ursolic acid as a non-enzymatic antioxidant capable of fortifying cellular and organismal antioxidant defenses, thereby mitigating oxidative stress.

Interestingly, a previous study showed that ursolic acid increased IL-1β levels in healthy mice in a concentration- and time-dependent manner ( Ikeda et al., 2007a ). A high dosage of ursolic acid was associated with increased IL-1β production in healthy mice ( Ikeda et al., 2007b ). Notably, the impact of ursolic acid on IL-1β appeared to show opposite results in healthy versus diseased mice. While the exact reason for this discrepancy remains unclear, the aforementioned study suggests that the dose and duration of ursolic acid treatment could be decisive factors in its effects. Therefore, through regression analysis and subgroup analysis, we explored whether these two factors influence the effect of ursolic acid treatment and attempted to identify the source of heterogeneity. Ultimately, we identified dosage as a crucial factor affecting ursolic acid’s ability to reduce IL-1 levels in animals. Lower doses (< 25 mg/kg) yielded a more potent therapeutic effect, whereas no therapeutic effect was found in the high-dosage group (>50 mg/kg). However, high heterogeneity remained in the low and intermediate dose groups, indicating the existence of other factors that may modulate ursolic acid’s anti-inflammatory effects. In conclusion, ursolic acid possesses a robust anti-inflammatory effect, with lower doses being more efficacy, suggesting that ursolic acid has a complex mechanism of action and that pro-inflammatory effects may arise at higher doses.

In an investigation into the in vitro study, duration significantly affected IL-1β levels, with longer durations (> 40 h) being able to reduce IL-1β levels more substantially. Notably, we did not observe heterogeneity in any of the three subgroups, suggesting that varying durations may be the primary source of heterogeneity. Consequently, it appears that a longer duration is a critical factor contributing to the anti-inflammatory effects of ursolic acid in vitro . Interestingly, we also noted inconsistencies between factors affecting in vivo and in vitro studies. These disparities may be attributed to factors such as the bioavailability of ursolic acid, which could help elucidate these differences. In our in vitro investigations, we observed that dose was the main factor influencing the effect of ursolic acid on IL-8 production, where high doses (> 19 μM) were able to produce greater therapeutic effects, and the low heterogeneity in the three subgroups suggests that different doses were a source of heterogeneity across these studies. Additionally, our observations indicated that ursolic acid significantly reduces SOD levels in animal studies, whereas no consistent effect was observed in in vitro studies. This inconsistency may be attributed to differences between in vitro and in vivo biological modeling systems.

The precise mechanisms underlying the effects of ursolic acid supplementation on markers of inflammation and oxidative stress remain elusive. However, we have suggested some potential mechanisms for ursolic acid and markers of inflammation and oxidative stress in our meta-analysis. Major molecular targets of Inflammatory diseases include pro-inflammatory cytokines and their receptors, nuclear factor kappa B (NF-κB), c-Jun-N-terminal kinases (JNK) and mitogen-activated protein kinases (MAPK) ( Gautam and Jachak, 2009 ). Ursolic acid can suppress NF-κB activation by inhibiting IκB kinase and p65 phosphorylation ( Shishodia et al., 2003 ). Notably, NF-κB regulates the expression of genes associated with proinflammatory cytokines ( Sun, 2017 ; Yu et al., 2020 ). Thus, the anti-inflammatory effect of ursolic acid may be through the inhibition of NF-κB to reduce inflammatory markers. Another pathway may involve ursolic acid exerting its anti-inflammatory effects by inhibiting the MAPK signaling pathway ( Ma et al., 2014 ). Regarding its antioxidant function, ursolic acid may operate by scavenging free radicals ( Shih et al., 2004 ; Li et al., 2018b ). In addition, ursolic acid has been shown to inhibit oxidative stress through the liver kinase B1 (LKB1)-activated protein kinase (AMPK) signaling pathway ( Yang et al., 2015 ).

Ursolic acid demonstrates the potential to reduce the marker levels of inflammation and oxidative stress, making it a valuable candidate for both preventive measures and adjunctive treatments in cases of chronic inflammation and oxidative stress-related damage. Given that chronic inflammation and oxidative stress tend to escalate with age and are implicated in the onset of numerous age-related diseases, the versatility of ursolic acid makes it particularly promising, especially for elderly individuals. Ursolic acid has been proposed as a therapeutic option for addressing conditions such as rheumatism, arthritis, and metabolic disorders ( Kim et al., 2015 ; Nguyen et al., 2021 ). Moreover, considering that older adults often contend with multiple medical conditions necessitating polypharmacy, ursolic acid’s low potential for drug-drug interactions renders it even more advantageous. Consequently, older adults grappling with chronic inflammatory and oxidative stress-related issues stand to benefit significantly from the potential therapeutic effects of ursolic acid.

While we aimed for a comprehensive review in this study, it is essential to acknowledge its limitations: 1) We did not assess clinical outcomes and there are no ongoing randomized controlled trials assessing the effect of ursolic acid on clinical outcomes. 2) Despite our efforts to mitigate heterogeneity through regression and subgroup analyses, substantial heterogeneity persisted in certain parameters due to the limited number of included studies. Exclusion of individual studies did not significantly alter this heterogeneity. 3) In the majority of experimental studies, there was a lack of information regarding blinding procedures for participants, personnel, and outcome assessment. This omission introduces uncertainty regarding the risk of bias, particularly in terms of performance and detection bias. The strength of this study lies in its comprehensive systematic review of all relevant animal and in vitro studies. Ursolic acid, while promising, remains an unproven natural compound. Nonetheless, our findings underscore the potential role of ursolic acid in anti-inflammatory processes and in enhancing antioxidant defense mechanisms.

5 Conclusion

This meta-analysis suggests that ursolic acid may indeed lower levels of inflammatory cytokines, increase antioxidant enzyme levels, and reduce oxidative stress levels. Notably, it appears that cells and animals with existing inflammatory responses may benefit more from ursolic acid compared to healthy states. This study addresses the controversy over the effects of ursolic acid on inflammatory and oxidative stress processes and provides a basis for future applications of ursolic acid. To advance this field of research, it is crucial to conduct future studies with heightened methodological precision, larger sample sizes, and increased consistency in parameters such as dosage/concentration and route of administration. By doing so, we can gain a clearer understanding of the strength of the relationship between ursolic acid and inflammation and oxidative stress. This can ultimately pave the way for more definitive large-scale randomized controlled trials, both for treatment and prevention purposes, which are clearly warranted.

Data availability statement

The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding author.

Author contributions

MZ: Conceptualization, Data curation, Formal Analysis, Methodology, Software, Validation, Visualization, Writing–original draft. FW: Data curation, Formal Analysis, Software, Validation, Visualization, Writing–original draft. ZT: Data curation, Formal Analysis, Software, Validation, Visualization, Writing–original draft. XY: Data curation, Methodology, Visualization, Writing–review and editing. YL: Data curation, Methodology, Visualization, Writing–review and editing. FW: Data curation, Methodology, Visualization, Writing–review and editing. BC: Conceptualization, Writing–review and editing, Funding acquisition.

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

Conflict of interest

Author ZT was employed by Hebei Research Institute of Microbiology Co.

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

Publisher’s note

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

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fphar.2023.1256946/full#supplementary-material

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Keywords: ursolic acid, antioxidants, anti-inflammatory, in vitro , animals, meta-analysis

Citation: Zhao M, Wu F, Tang Z, Yang X, Liu Y, Wang F and Chen B (2023) Anti-inflammatory and antioxidant activity of ursolic acid: a systematic review and meta-analysis. Front. Pharmacol. 14:1256946. doi: 10.3389/fphar.2023.1256946

Received: 12 July 2023; Accepted: 19 September 2023; Published: 28 September 2023.

Reviewed by:

Copyright © 2023 Zhao, Wu, Tang, Yang, Liu, Wang and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Baojiang Chen, [email protected]

† These authors have contributed equally to this work

• Open Access
• Published: 28 September 2023

Effectiveness of virtual reality in nursing education: a systematic review and meta-analysis

• Kai Liu 1 ,
• Weiwei Zhang 2 ,
• Ting Wang 1 &
• Yanxue Zheng 1  

BMC Medical Education volume  23 , Article number:  710 ( 2023 ) Cite this article

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This study aims to assess the transformative potential of Virtual Reality (VR) has shown significant potential in transforming nursing education by providing immersive and interactive learning experiences. Our objective is to systematically evaluate and conduct a meta-analysizes on the impact effect of virtual reality technology in teaching nursing students.

To achieve this, we conducted comprehensive computer searches on platforms including of PubMed, Web of Science, Wiley Online Library, Zhiwang database, Wanfang database, and China Biomedical Literature Service (SinoMed), were conducted to collect randomized controlled trial studies on the use of virtual reality’s technology for teaching nursing students built up to until March 2023., and the Cochrane Furthermore, the quality of the included literature was assessed evaluated using the quality evaluation criteria specified for randomized controlled trial studies within the Cochrane provided in the evaluation handbook manual. In addition, a meta-analysis was performed using Review Manager 5.3 software.

The aggregate outcomes from a total of 12 randomized controlled trials, encompassing including 1167 students, indicate were included. Meta-analysis results showed that virtual reality technology significantly enhances could better improve nursing students’’ theoretical knowledge [(SMD = 0.97, 95% CI [0.48, 1.46], p < 0.001)], practical skills (SMD = 0.52, 95% CI [0.33, 1.46], p < 0.001), skill retention, (SMD = 0.52, 95% CI [0.33, 0.71], p < 0.001), and satisfaction levels (SMD = 1.14, 95% CI [0.85, 1.43], p < 0.001), in comparison with traditional or alternative teaching methodologies. However, no statistically significant impact was observed on the enhancement of critical thinking skills (SMD = 0.79, 95% CI [-0.05, 1.64], p = 0.07) among nursing students.

Our findings underscore that compared to conventional teaching methods, virtual reality offers superior potential in advancing nursing students’ theoretical knowledge, practice proficiencies, and overall satisfaction, while not yielding a significant advantage in enhancing critical thinking skills. The incorporated literature consisted exclusively of randomized controlled trials, albeit a subset of these studies omitted descriptions of the allocation concealment strategy.

