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This guide is designed to help novice and experienced review teams navigate the systematic review and/or meta-analysis process

One of the final steps in a systematic review is the **synthesis of evidence **and writing the **discussion.**

*Your team began working toward this stage in the protocol when you clearly identified the comparisons of interest. The work you've done in data extraction and critical appraisal phases will feed directly into the synthesis.*

Selecting the best approach for synthesis will depend on your scope, included material, field of research, etc. Therefore, it is important to follow methodological guidance that best matches your scope and field (e.g., *a heath-focused** review guided by the Cochrane Handbook*). It can also be helpful to check out the synthesis and discussion of systematic reviews published by journals to which you plan to submit your review.

In almost all cases, a **qualitative synthesis of some kind** will be part of your systematic review. A quantitative synthesis (e.g., meta-analysis) should only be pursued as appropriate.

**Meta-synthesis** and **Qualitative Evidence Synthesis **are term sometimes used to describe a systematic review with **only a qualitative synthesis**.

In some methodological guidance, this stage may effectively be described as a separate methodology altogether.

For example, the Cochrane Handbook, *Part 2: Core Methods* covers synthesis through the lens of conducting a meta-analysis and/or quantitative synthesis. In *Part 3: Specific perspectives in reviews, *Cochrane goes into more detail about qualitative evidence synthesis in Chapter 21: Qualitative Evidence. Similarly, the JBI Manual for Evidence Synthesis contains a stand-alone chapter, Chapter 2: Systematic Reviews of Qualitative Evidence

- How you will
**group data**for your synthesis**how grouping decisions are made**, whether you're pursuing just a qualitative synthesis or both a qualitative synthesis and a meta-analysis, is an important consideration prior to starting the synthesis. - Assess
**heterogeneity**between studies, even if you don't plan to pursue a meta-analysis. Consider variability in participants studied, the definitions/measurements/frequency/etc. of interventions, or exposures, or outcomes, etc. This is part of the process to determine which studies are reasonable to synthesize. **Selection of a formal qualitative synthesis approach**(*optional*)

**This is not a comprehensive list of approaches. **However, it can be a jumping off point for your team as you plan. The selection of approaches listed here is partially informed by Barnett-Page & Thomas (2009)

Note: Many of these approaches are *also* stand-alone qualitative research methods.

"In the case of qualitative systematic reviews,** raw data** consist of qualitative research findings (i.e. text) that have been** systematically extracted** from existing research reports...The manner in which these findings are coded is largely guided by the research topic and questions and the data that are available for analysis." (Finfgeld-Connett, 2014)

- Identification of data segments
- Memoing & diagramming
- Reflection

- Finfgeld-Connett D.
**Use of content analysis to conduct knowledge-building and theory-generating qualitative systematic reviews**.*Qualitative Research*. 2014;14(3):341-352. doi:10.1177/1468794113481790 - Neuendorf, K. (2017).
*The content analysis guidebook*.doi. org/10.4135/9781071873045

"Developed out of a need to conduct reviews that addressed questions relating to intervention need, appropriateness, acceptability, [and effectiveness] **without compromising on key principles** developed in systematic reviews"(Barnett-Paige & Thomas 2009)

According to Thomas & Harden (2008):

- Code text (line-by-line)
- Develop descriptive themes
- Generate analytic themes

Thomas J, Harden A. **Methods for the thematic synthesis of qualitative research in systematic reviews**. BMC Med Res Methodol. 2008 Jul 10;8:45. doi: 10.1186/1471-2288-8-45. PMID: 18616818; PMCID: PMC2478656.

The "rationale [behind framework synthesis] is that qualitative research produces large amounts of textual data in the form of transcripts, observational fieldnotes etc. The sheer wealth of information poses a challenge for rigorous analysis. Framework synthesis offers a **highly structured approach** to **organising **and **analysing data **(e.g. indexing using numerical codes, rearranging data into charts etc)." (Barnett-Page & Thomas, 2009)

According to Brunton & James (2020):

- Familiarization (with existing literature)
- Framework selection
- Indexing & charting
- Mapping & interpretation

