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Systematic Reviews and Meta-Analyses: Synthesis & Discussion

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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.

Qualitative Synthesis

Qualitative synthesis in systematic reviews and/or meta-analyses.

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 . 

Guidance for 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

Considerations and Decisions

• How you will group data for your synthesis   and 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 )

Qualitative Data and Analysis Tools

Check out this Library Guide for more information about tools for qualitative data anlaysis at Virginia Tech.

Qualitative Synthesis Approaches

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. 

Content Analysis

"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

Resources for Content Analysis

• 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
• Elo, S., & Kyngäs, H. (2008). The qualitative content analysis process . Journal of Advanced Nursing, 62(1), 107–115. https://doi.org/10.1111/j.1365-2648.2007.04569.x 
• Mayring, P. (2015). Qualitative content analysis: Theoretical background and procedures . In A. Bikner-Ahsbahs, C. Knipping, & N. Presmeg (Eds.), Approaches to Qualitative Research in Mathematics Education: Examples of Methodology and Methods (pp. 365–380). Springer Netherlands. https://doi.org/10.1007/978-94-017-9181-6_13

Thematic Synthesis 

"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

Resources for Thematic Synthesis 

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.

Framework Synthesis

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

Resources for Framework Synthesis 

• 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

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"

Resources for Grounded Theory

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

Meta-Ethnography 

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) 

Reporting Guideline

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

Resources for Meta-Ethnography

• 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).  Meta-ethnography . SAGE Publications, Inc. https://dx. 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

Meta-Analysis

• Presenting Results
• Alternative Quantitative Synthesis

Meta-analysis

“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 given to 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. 

Choosing to pursue a Meta-Analysis

Reasons to pursue a meta-analysis.

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

Reasons  not  to pursue a Meta-Analysis

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   and  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. 
• 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). Introduction to Meta-Analysis . John Wiley & Sons, Ltd. https://doi.org/10.1002/9780470743386
• 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

Tools for Meta-Analyses

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

Graphical User Interface (no programming required) 

• 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

Command Line Interface (programming required)

• 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

Present Meta-Analysis Results

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

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 .

Alternative Quantitative Synthesis Methods

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).

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. 

Methodological Guidance

• Health Sciences
• Animal, Food Sciences
• Social Sciences
• Environmental Sciences

Cochrane Handbook  - Part 1: About Cochrane Reviews

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

Cochrane Handbook  -  Part 2: Core Methods

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 

Cochrane Handbook  - Part 3: Specific Perspectives in Reviews

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

SYREAF Tutorials

Step 5 . data synthesis.

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

Step 6. Presenting the results &  Step 7. Reaching a conclusion

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

Campbell -  MECCIR

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  ( review / final manuscript )

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

CEE  -  Guidelines and Standards for Evidence synthesis in Environmental Management

Section 9. data synthesis.

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

Section 10. Interpreting findings and reporting conduct

10.1 The interpretation of evidence syntheses

10.2 Reporting conduct of evidence synthesis

10.3 Reporting findings of evidence syntheses

Reporting in Protocol and Final Manuscript

• Final Manuscript

In the Protocol |  PRISMA-P

Data synthesis   (item 15), qualitative synthesis only.

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, describe planned summary measures , methods of handling data and methods of combining data from studies , including any planned exploration of consistency (such as I2 , Kendall’s τ)  (Item 15b) ...describe any proposed additional analyses (such as sensitivity or subgroup analyses, meta-regression)  (Item 15c)

In the Final Manuscript |  PRISMA

Synthesis methods (item 13; report in  methods ), 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)

Meta-Analysis (or other quantitative methods used)

• ...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)
• 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 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) 
• 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)
• 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)

Reporting Bias Assessment (Item 14; report in methods )

• 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

Results of Synthesis (Item 20; report in results )

• 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)

Meta-Analysis (or other quantitative methods used)

• 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).
• 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)
• 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)
• 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)
• 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)
• 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)
• presenting results of sensitivity analyses visually using forest plots   (Item 20d)

Reporting Biases (Item 21; report in results )

• 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)

Discussion (Item 23)

• 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)
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Literature Syntheis 101

How To Synthesise The Existing Research (With Examples)

By: Derek Jansen (MBA) | Expert Reviewer: Eunice Rautenbach (DTech) | August 2023

One of the most common mistakes that students make when writing a literature review is that they err on the side of describing the existing literature rather than providing a critical synthesis of it. In this post, we’ll unpack what exactly synthesis means and show you how to craft a strong literature synthesis using practical examples.

This post is based on our popular online course, Literature Review Bootcamp . In the course, we walk you through the full process of developing a literature review, step by step. If it’s your first time writing a literature review, you definitely want to use this link to get 50% off the course (limited-time offer).

Overview: Literature Synthesis

• What exactly does “synthesis” mean?
• Aspect 1: Agreement
• Aspect 2: Disagreement
• Aspect 3: Key theories
• Aspect 4: Contexts
• Aspect 5: Methodologies
• Bringing it all together

What does “synthesis” actually mean?

As a starting point, let’s quickly define what exactly we mean when we use the term “synthesis” within the context of a literature review.

Simply put, literature synthesis means going beyond just describing what everyone has said and found. Instead, synthesis is about bringing together all the information from various sources to present a cohesive assessment of the current state of knowledge in relation to your study’s research aims and questions .

Put another way, a good synthesis tells the reader exactly where the current research is “at” in terms of the topic you’re interested in – specifically, what’s known , what’s not , and where there’s a need for more research .

So, how do you go about doing this?

Well, there’s no “one right way” when it comes to literature synthesis, but we’ve found that it’s particularly useful to ask yourself five key questions when you’re working on your literature review. Having done so,  you can then address them more articulately within your actual write up. So, let’s take a look at each of these questions.

1. Points Of Agreement

The first question that you need to ask yourself is: “Overall, what things seem to be agreed upon by the vast majority of the literature?”

For example, if your research aim is to identify which factors contribute toward job satisfaction, you’ll need to identify which factors are broadly agreed upon and “settled” within the literature. Naturally, there may at times be some lone contrarian that has a radical viewpoint , but, provided that the vast majority of researchers are in agreement, you can put these random outliers to the side. That is, of course, unless your research aims to explore a contrarian viewpoint and there’s a clear justification for doing so. 

Identifying what’s broadly agreed upon is an essential starting point for synthesising the literature, because you generally don’t want (or need) to reinvent the wheel or run down a road investigating something that is already well established . So, addressing this question first lays a foundation of “settled” knowledge.

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2. Points Of Disagreement

Related to the previous point, but on the other end of the spectrum, is the equally important question: “Where do the disagreements lie?” .

In other words, which things are not well agreed upon by current researchers? It’s important to clarify here that by disagreement, we don’t mean that researchers are (necessarily) fighting over it – just that there are relatively mixed findings within the empirical research , with no firm consensus amongst researchers.

This is a really important question to address as these “disagreements” will often set the stage for the research gap(s). In other words, they provide clues regarding potential opportunities for further research, which your study can then (hopefully) contribute toward filling. If you’re not familiar with the concept of a research gap, be sure to check out our explainer video covering exactly that .

3. Key Theories

The next question you need to ask yourself is: “Which key theories seem to be coming up repeatedly?” .

Within most research spaces, you’ll find that you keep running into a handful of key theories that are referred to over and over again. Apart from identifying these theories, you’ll also need to think about how they’re connected to each other. Specifically, you need to ask yourself:

• Are they all covering the same ground or do they have different focal points  or underlying assumptions ?
• Do some of them feed into each other and if so, is there an opportunity to integrate them into a more cohesive theory?
• Do some of them pull in different directions ? If so, why might this be?
• Do all of the theories define the key concepts and variables in the same way, or is there some disconnect? If so, what’s the impact of this ?

Simply put, you’ll need to pay careful attention to the key theories in your research area, as they will need to feature within your theoretical framework , which will form a critical component within your final literature review. This will set the foundation for your entire study, so it’s essential that you be critical in this area of your literature synthesis.

If this sounds a bit fluffy, don’t worry. We deep dive into the theoretical framework (as well as the conceptual framework) and look at practical examples in Literature Review Bootcamp . If you’d like to learn more, take advantage of our limited-time offer to get 60% off the standard price.

4. Contexts

The next question that you need to address in your literature synthesis is an important one, and that is: “Which contexts have (and have not) been covered by the existing research?” .

For example, sticking with our earlier hypothetical topic (factors that impact job satisfaction), you may find that most of the research has focused on white-collar , management-level staff within a primarily Western context, but little has been done on blue-collar workers in an Eastern context. Given the significant socio-cultural differences between these two groups, this is an important observation, as it could present a contextual research gap .

In practical terms, this means that you’ll need to carefully assess the context of each piece of literature that you’re engaging with, especially the empirical research (i.e., studies that have collected and analysed real-world data). Ideally, you should keep notes regarding the context of each study in some sort of catalogue or sheet, so that you can easily make sense of this before you start the writing phase. If you’d like, our free literature catalogue worksheet is a great tool for this task.

5. Methodological Approaches

Last but certainly not least, you need to ask yourself the question: “What types of research methodologies have (and haven’t) been used?”

For example, you might find that most studies have approached the topic using qualitative methods such as interviews and thematic analysis. Alternatively, you might find that most studies have used quantitative methods such as online surveys and statistical analysis.

But why does this matter?

Well, it can run in one of two potential directions . If you find that the vast majority of studies use a specific methodological approach, this could provide you with a firm foundation on which to base your own study’s methodology . In other words, you can use the methodologies of similar studies to inform (and justify) your own study’s research design .