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Introduction

Virtual reality (VR) technology, stemming from mathematical reasoning and scientific experimentation, assumes a pivotal role as a universal and strategic tool for comprehending, reshaping, and innovating the tangible world [ 1 , 2 ]. VR involves creating a computer-generated simulation of a three-dimensional image or environment that individuals can interact with as if it were real or physical. Thus, this interaction is achieved through specialized electronic equipment, such as a helmet with an integrated screen or gloves equipped with sensors. This holds within the evolving landscape of education reform and heightened aspirations for elevated higher education standards. Significantly accentuating this trajectory, VR’s educational potential is thrust into the spotlight [ 3 ], propelling it into a burgeoning realm of investigation with expansive practical applications. Notably in the domain of nursing education, this technology garners increasing attention from medical education scholars who seek to curtail teaching expenses and mitigate instructional hazards while upholding pedagogical excellence [ 4 , 5 , 6 ].

Amid the rapid evolution of information technology, novel advancements like VR are ushering in a fresh pedagogical approach to nursing education [ 7 ]. This technique engenders an immersive, interactive encounter for nursing students, replicating authentic clinical scenarios and furnishing them with robust hands-on training experiences, all while circumventing direct patient engagement. This not only economizes the valuable time of clinical nursing professionals but also mitigates the predicaments associated with conventional patient interaction in pedagogy [ 8 ], thereby addressing the dearth of clinical educational resources. Nursing students interact with VR through immersive experiences that simulate real-life clinical scenarios. Using specialized VR equipment, such as VR headsets or gloves with sensors, nursing students can engage with virtual patients, medical equipment, and healthcare environments.

This allows them to practice clinical skills, make decisions in simulated patient care situations, and explore various medical scenarios. VR technology enables nursing students to actively participate in realistic learning experiences, enhancing their understanding of theoretical concepts and providing hands-on training in a safe and controlled environment. Besides, the interactive dimension inherent to VR technology augments the didactic process, bestowing nursing students with an intuitively enriched learning experience [ 9 ]. Through its immersive interactivity, VR effectively eradicates the dullness of conventional teaching, and rigid teaching methodologies, kindling greater scholarly enthusiasm among nursing students and markedly improving their operational skills [ 10 ]. By proficiently role-modeling clinical environments, VR fosters a profound sense of engagement, inherently nurturing nursing students’ professional self-conception [ 11 ], strengthening their sense of commitment and calling, and galvanizing autonomous knowledge exploration. Moreover, the interactive operability at the core of VR fundamentally amplifies the intrinsic impetus for nursing students to actively pursue learning [ 12 ].

Jang et al. [ 13 ] demonstrated that the interactive and operational attributes of VR outperform 3D videos in enhancing students’ comprehension and assimilation of knowledge. Within the realm of nursing education, there exists a significant challenge in devising a curriculum that encompasses both depth and breadth, rectifying the limitations intrinsic to conventional pedagogy. This challenge seeks to seamlessly guide nursing students in the transition from fragmented textual knowledge to its clinical application, concurrently conserving invaluable clinical teaching resources and nurturing adept nursing practitioners [ 14 ].

Virtual reality (VR) is the use of computer technology to create an interactive three-dimensional (3D) world, which gives users a sense of spatial presence. In nursing education, VR has been used to help optimize teaching and learning processes. In the contemporary landscape of nursing education reform, this stands as a crucial and intricate juncture demanding resolution. Consequently, a symbiotic fusion of nursing education with the ever-evolving era is indispensable for nurturing adaptable nursing professionals capable of propelling the progress and expansion of both nursing education and clinical practice. As the trajectory of nursing education evolves, the integration of VR instruction emerges as a definitive trend [ 15 ], yet it remains in its nascent exploratory phase, necessitating substantial engagement from nursing educators to chart a scientifically sound path toward effective VR nursing education.

Hence, this study meticulously reviewed the existing literature concerning the integration of VR into nursing education curricula, with a focus on both current and prospective nursing educators. Employing a systematic evaluation and subsequent meta-analysis, we aimed to discern optimal approaches in nursing student instruction, by identifying essential attributes of nursing education and furnishing a guiding trajectory for future research about virtual reality-infused nursing educational programs.

Study design

This study employed “The Preferred Reporting Items for Systematic Reviews and Meta-Analyses”, otherwise known as the principles of the PRISMA statement in the reporting of the meta-analysis [ 16 ].

Search strategy

We conducted computer-based searches across multiple databases including PubMed, Web of Science, Wiley Online Library, Zhiwang database, Wanfang database, and China Biomedical Literature Service (SinoMed). The search spanned from the establishment of each database up to March 2023, employing a search strategy that combined both free terms and subject descriptors. Equally, by employing literature tracing techniques, we located pertinent studies. On top of that, the search strategy encompassed a fusion of free terms and subject descriptors. Within the English databases, search terms include “virtual reality/patient simulat*/virtual patient*/virtual simulation” and “education, nursing /nurs*education/education of nursing.” As an illustrative instance, the search strategy utilized for PubMed is outlined in Fig.  1 .

Inclusion and exclusion criteria

Inclusion criteria.

Adhering to the population, intervention, control, outcomes, and study design (PICOS) principles, we methodically screened the literature based on the following criteria: (1) study population (P): nursing students; (2) intervention (I): experimental groups in the studies that employed VR technology for instruction, implementing the four essential components delineated by Sherman and Craig (virtual world, immersion, sensory feedback, interactivity) to establish varying degrees of immersion through diverse VR platforms [ 17 ]; (3) control measures (C): control groups were exposed to conventional pedagogical techniques (comprising classroom lectures, demonstrations, model-based instruction, etc.) or non-VR simulation scenarios (encompassing high-fidelity/low-fidelity simulation, mannequin simulation, etc.); (4) outcomes (O): evaluated outcome indicators, which includes theoretical knowledge scores, practical skills scores, satisfaction levels, and critical thinking abilities; (5) study design (S): exclusively encompassing randomized controlled trials.

Exclusion criteria

We excluded the following types of literature during the selection process: (1) conference papers, abstracts, and catalogs; (2) duplicate publications; (3) literature containing errors, incomplete study data, or being inaccessible for comprehensive analysis; (4) literature with inaccessible full text; (5) literature not published in English or Chinese; (6) Other types of literature besides experimental studies.

Study selection and data extraction

Two researchers conducted an independent screening of the literature based on the inclusion and exclusion criteria. Initially, they reviewed the titles and abstracts of the literature, excluding those that did not meet the inclusion criteria. Subsequently, a meticulous assessment of the full texts was undertaken for the remaining literature, leading to their inclusion upon alignment with the set criteria. Ultimately, the literature that adhered to the inclusion criteria was definitively identified. In instances of discrepancies, a third researcher was consulted to facilitate the decision-making process, and any information gaps were addressed by reaching out to the original authors whenever feasible. When confronted with duplicate publications, precedence was given to the Chinese literature.

Following the identification of the literature, two researchers autonomously undertook the task of data extraction. They meticulously extracted data from the selected studies in alignment with the prescribed data extraction protocols as outlined in the Cochrane Handbook for the Evaluation of Intervention Systems [ 18 ]. Furthermore, the extracted information encompassed a range of elements including authors, year of publication, country, study population, number of participants, and number of interventionists.

Correspondingly, we adhered to the risk of bias assessment of the principles for Randomized Controlled Trials (RCT) as prescribed by the Cochrane Collaboration Network Handbook on Systematic Evaluation of Interventional Studies, version 5.1. Two investigators autonomously conducted evaluations of the included RCTs, while any disparities were resolved through deliberation or consultation with a third investigator when necessary.

Study quality and risk of bias assessment

Two investigators independently conducted assessments in accordance with the evaluation criteria outlined in Cochrane Evaluation Manual 5.1.0 [ 19 ]. In instances where discrepancies arose, a third investigator was consulted to facilitate resolution through discussion or consultation. The assessment encompassed the following items: ① generation of randomized sequences; ② allocation scheme concealment; ③ blinding of investigators and subjects; ④ blinding of assessors; ⑤ completeness of data; ⑥ selective reporting; and ⑦ other biases. Thus, the classification of risk levels for each element was divided into high risk, low risk, and unclear. This study, therefore, elucidates the rationale behind each judgment by the assessment framework of the Review Manager 5.3 program.

Statistical methods

We conducted the meta-analysis of the included literature utilizing Review Manager 5.3 software and Endnote software. Continuous variables were elucidated through mean difference (MD), standardized mean difference (SMD), and a 95% confidence interval (CI). Statistical significance and differences between the experimental and control groups were established at P < 0.05. Besides, we assessed the heterogeneity of the meta-analysis results utilizing the I 2 quantitative test. A value of I 2  < 50% indicated low heterogeneity, enabling the selection of a fixed-effect model. Conversely, an I 2 value ≥ 50% denoted high heterogeneity, warranting the adoption of a random-effect model. For I 2 values exceeding 75%, significant heterogeneity within the meta-analysis results was ascertained.

Characteristics of the study population (study selection)

A computer search of PubMed, Web of Science, Wiley Online Library, Zhiwang database, Wanfang database and China Biomedical Literature Service (SinoMed) retrieved 2179 papers; titles and abstracts were reviewed and 152 articles were selected considering the inclusion and exclusion criteria. After excluding 140 papers that did not meet the inclusion criteria, 12 papers were finally selected [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 ]. As shown in Fig.  2 .

Literature screening process and result

Characteristics of research on educational interventions using virtual reality for current and future health personnel (research characteristics)

This study includes general characteristics of 12 studies of educational interventions using virtual reality; detailed information is provided in Table  1 In terms of study design characteristics, all 12 studies were randomized controlled studies. The number of study participants was 585 for the experimental group and 582 for the control group, for a total of 1167 participants.

Methodological quality assessment of intervention studies

The risk of bias assessment is summarized in Fig.  3 below. 9 of the 12 studies described detailed information related to randomization, and 7 studies lacked clarity regarding allocation concealment. The detailed risk of bias assessment is shown in Fig.  4 .

Overall risk of bias analysis of included studies

Risk of bias analysis of each included study

Meta-analysis results

Theoretical knowledge.

Eleven studies [20–25,27−31] evaluated the effectiveness of VR technology in theoretical knowledge levels. The results showed a high heterogeneity of the included studies (p < 0.001, I2 = 92%), so a random effects model was used. The combined results showed that the use of VR technology was effective in improving students’ theoretical knowledge compared to other traditional nursing teaching methods (SMD = 0.97, 95% CI [0.48, 1.46], P < 0.001, Fig.  5 ) .