- Brunton, G., Oliver, S., & Thomas, J. (2020).
**Innovations in framework synthesis as a systematic review method**. Research Synthesis Methods, 11(3), 316–330. https://doi.org/10.1002/jrsm.1399 - Dixon-Woods, M.
**Using framework-based synthesis for conducting reviews of qualitative studies**.*BMC Med***9,**39 (2011). https://doi.org/10.1186/1741-7015-9-39

Grounded theory is defined as "a specific methodology developed by Glaser and Strauss (1967) for the **purpose of building theory from data**. In this book the term grounded theory is used in a more generic sense to denote theoretical constructs derived from qualitative analysis of data." (Strauss & Corbin, 2008)

According to Barnett-Paige & Thomas, 2009, "key methods and assumptions...include":

- "
**simultaneous phases**of data collection and analysis; - inductive approach to analysis, allowing the
**theory to emerge from the theory**; - the use of
**constant comparison method**; - the use of theoretical sampling to reach theoretical saturation; and the generation of new theory"

- Glaser, B. G., & Strauss, A. L. (1967).
. Aldine.*The Discovery of Grounded Theory: Strategies for Qualitative Research* - Corbin, J., & Strauss, A. (2008).
. SAGE Publications, Inc. https://dx.*Basics of qualitative research (3rd ed.): Techniques and procedures for developing grounded theory*doi. org/10.4135/9781452230153

This is proposed as an alternative to "Meta-Analysis" (Nolbit & Hare, 1998; Barnett-Paige & Thomas 2009) and "should be **interpretive rather than aggregative**. We make the case that is should take the form of reciprocal translations of studies into one another" (Nolbit & Hare, 1998)

- Reciprocal translational analysis (RTA) - translate concepts; evolve overarching concepts
- Refutational synthesis - explore and explain contradictions between studies
- Lines-of-argument (LOA) synthesis - building up a picture of a whole from the parts (the individual studies)

**Improving reporting of meta-ethnography: The eMERGe reporting guidance** (documents the development of eMERGe)

- Sattar, R., Lawton, R., Panagioti, M.
*et al.***Meta-ethnography in healthcare research: a guide to using a meta-ethnographic approach for literature synthesis**.*BMC Health Serv Res***21,**50 (2021). https://doi-org.ezproxy.lib.vt.edu/10.1186/s12913-020-06049-w - France, E.F., Wells, M., Lang, H.
*et al.***Why, when and how to update a meta-ethnography qualitative synthesis**.*Syst Rev***5,**44 (2016). https://doi-org.ezproxy.lib.vt.edu/10.1186/s13643-016-0218-4 - Noblit, G. W., & Hare, R. D. (1988).
. SAGE Publications, Inc. https://dx.*Meta-ethnography*doi. org/10.4135/9781412985000

- Barnett-Page, E., Thomas, J.
**Methods for the synthesis of qualitative research: a critical review**.*BMC Med Res Methodoly***9,**59 (2009). https://doi-org.ezproxy.lib.vt.edu/10.1186/1471-2288-9-59 - Flemming, K., & Noyes, J. (2021).
**Qualitative Evidence Synthesis: Where Are We at?***International Journal of Qualitative Methods*. https://doi.org/10.1177/1609406921993276

“The statistical analysis of a large collection of **analysis results from individual studies** for the purpose of **integrating the findings**.” (Glass, 1976)

“A statistical analysis which combines the results of **several independent studies **considered by the analyst to be **‘combinable’.**” (Huque, 1988)

“Meta-analysis is the **statistical combination of results from two or more separate studies**.” (Cochrane Handbook for Systematic Reviews of Interventions version 6.3, Chapter 10)

The Cochrane Handbook (Chapter 10.1) states:

"Do not start here!"...results of meta-analyses can be

very misleading if suitable attention has not been givento formulating the review question; specifying eligibility criteria; identifying and selecting studies; collecting appropriate data; considering risk of bias; planning intervention comparisons; and deciding what data would be meaningful to analyse.

Meta-analyses are a desirable end-goal as a this kind of synthesis can:

- Increase statistical power / improve precision
- Result in a summary estimate of the direction and size of the effect or association
- Determine consistent across studies and explore why studies found different results
- Address questions that can’t be addressed by the individual studies (related to factors that differ across studies)
- Potentially resolve uncertainties if disagreement in literature and identify areas where evidence is insufficient

Despite the appeal of the meta-analytic approach, it is vital that studies in the meta-analysis **measure the same thing in the same way **- that the studies themselves are **reasonable to combine statistically**.