On the other hand, you might argue that the lack of diverse methodological approaches presents a research gap , and therefore your study could contribute toward filling that gap by taking a different approach. For example, taking a qualitative approach to a research area that is typically approached quantitatively. Of course, if you’re going to go against the methodological grain, you’ll need to provide a strong justification for why your proposed approach makes sense. Nevertheless, it is something worth at least considering.

Regardless of which route you opt for, you need to pay careful attention to the methodologies used in the relevant studies and provide at least some discussion about this in your write-up. Again, it’s useful to keep track of this on some sort of spreadsheet or catalogue as you digest each article, so consider grabbing a copy of our free literature catalogue if you don’t have anything in place.

Bringing It All Together

Alright, so we’ve looked at five important questions that you need to ask (and answer) to help you develop a strong synthesis within your literature review.  To recap, these are:

• Which things are broadly agreed upon within the current research?
• Which things are the subject of disagreement (or at least, present mixed findings)?
• Which theories seem to be central to your research topic and how do they relate or compare to each other?
• Which contexts have (and haven’t) been covered?
• Which methodological approaches are most common?

Importantly, you’re not just asking yourself these questions for the sake of asking them – they’re not just a reflection exercise. You need to weave your answers to them into your actual literature review when you write it up. How exactly you do this will vary from project to project depending on the structure you opt for, but you’ll still need to address them within your literature review, whichever route you go.

The best approach is to spend some time actually writing out your answers to these questions, as opposed to just thinking about them in your head. Putting your thoughts onto paper really helps you flesh out your thinking . As you do this, don’t just write down the answers – instead, think about what they mean in terms of the research gap you’ll present , as well as the methodological approach you’ll take . Your literature synthesis needs to lay the groundwork for these two things, so it’s essential that you link all of it together in your mind, and of course, on paper.

Psst… there’s more!

This post is an extract from our bestselling Udemy Course, Literature Review Bootcamp . If you want to work smart, you don't want to miss this .

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What Synthesis Methodology Should I Use? A Review and Analysis of Approaches to Research Synthesis

Kara schick-makaroff.

1 Faculty of Nursing, University of Alberta, Edmonton, AB, Canada

Marjorie MacDonald

2 School of Nursing, University of Victoria, Victoria, BC, Canada

Marilyn Plummer

3 College of Nursing, Camosun College, Victoria, BC, Canada

Judy Burgess

4 Student Services, University Health Services, Victoria, BC, Canada

Wendy Neander

Associated data, additional file 1.

When we began this process, we were doctoral students and a faculty member in a research methods course. As students, we were facing a review of the literature for our dissertations. We encountered several different ways of conducting a review but were unable to locate any resources that synthesized all of the various synthesis methodologies. Our purpose is to present a comprehensive overview and assessment of the main approaches to research synthesis. We use ‘research synthesis’ as a broad overarching term to describe various approaches to combining, integrating, and synthesizing research findings.

We conducted an integrative review of the literature to explore the historical, contextual, and evolving nature of research synthesis. We searched five databases, reviewed websites of key organizations, hand-searched several journals, and examined relevant texts from the reference lists of the documents we had already obtained.

We identified four broad categories of research synthesis methodology including conventional, quantitative, qualitative, and emerging syntheses. Each of the broad categories was compared to the others on the following: key characteristics, purpose, method, product, context, underlying assumptions, unit of analysis, strengths and limitations, and when to use each approach.

Conclusions

The current state of research synthesis reflects significant advancements in emerging synthesis studies that integrate diverse data types and sources. New approaches to research synthesis provide a much broader range of review alternatives available to health and social science students and researchers.

1. Introduction

Since the turn of the century, public health emergencies have been identified worldwide, particularly related to infectious diseases. For example, the Severe Acute Respiratory Syndrome (SARS) epidemic in Canada in 2002-2003, the recent Ebola epidemic in Africa, and the ongoing HIV/AIDs pandemic are global health concerns. There have also been dramatic increases in the prevalence of chronic diseases around the world [1] – [3] . These epidemiological challenges have raised concerns about the ability of health systems worldwide to address these crises. As a result, public health systems reform has been initiated in a number of countries. In Canada, as in other countries, the role of evidence to support public health reform and improve population health has been given high priority. Yet, there continues to be a significant gap between the production of evidence through research and its application in practice [4] – [5] . One strategy to address this gap has been the development of new research synthesis methodologies to deal with the time-sensitive and wide ranging evidence needs of policy makers and practitioners in all areas of health care, including public health.

As doctoral nursing students facing a review of the literature for our dissertations, and as a faculty member teaching a research methods course, we encountered several ways of conducting a research synthesis but found no comprehensive resources that discussed, compared, and contrasted various synthesis methodologies on their purposes, processes, strengths and limitations. To complicate matters, writers use terms interchangeably or use different terms to mean the same thing, and the literature is often contradictory about various approaches. Some texts [6] , [7] – [9] did provide a preliminary understanding about how research synthesis had been taken up in nursing, but these did not meet our requirements. Thus, in this article we address the need for a comprehensive overview of research synthesis methodologies to guide public health, health care, and social science researchers and practitioners.

Research synthesis is relatively new in public health but has a long history in other fields dating back to the late 1800s. Research synthesis, a research process in its own right [10] , has become more prominent in the wake of the evidence-based movement of the 1990s. Research syntheses have found their advocates and detractors in all disciplines, with challenges to the processes of systematic review and meta-analysis, in particular, being raised by critics of evidence-based healthcare [11] – [13] .

Our purpose was to conduct an integrative review of the literature to explore the historical, contextual, and evolving nature of research synthesis [14] – [15] . We synthesize and critique the main approaches to research synthesis that are relevant for public health, health care, and social scientists. Research synthesis is the overarching term we use to describe approaches to combining, aggregating, integrating, and synthesizing primary research findings. Each synthesis methodology draws on different types of findings depending on the purpose and product of the chosen synthesis (see Additional File 1 ).

3. Method of Review

Based on our current knowledge of the literature, we identified these approaches to include in our review: systematic review, meta-analysis, qualitative meta-synthesis, meta-narrative synthesis, scoping review, rapid review, realist synthesis, concept analysis, literature review, and integrative review. Our first step was to divide the synthesis types among the research team. Each member did a preliminary search to identify key texts. The team then met to develop search terms and a framework to guide the review.

Over the period of 2008 to 2012 we extensively searched the literature, updating our search at several time points, not restricting our search by date. The dates of texts reviewed range from 1967 to 2015. We used the terms above combined with the term “method* (e.g., “realist synthesis” and “method*) in the database Health Source: Academic Edition (includes Medline and CINAHL). This search yielded very few texts on some methodologies and many on others. We realized that many documents on research synthesis had not been picked up in the search. Therefore, we also searched Google Scholar, PubMed, ERIC, and Social Science Index, as well as the websites of key organizations such as the Joanna Briggs Institute, the University of York Centre for Evidence-Based Nursing, and the Cochrane Collaboration database. We hand searched several nursing, social science, public health and health policy journals. Finally, we traced relevant documents from the references in obtained texts.

We included works that met the following inclusion criteria: (1) published in English; (2) discussed the history of research synthesis; (3) explicitly described the approach and specific methods; or (4) identified issues, challenges, strengths and limitations of the particular methodology. We excluded research reports that resulted from the use of particular synthesis methodologies unless they also included criteria 2, 3, or 4 above.

Based on our search, we identified additional types of research synthesis (e.g., meta-interpretation, best evidence synthesis, critical interpretive synthesis, meta-summary, grounded formal theory). Still, we missed some important developments in meta-analysis, for example, identified by the journal's reviewers that have now been discussed briefly in the paper. The final set of 197 texts included in our review comprised theoretical, empirical, and conceptual papers, books, editorials and commentaries, and policy documents.

In our preliminary review of key texts, the team inductively developed a framework of the important elements of each method for comparison. In the next phase, each text was read carefully, and data for these elements were extracted into a table for comparison on the points of: key characteristics, purpose, methods, and product; see Additional File 1 ). Once the data were grouped and extracted, we synthesized across categories based on the following additional points of comparison: complexity of the process, degree of systematization, consideration of context, underlying assumptions, unit of analysis, and when to use each approach. In our results, we discuss our comparison of the various synthesis approaches on the elements above. Drawing only on documents for the review, ethics approval was not required.

We identified four broad categories of research synthesis methodology: Conventional, quantitative, qualitative, and emerging syntheses. From our dataset of 197 texts, we had 14 texts on conventional synthesis, 64 on quantitative synthesis, 78 on qualitative synthesis, and 41 on emerging syntheses. Table 1 provides an overview of the four types of research synthesis, definitions, types of data used, products, and examples of the methodology.

Although we group these types of synthesis into four broad categories on the basis of similarities, each type within a category has unique characteristics, which may differ from the overall group similarities. Each could be explored in greater depth to tease out their unique characteristics, but detailed comparison is beyond the scope of this article.

Additional File 1 presents one or more selected types of synthesis that represent the broad category but is not an exhaustive presentation of all types within each category. It provides more depth for specific examples from each category of synthesis on the characteristics, purpose, methods, and products than is found in Table 1 .

4.1. Key Characteristics

4.1.1. what is it.

Here we draw on two types of categorization. First, we utilize Dixon Woods et al.'s [49] classification of research syntheses as being either integrative or interpretive . (Please note that integrative syntheses are not the same as an integrative review as defined in Additional File 1 .) Second, we use Popay's [80] enhancement and epistemological models .