Impact of VR technology on nursing students’ theoretical knowledge

Practical skills

Four studies [ 24 , 28 , 29 , 31 ]evaluated the effectiveness of VR technology in practice skills. The results showed that there was no heterogeneity in the included studies (P = 0.34, I2 = 10%), so a fixed-effects model was used. The combined results showed a statistically significant difference compared to other traditional nursing teaching methods (SMD = 0.15, 95% CI [-0.21, 0.51], P < 0.001, Fig.  6 ).

Impact of VR technology on nursing students’ practice skills

Satisfaction

Four studies [ 20 , 21 , 23 , 25 ]evaluated the effect of VR technology on nursing teaching satisfaction, and the results showed that there was no heterogeneity in the included studies (P = 0.36, I 2  = 7%), so a fixed-effects model was used. The combined results showed a significant difference in the improvement of satisfaction with nursing education with VR technology compared to the control teaching modality (SMD = 1.14, 95% CI [0.85, 1.43], P < 0.001, Fig.  7 ).

Impact of VR technology on academic satisfaction of nursing students

Critical thinking

Three studies [ 26 , 30 , 31 ]evaluated the effect of VR technology on the application of critical thinking among nursing students, but the results showed high heterogeneity in the included studies (P < 0.001, I 2  = 93%), so a random effects model was used. The combined results showed no significant difference in the improvement of satisfaction in nursing education with VR technology compared to the control teaching modality (SMD = 0.79, 95% CI [-0.05, 0.46], p = 0.07, Fig.  8 ).

Impact of VR technology on nursing students’ critical thinking

The effect of the application of VR technology on nursing students

The results of the aforementioned meta-analysis revealed that the utilization of VR technology in nursing student education yielded more effective enhancement in theoretical knowledge in comparison to other conventional teaching methods, and this distinction achieved statistical significance (P < 0.05). Contemporaneously, the theoretical component of nursing education stands as a crucial underpinning for nurses to translate their knowledge into clinical competence, constituting an integral part of nursing instruction. In a bid to bolster the teaching effectiveness of the theoretical course, nursing educators have incorporated virtual reality technology. Similarly, West Chavez et al. [ 32 ] demonstrated how VR technology increased student engagement by immersing them in realistic learning experiences that closely mirrored their real environment.

Moreover, a qualitative exploration into VR technology’s integration within nursing education [ 33 ] suggests that amalgamating VR technology with conventional nursing pedagogy enables students to interact with objects within a specific virtual teaching environment, engendering equivalent sentiments and experiences as in the real environment. This immersion empowers learners to fathom what they have imbibed and how to practically apply that knowledge. Furthermore, aligned with Kolb’s experiential learning model [ 34 ], nursing students glean insights from their virtual world experiences akin to real-life occurrences, thereby garnering more immediate and enduring outcomes. This explains the observed escalation in theoretical knowledge. According to Pei Ning Woon et al. [ 35 ] ,Virtual reality may be a viable teaching strategy to improve knowledge acquisition, but it is presently suitable for supplementing conventional teaching methods. However, the incorporation of VR technology into nursing instruction not only captivates nursing students’ dedication to learning but also fortifies their knowledge and skills, serving as a foundational requisite for propelling nursing students’ transition from knowledge-based to competence-driven paradigms.

VR technology effect on the practical skills of nursing students

In comparison with conventional or alternative nursing education methodologies, the application of VR technology in teaching exhibits a disparity in nursing practical skills (P > 0.05). That said, virtual simulation technology distinctly elucidates operational intricacies, facilitating accelerated and comprehensive knowledge assimilation among students, thereby augmenting instructional efficacy. A pertinent example stems from Hong Kong Polytechnic University’s successful integration of virtual reality technology in nasogastric tube placement training, attesting to the technology’s safety, flexibility, and interactivity advantages that accelerates the learning curve for this procedure [ 36 ].

Consistent with prior studies, Jefferson (2022) devised a high-fidelity simulation (HFS) course, whereby participants exemplified heightened learning retention and enhanced practical aptitude levels [ 37 ]. Consequently, future endeavors should prioritize refining the technical effectiveness of VR teaching environments, as well as enhancing the transference of acquired practical skills from virtual to clinical settings. In addition, empowering nursing students to engage with patients within virtual environments considerably enhances their clinical technique comprehension and enables them to navigate clinical scenarios during practice. Congruently, certain techniques unfeasible for real patients can be practiced on virtual patients, thereby streamlining the transformation process from theory to practice, student to practitioner, and classroom to clinical settings. This redresses inherent limitations within traditional practical training approaches, subsequently boosting nursing students’ learning efficiency [ 38 ].

VR technology’s improvement effect on nursing students’ academic satisfaction

VR technology imbues learning with vividness and imagery, exuding a potent contagious influence that substantially heightens nursing students’ perceptual acuity, enthusiasm, and active engagement in learning, effectively positioning them at the center of the learning process. When applied to nursing instruction, VR amplifies the liveliness of educational content, fostering augmented interest in independent learning among nursing students, and catalyzing a shift from passivity to activeness in their journey of intellectual voyage. Apart from that, this technology propels students beyond the mere exercise of operational skills within virtual contexts; rather, it serves as a platform where they refine not only operational proficiencies but also their clinical reasoning, decision-making acumen, and aptitude for troubleshooting practical clinical problems [ 39 ]. At the same time, VR offers a robust milieu for collaborative learning, promoting teacher-student interactions. Through group discussions and cooperative endeavors facilitated by VR, educators, and learners deepen their problem analysis and critical thinking, honing their cognitive capacities, and inadvertently enhancing students’ prowess in collaborative communication. This progressive enhancement of collaborative communication inadvertently bolsters the academic contentment of nursing students [ 40 ].

The effect of VR technology on the level of nursing students’ critical thinking

The findings of this study revealed a lack of statistically significant difference (P > 0.05) in the improvement of critical thinking with in nursing education through the implementation of VR technology. This outcome is chiefly attributed to the paucity of research on the relationship between virtual learning environments and the cultivation of critical thinking skills among college students. Also, the obscurity surrounding the determinants influencing college students’ critical thinking development within virtual learning environments, the intricate processes underlying each determinant’s impact, and the varying degrees of influence exerted by these determinants, remain unresolved.

By the same token, capitalizing on the rapid advancements in virtual reality technology, researchers have turned their attention towards harnessing virtual learning environments to foster and nurture college students’ critical thinking prowess. Notably, Kandi et al. (2020) conducted an experimental inquiry that unveiled that architecture students immersed in a virtual learning environment exhibited enhancements in their design, review, and innovation skills. Furthermore, the study ascertained that a virtual reality game design simulator empowered students to pinpoint design errors more effectively and subsequently excel in critical thinking tests [ 41 ]. In like manner, Kang (2020) developed a virtual reality nursing course and found that it facilitated students’ critical thinking development and independent learning skills [ 42 ]. Nonetheless, the utilization of virtual learning environments encounters challenges such as heightened cognitive load and information disorientation. Consequently, the meticulous design of virtual learning environments to maximize the development and augmentation of college students’ critical thinking capacities becomes paramount.

Limitations and prospects of this study

The conclusions drawn from this study are based on a high-quality randomized controlled trial, significantly elevating the strength of its evidentiary foundation in contrast to cohort studies. This robust evidence, synonymous with evidence-based medicine, lays a foundational bedrock for the prospective application of virtual reality technology within nursing education. Nevertheless, this meta-analysis has certain limitations: (1) The incorporated literature consisted exclusively of randomized controlled trials, albeit a subset of these studies omitted descriptions of the allocation concealment strategy; (2) Disparities in intervention types and assessment methods for outcome indicators among the included studies might have potentially influenced the eventual aggregated outcomes; (3) This investigation limited its scope to Chinese and English literature, potentially introducing an influence on the study outcomes. Consequently, to further establish the efficacy of psychotherapy in treating depression and anxiety among college students, subsequent stages necessitate the design of more rigorous, multicenter, and large-scale randomized controlled trials.

The outcomes of this meta-analysis demonstrate that VR technology can be more effective in improving nursing students’ knowledge of nursing teaching skills, practical nursing teaching aptitude, and academic contentment. Nevertheless, no notable superiority of VR technology was observed in enhancing nursing students’ critical thinking abilities. This could potentially stem from variations in intervention delivery, assessment methodologies, study participants, and research schemes. Consequently, educators must reorient their teaching paradigms, reinforcing the significance of virtual reality technology, and proactively integrating advanced technological tools for educational advancement. Based on the aforementioned points, VR technology stands poised to emerge as a pivotal breakthrough in the future of education, ushering in far-reaching impacts on the evolution of pedagogical methodologies in nursing education.

In conclusion, this study demonstrates the potential of VR technology to enhance nursing education by improving theoretical and practical knowledge as well as academic satisfaction among nursing students. However, the absence of a significant advantage in enhancing critical thinking skills through VR interventions suggests the need for further investigation into the design of VR-based learning environments tailored to fostering critical thinking. Despite the rigorous methodology applied in this study, limitations include variations in intervention types, assessment methods, and subject characteristics across the included studies. To address these limitations, future research should focus on refining VR interventions for nursing education, considering the specific components that effectively promote critical thinking, and conducting multicenter studies with larger sample sizes to provide more robust evidence of VR’s impact on nursing education outcomes.

Data Availability

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

Abbreviations

China National Knowledge Infrastructure

Mean difference

The Preferred Reports for Systematic Reviews and Meta-Analyses

Randomized controlled trial

China Biomedical Literature Service

Standardized mean difference.

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Funding for this study was provided by the Jining Medical University Practical Teaching Education Research Program Project, China (JYSJ2022A05). Funding body played a role in the design of the study.