According to Cochrane Chapter 12.1, "Legitimate reasons [for not conducting a meta-analysis] include** limited evidence**; **incompletely reported **outcome/effect estimates, or **different effect measures** used across studies; and** ****bias **in the evidence." Table 12.1.a describes scenarios that may preclude meta-analyses, with possible solutions

Likewise, a synthesis is **only as good as the studies included**. In other words, a meta-analysis cannot improve poor quality studies.

*This is not a comprehensive list - as with any analysis, you'll need to select specific approaches based on the kind of data you have.*

- How you will
**group data**for your synthesis**how grouping decisions are made**, is an important consideration prior to starting the synthesis. **Effect size measures**must be comparable across included studies and/or computable given the information available in the primary studies. For example, in a review of weight loss studies, you may convert all effects to pounds of lost weight.**Choose a fixed- or random-effects model.**In most cases, random-effects model will be most appropriate as meeting fixed-effects assumptions is difficult. In fact, Cochrane and Campbell Collaborations say**never report only fixed effects, either random or both.****Fixed-Effects:**"assumes (1) all studies are measuring the same common (true) effect size (why we call it fixed), [and] (2) the observed results would be identical expect for random (sampling error)" (Borenstein, 2009)**Random-Effects:**"assumes (1) there are multiple population effects that the studies are estimating - different effect sizes underlying different studies, [and] (2) variability between effect sizes is due to sampling error + variability in population of effects" (Borenstein, 2009)

- There are some
**additional analyses**you'll need to run to determine**heterogeneity**(how different studies are from each other). A**sensitivity analysis**or**meta-regression**is used to evaluate the effects of including or excluding certain groups of studies in your analysis, for example studies rated as low quality or high-risk of bias during the critical appraisal. You can also consider**publication bias**in your sample using a funnel plot (although there are valid critiques of the reliability of this practice).

- Glass, Gene V.
**“Primary, Secondary, and Meta-Analysis of Research.”***Educational Researcher*, vol. 5, no. 10, 1976, pp. 3–8, https://doi.org/10.2307/1174772. - Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009).
. John Wiley & Sons, Ltd. https://doi.org/10.1002/9780470743386*Introduction to Meta-Analysis* - Pigott, T. D., & Polanin, J. R. (2020).
**Methodological Guidance Paper: High-Quality Meta-Analysis in a Systematic Review**.*Review of Educational Research*,*90*(1), 24–46. https://doi.org/10.3102/0034654319877153

*Several tools exist for running your own meta-analyses. If you need further support, check out the help tab in this box.*

**RevMan**| Developed by the Cochrane Collaboration; good for beginners**PyMeta**| Built from PythonMeta package for command line interface in python**Comprehensive Meta-Analysis |***fee-based***MedCalc**|*fee-based*

**Metafor**| R package; introduction from creator, Wolfgang Viechtbauer**xmeta**| R package; toolbox for multivariate meta-analyses**PythonMeta**| Python package; graphical interface available as PyMeta

- Polanin, J. R., Hennessy, E. A., & Tanner-Smith, E. E. (2017).
**A Review of Meta-Analysis Packages in R**.*Journal of Educational and Behavioral Statistics*,*42*(2), 206–242. https://doi.org/10.3102/1076998616674315 - Video for using R for Meta package

*A meta-analysis is most commonly presented as a Forest Plot.*

If you are new to the concept of forest plots, check out Dr. Terry Shaneyfelt from UAB School of Medicine **How to interpret a forest plot.**

According to Cochrane Chapter 9.5, "There are circumstances under which a meta-analysis is not possible, however, and other statistical synthesis methods might be considered, so as to make best use of the available data."

Table 9.5.a from the Cochrane Handbook, represented below, outlines some alternative synthesis method (and one *summary* method in the first row).