The defining characteristics of integrative syntheses are that they involve summarizing the data achieved by pooling data [49] . Integrative syntheses include systematic reviews, meta-analyses, as well as scoping and rapid reviews because each of these focus on summarizing data. They also define concepts from the outset (although this may not always be true in scoping or rapid reviews) and deal with a well-specified phenomenon of interest.

Interpretive syntheses are primarily concerned with the development of concepts and theories that integrate concepts [49] . The analysis in interpretive synthesis is conceptual both in process and outcome, and “the product is not aggregations of data, but theory” [49] , [p.12]. Interpretive syntheses involve induction and interpretation, and are primarily conceptual in process and outcome. Examples include integrative reviews, some systematic reviews, all of the qualitative syntheses, meta-narrative, realist and critical interpretive syntheses. Of note, both quantitative and qualitative studies can be either integrative or interpretive

The second categorization, enhancement versus epistemological , applies to those approaches that use multiple data types and sources [80] . Popay's [80] classification reflects the ways that qualitative data are valued in relation to quantitative data.

In the enhancement model , qualitative data adds something to quantitative analysis. The enhancement model is reflected in systematic reviews and meta-analyses that use some qualitative data to enhance interpretation and explanation. It may also be reflected in some rapid reviews that draw on quantitative data but use some qualitative data.

The epistemological model assumes that quantitative and qualitative data are equal and each has something unique to contribute. All of the other review approaches, except pure quantitative or qualitative syntheses, reflect the epistemological model because they value all data types equally but see them as contributing different understandings.

4.1.2. Data type

By and large, the quantitative approaches (quantitative systematic review and meta-analysis) have typically used purely quantitative data (i.e., expressed in numeric form). More recently, both Cochrane [81] and Campbell [82] collaborations are grappling with the need to, and the process of, integrating qualitative research into a systematic review. The qualitative approaches use qualitative data (i.e., expressed in words). All of the emerging synthesis types, as well as the conventional integrative review, incorporate qualitative and quantitative study designs and data.

4.1.3. Research question

Four types of research questions direct inquiry across the different types of syntheses. The first is a well-developed research question that gives direction to the synthesis (e.g., meta-analysis, systematic review, meta-study, concept analysis, rapid review, realist synthesis). The second begins as a broad general question that evolves and becomes more refined over the course of the synthesis (e.g., meta-ethnography, scoping review, meta-narrative, critical interpretive synthesis). In the third type, the synthesis begins with a phenomenon of interest and the question emerges in the analytic process (e.g., grounded formal theory). Lastly, there is no clear question, but rather a general review purpose (e.g., integrative review). Thus, the requirement for a well-defined question cuts across at least three of the synthesis types (e.g., quantitative, qualitative, and emerging).

4.1.4. Quality appraisal

This is a contested issue within and between the four synthesis categories. There are strong proponents of quality appraisal in the quantitative traditions of systematic review and meta-analysis based on the need for strong studies that will not jeopardize validity of the overall findings. Nonetheless, there is no consensus on pre-defined criteria; many scales exist that vary dramatically in composition. This has methodological implications for the credibility of findings [83] .

Specific methodologies from the conventional, qualitative, and emerging categories support quality appraisal but do so with caveats. In conventional integrative reviews appraisal is recommended, but depends on the sampling frame used in the study [18] . In meta-study, appraisal criteria are explicit but quality criteria are used in different ways depending on the specific requirements of the inquiry [54] . Among the emerging syntheses, meta-narrative review developers support appraisal of a study based on criteria from the research tradition of the primary study [67] , [84] – [85] . Realist synthesis similarly supports the use of high quality evidence, but appraisal checklists are viewed with scepticism and evidence is judged based on relevance to the research question and whether a credible inference may be drawn [69] . Like realist, critical interpretive syntheses do not judge quality using standardized appraisal instruments. They will exclude fatally flawed studies, but there is no consensus on what ‘fatally flawed’ means [49] , [71] . Appraisal is based on relevance to the inquiry, not rigor of the study.

There is no agreement on quality appraisal among qualitative meta-ethnographers with some supporting and others refuting the need for appraisal. [60] , [62] . Opponents of quality appraisal are found among authors of qualitative (grounded formal theory and concept analysis) and emerging syntheses (scoping and rapid reviews) because quality is not deemed relevant to the intention of the synthesis; the studies being reviewed are not effectiveness studies where quality is extremely important. These qualitative synthesis are often reviews of theoretical developments where the concept itself is what is important, or reviews that provide quotations from the raw data so readers can make their own judgements about the relevance and utility of the data. For example, in formal grounded theory, the purpose of theory generation and authenticity of data used to generate the theory is not as important as the conceptual category. Inaccuracies may be corrected in other ways, such as using the constant comparative method, which facilitates development of theoretical concepts that are repeatedly found in the data [86] – [87] . For pragmatic reasons, evidence is not assessed in rapid and scoping reviews, in part to produce a timely product. The issue of quality appraisal is unresolved across the terrain of research synthesis and we consider this further in our discussion.

4.2. Purpose

All research syntheses share a common purpose -- to summarize, synthesize, or integrate research findings from diverse studies. This helps readers stay abreast of the burgeoning literature in a field. Our discussion here is at the level of the four categories of synthesis. Beginning with conventional literature syntheses, the overall purpose is to attend to mature topics for the purpose of re-conceptualization or to new topics requiring preliminary conceptualization [14] . Such syntheses may be helpful to consider contradictory evidence, map shifting trends in the study of a phenomenon, and describe the emergence of research in diverse fields [14] . The purpose here is to set the stage for a study by identifying what has been done, gaps in the literature, important research questions, or to develop a conceptual framework to guide data collection and analysis.

The purpose of quantitative systematic reviews is to combine, aggregate, or integrate empirical research to be able to generalize from a group of studies and determine the limits of generalization [27] . The focus of quantitative systematic reviews has been primarily on aggregating the results of studies evaluating the effectiveness of interventions using experimental, quasi-experimental, and more recently, observational designs. Systematic reviews can be done with or without quantitative meta-analysis but a meta-analysis always takes place within the context of a systematic review. Researchers must consider the review's purpose and the nature of their data in undertaking a quantitative synthesis; this will assist in determining the approach.

The purpose of qualitative syntheses is broadly to synthesize complex health experiences, practices, or concepts arising in healthcare environments. There may be various purposes depending on the qualitative methodology. For example, in hermeneutic studies the aim may be holistic explanation or understanding of a phenomenon [42] , which is deepened by integrating the findings from multiple studies. In grounded formal theory, the aim is to produce a conceptual framework or theory expected to be applicable beyond the original study. Although not able to generalize from qualitative research in the statistical sense [88] , qualitative researchers usually do want to say something about the applicability of their synthesis to other settings or phenomena. This notion of ‘theoretical generalization’ has been referred to as ‘transferability’ [89] – [90] and is an important criterion of rigour in qualitative research. It applies equally to the products of a qualitative synthesis in which the synthesis of multiple studies on the same phenomenon strengthens the ability to draw transferable conclusions.

The overarching purpose of emerging syntheses is challenging the more traditional types of syntheses, in part by using data from both quantitative and qualitative studies with diverse designs for analysis. Beyond this, however, each emerging synthesis methodology has a unique purpose. In meta-narrative review, the purpose is to identify different research traditions in the area, synthesize a complex and diverse body of research. Critical interpretive synthesis shares this characteristic. Although a distinctive approach, critical interpretive synthesis utilizes a modification of the analytic strategies of meta-ethnography [61] (e.g., reciprocal translational analysis, refutational synthesis, and lines of argument synthesis) but goes beyond the use of these to bring a critical perspective to bear in challenging the normative or epistemological assumptions in the primary literature [72] – [73] . The unique purpose of a realist synthesis is to amalgamate complex empirical evidence and theoretical understandings within a diverse body of literature to uncover the operative mechanisms and contexts that affect the outcomes of social interventions. In a scoping review, the intention is to find key concepts, examine the range of research in an area, and identify gaps in the literature. The purpose of a rapid review is comparable to that of a scoping review, but done quickly to meet the time-sensitive information needs of policy makers.

4.3. Method

4.3.1. degree of systematization.

There are varying degrees of systematization across the categories of research synthesis. The most systematized are quantitative systematic reviews and meta-analyses. There are clear processes in each with judgments to be made at each step, although there are no agreed upon guidelines for this. The process is inherently subjective despite attempts to develop objective and systematic processes [91] – [92] . Mullen and Ramirez [27] suggest that there is often a false sense of rigour implied by the terms ‘systematic review’ and ‘meta-analysis’ because of their clearly defined procedures.

In comparison with some types of qualitative synthesis, concept analysis is quite procedural. Qualitative meta-synthesis also has defined procedures and is systematic, yet perhaps less so than concept analysis. Qualitative meta-synthesis starts in an unsystematic way but becomes more systematic as it unfolds. Procedures and frameworks exist for some of the emerging types of synthesis [e.g., [50] , [63] , [71] , [93] ] but are not linear, have considerable flexibility, and are often messy with emergent processes [85] . Conventional literature reviews tend not to be as systematic as the other three types. In fact, the lack of systematization in conventional literature synthesis was the reason for the development of more systematic quantitative [17] , [20] and qualitative [45] – [46] , [61] approaches. Some authors in the field [18] have clarified processes for integrative reviews making them more systematic and rigorous, but most conventional syntheses remain relatively unsystematic in comparison with other types.