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Liu, K., Zhang, W., Li, W. et al. Effectiveness of virtual reality in nursing education: a systematic review and meta-analysis. BMC Med Educ 23 , 710 (2023). https://doi.org/10.1186/s12909-023-04662-x

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• Published: 30 September 2023

Association of reduced glutathione levels with Plasmodium falciparum and Plasmodium vivax malaria: a systematic review and meta-analysis

• Manas Kotepui 1 ,
• Kwuntida Kotepui 1 ,
• Aongart Mahittikorn 2 ,
• Hideyuki J. Majima 1 ,
• Jitbanjong Tangpong 1 &
• Hsiu-Chuan Yen 3 , 4  

Scientific Reports volume  13 , Article number:  16483 ( 2023 ) Cite this article

Metrics details

• Diagnostic markers

Reduced glutathione (GSH) is a crucial antioxidant with recognized roles in malaria pathogenesis and host response. Despite its importance, reports on the association of GSH with malaria are inconsistent. Therefore, this systematic review and meta-analysis investigated the differences in GSH levels in relation to Plasmodium infection. A comprehensive literature search of six electronic databases (Embase, MEDLINE, Ovid, PubMed, Scopus, and ProQuest) was conducted. Of the 2158 initially identified records, 18 met the eligibility criteria. The majority of studies reported a significant decrease in GSH levels in malaria patients compared with uninfected controls, and this was confirmed by meta-analysis ( P  < 0.01, Hedges g: − 1.47, 95% confidence interval [CI] − 2.48 to − 0.46, I 2 : 99.12%, 17 studies). Additionally, there was no significant difference in GSH levels between Plasmodium falciparum malaria and P. vivax malaria ( P  = 0.80, Hedges g:  0.11, 95% CI − 0.76 to 0.98, I 2 : 93.23%, three studies). Similarly, no significant variation was observed between symptomatic and asymptomatic malaria cases ( P  = 0.78, Hedges g: 0.06, 95% CI − 0.34 to 0.46, I 2 : 48.07%, two studies). In conclusion, although GSH levels appear to be generally lower in malaria patients, further detailed studies are necessary to fully elucidate this complex relationship.

Introduction

Malaria is a life-threatening disease caused by protozoan parasites of the Plasmodium genus that are transmitted to humans through infecting bites of female Anopheles mosquitoes 1 . Among them, Plasmodium falciparum and P. vivax are the most prevalent and cause the most significant public health burden 2 . Malaria is characterized by cycles of fever, chills, and sweats. Severe cases can lead to complications, such as cerebral malaria, severe anemia, and multiorgan failure 3 . During the intraerythrocytic stage, Plasmodium parasites metabolize hemoglobin, producing heme as a by-product 4 . Oxidative stress, an imbalance between the production of reactive oxygen species (ROS) and the body’s ability to neutralize their harmful effects through antioxidants, has been implicated in malaria pathogenesis and progression 5 . To detoxify heme, the parasite polymerizes it into hemozoin. However, this process also generates free radicals, thereby inducing oxidative stress in the host 4 . Additionally, during Plasmodium infection, ROS are produced by activated host phagocytes, such as neutrophils 6 . Enzymatic antioxidants, such as superoxide dismutases, catalase, and glutathione peroxidases (GPxs), and nonenzymatic antioxidants, such as vitamins C and E, β-carotene, and reduced glutathione (GSH), are activated by the host’s antioxidant defense system in response to oxidant stress 7 .

GSH is a pivotal nonenzymatic antioxidant in mammalian cells 8 , 9 . Besides its direct antioxidant activity, it plays several distinct roles. GSH acts as a cofactor for various enzymes, including GPx, glutathione S-transferases (GSTs), and glyoxalases 8 . Specifically, GPx uses GSH to detoxify peroxides, thereby converting GSH into glutathione disulfide (GSSG). Then, with the aid of the cofactor nicotinamide adenine dinucleotide phosphate hydrogen, glutathione reductase restores GSH from GSSG 8 , 10 . Additionally, GSH directly scavenges free radicals, such as superoxide anions, hydroxyl radicals, and nitric oxide, neutralizing their reactivity and preventing cellular damage 11 . It is also involved in regenerating other antioxidants, notably vitamins C and E 12 , and is a substrate for GPx, which reduces peroxides, including hydrogen peroxide and lipid peroxides. This function is crucial because it prevents the formation of more reactive species, like hydroxyl radicals 13 .

Despite the known roles of GSH, the results of studies examining its relationship with malaria are inconsistent and often limited by small sample sizes. Some studies have shown reduced GSH levels in malaria patients compared with uninfected controls 14 , 15 , 16 , while others reported increased GSH levels 17 , 18 or no difference 19 , 20 . A comprehensive understanding of the role of GSH in Plasmodium infection, including the effects of specific species, clinical outcomes, and the relationship between GSH levels and parasite density, remains elusive. Our investigation addresses this knowledge gap, setting the groundwork for future research to translate our findings into tangible clinical and public health benefits. Elevated or diminished GSH levels may be critical markers of malaria’s clinical course, enabling earlier detection of severe cases and timely intervention. Furthermore, insights into the role of GSH may inform both clinical management and preventive strategies. Thus, this systematic review and meta-analysis investigated the differences in GSH levels in relation to Plasmodium infection, considering various Plasmodium species, clinical outcomes, and the correlation of GSH levels with parasite density.

The protocol for this systematic review and meta-analysis was registered with PROSPERO (CRD42023434937) and performed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines 21 .

Research question for the systematic review

The structure of this systematic review was based on the Population, Exposure, Comparator, Outcome framework 22 (P: participants included in the studies, E: occurrence of malaria, C: uninfected controls, and O: GSH levels).

Search strategy

A comprehensive literature search was conducted across six electronic databases (Embase, MEDLINE, Ovid, PubMed, Scopus, and ProQuest). The search terms included “(“reduced glutathione” OR GSH OR “gamma-L-Glutamyl-L-Cysteinylglycine” OR “gamma L Glutamyl L Cysteinylglycine” OR “gamma-L-Glu-L-Cys-Gly” OR “gamma L Glu L Cys Gly”) AND (malaria OR plasmodium OR “Remittent Fever” OR “Marsh Fever” OR “Paludism)”, with slight variations for each database (Supplementary Table S1 ). We also searched Google Scholar and the reference lists of selected articles. Although Google Scholar is an expansive database, it was used as a supplementary literature search tool. This decision was based on its limitations: it only supports basic Boolean operators in search strings, lacks the ability to export results in bulk as citations, and displays only the first 1000 search records, which cannot be sorted 23 . Additionally, only the first 200 search records were screened for eligibility, as previously suggested 23 . The searches were restricted to articles written in English, but there was no restriction on the publication date. The searches began from database inception to June 12, 2023.

Study selection and eligibility criteria

The study selection process was conducted in a stepwise manner by two independent authors (M.K. and A.M.). Any disagreement between the two authors was resolved via consensus.

First, duplicate records from the various database searches were removed manually and using automated tools. Then, the remaining unique records underwent a screening process, where irrelevant studies and those without abstracts were excluded. Next, the full texts of the remaining articles were retrieved for a detailed eligibility assessment. Studies were included in the review if they were original research articles, reported GSH levels in malaria and uninfected controls, and provided sufficient quantitative data for meta-analysis, such as the mean (with standard deviation) or median (with interquartile range) GSH levels 24 . The exclusion criteria encompassed in vitro/in vivo studies, review articles, studies lacking GSH information, studies not specifying the GSH type, studies without malaria cases, conference abstracts, or studies analyzing post-treatment GSH levels.

Data extraction and quality assessment

The following data were extracted for each eligible study: first author’s name, year of publication, study design, year in which the study was conducted, geographic location, targeted Plasmodium species, clinical status, data on GSH levels, method of malaria detection, and method of GSH measurement. The quality of the included studies was assessed using Joanna Briggs Institute Critical Appraisal tools, depending on the study design (cross-sectional, cohort, or case–control) 25 . The cross-sectional studies were evaluated for clarity of inclusion criteria, validity of exposure and outcome measurements, and management of confounding factors. The cohort studies were appraised based on group similarity, validity of exposure measurement, strategies for handling confounding factors, adequacy of the follow-up period, and appropriateness of statistical analyses. The case–control studies were assessed for group comparability, appropriateness of case–control matching, validity of exposure measurement, management of confounding factors, and sufficiency of the exposure period. Responses were categorized as “Yes,” “No,” “Unclear,” or “Not applicable” based on the relevance and availability of information for each criterion. The quality rank of an individual study was determined by the percentage of “Yes” responses among all items as follows: > 75th percentile, high quality; 50th–75th percentile, moderate quality; and < 50th percentile, low quality 26 .

Data synthesis and statistical analysis

The extracted data were used for qualitative synthesis. Additionally, a meta-analysis was conducted for quantitative synthesis. For the meta-analysis, the standardized mean difference (Hedges g) of GSH levels between groups of participants was calculated along with their 95% confidence intervals (CIs). Heterogeneity was quantified using the I 2 statistic 27 as follows: 0–40%, low heterogeneity; 30–60%, moderate heterogeneity; 50–90%, substantial heterogeneity; and 75–100%, considerable heterogeneity 27 . To explore the potential sources of heterogeneity, a meta-regression analysis using various factors, like the publication year, study design, continent, participant groups, Plasmodium species, diagnostic method for malaria, and quality rank of included studies, was conducted 28 . Subgroup analysis was conducted based on publication year, study design, geographic location, participant group, Plasmodium species, diagnostic method for malaria, and quality rank of included studies. A sensitivity analysis was performed using the fixed-effect model and the leave-one-out meta-analysis 29 . The leave-one-out meta-analysis was used to determine the effect of each individual study on the pooled effect estimate of the remainder of the studies 29 . Publication bias was evaluated by funnel plot analysis and Egger regression test 30 . All statistical analyses were performed using Stata v17.0 software (StataCorp. College Station, TX). P -values < 0.05 were considered statistically significant.

Search results

The searches yielded a total of 2158 records from six databases, including Embase, MEDLINE, Ovid, PubMed, Scopus, and ProQuest (n = 649, 295, 226, 115, 285, and 588 records, respectively). Initially, 663 duplicate records were eliminated, resulting in 1495 unique records for screening. Of them, 1164 were excluded due to their irrelevance to malaria or GSH or a lack of abstract, leaving 331 records for retrieval. Two records were irretrievable, so 329 reports were assessed for eligibility. This led to the exclusion of 317 records for various reasons, including being in vitro/in vivo studies, review articles, or conference abstracts, as well as lacking GSH information, the absence of malaria cases, not specifying GSH type, or analyzing post-treatment GSH levels. Eventually, 18 studies meeting the criteria were included in the review 14 , 15 , 16 , 17 , 18 , 19 , 20 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 : 12 from the primary database search 15 , 16 , 17 , 20 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 39 , five from Google Scholar 14 , 18 , 19 , 38 , 41 , and one from a reference list 40 (Fig.  1 ).