Methods |
Questions addressed |
Example plots |

( |
narrative summary of evidence presented in either text or tabular form |
Forest plot ( |

Vote counting |
Is there any evidence of an effect? |
Harvest plot Effect direction plot |

Combining P values |
Is there evidence that there is an effect in at least one study? | Albatross plot |

Summary of effect estimates |
What is the range and distribution of observed effects? |
Box and whisker plot Bubble plot |

Pairwise meta-analysis |
What is the common intervention effect? (fixed-effects model) What is the average intervention effect? (random-effects model) |
Forest plot |

Network meta-analysis |
Which intervention of multiple is most effective? |
Forest plot Network diagram Rankogram plot |

Subgroup analysis / meta-regression |
What factors modify the magnitude of the intervention effects? |
Forest plot Box and whiskey plot Bubble plot |

While the Evidence Synthesis Services (ESS) team at the University Libraries is available to support the other stages of a systematic review and/or meta-analysis,

we recommend reaching out to the **Statistical Applications and Innovations Group (SAIG)** for support in the statistical synthesis / meta-analysis.

Chapter III: Reporting the Review (specifically part III.III); *Note: if you are not conducting a Cochrane Review, use this resource as a guidepost*

Chapter 9: Summarizing study characteristics and **preparing for synthesis**

- 9.2 A
**general framework**for synthesis - 9.3
**Preliminary steps**of a synthesis - 9.4
**Checking data**before synthesis - 9.5
**Types**of synthesis

Chapter 10: **Analyzing data and undertaking meta-analyses **

- 10.1
**Do not start here!** - 10.2 Introduction to
**meta-analysis** - 10.3 A generic
**inverse-variance approach**to meta-analysis - 10.4 Meta-analysis of
**dichotomous outcomes** - 10.5 Meta-analysis of
**continuous outcomes** - 10.6
**Combining dichotomous and continuous**outcomes - 10.7 Meta-analysis of
**ordinal outcomes**and measurement scales - 10.8 Meta-analysis of
**counts**and rates - 10.9 Meta-analysis of
**time-to-event****outcomes** - 10.10
**Heterogeneity** - 10.11 Investing heterogeneity
- 10.12
**Missing data** - 10.13
**Bayesian approaches**to meta-analysis - 10.14
**Sensitivity analyses** - 10.S1 Supplementary material:
**Statistical algorithms in Review Manager 5.1**

Chapter 12: Synthesizing and presenting findings using** other methods**

- 12.1 Why a meta-analysis of effect estimates
**may not be possible** - 12.2
**Statistical synthesis when**meta-analysis of effect estimates is**not possible** - 12.3
**Visual display and presentation**of the data

Chapter 13: Assessing** risk of bias due to missing results **in a synthesis

- 13.2 Minimizing risk of bias
**due to missing results** - 13.3 A
**framework for assessing**risk of bias due to missing results in a synthesis

Chapter 15: **Interpreting results **and drawing conclusions

- 15.2 Issues of
**indirectness and applicability** - 15.3
**Interpreting results**of statistical analyses - 15.4 Interpreting results from
**dichotomous outcomes** - 15.5 Interpreting results from
**continuous outcomes**(including standardized mean differences) - 15.6
**Drawing conclusions**

Chapter 21: **Qualitative Evidence **

- 21.2 Designs for synthesizing and
**integrating qualitative evidence with intervention reviews** - 21.3
**Defining qualitative evidence**and studies - 21.4
**Planning qualitative evidence synthesis**linked to an intervention review - 21.5
**Question development** - 21.13
**Methods for integrating the qualitative evidence synthesis**with an intervention review

Conducting systematic reviews of intervention questions III: **Synthesizing data** from intervention studies using meta-analysis. O’Connor AM, Sargeant JM, Wang C. Zoonoses Public Health. 2014 Jun;61 Suppl 1:52-63. doi: 10.1111/zph.12123. PMID: 24905996

**Meta-analyses** including data from observational studies. O’Connor AM, Sargeant JM. Prev Vet Med. 2014 Feb 15;113(3):313-22. doi: 10.1016/j.prevetmed.2013.10.017. Epub 2013 Oct 31. PMID: 24268538

Conducting systematic reviews of intervention questions II: Relevance screening, data extraction, assessing risk of bias, presenting the **results and interpreting the findings.** Sargeant JM, O’Connor AM. Zoonoses Public Health. 2014 Jun;61 Suppl 1:39-51. doi: 10.1111/zph.12124. PMID: 24905995

C59.** Addressing risk of bias** / study quality in the synthesis (*review / final manuscript*)

C60**. Incorporating assessments** of risk of bias (*review / final manuscript*)

C61. **Combining **different **scales **(*review / final manuscript*)