4.3.2. Complexity of the process

Some synthesis processes are considerably more complex than others. Methodologies with clearly defined steps are arguably less complex than the more flexible and emergent ones. We know that any study encounters challenges and it is rare that a pre-determined research protocol can be followed exactly as intended. Not even the rigorous methods associated with Cochrane [81] systematic reviews and meta-analyses are always implemented exactly as intended. Even when dealing with numbers rather than words, interpretation is always part of the process. Our collective experience suggests that new methodologies (e.g., meta-narrative synthesis and realist synthesis) that integrate different data types and methods are more complex than conventional reviews or the rapid and scoping reviews.

4.4. Product

The products of research syntheses usually take three distinct formats (see Table 1 and Additional File 1 for further details). The first representation is in tables, charts, graphical displays, diagrams and maps as seen in integrative, scoping and rapid reviews, meta-analyses, and critical interpretive syntheses. The second type of synthesis product is the use of mathematical scores. Summary statements of effectiveness are mathematically displayed in meta-analyses (as an effect size), systematic reviews, and rapid reviews (statistical significance).

The third synthesis product may be a theory or theoretical framework. A mid-range theory can be produced from formal grounded theory, meta-study, meta-ethnography, and realist synthesis. Theoretical/conceptual frameworks or conceptual maps may be created in meta-narrative and critical interpretive syntheses, and integrative reviews. Concepts for use within theories are produced in concept analysis. While these three product types span the categories of research synthesis, narrative description and summary is used to present the products resulting from all methodologies.

4.5. Consideration of context

There are diverse ways that context is considered in the four broad categories of synthesis. Context may be considered to the extent that it features within primary studies for the purpose of the review. Context may also be understood as an integral aspect of both the phenomenon under study and the synthesis methodology (e.g., realist synthesis). Quantitative systematic reviews and meta-analyses have typically been conducted on studies using experimental and quasi-experimental designs and more recently observational studies, which control for contextual features to allow for understanding of the ‘true’ effect of the intervention [94] .

More recently, systematic reviews have included covariates or mediating variables (i.e., contextual factors) to help explain variability in the results across studies [27] . Context, however, is usually handled in the narrative discussion of findings rather than in the synthesis itself. This lack of attention to context has been one criticism leveled against systematic reviews and meta-analyses, which restrict the types of research designs that are considered [e.g., [95] ].

When conventional literature reviews incorporate studies that deal with context, there is a place for considering contextual influences on the intervention or phenomenon. Reviews of quantitative experimental studies tend to be devoid of contextual considerations since the original studies are similarly devoid, but context might figure prominently in a literature review that incorporates both quantitative and qualitative studies.

Qualitative syntheses have been conducted on the contextual features of a particular phenomenon [33] . Paterson et al. [54] advise researchers to attend to how context may have influenced the findings of particular primary studies. In qualitative analysis, contextual features may form categories by which the data can be compared and contrasted to facilitate interpretation. Because qualitative research is often conducted to understand a phenomenon as a whole, context may be a focus, although this varies with the qualitative methodology. At the same time, the findings in a qualitative synthesis are abstracted from the original reports and taken to a higher level of conceptualization, thus removing them from the original context.

Meta-narrative synthesis [67] , [84] , because it draws on diverse research traditions and methodologies, may incorporate context into the analysis and findings. There is not, however, an explicit step in the process that directs the analyst to consider context. Generally, the research question guiding the synthesis is an important factor in whether context will be a focus.

More recent iterations of concept analysis [47] , [96] – [97] explicitly consider context reflecting the assumption that a concept's meaning is determined by its context. Morse [47] points out, however, that Wilson's [98] approach to concept analysis, and those based on Wilson [e.g., [45] ], identify attributes that are devoid of context, while Rodgers' [96] , [99] evolutionary method considers context (e.g., antecedents, consequences, and relationships to other concepts) in concept development.

Realist synthesis [69] considers context as integral to the study. It draws on a critical realist logic of inquiry grounded in the work of Bhaskar [100] , who argues that empirical co-occurrence of events is insufficient for inferring causation. One must identify generative mechanisms whose properties are causal and, depending on the situation, may nor may not be activated [94] . Context interacts with program/intervention elements and thus cannot be differentiated from the phenomenon [69] . This approach synthesizes evidence on generative mechanisms and analyzes contextual features that activate them; the result feeds back into the context. The focus is on what works, for whom, under what conditions, why and how [68] .

4.6. Underlying Philosophical and Theoretical Assumptions

When we began our review, we ‘assumed’ that the assumptions underlying synthesis methodologies would be a distinguishing characteristic of synthesis types, and that we could compare the various types on their assumptions, explicit or implicit. We found, however, that many authors did not explicate the underlying assumptions of their methodologies, and it was difficult to infer them. Kirkevold [101] has argued that integrative reviews need to be carried out from an explicit philosophical or theoretical perspective. We argue this should be true for all types of synthesis.

Authors of some emerging synthesis approaches have been very explicit about their assumptions and philosophical underpinnings. An implicit assumption of most emerging synthesis methodologies is that quantitative systematic reviews and meta-analyses have limited utility in some fields [e.g., in public health – [13] , [102] ] and for some kinds of review questions like those about feasibility and appropriateness versus effectiveness [103] – [104] . They also assume that ontologically and epistemologically, both kinds of data can be combined. This is a significant debate in the literature because it is about the commensurability of overarching paradigms [105] but this is beyond the scope of this review.

Realist synthesis is philosophically grounded in critical realism or, as noted above, a realist logic of inquiry [93] , [99] , [106] – [107] . Key assumptions regarding the nature of interventions that inform critical realism have been described above in the section on context. See Pawson et al. [106] for more information on critical realism, the philosophical basis of realist synthesis.

Meta-narrative synthesis is explicitly rooted in a constructivist philosophy of science [108] in which knowledge is socially constructed rather than discovered, and what we take to be ‘truth’ is a matter of perspective. Reality has a pluralistic and plastic character, and there is no pre-existing ‘real world’ independent of human construction and language [109] . See Greenhalgh et al. [67] , [85] and Greenhalgh & Wong [97] for more discussion of the constructivist basis of meta-narrative synthesis.

In the case of purely quantitative or qualitative syntheses, it may be an easier matter to uncover unstated assumptions because they are likely to be shared with those of the primary studies in the genre. For example, grounded formal theory shares the philosophical and theoretical underpinnings of grounded theory, rooted in the theoretical perspective of symbolic interactionism [110] – [111] and the philosophy of pragmatism [87] , [112] – [114] .

As with meta-narrative synthesis, meta-study developers identify constructivism as their interpretive philosophical foundation [54] , [88] . Epistemologically, constructivism focuses on how people construct and re-construct knowledge about a specific phenomenon, and has three main assumptions: (1) reality is seen as multiple, at times even incompatible with the phenomenon under consideration; (2) just as primary researchers construct interpretations from participants' data, meta-study researchers also construct understandings about the primary researchers' original findings. Thus, meta-synthesis is a construction of a construction, or a meta-construction; and (3) all constructions are shaped by the historical, social and ideological context in which they originated [54] . The key message here is that reports of any synthesis would benefit from an explicit identification of the underlying philosophical perspectives to facilitate a better understanding of the results, how they were derived, and how they are being interpreted.

4.7. Unit of Analysis

The unit of analysis for each category of review is generally distinct. For the emerging synthesis approaches, the unit of analysis is specific to the intention. In meta-narrative synthesis it is the storyline in diverse research traditions; in rapid review or scoping review, it depends on the focus but could be a concept; and in realist synthesis, it is the theories rather than programs that are the units of analysis. The elements of theory that are important in the analysis are mechanisms of action, the context, and the outcome [107] .

For qualitative synthesis, the units of analysis are generally themes, concepts or theories, although in meta-study, the units of analysis can be research findings (“meta-data-analysis”), research methods (“meta-method”) or philosophical/theoretical perspectives (“meta-theory”) [54] . In quantitative synthesis, the units of analysis range from specific statistics for systematic reviews to effect size of the intervention for meta-analysis. More recently, some systematic reviews focus on theories [115] – [116] , therefore it depends on the research question. Similarly, within conventional literature synthesis the units of analysis also depend on the research purpose, focus and question as well as on the type of research methods incorporated into the review. What is important in all research syntheses, however, is that the unit of analysis needs to be made explicit. Unfortunately, this is not always the case.

4.8. Strengths and Limitations

In this section, we discuss the overarching strengths and limitations of synthesis methodologies as a whole and then highlight strengths and weaknesses across each of our four categories of synthesis.

4.8.1. Strengths of Research Syntheses in General

With the vast proliferation of research reports and the increased ease of retrieval, research synthesis has become more accessible providing a way of looking broadly at the current state of research. The availability of syntheses helps researchers, practitioners, and policy makers keep up with the burgeoning literature in their fields without which evidence-informed policy or practice would be difficult. Syntheses explain variation and difference in the data helping us identify the relevance for our own situations; they identify gaps in the literature leading to new research questions and study designs. They help us to know when to replicate a study and when to avoid excessively duplicating research. Syntheses can inform policy and practice in a way that well-designed single studies cannot; they provide building blocks for theory that helps us to understand and explain our phenomena of interest.

4.8.2. Limitations of Research Syntheses in General

The process of selecting, combining, integrating, and synthesizing across diverse study designs and data types can be complex and potentially rife with bias, even with those methodologies that have clearly defined steps. Just because a rigorous and standardized approach has been used does not mean that implicit judgements will not influence the interpretations and choices made at different stages.