Flow diagram of the study selection process.

Characteristics of the included studies

The 18 included studies showed diverse characteristics. The majority were published during 2010–2023 (83.3%), indicating a greater interest in the investigation of the association between oxidative stress and malaria during this period. Of the studies included, only 50% specified the year in which they were conducted. The research designs were primarily cross-sectional studies (61.1%) and case–control studies (27.8%). Geographically, the studies were fairly evenly distributed between Africa (55.6%) and Asia (44.4%), with Nigeria and India being the predominant countries, respectively. Plasmodium species targeted in these studies were mostly P. falciparum (72.2%, n = 13), indicating its global importance. Although participant demographics varied, suggesting the universal impact of malaria, it is notable that approximately a quarter of the studies (27.8%) focused on children. The common method of malaria detection was light microscopy (72.2%) (Tables 1 , 2 , Supplementary Table S2 ).

Quality of the included studies

For the cross-sectional studies, the majority 15 , 16 , 20 , 32 , 35 , 40 exhibited robust adherence to the predetermined criteria but failed to address confounding factors. However, three studies 17 , 19 , 38 successfully met all quality parameters. Two studies 36 , 41 , although fulfilling most criteria and identifying confounding factors, neglected to proffer strategies to mitigate confounders. Regarding the cohort studies, only one 34 met all quality parameters. However, the other cohort study 39 displayed certain inadequacies and ambiguities, including exposure measurement and handling of confounding factors. For the case–control studies, one 14 struggled with group comparability and case–control matching and did not address confounding factors. Another 31 upheld all quality criteria. The remaining three case–control studies 18 , 33 , 37 , while fulfilling most criteria, were vague regarding case–control matching and the duration of the exposure period (Supplementary Table S3 ).

Qualitative synthesis

The majority of African studies on GSH levels in malaria were conducted in Nigeria, with significant contributions from authors such as Abduljalil et al. 14 , Abubakar et al. 15 , Akanbi et al. 16 , Babalola et al. 19 , Nsonwu-Anyanwu et al. 37 , Oluba et al. 39 , Onyeneke et al. 40 , and Ozojiofor et al. 41 . The majority of Asian studies were conducted in India, as evidenced by works from Aqeel et al. 31 , Bhattacharya and Swarup-Mitra 33 , Das and Nanda 34 , Sohail et al. 17 , and Tyagi et al. 18 . Overall, a significant decrease in GSH levels in individuals with malaria compared with uninfected controls was observed in 13 of these studies. Regarding different age groups, the majority of studies focused on children observed a significant decrease in GSH levels when infected with malaria, as seen in studies by Abduljalil et al. 14 , Abubakar et al. 15 , Das and Nanda 34 , Oluba et al. 39 , and Ojongnkpot et al. 38 . In particular, Ojongnkpot’s study from Cameroon highlighted a negative relationship between GSH levels and parasite density in children 38 . A decline in GSH levels in malaria patients was predominantly observed in studies on adults, including studies by Erel et al. in Turkey 35 , Javeed et al. in Pakistan 36 , and Nsonwu-Anyanwu et al. in Nigeria 37 . In Indonesia, Fitri et al. 20 noted no difference in GSH levels between severe and nonsevere malaria in adults. Two Nigerian studies specifically focused on pregnant and nonpregnant women: Akanbi et al. 16 and Onyeneke et al. 40 . Both reported decreased GSH levels in subjects with malaria compared with uninfected controls. However, Onyeneke et al. did not find an association between GSH levels and parasite density in this group 40 . Some studies enrolled participants from all age groups, with Bhattacharya and Swarup-Mitra 33 and Ozojiofor et al. 41 , from India and Nigeria, respectively, noting a decline in GSH levels in malaria patients. In contrast, the Indian studies by Sohail et al. 17 and Tyagi et al. 18 observed increased GSH levels in malaria patients, providing an intriguing counterpoint.

GSH levels between malaria and uninfected controls

A total of 17 studies investigated GSH levels in both malaria and uninfected controls and reported quantitative data, which we used in the meta-analysis 14 , 15 , 16 , 17 , 18 , 19 , 20 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 40 , 41 . Compared with uninfected controls, GSH levels were reduced in 11 malaria studies 14 , 15 , 16 , 31 , 32 , 33 , 34 , 35 , 36 , 38 , 41 , increased in three malaria studies 17 , 18 , 37 , and showed no difference in three malaria studies 19 , 20 , 40 . The meta-analysis result showed the reduction of GSH in malaria compared with uninfected controls ( P  < 0.01, Hedges g: − 1.47, 95% CI − 2.48 to − 0.46, I 2 : 99.12%, 17 studies; Fig.  2 ). The meta-regression analysis, which considered factors such as publication year, study design, continent, participant groups, Plasmodium species, diagnostic methods for malaria, and the quality rank of the included studies, showed that only the Plasmodium species influenced the pooled effect estimate (Supplementary Table S4 ). This suggests that different Plasmodium species may influence variations in GSH levels in patients with malaria.

Forest plot showing the difference in the reduced glutathione levels between malaria patients and uninfected controls. CI confidence interval, N number of participants, SD standard deviation, blue square effect estimate, green diamond pooled effect estimate, red vertical line pooled effect estimate, gray vertical line no effect line.

The subgroup analysis results are shown in Table 3 . Studies published from 2010–2023 indicated no significant difference in GSH levels between the groups ( P  = 0.08, Hedges g =  − 1.01, 95% CI: − 2.15 to 0.12), whereas studies conducted before 2010 showed a significant difference ( P  < 0.01, Hedges g =  − 3.69, 95% CI − 6.09 to − 1.29). Cross-sectional studies showed significant differences in GSH levels between malaria cases and controls ( P  < 0.01, Hedges g =  − 1.53, 95% CI − 2.44 to − 0.62), while case–control studies did not ( P  = 0.27, Hedges g =  − 1.52, 95% CI − 4.23 to 1.19). Geographically, studies from Africa demonstrated significant differences ( P  < 0.01, Hedges g =  − 1.32, 95% CI − 2.16 to − 4.09), but those conducted in Asia did not ( P  = 0.11, Hedges g =  − 1.69, 95% CI − 3.74 to 0.37). Regarding participant groups, only studies involving children showed a significant difference in GSH levels ( P  = 0.01, Hedges g =  − 2.16, 95% CI − 3.80 to − 0.53), while others did not. Differences in Plasmodium species ( P. falciparum , P. vivax , or a mix of both species) did not show significant differences in GSH levels. In terms of diagnostic methods for malaria, studies using microscopy showed significant differences ( P  < 0.01, Hedges g =  − 1.95, 95% CI: − 3.28 to − 0.62), but those using a combination of microscopy and rapid diagnostic tests did not ( P  = 0.59, Hedges g =  − 0.30, 95% CI − 1.42 to 0.81). Concerning the studies’ quality, high-quality studies showed significant differences ( P  < 0.01, Hedges g =  − 1.56, 95% CI − 2.35 to − 0.76), but moderate-quality studies did not ( P  = 0.36, Hedges g =  − 1.33, 95% CI − 4.20 to 1.54).

GSH levels between P. falciparum and P. vivax

Three studies investigated GSH levels in both P. falciparum and P. vivax malaria cases, providing quantitative data applicable to the meta-analysis 17 , 31 , 36 . The results showed a significant difference in GSH levels between P. falciparum and P. vivax malaria ( P  = 0.80, Hedges g: 0.11, 95% CI: − 0.76 to 0.98, I 2 : 93.23%, three studies; Fig.  3 ). Performing both meta-regression and subgroup analysis was not feasible in this context due to the restricted number of studies available.

Forest plot showing the difference in the reduced glutathione levels between patients with P. falciparum malaria and those with P. vivax malaria. CI confidence interval, N number of participants, SD standard deviation, blue square effect estimate, green diamond pooled effect estimate, red vertical line pooled effect estimate, gray vertical line no effect line.

GSH levels between symptomatic and asymptomatic malaria

Two studies investigated GSH levels in both symptomatic and asymptomatic P. falciparum malaria and reported quantitative data, which we used in the meta-analysis 19 , 38 . The results revealed no significant difference in GSH levels between symptomatic and asymptomatic malaria cases ( P  = 0.78, Hedges g: 0.06, 95% CI: − 0.34 to 0.46, I 2 : 48.07%, two studies; Fig.  4 ). Due to the limited number of studies available, both a meta-regression and subgroup analysis could not be conducted.

Forest plot showing the difference in the reduced glutathione levels between patients with symptomatic and asymptomatic malaria. CI confidence interval, N number of participants, SD standard deviation, blue square effect estimate, green diamond pooled effect estimate, red vertical line pooled effect estimate, gray vertical line no effect line.

Sensitivity analysis

Two approaches were employed to perform sensitivity analysis: the fixed-effect model and the leave-one-out meta-analysis. The fixed-effect model revealed a significant reduction in GSH levels in individuals with malaria compared with uninfected controls ( P  = 0.01, Hedges g: − 0.12, 95% CI − 0.21 to − 0.03), as confirmed by the meta-analysis of 17 studies ( I 2 : 99.12%, Supplementary Fig. S1 ). The leave-one-out meta-analysis pinpointed the study by Bhattacharya and Swarup-Mitra 33 as an outlier. Its removal altered the meta-analysis results ( P  = 0.052, Hedges g: − 0.99, 95% CI − 1.98 to − 0.01; Fig.  5 ).

Results of the leave-one-out rerun meta-analysis of the difference in the reduced glutathione levels between malaria patients and uninfected controls. CI confidence interval, green dot pooled effect estimate, green horizontal line confidence interval, red vertical line pooled effect estimate, gray vertical line no effect line.

Publication bias

Two standard methodologies were implemented to evaluate the presence of publication bias: a funnel plot analysis and Egger regression test. The results depicted in the funnel plot were asymmetrical (Fig.  6 ), suggesting an imbalanced distribution of studies around the mean effect size, implying substantial publication bias. Egger test was further conducted to quantify the bias captured in the funnel plot. Notably, this test identified a significant result ( P  < 0.01). Therefore, both the asymmetrical funnel plot and the significant Egger test result collectively indicate the possible presence of publication bias due to the small-study effect in the meta-analysis.