C62. Ensuring **meta-analyses are meaningful** (*review / final manuscript*)

C63. Assessing **statistical heterogeneity** (*protocol &* *review / final manuscript*)

C64. Addressing **missing outcome data** (*review / final manuscript*)

C65. Addressing **skewed data** (*review / final manuscript*)

C66. Addressing studies with **more than two groups** (*protocol &* *review / final manuscript*)

C67.** Comparing subgroups** (*protocol &* *review / final manuscript*)

C68.** Interpreting subgroup analyses** (*protocol &* *review / final manuscript*)

C69. Considering **statistical heterogeneity when interpreting **the results (*review / final manuscript*)

C70. Addressing **non-standard designs **(*protocol &* *review / final manuscript*)

C71. Conducting **sensitivity analysis** (*protocol &* *review / final manuscript*)

C72. **Interpreting results** (*review / final manuscript*)

C73. Investigating **reporting biases** (*review / final manuscript*)

C77. Formulating **implications for practice** (*review / final manuscript*)

C78. ** Avoiding recommendations** (

C79. Formulating** implications for research** (*review / final manuscript*)

CEE **Standards for conduct **and reporting

9.1 Systematic Reviews

9.1.1 **Narrative **Synthesis

9.1.2 **Quantitative **Data Synthesis

9.1.3 **Qualitative **Data Synthesis

10.1 The **interpretation **of evidence syntheses

10.2 **Reporting conduct** of evidence synthesis

10.3 **Reporting findings** of evidence syntheses

If quantitative synthesis is not appropriate, describe the

type of summary planned(Item 15d)

*all of the above plus:*

Describe

criteria under which study data will be quantitatively synthesised(Item 15a)...quantitative synthesis, describeplanned summary measures, methods ofhandling dataand methods ofcombining data from studies, including any plannedexploration of consistency(such as I2 , Kendall’s τ)(Item 15b)...describe any proposedadditional analyses(such as sensitivity or subgroup analyses, meta-regression)(Item 15c)

**Essential Items**

- Describe the
**processes used to decide**which studies were**eligible for each synthesis**.*(Item 13a)* - Report any
**methods required to prepare the data**collected from studies for presentation or synthesis, such as handling of missing summary statistics or data conversions*(Item 13b)* - Report
**chosen tabular structure(s)**used to display results of individual studies and syntheses, along with details of the data presented*(Item 13c)* - Report
**chosen graphical methods**used to visually display results of individual studies and syntheses*(Item 13c)* - If it was not possible to conduct a meta-analysis,
**describe and justify the synthesis methods**...or**summary approach used***(Item 13d)* - If a
**planned synthesis was not considered possible**or appropriate, report this and the**reason for that decision***(Item 13d)*

**Additional Items**

- If studies are ordered or grouped within tables or graphs based on study characteristics (such as by size of the study effect, year of publication), consider
**reporting the basis for the chosen ordering/grouping***(Item 13c)* - If non-standard graphs were used, consider reporting the
**rationale for selecting the chosen graph***(Item 13c)*

*all of the above plus:*

- ...reference the
**software, packages, and version numbers**used to implement synthesis methods (such as metan in Stata metafor (version 2.1-0) in R118)*(Item 13d)* - ...specify
*(Item 13d)*:- the meta-analysis
**model**(fixed-effect, fixed-effects, or random-effects) and provide**rationale**for the selected model. - the
**method**used (such as Mantel-Haenszel, inverse-variance). - any methods used to identify or quantify
**statistical heterogeneity**(such as visual inspection of results, a formal statistical test for heterogeneity, heterogeneity variance (τ2), inconsistency (such as I2), and prediction intervals)

- the meta-analysis
- If a
**random-effects meta-analysis model was used**, specify*(Item 13d)*:- the
**between-study (heterogeneity)**variance estimator used (such as DerSimonian and Laird, restricted maximum likelihood (REML)). - the
**method used to calculate the confidence interval for the summary effect**(such as Wald-type confidence interval, Hartung-Knapp-Sidik-Jonkman)