In all types of synthesis, the quantity of data can be considerable, requiring difficult decisions about scope, which may affect relevance. The quantity of available data also has implications for the size of the research team. Few reviews these days can be done independently, in particular because decisions about inclusion and exclusion may require the involvement of more than one person to ensure reliability.

For all types of synthesis, it is likely that in areas with large, amorphous, and diverse bodies of literature, even the most sophisticated search strategies will not turn up all the relevant and important texts. This may be more important in some synthesis methodologies than in others, but the omission of key documents can influence the results of all syntheses. This issue can be addressed, at least in part, by including a library scientist on the research team as required by some funding agencies. Even then, it is possible to miss key texts. In this review, for example, because none of us are trained in or conduct meta-analyses, we were not even aware that we had missed some new developments in this field such as meta-regression [117] – [118] , network meta-analysis [119] – [121] , and the use of individual patient data in meta-analyses [122] – [123] .

One limitation of systematic reviews and meta-analyses is that they rapidly go out of date. We thought this might be true for all types of synthesis, although we wondered if those that produce theory might not be somewhat more enduring. We have not answered this question but it is open for debate. For all types of synthesis, the analytic skills and the time required are considerable so it is clear that training is important before embarking on a review, and some types of review may not be appropriate for students or busy practitioners.

Finally, the quality of reporting in primary studies of all genres is variable so it is sometimes difficult to identify aspects of the study essential for the synthesis, or to determine whether the study meets quality criteria. There may be flaws in the original study, or journal page limitations may necessitate omitting important details. Reporting standards have been developed for some types of reviews (e.g., systematic review, meta-analysis, meta-narrative synthesis, realist synthesis); but there are no agreed upon standards for qualitative reviews. This is an important area for development in advancing the science of research synthesis.

4.8.3. Strengths and Limitations of the Four Synthesis Types

The conventional literature review and now the increasingly common integrative review remain important and accessible approaches for students, practitioners, and experienced researchers who want to summarize literature in an area but do not have the expertise to use one of the more complex methodologies. Carefully executed, such reviews are very useful for synthesizing literature in preparation for research grants and practice projects. They can determine the state of knowledge in an area and identify important gaps in the literature to provide a clear rationale or theoretical framework for a study [14] , [18] . There is a demand, however, for more rigour, with more attention to developing comprehensive search strategies and more systematic approaches to combining, integrating, and synthesizing the findings.

Generally, conventional reviews include diverse study designs and data types that facilitate comprehensiveness, which may be a strength on the one hand, but can also present challenges on the other. The complexity inherent in combining results from studies with diverse methodologies can result in bias and inaccuracies. The absence of clear guidelines about how to synthesize across diverse study types and data [18] has been a challenge for novice reviewers.

Quantitative systematic reviews and meta-analyses have been important in launching the field of evidence-based healthcare. They provide a systematic, orderly and auditable process for conducting a review and drawing conclusions [25] . They are arguably the most powerful approaches to understanding the effectiveness of healthcare interventions, especially when intervention studies on the same topic show very different results. When areas of research are dogged by controversy [25] or when study results go against strongly held beliefs, such approaches can reduce the uncertainty and bring strong evidence to bear on the controversy.

Despite their strengths, they also have limitations. Systematic reviews and meta-analyses do not provide a way of including complex literature comprising various types of evidence including qualitative studies, theoretical work, and epidemiological studies. Only certain types of design are considered and qualitative data are used in a limited way. This exclusion limits what can be learned in a topic area.

Meta-analyses are often not possible because of wide variability in study design, population, and interventions so they may have a narrow range of utility. New developments in meta-analysis, however, can be used to address some of these limitations. Network meta-analysis is used to explore relative efficacy of multiple interventions, even those that have never been compared in more conventional pairwise meta-analyses [121] , allowing for improved clinical decision making [120] . The limitation is that network meta-analysis has only been used in medical/clinical applications [119] and not in public health. It has not yet been widely accepted and many methodological challenges remain [120] – [121] . Meta-regression is another development that combines meta-analytic and linear regression principles to address the fact that heterogeneity of results may compromise a meta-analysis [117] – [118] . The disadvantage is that many clinicians are unfamiliar with it and may incorrectly interpret results [117] .

Some have accused meta-analysis of combining apples and oranges [124] raising questions in the field about their meaningfulness [25] , [28] . More recently, the use of individual rather than aggregate data has been useful in facilitating greater comparability among studies [122] . In fact, Tomas et al. [123] argue that meta-analysis using individual data is now the gold standard although access to the raw data from other studies may be a challenge to obtain.

The usefulness of systematic reviews in synthesizing complex health and social interventions has also been challenged [102] . It is often difficult to synthesize their findings because such studies are “epistemologically diverse and methodologically complex” [ [69] , p.21]. Rigid inclusion/exclusion criteria may allow only experimental or quasi-experimental designs into consideration resulting in lost information that may well be useful to policy makers for tailoring an intervention to the context or understanding its acceptance by recipients.

Qualitative syntheses may be the type of review most fraught with controversy and challenge, while also bringing distinct strengths to the enterprise. Although these methodologies provide a comprehensive and systematic review approach, they do not generally provide definitive statements about intervention effectiveness. They do, however, address important questions about the development of theoretical concepts, patient experiences, acceptability of interventions, and an understanding about why interventions might work.

Most qualitative syntheses aim to produce a theoretically generalizable mid-range theory that explains variation across studies. This makes them more useful than single primary studies, which may not be applicable beyond the immediate setting or population. All provide a contextual richness that enhances relevance and understanding. Another benefit of some types of qualitative synthesis (e.g., grounded formal theory) is that the concept of saturation provides a sound rationale for limiting the number of texts to be included thus making reviews potentially more manageable. This contrasts with the requirements of systematic reviews and meta-analyses that require an exhaustive search.

Qualitative researchers debate about whether the findings of ontologically and epistemological diverse qualitative studies can actually be combined or synthesized [125] because methodological diversity raises many challenges for synthesizing findings. The products of different types of qualitative syntheses range from theory and conceptual frameworks, to themes and rich descriptive narratives. Can one combine the findings from a phenomenological study with the theory produced in a grounded theory study? Many argue yes, but many also argue no.

Emerging synthesis methodologies were developed to address some limitations inherent in other types of synthesis but also have their own issues. Because each type is so unique, it is difficult to identify overarching strengths of the entire category. An important strength, however, is that these newer forms of synthesis provide a systematic and rigorous approach to synthesizing a diverse literature base in a topic area that includes a range of data types such as: both quantitative and qualitative studies, theoretical work, case studies, evaluations, epidemiological studies, trials, and policy documents. More than conventional literature reviews and systematic reviews, these approaches provide explicit guidance on analytic methods for integrating different types of data. The assumption is that all forms of data have something to contribute to knowledge and theory in a topic area. All have a defined but flexible process in recognition that the methods may need to shift as knowledge develops through the process.

Many emerging synthesis types are helpful to policy makers and practitioners because they are usually involved as team members in the process to define the research questions, and interpret and disseminate the findings. In fact, engagement of stakeholders is built into the procedures of the methods. This is true for rapid reviews, meta-narrative syntheses, and realist syntheses. It is less likely to be the case for critical interpretive syntheses.

Another strength of some approaches (realist and meta-narrative syntheses) is that quality and publication standards have been developed to guide researchers, reviewers, and funders in judging the quality of the products [108] , [126] – [127] . Training materials and online communities of practice have also been developed to guide users of realist and meta-narrative review methods [107] , [128] . A unique strength of critical interpretive synthesis is that it takes a critical perspective on the process that may help reconceptualize the data in a way not considered by the primary researchers [72] .

There are also challenges of these new approaches. The methods are new and there may be few published applications by researchers other than the developers of the methods, so new users often struggle with the application. The newness of the approaches means that there may not be mentors available to guide those unfamiliar with the methods. This is changing, however, and the number of applications in the literature is growing with publications by new users helping to develop the science of synthesis [e.g., [129] ]. However, the evolving nature of the approaches and their developmental stage present challenges for novice researchers.

4.9. When to Use Each Approach

Choosing an appropriate approach to synthesis will depend on the question you are asking, the purpose of the review, and the outcome or product you want to achieve. In Additional File 1 , we discuss each of these to provide guidance to readers on making a choice about review type. If researchers want to know whether a particular type of intervention is effective in achieving its intended outcomes, then they might choose a quantitative systemic review with or without meta-analysis, possibly buttressed with qualitative studies to provide depth and explanation of the results. Alternately, if the concern is about whether an intervention is effective with different populations under diverse conditions in varying contexts, then a realist synthesis might be the most appropriate.

If researchers' concern is to develop theory, they might consider qualitative syntheses or some of the emerging syntheses that produce theory (e.g., critical interpretive synthesis, realist review, grounded formal theory, qualitative meta-synthesis). If the aim is to track the development and evolution of concepts, theories or ideas, or to determine how an issue or question is addressed across diverse research traditions, then meta-narrative synthesis would be most appropriate.

When the purpose is to review the literature in advance of undertaking a new project, particularly by graduate students, then perhaps an integrative review would be appropriate. Such efforts contribute towards the expansion of theory, identify gaps in the research, establish the rationale for studying particular phenomena, and provide a framework for interpreting results in ways that might be useful for influencing policy and practice.

For researchers keen to bring new insights, interpretations, and critical re-conceptualizations to a body of research, then qualitative or critical interpretive syntheses will provide an inductive product that may offer new understandings or challenges to the status quo. These can inform future theory development, or provide guidance for policy and practice.