Funnel plot showing an asymmetrical distribution of the effect estimates between the middle line of the plot. CI confidence interval, Blue dot effect estimate, red vertical line pooled effect estimate.

Qualitatively, most studies concur that GSH levels significantly decrease in malaria patients compared with uninfected controls, corroborating the role of GSH in malaria pathogenesis. Furthermore, the meta-analysis confirmed that GSH levels significantly decreased in malaria patients compared with uninfected controls. GSH, a critical antioxidant in human cells, protects the body from damage caused by oxidative stress 42 . The observed decrease in GSH levels in malaria patients may be a consequence of the body utilizing its GSH reserves to counteract the oxidative stress caused by malaria. Reductions in host GSH levels during malaria can have dual implications for disease pathogenesis. On the one hand, diminished GSH renders host erythrocytes more vulnerable to oxidative damage, potentially exacerbating disease symptoms due to increased oxidative stress 43 . Conversely, the malaria parasite, particularly P. falciparum , relies on host GSH to detoxify and resist antimalarial drugs 4 . Therefore, while reduced GSH may weaken the host’s defense against oxidative damage, it can also hinder the parasite’s ability to survive drug treatments. Thus, the intricate balance between host and parasite GSH dynamics underscores the complex nature of malaria pathogenesis 44 . However, this generalized trend is subject to certain exceptions. For instance, Aqeel et al. found decreased GSH levels, specifically in patients with P. vivax malaria but not in patients with P. falciparum malaria 31 . This divergence may stem from the different pathophysiological mechanisms employed by P. falciparum and P. vivax . Since P. vivax and P. falciparum exhibit different levels of disease severity, this may influence the level of oxidative stress and, consequently, GSH consumption 45 . For example, infection with P. falciparum can lead to more severe complications, yet some P. vivax cases can also develop severe malaria 46 , 47 . Nevertheless, no difference in GSH levels between P. falciparum and P. vivax malaria was observed, suggesting that more studies are necessary to determine differences in the distinct antioxidant levels between these two species. Furthermore, the meta-analysis of the clinical status of patients revealed no significant difference in GSH levels between symptomatic and asymptomatic malaria cases. This suggests that alterations in GSH levels are consistent, irrespective of the presence of symptoms. Additionally, a persistent reduction of plasma GSH levels in the early stages of the disease has been observed, which was later compensated during the advanced phase 31 . Thus, reduced GSH levels may be common during the acute phase of Plasmodium infection, regardless of disease severity or whether the infection is caused by P. vivax or P. falciparum .

Other subgroup meta-analyses demonstrated differences in GSH levels between malaria patients and controls across specific parameters, such as geographic location and participant groups. Notably, African studies showed a significant difference in GSH levels between malaria patients and controls, whereas Asian studies did not. This discrepancy may be because the African studies mainly enrolled children. In the subgroup analysis of age groups of participants, only studies involving children showed significant differences in GSH levels, possibly indicating that malaria has a more pronounced effect on GSH levels in this age group. Furthermore, the less mature immune systems of children may impact the oxidative stress response 48 . Additionally, children in Africa have lower antioxidant levels, which may lead to more severe malaria cases 49 .

Interestingly, Babalola et al. 19 and Fitri et al. 20 reported no significant differences in GSH levels between different patient groups. This finding may be attributed to a range of factors, including the timing of sample collection, the disease stage, and individual variations in patients’ antioxidant response. In contrast, two studies reported increased GSH levels in malaria patients 17 , 18 . While this may initially seem counterintuitive given the body’s typical response to oxidative stress, it is important to note that the elevated GSH levels are likely attributed to the parasite itself. In their bid to survive and resist antimalarial drugs, Plasmodium species can upregulate GSH synthesis, leading to observed increases in overall GSH levels within the host 50 , 51 . Sohail et al. proposed that the observed increase in GSH levels in malaria patients could be due to transitional polymorphisms within GSTs, which might enhance the host’s GSH availability 17 . Tyagi et al. suggested that increased GSH levels among malaria patients might be due to decreased GSH utilization 18 .

The relationship between GSH levels and parasite density varied across studies, with some reporting a negative relationship and others finding no significant association 33 , 38 . These discrepancies may be attributed to factors such as variations in the host’s immune response, the parasite’s lifecycle stage when the sample was collected, or differences in Plasmodium species. Oxidative stress and sickle cell disease are related to each other 52 . One of the included studies demonstrated that patients with malaria and sickle cell disease experienced severe oxidative stress 32 . The authors reported that although the GSH levels were higher in patients without sickle cell disease compared with those with malaria and sickle cell disease, the difference was not statistically significant. Therefore, patients with both malaria and sickle cell disease may have a higher demand for GSH to detoxify the increased oxidative stress 32 .

While the meta-analysis demonstrated a significant reduction in GSH levels in malaria patients compared with uninfected controls, indicating an association between malaria and lower levels of this critical antioxidant, the high variability among studies ( I 2 : 99.12%) must not be ignored, suggesting substantial heterogeneity in the results. A limited number of studies investigated GSH levels in various contexts: (i) malaria patients with severe complications versus those without severe complications, (ii) asymptomatic versus symptomatic malaria, and (iii) P. falciparum versus non- P. falciparum malaria. Thus, the conclusions of our study were limited. Among the high-quality studies, there was a significant difference in GSH levels with a substantial effect size. Conversely, moderate-quality studies did not show a statistically significant difference. This may highlight the importance of study quality when interpreting results. Additionally, the level of heterogeneity remained high when the subgroup analyses were performed. Therefore, the true confounders of the relationship between GSH and malaria remain unidentified. Other potential confounders may include both infectious and noninfectious conditions that are co-endemic with malaria, such as nutritional deficiencies 53 , diabetes 54 , human immunodeficiency virus 55 , and coronavirus disease 2019 56 . Based on the information from the included studies, the timing of sample collection was not explicitly stated in each study. Consequently, a meta-regression analysis to test whether the timing of sample collection influenced the effect estimate of the meta-analysis could not be performed. The final limitation is the evidence of significant publication bias, and the sensitivity analysis calls for a cautious interpretation of these findings. The considerable impact of a single study on the overall meta-analysis outcome underscores the importance of incorporating a diverse range of studies to mitigate potential biases.

This comprehensive review and meta-analysis of the existing literature indicate a trend of decreased GSH levels in malaria patients compared with uninfected controls, which is consistent with the majority of the reviewed studies. Furthermore, the meta-analysis underlines the potential of GSH as a diagnostic biomarker for malaria. However, the relationship between GSH levels and specific characteristics, such as Plasmodium species, malaria symptoms, and geographic location, revealed more nuanced findings. Further studies are necessary to corroborate these findings and delve deeper into the complex relationship between malaria and GSH levels.

Data availability

All data relating to the present study are available in this manuscript and supplementary files.

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Manas Kotepui, Kwuntida Kotepui, Hideyuki J. Majima & Jitbanjong Tangpong

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Aongart Mahittikorn

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M.K., A.M., and K.U.K. carried out the study design, study selection, data extraction, statistical analysis; and drafted the manuscript. H.J.M., J.T., and H.C.Y. participated in reviewing and critical editing the manuscript. All authors read and approved the final manuscript.

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Kotepui, M., Kotepui, K., Mahittikorn, A. et al. Association of reduced glutathione levels with Plasmodium falciparum and Plasmodium vivax malaria: a systematic review and meta-analysis. Sci Rep 13 , 16483 (2023). https://doi.org/10.1038/s41598-023-43583-z

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• Volume 13, Issue 9
• Efficacy and safety of oropharyngeal muscle strength training on poststroke oropharyngeal dysphagia: a systematic review and meta-analysis
• Article Text
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• http://orcid.org/0000-0003-4397-1723 Minxing Gao 1 , 2 ,
• Lingyuan Xu 1 ,
• Xin Wang 1 ,
• Xiaoqiu Yang 1 ,
• Ying Wang 1 ,
• Heying Wang 1 ,
• Jinan Song 1 ,
• Fenghua Zhou 1
• 1 Department of Rehabilitation , Shengjing Hospital of China Medical University , Shenyang , Liaoning , China
• 2 Department of Physical Medicine and Rehabilitation , Second Clinical College China Medical University , Shenyang , Liaoning , China
• Correspondence to Fenghua Zhou; zhoufh{at}sj-hospital.org

Objectives To investigate how oropharyngeal muscle strength training affected the safety and performance of swallowing in patients with poststroke oropharyngeal dysphagia.

Design Systematic review and meta-analysis.

Data sources Cochrane Central Register of Controlled of Trials, Web of Science, PubMed, Embase databases and ClinicalTrials.gov were systematically searched, for publications in English, from database inception to December 2022.

Eligibility criteria Studies comparing the effect of oropharyngeal muscle strength training with conventional dysphagia therapy in patients with poststroke. Penetration-Aspiration Scale (PAS) and Functional Oral Intake Scale (FOIS) were assessed as the main outcomes.

Data extraction and synthesis Two researchers independently screened the literature, extracted data and evaluated the quality of the included studies, with disagreements resolved by another researcher. The Cochrane risk-of-bias tool was used to assess the risk of bias. Review Manager V.5.3 was employed for the meta-analysis. Random effect models were used for meta-analysis.

Results Seven studies with 259 participants were included in this meta-analysis. The results showed that oropharyngeal muscle strength training could reduce PAS score compared with conventional dysphagia therapy (mean difference=−0.98, 95% CI −1.34 to −0.62, p<0.0001, I 2 =28%). The results also showed that oropharyngeal muscle strength training could increase FOIS score (mean difference=1.04, 95% CI 0.55 to 1.54, p<0.0001, I 2 =0%) and the vertical displacement of the hyoid bone (mean difference=0.20, 95% CI 0.01 to 0.38, p=0.04, I 2 =0%) compared with conventional dysphagia therapy.

Conclusion In patients with poststroke oropharyngeal dysphagia, oropharyngeal muscle strength training can improve swallowing safety and performance.

PROSPERO registration number CRD42022302471.