- the
- If a
**Bayesian approach to meta-analysis**was used, describe the**prior distributions**about quantities of interest (such as intervention effect being analysed, amount of heterogeneity in results across studies)*(Item 13d)* - If
**multiple effect estimates from a study**were included in a meta-analysis...describe the**method(s) used to model or account for the statistical dependency.**..*(Item 13d)* - If methods were used to explore possible
**causes of statistical heterogeneity**, specify the**method used**(such as subgroup analysis, meta-regression)*(Item 13e)* - If
**subgroup analysis or meta-regression**was performed, specify for each:**which factors**were explored,**levels**of those factors, and which**direction of effect**modification was expected and why (where possible)*(Item 13e)*- whether analyses were conducted using
**study-level variables**(where each study is included in one subgroup only),**within-study contrasts**(where data on subsets of participants within a study are available, allowing the study to be included in more than one subgroup), or**some combination**of the above (*Item 13e)* - how
**subgroup effects were compared**(such as statistical test for interaction for subgroup analyses)*(Item 13e)*

- If other methods were used to
**explore heterogeneity**because data were not amenable to meta-analysis of effect estimates, describe the methods used (such as structuring tables to examine variation in results across studies based on subpopulation, key intervention components, or contextual factors) along with the**factors and levels***(Item 13e)* - If any analyses used to explore heterogeneity were
**not pre-specified,**identify them as such*(Item 13e)* - If
**sensitivity analyses**were performed, provide d**etails of each analysis**(such as removal of studies at high risk of bias, use of an alternative meta-analysis model)*(Item 13f)* - If any
**sensitivity analyses**were**not pre-specified**, identify them as such*(Item 13f)*

If a random-effects meta-analysis model was used, consider specifying other details about the methods used, such as the method for calculating confidence limits for the heterogeneity variance *(Item 13d)*

- Specify the
**methods**...**used to assess the risk of bias due to missing results**in a synthesis (arising from reporting biases). - If risk of bias due to missing results was assessed using an existing tool, specify the
**methodological components/domains/items**of the tool, and the**process used**to reach a judgment of**overall risk of bias**. - If any
**adaptations**to an existing tool to assess risk of bias due to missing results were made (such as omitting or modifying items), specify the adaptations. - If a
**new tool**to assess risk of bias due to missing results was developed for use in the review, describe the content of the tool and make it publicly accessible. - Report
**how many reviewers**assessed risk of bias due to missing results in a synthesis, whether multiple reviewers worked independently, and any processes used to resolve disagreements between assessors. - Report any
**processes used to obtain or confirm relevant information**from study investigators. - If an
**automation tool**was used to assess risk of bias due to missing results, report**how the tool was used**, how the tool was**trained**, and details on the**tool’s performance and internal validation**

- Provide a
**brief summary of the characteristics and risk of bias**among studies contributing to each synthesis (meta-analysis or other). The summary should focus only on study characteristics that help in interpreting the results (especially those that suggest the evidence addresses only a restricted part of the review question, or indirectly addresses the question). If the same set of studies contribute to more than one synthesis, or if the same risk of bias issues are relevant across studies for different syntheses, such a summary need be provided once only*(Item 20a)* - Indicate
**which studies were included in each synthesis**(such as by listing each study in a forest plot or table or citing studies in the text)*(Item 20a)* - Report
**results of all statistical syntheses**described in the protocol and all syntheses conducted that were not pre-specified*(Item 20b)*

*all of the above plus:*

- ...report for each:
- the
**summary estimate and its precision**(such as standard error or 95% confidence/credible interval). - measures of
**statistical heterogeneity**(such as τ2, I2, prediction interval).

- the
- If
**other statistical synthesis methods**were used (such as summarising effect estimates, combining P values), report the**synthesised result and a measure of precision**(or equivalent information, for example, the number of studies and total sample size)*(Item 20b)* - If the statistical synthesis
**method does not yield an estimate of effect**(such as when P values are combined), report the**relevant statistics**(such as P value from the statistical test), along with an**interpretation of the result**that is consistent with the question addressed by the synthesis method (for example, “There was strong evidence of benefit of the intervention in at least one study (P < 0.001, 10 studies)” when P values have been combined)*(Item 20b)* - If
**comparing groups**, describe the**direction of effect**(such as fewer events in the intervention group, or higher pain in the comparator group)*(Item 20b)* - If
**synthesising mean differences**, specify for each synthesis, where applicable, the**unit of measurement**(such as kilograms or pounds for weight), the**upper and lower limits**of the measurement scale (for example, anchors range from 0 to 10),**direction of benefit**(for example, higher scores denote higher severity of pain), and the**minimally important difference**, if known. If synthesising standardised mean differences and the effect estimate is being re-expressed to a particular instrument, details of the instrument, as per the mean difference, should be reported*(Item 20b)* - If investigations of possible
**causes of heterogeneity**were conducted:**present results regardless**of the statistical significance, magnitude, or direction of effect modification*(Item 20c)*- identify the
**studies contributing to each subgroup***(Item 20c)* - report results with due consideration to the
**observational nature of the analysis**and risk of**confounding due to other factors***(Item 20c)*