5. Discussion

What is the current state of science regarding research synthesis? Public health, health care, and social science researchers or clinicians have previously used all four categories of research synthesis, and all offer a suitable array of approaches for inquiries. New developments in systematic reviews and meta-analysis are providing ways of addressing methodological challenges [117] – [123] . There has also been significant advancement in emerging synthesis methodologies and they are quickly gaining popularity. Qualitative meta-synthesis is still evolving, particularly given how new it is within the terrain of research synthesis. In the midst of this evolution, outstanding issues persist such as grappling with: the quantity of data, quality appraisal, and integration with knowledge translation. These topics have not been thoroughly addressed and need further debate.

5.1. Quantity of Data

We raise the question of whether it is possible or desirable to find all available studies for a synthesis that has this requirement (e.g., meta-analysis, systematic review, scoping, meta-narrative synthesis [25] , [27] , [63] , [67] , [84] – [85] ). Is the synthesis of all available studies a realistic goal in light of the burgeoning literature? And how can this be sustained in the future, particularly as the emerging methodologies continue to develop and as the internet facilitates endless access? There has been surprisingly little discussion on this topic and the answers will have far-reaching implications for searching, sampling, and team formation.

Researchers and graduate students can no longer rely on their own independent literature search. They will likely need to ask librarians for assistance as they navigate multiple sources of literature and learn new search strategies. Although teams now collaborate with library scientists, syntheses are limited in that researchers must make decisions on the boundaries of the review, in turn influencing the study's significance. The size of a team may also be pragmatically determined to manage the search, extraction, and synthesis of the burgeoning data. There is no single answer to our question about the possibility or necessity of finding all available articles for a review. Multiple strategies that are situation specific are likely to be needed.

5.2. Quality Appraisal

While the issue of quality appraisal has received much attention in the synthesis literature, scholars are far from resolution. There may be no agreement about appraisal criteria in a given tradition. For example, the debate rages over the appropriateness of quality appraisal in qualitative synthesis where there are over 100 different sets of criteria and many do not overlap [49] . These differences may reflect disciplinary and methodological orientations, but diverse quality appraisal criteria may privilege particular types of research [49] . The decision to appraise is often grounded in ontological and epistemological assumptions. Nonetheless, diversity within and between categories of synthesis is likely to continue unless debate on the topic of quality appraisal continues and evolves toward consensus.

5.3. Integration with Knowledge Translation

If research syntheses are to make a difference to practice and ultimately to improve health outcomes, then we need to do a better job of knowledge translation. In the Canadian Institutes of Health Research (CIHR) definition of knowledge translation (KT), research or knowledge synthesis is an integral component [130] . Yet, with few exceptions [131] – [132] , very little of the research synthesis literature even mentions the relationship of synthesis to KT nor does it discuss strategies to facilitate the integration of synthesis findings into policy and practice. The exception is in the emerging synthesis methodologies, some of which (e.g., realist and meta-narrative syntheses, scoping reviews) explicitly involve stakeholders or knowledge users. The argument is that engaging them in this way increases the likelihood that the knowledge generated will be translated into policy and practice. We suggest that a more explicit engagement with knowledge users in all types of synthesis would benefit the uptake of the research findings.

Research synthesis neither makes research more applicable to practice nor ensures implementation. Focus must now turn seriously towards translation of synthesis findings into knowledge products that are useful for health care practitioners in multiple areas of practice and develop appropriate strategies to facilitate their use. The burgeoning field of knowledge translation has, to some extent, taken up this challenge; however, the research-practice gap continues to plague us [133] – [134] . It is a particular problem for qualitative syntheses [131] . Although such syntheses have an important place in evidence-informed practice, little effort has gone into the challenge of translating the findings into useful products to guide practice [131] .

5.4. Limitations

Our study took longer than would normally be expected for an integrative review. Each of us were primarily involved in our own dissertations or teaching/research positions, and so this study was conducted ‘off the sides of our desks.’ A limitation was that we searched the literature over the course of 4 years (from 2008–2012), necessitating multiple search updates. Further, we did not do a comprehensive search of the literature after 2012, thus the more recent synthesis literature was not systematically explored. We did, however, perform limited database searches from 2012–2015 to keep abreast of the latest methodological developments. Although we missed some new approaches to meta-analysis in our search, we did not find any new features of the synthesis methodologies covered in our review that would change the analysis or findings of this article. Lastly, we struggled with the labels used for the broad categories of research synthesis methodology because of our hesitancy to reinforce the divide between quantitative and qualitative approaches. However, it was very difficult to find alternative language that represented the types of data used in these methodologies. Despite our hesitancy in creating such an obvious divide, we were left with the challenge of trying to find a way of characterizing these broad types of syntheses.

6. Conclusion

Our findings offer methodological clarity for those wishing to learn about the broad terrain of research synthesis. We believe that our review makes transparent the issues and considerations in choosing from among the four broad categories of research synthesis. In summary, research synthesis has taken its place as a form of research in its own right. The methodological terrain has deep historical roots reaching back over the past 200 years, yet research synthesis remains relatively new to public health, health care, and social sciences in general. This is rapidly changing. New developments in systematic reviews and meta-analysis, and the emergence of new synthesis methodologies provide a vast array of options to review the literature for diverse purposes. New approaches to research synthesis and new analytic methods within existing approaches provide a much broader range of review alternatives for public health, health care, and social science students and researchers.

Acknowledgments

KSM is an assistant professor in the Faculty of Nursing at the University of Alberta. Her work on this article was largely conducted as a Postdoctoral Fellow, funded by KRESCENT (Kidney Research Scientist Core Education and National Training Program, reference #KRES110011R1) and the Faculty of Nursing at the University of Alberta.

MM's work on this study over the period of 2008-2014 was supported by a Canadian Institutes of Health Research Applied Public Health Research Chair Award (grant #92365).

We thank Rachel Spanier who provided support with reference formatting.

List of Abbreviations (in Additional File 1 )

Conflict of interest: The authors declare that they have no conflicts of interest in this article.

Authors' contributions: KSM co-designed the study, collected data, analyzed the data, drafted/revised the manuscript, and managed the project.

MP contributed to searching the literature, developing the analytic framework, and extracting data for the Additional File.

JB contributed to searching the literature, developing the analytic framework, and extracting data for the Additional File.

WN contributed to searching the literature, developing the analytic framework, and extracting data for the Additional File.

All authors read and approved the final manuscript.

Additional Files: Additional File 1 – Selected Types of Research Synthesis

This Additional File is our dataset created to organize, analyze and critique the literature that we synthesized in our integrative review. Our results were created based on analysis of this Additional File.

A Guide to Evidence Synthesis: 1. Draft your Research Question

• Meet Our Team
• Our Published Reviews and Protocols
• What is Evidence Synthesis?
• Types of Evidence Synthesis
• Evidence Synthesis Across Disciplines
• Finding and Appraising Existing Systematic Reviews
• 0. Develop a Protocol
• 1. Draft your Research Question
• 2. Select Databases
• 3. Select Grey Literature Sources
• 4. Write a Search Strategy
• 5. Register a Protocol
• 6. Translate Search Strategies
• 7. Citation Management
• 8. Article Screening
• 9. Risk of Bias Assessment
• 10. Data Extraction
• 11. Synthesize, Map, or Describe the Results
• Evidence Synthesis Institute for Librarians
• Open Access Evidence Synthesis Resources

Video: Formulating a research question (4:43 minutes)

Developing a Research Question

Developing your research question.

Developing your research question is one of the most important steps in the evidence synthesis process. At this stage in the process, you and your team have identified a knowledge gap in your field and are aiming to answer a specific question:

• If X is prescribed, then Y will happen to patients?

OR assess an intervention:

• How does X affect Y?

OR synthesize the existing evidence

• What is the nature of X? ​

​​Whatever your aim, formulating a clear, well-defined research question of appropriate scope is key to a successful evidence synthesis . The research question will be the foundation of your  synthesis and from it your research team will identify 2-5 possible search concepts. These search concepts will later be used in step 5 to build your search strategy. 

Search Concepts

Research question frameworks.

Formulating a research question takes time and your team may go through different versions until settling on the right research question. To help formulate your research question, some research question frameworks are listed below (there are dozen of different types of these frameworks--for a comprehensive overview, see this guide from the University of Maryland )

Think of these frameworks as you would for a house or building. A framework is there to provide support and to be a scaffold for the rest of the structure. In the same way, a research question framework can also help structure your evidence synthesis  question.  Probably the most common framework is PICO:

PICO for Quantitative Studies

• P        Population/Problem
• I         Intervention/Exposure
• C        Comparison
• O       Outcome

Example: Is gabapentin (intervention), compared to placebo (comparison), effective in decreasing pain symptoms (outcome) in middle aged male amputees suffering phantom limb pain  (population)?

------------------------------------------------------------------------------------------------------------------------------------------------------------- While PICO is a helpful framework for clinical research questions, it may not be the best choice for other types of research questions, especially outside the health sciences.  Here are a few others (for a comprehensive, but concise, overview of the almost 40 different types of research question frameworks, see this review from the British Medical Journal: Rapid review of existing question formulation frameworks)

PICo for Qualitative Studies

• P         Population/Problem
• I           Phenomenon of Interest 
• Co     Context

Example: What are the experiences (phenomenon of interest) of caregivers providing home based care to patients with Alzheimer's disease  (population) in Australia  (context)?

• S     Setting
• P    Perspective (for whom)
• I     Intervention/Exposure
• C    Comparison
• E   Evaluation

Example: What are the benefits (evaluation) of a doula  (intervention) for low income mothers (perspective) in the developed world (setting) compared to no support (comparison)?