• Rehabilitation medicine
• Stroke medicine

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

http://dx.doi.org/10.1136/bmjopen-2023-072638

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STRENGTHS AND LIMITATIONS OF THIS STUDY

The study was registered in PROSPERO.

The risk of bias was assessed using the Cochrane risk-of-bias tool.

The Grading of Recommendations Assessment, Development and Evaluation system were used to assess the quality of evidence.

Rigorous reviewing methods were used in this systematic review and meta-analysis, including study selection, data extraction and risk of bias assessment by two independent reviewers.

The small number of randomised controlled trials published in English were included. More high-quality randomised controlled trials are needed to confirm our findings.

Introduction

Approximately 13.7 million people worldwide suffer from stroke annually, 1 and nearly half experience functional impairments to varying degrees, which seriously affects individuals’ quality of life. 2 3 Oropharyngeal dysphagia is a common poststroke functional impairment with an incidence of up to 80%. 4 Patients with oropharyngeal dysphagia exhibit symptoms such as aspiration and pharyngeal residue. 5

Most patients will recover swallowing function spontaneously. However, in many Asian countries, patients with chronic and severe dysphagia are commonly provided with a long-term nasogastric tube (NGT). 6 This both increases medical expenses and leads to complications, such as malnutrition, dehydration and aspiration pneumonia. 7 Therefore, proper swallowing training is especially important for safe swallowing. Training for oropharyngeal dysphagia may include surgery, drugs, compensatory dysphagia strategies, oropharyngeal muscle strength training, sensory and neurophysiologic stimulation and many others. Currently, oropharyngeal dysphagia trainings are often used for dysphagia caused by stroke, traumatic brain injury, spinal cord injury, head and neck tumours and Parkinson’s disease.

Compensatory dysphagia strategies often include swallowing manoeuvres, 8 improving oral sensory awareness, 9 postural changes 10 and dietary modifications, 11 among others. The goal of compensatory dysphagia strategies is to improve the symptoms of dysphagia to ensure a safety and adequate intake of nutrients and fluids. However, the effect is temporary. Therefore, additional scientific and novel training programmes are required as a supplement. Nowadays, oropharyngeal muscle strength training is one of popular programmes.

Oropharyngeal muscle strength training usually includes Shaker exercise 12 (or chin tuck against resistance exercise 13 ), and tongue strengthening exercise. 14–16 Suprahyoid muscles are the most basic structures responsible for hyoid and larynx elevation. 17 Insufficient elevation of the hyoid and larynx results in increasing the amount of pharyngeal residue and the risk of aspiration. 18 Fujiki et al 19 found that Shaker exercise aimed to improve swallowing biomechanical effects by increasing the excursion or duration of hyolaryngeal movement. During swallowing, superior hyolaryngeal excursion is thought to help protect the airway and prevent aspiration.

The number of studies investigating the effect of oropharyngeal muscle strength training on changes in swallowing physiology in healthy individuals 20 21 and treatment effectiveness in patients with dysphagia 22 has increased. Nonetheless, most studies have concentrated on healthy or elderly people, as well as dysphagia caused by Parkinson’s disease or head and neck cancer. Some studies examined the effect of oropharyngeal muscle strength training on patients with poststroke oropharyngeal dysphagia. 23 24 However, systematic reviews and meta-analyses are scarce.

Therefore, we conducted this meta-analysis to determine whether oropharyngeal muscle strength training can improve the safety and performance of swallowing in patients with poststroke oropharyngeal dysphagia, as well as whether differences in training type, time and intensity can affect the safety and treatment effect of swallowing.

This meta-analysis was conducted under the guidance of the Cochrane Handbook for Systematic Reviews of Interventions 25 and reported according to the update Preferred Reporting Items for Systematic Reviews and Meta-Analysis, 26 26 as well as the research protocol we developed. 27 The protocol for this study is available online.

Literature search and search strategy

We systematically searched the Cochrane Central Register of Controlled of Trials, Web of Science, Medline, Embase databases and ClinicalTrials.gov ( www.clinicaltrials.gov ). The retrieval method was a combination of medical subject headings terms and free terms. Key terms included ‘deglutition disorders’, ‘dysphagia’, ‘Shaker exercise’, ‘head lift exercise’, ‘chin tuck against resistance’, ‘Iowa oral performance instrument’, ‘isometric lingual exercise’, ‘tongue to palate resistance training’ and ‘tongue strengthening exercises’. The references of the included studies and systematic reviews of related topics were manually retrieved to execute a comprehensive search. The retrieval time limit was from the establishment of the database to 11 December 2022. The primary search strategy is outlined in online supplemental additional file 1 .

Supplemental material

Inclusion and exclusion criteria, inclusion criteria.

This systematic review and meta-analysis included randomised controlled trials (RCTs) published in English. Participants were stroke patients who were diagnosed with oropharyngeal dysphagia via the videofluoroscopic swallowing study, flexible endoscopic evaluation of swallowing or clinical assessment. Regardless of whether other training methods are combined, the intervention must contain at least one of the following methods: Shaker exercise (or chin tuck against resistance exercise or head lift exercise), device facilitated lingual exercise (Iowa Oral Performance Instrument, IOPI MEDICAL LLC, Redmond, Washington, USA) or low technology (tongue to palate or tongue to tongue depressor) exercises. Lingual range of motion exercises are not considered as experimental group. Comparison involved conventional dysphagia therapy or placebo training (the same equipment was used as in the intervention group, but without resistance). Primary outcomes included safety (Penetration-Aspiration Scale, PAS) 28 and performance outcomes (Functional Oral Intake Scale, FOIS) 29 of swallowing. Secondary outcomes included the severity of dysphagia (such as Functional Dysphagia Scale 30 and Videofluoroscopic Dysphagia Scale 31 ) and indicators of swallowing physiology (such as hyoid movement 32 and tongue pressure 33 ).

Exclusion criteria

Participants were under 18 years old; recurrent stroke; a history of head and neck surgery before stroke onset, such as thyroidectomy and symptoms of dysphagia caused by oropharyngeal cancer, Parkinson’s disease or drugs before onset.

Study selection

Two researchers (HW and JS) independently screened the literature titles and abstracts according to the research protocol, 27 eliminated literature that did not meet the selection criteria and independently reviewed the full texts of the remaining literature before finally confirming inclusion. Any disagreement should be resolved in consultation with a third reviewer (FZ).

Data extraction

Two researchers (YW and XW) documented and independently extracted data from eligible articles using Excel spreadsheets. The specific format is as follows: (1) general characteristics: country, publication year, the first author’s name, sample size and patient characteristics. (2) intervention and comparison: training type, intensity, duration and frequency. (3) outcome: PAS, FOIS, Functional Dysphagia Scale, Videofluoroscopic Dysphagia Scale, hyoid bone movement and tongue pressure. The lead author was contacted by email if incomplete data were provided for analysis. Any disagreements between the two researchers during the abovementioned process were resolved by discussion or consultation with a third researcher (FZ).

Risk of bias assessment

Two researchers (LX and XY) independently assessed the risk of bias of included studies using the Cochrane risk-of-bias tool. 34 The Cochrane risk-of-bias tool was recommended by Cochrane handbook including random sequence generation (selection bias), allocation concealment (selection bias), blinding of participants and personnel (performance bias), blinding of outcome assessment (detection bias), incomplete outcome data (attrition bias), selective reporting (reporting bias) and other bias (bias due to problems not covered elsewhere). In the Cochrane risk-of-bias tool, the risk of bias was classified as ‘low risk’, ‘unclear’ and ‘high risk’. The risk of bias graph was performed using the Cochrane Review Manager software (V.5.3; Cochrane, London, UK). Any disagreements between the two researchers during the abovementioned process were resolved by discussion or consultation with a third researcher (FZ).

Quality of evidence

The quality of the evidence was assessed in terms of the risk of bias, inconsistency, indirectness, imprecision and publication bias according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. 35 The quality of the evidence for the primary and secondary outcomes was assessed and rated as very low, low, moderate or high.

Data analysis

This meta-analysis was performed using the Cochrane Review Manager software (V.5.3; Cochrane, London, UK). Based on the Cochrane Handbook for Systematic Reviews of Interventions (V.6.3, 2022), we calculated mean and SD in each group. If included study had more than one experimental group, we will combine the sample data according to the following formula. A random-effects model was used to quantitatively pool data to assess the treatment effects. Continuous data were presented using mean differences and 95% CI. The I 2 statistic 36 was used to assess heterogeneity among included studies; results were classified as low (I 2 <25%), moderate (I 2 between 25% and 50%) and high (I 2 >50%). Considering certain differences in intervention methods across studies, we performed subgroup analyses for training type, intensity and duration to explain the sources of heterogeneity.

SD combined=

Patient and public involvement

Patients or the general public will not be directly involved in the study. All data collected in this study will be derived from published data in databases or clinical trial registries.

Trial selection

We retrieved a total of 925 records from the Medline (n=276), Embase (n=346), Cochrane Central Register of Controlled of Trials (n=86) and Web of Science (n=217) databases. After deleting duplicated records (n=449), the titles and abstracts of the remaining 476 records were screened, and 49 records that appeared to meet the selection criteria were identified. After reading the full text, seven studies 37–43 were finally included. The screening process is outlined in figure 1 .

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Preferred reporting items for systematic reviews and meta-analysis flow diagram.

Study characteristics

The seven studies 37–43 included 259 participants; sample sizes ranged from 25 to 90 participants. The average disease course ranged from 19.2 to 37.2 weeks. The number of participants lost to follow-up varied between 0 and 11 (25%); the main reasons included hospital discharge and neck muscle fatigue. In the seven included studies, PAS was used to assess the safety of swallowing. FOIS was used in three studies 37 40 41 to assess swallowing performance. Characteristics of the included studies and interventions are shown in table 1 .

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Characteristics of the included studies

Results for the risk of bias assessment are shown in online supplemental figure 1 . While all studies used randomisation, there was a lack of detailed explanations and descriptions for allocation concealment. Five studies 37 38 41–43 used a blinded design, and in three studies, 37 41 43 the rate of loss to follow-up exceeded 20%, resulting in incomplete outcome data.

Safety of swallowing-PAS

All seven included studies (n=259) used PAS to assess the safety of swallowing. The results indicated a reduction (MD=−0.98, 95% CI −1.34 to −0.62, I 2 =28%, p<0.0001) in PAS score during oropharyngeal muscle strength training when compared with conventional dysphagia therapy group ( Figure 2 ).