- If
**subgroup analysis**was conducted, report for each analysis the**exact P value**for a test for interaction as well as, within each subgroup, the**summary estimates**, their**precision**(such as standard error or 95% confidence/credible interval) and measures of**heterogeneity**. Results from subgroup analyses might usefully be presented graphically*(Item 20c)* - If
**meta-regression**was conducted, report for**each analysis the exact P value**for the regression**coefficient**and its**precision***(Item 20c)* - If
**informal methods**(that is, those that do not involve a formal statistical test) were used to**investigate heterogeneity**—which may arise particularly when the data are not amenable to meta-analysis—**describe the results observed**. For example, present a table that groups study results by dose or overall risk of bias and comment on any patterns observed*(Item 20c)* - If any
**sensitivity analyses**were conducted:- report the
**results for each**sensitivity analysis*(Item 20d)* - comment on
**how robust the main analysis**was given the results of all**corresponding sensitivity analyses***(Item 20d)*

- report the

- If
**subgroup analysis**was conducted, consider**presenting the estimate****for the difference**between subgroups and its**precision***(Item 20c)* - If
**meta-regression**was conducted, consider presenting a meta-regression**scatterplot**with the**study effect estimates plotted against the potential effect modifier***(Item 20c)* - If any
**sensitivity analyses**were conducted, consider:- presenting results in
**tables**that indicate:- the
**summary effect estimate**, a measure of**precision**(and potentially other relevant statistics, for example, I2 statistic) and contributing studies for the original meta-analysis; - the same information for the
**sensitivity analysis**; and **details of the original and sensitivity analysis assumptions***(Item 20d)*

- the
- presenting results of
**sensitivity analyses visually using forest plots***(Item 20d)*

- presenting results in

- Present assessments of
**risk of bias due to missing results**(arising from reporting biases) for each synthesis assessed. - If a
**tool was used**to assess risk of bias due to missing results in a synthesis, present**responses to questions**in the tool,**judgments**about risk of bias, and any i**nformation used to support such judgments**to help readers understand why particular judgments were made. - If a
**funnel plot**was generated to evaluate**small-study effects**(one cause of which is reporting biases), present the**plot**and specify the**effect estimate and measure of precision**used in the plot (presented typically on the horizontal axis and vertical axis respectively). If a contour-enhanced funnel plot was generated, specify the “milestones” of statistical significance that the plotted contour lines represent (P=0.01, 0.05, 0.1, etc). - If a
**test for funnel plot asymmetry**was used, report the**exact P value**observed for the test and potentially other relevant statistics, such as the standardised normal deviate, from which the P value is derived. - If any
**sensitivity analyses**seeking to explore the potential impact of missing results on the synthesis were conducted, present**results of each analysis**(see item #20d),**compare them with results of the primary analysis,**and report results with due**consideration of the limitations**of the statistical method.

- If studies were assessed for selective non-reporting of results by comparing outcomes and analyses pre-specified in study registers, protocols, and statistical analysis plans with results that were available in study reports, consider presenting a matrix (with rows as studies and columns as syntheses) to present the availability of study results.
- If an assessment of selective non-reporting of results reveals that some studies are missing from the synthesis, consider displaying the studies with missing results underneath a forest plot or including a table with the available study results (for example, see forest plot in Page et al)

- Provide a
**general interpretation of the results**in the context of other evidence*(Item 23a)* - Discuss any
**limitations of the evidence**included in the review*(Item 23b)* - Discuss any
**limitations of the review processes**used and comment on the**potential impact**of each limitation*(Item 23c)* - Discuss
**implications of the results**for practice and policy*(Item 23d)* - Make
**explicit recommendations**for**future research***(Item 23d)*