• S     Sample
• PI    Phenomenon of Interest
• D    Design
• E     Evaluation
• R    Study Type

Example: What are the experiences (evaluation) of women (sample) undergoing IVF treatment (phenomenon of interest) as assessed?

Design:    questionnaire or survey or interview

Study Type:  qualitative or mixed method

Inclusion/Exclusion Criteria

Inclusion and exclusion criteria.

Inclusion and exclusion criteria are developed after a research question is finalized but before a search is carried out. They determine the limits for the evidence synthesis and are typically reported in the methods section of the publication. For unfamiliar or unclear concepts, a definition may be necessary to adequately describe the criterion for readers. 

How a Librarian Can Help

How librarians can help.

Librarians can help you learn how to search for existing information on your topic. Finding existing reviews on your topic will inform the development of your research question, identify gaps, and confirm that you are not duplicating the efforts of previous reviews.  Email us at [email protected] to learn more about developing a research question.

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• Next: 2. Select Databases >>
• Last Updated: Apr 5, 2024 4:35 PM
• URL: https://guides.library.cornell.edu/evidence-synthesis

Literature Review Basics

• What is a Literature Review?
• Synthesizing Research
• Using Research & Synthesis Tables
• Additional Resources

Synthesis: What is it?

First, let's be perfectly clear about what synthesizing your research isn't :

• - It isn't  just summarizing the material you read
• - It isn't  generating a collection of annotations or comments (like an annotated bibliography)
• - It isn't  compiling a report on every single thing ever written in relation to your topic

When you  synthesize  your research, your job is to help your reader understand the current state of the conversation on your topic, relative to your research question.  That may include doing the following:

• - Selecting and using representative work on the topic
• - Identifying and discussing trends in published data or results
• - Identifying and explaining the impact of common features (study populations, interventions, etc.) that appear frequently in the literature
• - Explaining controversies, disputes, or central issues in the literature that are relevant to your research question
• - Identifying gaps in the literature, where more research is needed
• - Establishing the discussion to which your own research contributes and demonstrating the value of your contribution

Essentially, you're telling your reader where they are (and where you are) in the scholarly conversation about your project.

Synthesis: How do I do it?

Synthesis, step by step.

This is what you need to do  before  you write your review.

• Identify and clearly describe your research question (you may find the Formulating PICOT Questions table at  the Additional Resources tab helpful).
• Collect sources relevant to your research question.
• Organize and describe the sources you've found -- your job is to identify what  types  of sources you've collected (reviews, clinical trials, etc.), identify their  purpose  (what are they measuring, testing, or trying to discover?), determine the  level of evidence  they represent (see the Levels of Evidence table at the Additional Resources tab ), and briefly explain their  major findings . Use a Research Table to document this step.
• Study the information you've put in your Research Table and examine your collected sources, looking for  similarities  and  differences . Pay particular attention to  populations ,   methods  (especially relative to levels of evidence), and  findings .
• Analyze what you learn in (4) using a tool like a Synthesis Table. Your goal is to identify relevant themes, trends, gaps, and issues in the research.  Your literature review will collect the results of this analysis and explain them in relation to your research question.

Analysis tips

• - Sometimes, what you  don't  find in the literature is as important as what you do find -- look for questions that the existing research hasn't answered yet.
• - If any of the sources you've collected refer to or respond to each other, keep an eye on how they're related -- it may provide a clue as to whether or not study results have been successfully replicated.
• - Sorting your collected sources by level of evidence can provide valuable insight into how a particular topic has been covered, and it may help you to identify gaps worth addressing in your own work.
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• Next: Using Research & Synthesis Tables >>
• Last Updated: Sep 26, 2023 12:06 PM
• URL: https://usi.libguides.com/literature-review-basics

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Completing the Learning Loop: The Power of Synthesis and Reflection Prompts

by Jon Altbergs and Laurie Gagnon

At redesign, we encourage the adoption of a learning cycle that guides the learner through the habits and skills that support the development of competency with practice over time. in this post, we dig into the synthesis and reflection element of the learning cycle..

Let’s take a moment to revisit the two dimensions of the learning cycle. It represents the stages of meaningful learning that occur simultaneously during daily learning experiences (the “inner circle), and across multi-week units of study they constitute (the “outer circle”) that build toward authentic, competency-building work.

As our colleague Sydney Schaef explained in   A Friendly Introduction to the Competency-based Learning Cycle , 

In a nutshell, the Competency-based Learning Cycle is a visual framework that illustrates the cognitive and metacognitive processes that help learners develop competency with practice and feedback, as they work and learn in increasingly challenging contexts.  …The “outer circle” represents the four major stages of a competency-based project or unit of study through which learners explore a compelling question or issue.  …The “inner circle” structures daily learning experiences. … These learning experiences are purposefully and directly connected to the larger arc (outer circle), such that successful, recursive movement through this inner cycle enables progress through the four stages of the unit.

Ongoing synthesis and reflection anchor the learning cycle. Every learning experience, we believe, should culminate with synthesis and reflection questions.   Why are synthesis and reflection questions so important to close the loop of a lesson or learning experience? They are essential because the information they provide: 

• supports the provision of individualized feedback
• builds relationships through teacher attunement
• gauges student engagement
• offers insight into learners’ metacognition, the key to self-directed learning. 

Ultimately, synthesis and reflection questions are a moment of pause to “lift the hood” on learners’ thinking. 

Meaningful learning and assessment generate evidence of learning (as opposed to simply evidence of working). Synthesis and reflection help the learner situate new ideas into their overall understanding and helps the teacher gain insight into the thinking processes and conceptual understanding behind other work that the learner produces . When planning lessons, teachers often rightfully focus on designing assignments and activities that prompt students to think critically about the content they are learning. But rigorous assignments are not enough. Students need opportunities to synthesize and reflect on their learning. Synthesis connects the day’s learning to prior learning, helping students build schema and deepen their understanding. Reflection encourages metacognitive development by shifting the focus from the what of learning to the how. 

A synthesis prompt asks students to identify the important learning, summarize the learning, and articulate connections between the new learning and prior learning, knowledge, or experience in order to create or deepen understanding . Well-crafted synthesis questions lay the foundation for transferability of skills and knowledge. By incorporating synthesis into daily practice, building the connections that expand schema and ensure transferability is an ongoing process, rather than one that occurs at the end of a unit, the end of the year, or when new material is introduced. 

Synthesizing, like other strategies and skills, is a capability that develops over time and should be explicitly taught . Responding to a synthesis prompt calls upon three specific elements: determining importance, summarizing, and connecting. First, students identify the important parts of their learning, the key takeaways from the lesson or learning experience that were essential to completing the task at hand. Second, students summarize by concisely communicating the what and the why of their learning—the key content and its importance. Finally, when students synthesize they connect the day’s learning to a larger context, such as prior learning, the essential question, or their own experience and describe how connecting the two deepens their understanding. Connections can also be made to novel situations to extend thinking. 

Ultimately, the purpose of synthesis questions is the production, rather than reproduction, of knowledge . When students begin to explore a specific topic, their pool of knowledge may be limited, making rich connections and synthesis more difficult, but as they have more to call upon, those new (to them) insights happen more often. 

Though the thinking underlying synthesis prompts is complex, the prompts themselves don’t have to be. I used to think … but then I learned … and so now is a simple frame for synthesis. As part of an exit ticket, journaling prompt, or classroom discussion, this frame incorporates all three elements and creates the opportunity to uncover what students know and what gaps and misconceptions need to be addressed.

A reflection prompt asks students to look critically at their learning process from its inception to its completion . Reflection incorporates summarizing, evaluating, and inferring. When reflecting, students describe the steps they took to complete a task, focusing on their strategic action—the strategies and skills they used and the adjustments they made on their way toward their learning goal. They then make inferences about the influence of their actions on their outcomes to evaluate the effectiveness of those actions. Reflection is vital to fostering agency, self-efficacy, and independence, as it aids in building self-regulated learning skills: the ability to set goals and appraise tasks; monitor one’s learning progress; apply strategies as needed; and sustain motivation. 

Reflection helps the learner to evaluate whether their approach to their learning was successful and to surface lessons about how they learn, which can help them in being successful in their next learning endeavor. 

• What was my learning goal? Did I achieve my learning goal?
• How did I learn what I learned?
• What worked well as I learned? How do I know it worked well? What did not work as well as I wanted? How do I know it didn’t work well?
• What changes did I make on the fly? What was the effect of those changes?
• What did I learn about myself as a learner? How will this insight help me learn in the future?
• How did my thinking change as a result of my new learning?
• How can I use my new learning in the future?

If you are new to the idea of synthesis and reflection as a regular part of the learning process or if you want to bring more intention to how you craft questions, check out this self-assessment checklist for   Synthesis & Reflection Prompt Design . To see it in action, check out this   personal narrative unit outline   that illustrates how the reflection and synthesis prompts at each key stage of the unit build in complexity as learners move through the stages of the learning cycle: making meaning, investigating, creating, and finally, presenting, celebrating, and reflecting.

Back in the spring, our   first tip for meaningful learning in COVID   was to FOCUS ON EVIDENCE OF LEARNING (not evidence of working). Reflecting back, focusing on evidence of learning is actually a fundamental practice for learning. Now that schools and districts are getting back to school after the emergency learning situation of the spring, but still in very different conditions than before, we have the opportunity to design learning experiences that better incorporate key ideas from the research on how we learn. 