Forest plot for Penetration-Aspiration Scale.

Subgroup analysis of PAS was performed to explain the sources of heterogeneity of the findings. Supine and upright position groups were generated according to the training type. The results suggested that compared with conventional dysphagia therapy group, PAS score decreased in the supine position group (MD=−1.13, 95% CI −1.55 to −0.71, I 2 =0%, p<0.0001), and decreased in the upright position group (MD=−0.82, 95% CI −1.46 to −0.18, I 2 =57%, p=0.01). Also, 60s and <60s groups were generated according to training intensity. The results revealed that compared with conventional dysphagia therapy group, PAS score decreased in both the 60s group (MD=−1.14, 95% CI −1.53 to −0.75, I 2 =0%, p<0.0001), and the <60s group (MD=−0.71, 95% CI −1.54 to −0.11, I 2 =70%, p=0.09); but no statistically significant differences were identified in the <60s group. Four and 6 weeks groups were generated according to the training time; the results revealed that compared with conventional dysphagia therapy group, PAS score decreased in 4 weeks group (MD=−0.78, 95% CI −1.17 to −0.39, I 2 =10%, p<0.0001), and decreased in 6 weeks group (MD=−1.40, 95% CI −1.89 to −0.91, I 2 =0%, p<0.0001).

Performance of swallowing

Functional oral intake scale.

Three studies 37 40 41 (n=85) used FOIS to assess the performance of swallowing. The results indicated that oropharyngeal muscle strength training increased (MD=1.04, 95% CI 0.55 to 1.54, I 2 =0%, p<0.0001) when compared with conventional dysphagia therapy ( Figure 3 ).

Forest plot for Functional Oral Intake scale.

Hyoid movement

Two studies 41 43 (n=56) evaluated the hyoid movement, and a meta-analysis demonstrated that oropharyngeal muscle strength training was associated with an increase of 0.09 in horizontal displacement of the hyoid when compared with conventional dysphagia therapy; no significant difference was observed (MD=0.09, 95% CI −0.05 to 0.23, I 2 =0%, p=0.21), but the vertical displacement of the hyoid increased (MD=0.20, 95% CI 0.01 to 0.38, I 2 =0%, p=0.04) ( Figure 4 ).

Forest plot for hyoid movement.

GRADE certainty of evidence

The GRADE evidence for the primary and secondary outcome measures is summarised in online supplemental additional file 2 ; the quality of evidence for the PAS, FOIS and hyoid bone movement was moderate.

Our meta-analysis comprehensively and systematically reviewed the current literature, comparing oropharyngeal muscle strength training and conventional dysphagia therapy for the treatment of patients with poststroke oropharyngeal dysphagia. We found that oropharyngeal muscle strength training can reduce PAS score, improve FOIS score and increase the vertical displacement of the hyoid in patients with poststroke oropharyngeal dysphagia.

PAS is an 8-point scale used to describe the depth and response to airway invasion during videofluoroscopy, 44 which is a standard method used by researchers and clinicians to assess the safety of swallowing. PAS is used to describe the depth of material into laryngeal vestibule or airway and whether it can be expelled. 45 Higher scores indicate more severe aspiration and less safe swallowing. This meta-analysis revealed that oropharyngeal muscle strength training can effectively reduce PAS score in patients with poststroke oropharyngeal dysphagia.

Shaker exercise is also known as the head lift exercise. Studies have shown that 46 Shaker exercise can effectively activate the suprahyoid muscles (geniohyoid, mylohyoid, digastric anterior/posterior belly and stylohyoid), increase the forward and upward displacement of the hyoid, achieve epiglottis inversion and laryngeal vestibular closure, and reduce residues in the epiglottic valleculae and pyriform recess, thereby reducing the risk of aspiration. However, Shaker exercise is performed against gravity in the supine position and requires strenuous physical effort, often causing neck muscle fatigue and temporary pain. Shaker exercise is difficult to accomplish in patients with neurological disorders, explaining the relatively high rate of loss to follow-up in the studies included in this meta-analysis. Chin tuck against resistance exercise is a modification of Shaker exercise, 47 which induces activation of the suprahyoid muscles by forcefully pressing the mandible against an elastic rubber ball in the sitting position. Park et al 21 found that chin tuck against resistance exercise helped to activate the suprahyoid muscle group in healthy adults. Additionally, it activated the sternocleidomastoid muscle less than Shaker exercise. Training in the supine and sitting positions can effectively activate the suprahyoid muscles; however, the rate of loss to follow-up for training in the sitting position is relatively low. Therefore, it may better serve patients with neurological disorders.

The amount of effort or force exerted during a single repetition of an exercise is reflected in intensity, and the length of hold can be used to define intensity in isometric exercises. 48 The results of this study reveal that maintaining a training intensity of 60s can significantly reduce the risk of aspiration, while a training intensity <60s has no statistical difference. The duration represents the total length of the training plan. A previous study 49 has shown that at least 4 weeks of training are required for significant increases in muscle volume and strength. Kraaijenga et al 50 found that 6 weeks of chin tuck against resistance exercise increased the muscle volume of suprahyoid muscles in healthy adults. While Choi et al 51 discovered that 6 weeks of Shaker exercise could increase the thickness of digastric and mylohyoid muscles in patients with poststroke dysphagia. Therefore, all studies included in this meta-analysis performed at least 4 weeks of training. However, our results demonstrated that 6 weeks of training may be more effective than 4 weeks. Nevertheless, there was no statistical difference.

FOIS is a 7-point scale developed to assess the level of functional oral intake of food and liquids in stroke patients. 52 FOIS describes distinct levels of oral intake, with levels 1–3 relating to varying degrees of tube feeding and levels 4–7 relating to varying degrees of oral feeding without feeding tube supplements. Patients with levels 1–3 sometimes had partial oral intake capacity, but they were still dependent on a feeding tube. This may be due to the clinician’s cautious about aspiration during the initial oral intake, or it may be due to prevent malnutrition and dehydration. This meta-analysis suggests that oropharyngeal muscle strength training can improve FOIS score in patients with poststroke oropharyngeal dysphagia. This may be that oropharyngeal muscle strength training could increase the strength of the suprahyoid muscles with reducing the risk of aspiration, and promote the production of swallowing with allowing the patient to intake more food and liquids in a shorter time, thus reducing the risk of malnutrition and dehydration.

For all we know, Park et al 21 summarised the applications of CTAR exercise, including healthy participants and stroke patients. They found that compared with control group, CTAR group showed a more significant improvement in PAS, but no statistically significant difference in FOIS. This may be that CTAR could induce a greater mean and peak values of suprahyoid muscle activation. But this systematic review did not compare healthy participants and stroke patients in PAS and FOIS. Speyer et al 22 found that Shaker exercise, CTAR and expiratory muscle strength training had significant effects for reducing PAS scores compared with CDT in stroke patients. Because of the heterogeneity between studies, this systematic review did not conduct subgroup analysis on the training dose and duration. Antunes and Lunet 20 found that head lift exercise showed better effects regarding postswallow aspiration than traditional therapy in upper oesophageal sphincter dysfunction. The main results of these studies are consistent with ours. For clinical, standardised treatment protocol is good for the comparison of therapeutic effects. But training dose and duration are always influenced by age, primary dysphagia aetiology, physical fitness level and so on. Future research should continue to explore the relationship on training dose and duration with training efficacy in order to establish standard parameters for oropharyngeal muscle strength training to maximise patient benefits.

Although this meta-analysis was reported following the PRISMA (PRISMA, preferred reporting items for systematic reviews and meta-analysis) guidelines to reduce bias, it still has some limitations. First, the number of available studies limited current analyses, and although more published data on oropharyngeal muscle strength training, the literature remains sparse and always concerned about healthy or Parkinson’s disease. The participants in this meta-analysis were only concerned with stroke, so there was less amount of literature included. Second, unpublished literature was not included. This may have resulted in an over-representation of positive treatment effects in this review. Third, Egger’s publication bias test is known to have limit efficiency for meta-analysis that involving less than 10 studies, we did not conduct the test. Fourth, some included studies had a high risk of bias in terms of randomisation and allocation, which may limit the quality of the evidence. Fifth, the score of PAS may vary depending on different bolus volumes, consistencies, postural manoeuvres and barium concentration. When the same task is repeated several times, penetration-aspiration events are unlikely to occur consistently within a person. Some researchers used mean PAS scores to represent the airway protection capability, but sometimes it rarely or never happened. In this meta-analysis, the maximum score of PAS is commonly used to represent the patient’s status. This, however, risks distorting the overall impression to one of impairment. But Beall et al found using PAS maximum scores contributed to the accuracy of classification of swallowing impairment. 53 In the future, the most informative way to represent PAS scores may be to report both the mode and the maximum score across a set of swallows for clinical purposes. 54

The minimal clinically important difference 55 is the minimum value indicating whether the difference between the scores of the scale before and after the intervention in clinical research is clinically significant; that is, how much the scale score changes can be regarded as clinically meaningful. The primary and secondary outcome measures in this study were not linked to minimal clinically important difference studies. It is therefore hoped that in the future, there will be more high-quality RCTs regarding the treatment of dysphagia and minimal clinically important difference studies evaluating various scales of dysphagia, which would be beneficial for the judgement of clinical treatment efficacy.

In conclusion, this meta-analysis has found that oropharyngeal muscle strength training can improve the safety and performance of swallowing in patients with poststroke oropharyngeal dysphagia. The evidence is still insufficient to support clinical use. To fully investigate the clinical efficacy, large-scale, multicentre RCTs are required.

Acknowledgments

We gratefully acknowledge Professor Xueyong Liu for his management and support of this research. We wish to acknowledge Yu He and Zhan Zhang for their suggestions on this research. We would like to thank Editage (www. editage. cn) for English language editing.

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

• Data supplement 1
• Data supplement 2
• Data supplement 3

Contributors MG, YW, LX and FZ designed the study and interventions. HW, JS and XY designed search strategies and perform the study search. MG, YW, XW and FZ perform data collection, analysis and synthesis. MG wrote the manuscript and all coauthors critically reviewed and approved the final manuscript. FZ is the guarantor of the protocol and the final review.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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