If you’re interested in hands-on learning and support to help you design learning experiences that are research-based and built around the learning cycle, check out this upcoming workshop series,   The Learning Cycle Workshop , offered through reDesign’s Institute in October/November. We hope to see you there!

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Synthesis as a Conversation

Melanie Gagich

Synthesizing

To synthesize is to combine ideas and create a completely new idea. That new idea becomes the conclusion you have drawn from your reading. This is the true beauty of reading: it causes us to weigh ideas, to compare, judge, think, and explore—and then to arrive at a moment that we hadn’t known before. We begin with simple summary , work through analysis , evaluate using critique , and then move on to synthesis .

What are the features of synthesis?

Synthesis is a flexible skill involving the use of other sources that either support your own view or assert an opposing point of view. Good writers always consider the opinions of people with whom they disagree then use those opinions to further defend their own. Therefore, in this essay, synthesis means comparing and contrasting your views with those of others. You may also compare and contrast the views of your sources, noting places where they seem to support each others’ ideas, and places where they might disagree or conflict.

For a more in-depth explanation of what synthesis writing is, what its goals are and how you can approach synthesis, visit the Writing Commons article “ Identifying a Conversation”

The content on this page is from Melanie Gagich’s book Introduction to Writing in College, which is licensed as CC-BY-NC-SA 4.0 and can be accessed here .

Synthesis as a Conversation by Melanie Gagich is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Learning about Synthesis Analysis

What D oes Synthesis and Analysis Mean?

Synthesis: the combination of ideas to

• show commonalities or patterns

Analysis: a detailed examination

• of elements, ideas, or the structure of something
• can be a basis for discussion or interpretation

Synthesis and Analysis: combine and examine ideas to

• show how commonalities, patterns, and elements fit together
• form a unified point for a theory, discussion, or interpretation
• develop an informed evaluation of the idea by presenting several different viewpoints and/or ideas

Key Resource: Synthesis Matrix

Synthesis Matrix

A synthesis matrix is an excellent tool to use to organize sources by theme and to be able to see the similarities and differences as well as any important patterns in the methodology and recommendations for future research. Using a synthesis matrix can assist you not only in synthesizing and analyzing,  but it can also aid you in finding a researchable problem and gaps in methodology and/or research.

Use the Synthesis Matrix Template attached below to organize your research by theme and look for patterns in your sources .Use the companion handout, "Types of Articles" to aid you in identifying the different article types for the sources you are using in your matrix. If you have any questions about how to use the synthesis matrix, sign up for the synthesis analysis group session to practice using them with Dr. Sara Northern!

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• Next: How to Synthesize and Analyze >>
• Last Updated: Apr 2, 2024 6:35 PM
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• Synthesizing Sources | Examples & Synthesis Matrix

Synthesizing Sources | Examples & Synthesis Matrix

Published on July 4, 2022 by Eoghan Ryan . Revised on May 31, 2023.

Synthesizing sources involves combining the work of other scholars to provide new insights. It’s a way of integrating sources that helps situate your work in relation to existing research.

Synthesizing sources involves more than just summarizing . You must emphasize how each source contributes to current debates, highlighting points of (dis)agreement and putting the sources in conversation with each other.

You might synthesize sources in your literature review to give an overview of the field or throughout your research paper when you want to position your work in relation to existing research.

Table of contents

Example of synthesizing sources, how to synthesize sources, synthesis matrix, other interesting articles, frequently asked questions about synthesizing sources.

Let’s take a look at an example where sources are not properly synthesized, and then see what can be done to improve it.

This paragraph provides no context for the information and does not explain the relationships between the sources described. It also doesn’t analyze the sources or consider gaps in existing research.

Research on the barriers to second language acquisition has primarily focused on age-related difficulties. Building on Lenneberg’s (1967) theory of a critical period of language acquisition, Johnson and Newport (1988) tested Lenneberg’s idea in the context of second language acquisition. Their research seemed to confirm that young learners acquire a second language more easily than older learners. Recent research has considered other potential barriers to language acquisition. Schepens, van Hout, and van der Slik (2022) have revealed that the difficulties of learning a second language at an older age are compounded by dissimilarity between a learner’s first language and the language they aim to acquire. Further research needs to be carried out to determine whether the difficulty faced by adult monoglot speakers is also faced by adults who acquired a second language during the “critical period.”

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To synthesize sources, group them around a specific theme or point of contention.

As you read sources, ask:

• What questions or ideas recur? Do the sources focus on the same points, or do they look at the issue from different angles?
• How does each source relate to others? Does it confirm or challenge the findings of past research?
• Where do the sources agree or disagree?

Once you have a clear idea of how each source positions itself, put them in conversation with each other. Analyze and interpret their points of agreement and disagreement. This displays the relationships among sources and creates a sense of coherence.

Consider both implicit and explicit (dis)agreements. Whether one source specifically refutes another or just happens to come to different conclusions without specifically engaging with it, you can mention it in your synthesis either way.

Synthesize your sources using:

• Topic sentences to introduce the relationship between the sources
• Signal phrases to attribute ideas to their authors
• Transition words and phrases to link together different ideas

To more easily determine the similarities and dissimilarities among your sources, you can create a visual representation of their main ideas with a synthesis matrix . This is a tool that you can use when researching and writing your paper, not a part of the final text.

In a synthesis matrix, each column represents one source, and each row represents a common theme or idea among the sources. In the relevant rows, fill in a short summary of how the source treats each theme or topic.

This helps you to clearly see the commonalities or points of divergence among your sources. You can then synthesize these sources in your work by explaining their relationship.

If you want to know more about ChatGPT, AI tools , citation , and plagiarism , make sure to check out some of our other articles with explanations and examples.

• ChatGPT vs human editor
• ChatGPT citations
• Is ChatGPT trustworthy?
• Using ChatGPT for your studies
• What is ChatGPT?
• Chicago style
• Paraphrasing

 Plagiarism

• Types of plagiarism
• Self-plagiarism
• Avoiding plagiarism
• Academic integrity
• Consequences of plagiarism
• Common knowledge

Synthesizing sources means comparing and contrasting the work of other scholars to provide new insights.

It involves analyzing and interpreting the points of agreement and disagreement among sources.

You might synthesize sources in your literature review to give an overview of the field of research or throughout your paper when you want to contribute something new to existing research.

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

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

Topic sentences help keep your writing focused and guide the reader through your argument.

In an essay or paper , each paragraph should focus on a single idea. By stating the main idea in the topic sentence, you clarify what the paragraph is about for both yourself and your reader.

At college level, you must properly cite your sources in all essays , research papers , and other academic texts (except exams and in-class exercises).

Add a citation whenever you quote , paraphrase , or summarize information or ideas from a source. You should also give full source details in a bibliography or reference list at the end of your text.

The exact format of your citations depends on which citation style you are instructed to use. The most common styles are APA , MLA , and Chicago .

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Ryan, E. (2023, May 31). Synthesizing Sources | Examples & Synthesis Matrix. Scribbr. Retrieved April 9, 2024, from https://www.scribbr.com/working-with-sources/synthesizing-sources/

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Digital SAT Reading and Writing

Course: digital sat reading and writing   >   unit 2, rhetorical synthesis | lesson.

• Rhetorical synthesis — Worked example
• Rhetorical Synthesis — Quick example
• Rhetorical synthesis: foundations

What are "rhetorical synthesis" questions?

• The novel David Copperfield by Charles Dickens focuses on the adventures of its title character, David Copperfield.
• David Copperfield is considered a bildungsroman.
• In a bildungsroman, the main character grows, learns, and changes from experience.
• The novel Tom Jones by Henry Fielding focuses on the adventures of its title character, Tom Jones.
• Tom Jones is considered a picaresque novel.
• In a picaresque novel, the main character has many experiences but stays fundamentally the same.
• (Choice A)   David Copperfield and Tom Jones are both considered picaresque novels. A David Copperfield and Tom Jones are both considered picaresque novels.
• (Choice B)   Both David Copperfield and Tom Jones focus on the adventures of their title characters. B Both David Copperfield and Tom Jones focus on the adventures of their title characters.
• (Choice C)   David Copperfield was written by Charles Dickens; Tom Jones was written by Henry Fielding. C David Copperfield was written by Charles Dickens; Tom Jones was written by Henry Fielding.
• (Choice D)   In David Copperfield , unlike in Tom Jones , the main character grows, learns, and changes from experience. D In David Copperfield , unlike in Tom Jones , the main character grows, learns, and changes from experience.

Choice A: This choice does not accurately represent the information in the bullet points! Bullet point 2 tells us that David Copperfield is considered a bildungsroman. The next bullet points tell us that in a bildungsroman, the main character changes, while in a picaresque novel, the main character basically stays the same. This means that a bildungsroman can't also be a picaresque novel.

Choice B: This choice emphasizes a similarity and accurately represents the information in the bullet points. Bullet point 1 says that David Copperfield focuses on the adventures of its title character, and bullet point 4 says that Tom Jones focuses on the adventures of its title character.

Choice C: This choice accurately represents the bulleted information, but it doesn't accomplish the goal. It highlights a difference between the two novels—the fact that they have different authors. But we're looking for a similarity.

Choice D: Like choice C, this choice accurately represents the bulleted information, but it doesn't accomplish the goal. It emphasizes a difference between the two novels, but, again, we're looking for a similarity.

How should we think about rhetorical synthesis questions?

Question structure.

• an introduction
• a series of bulleted facts
• a question prompt
• the choices

How to approach rhetorical synthesis questions

Step 1: Identify the goal

Step 2: Read the bullet points and identify relevant info

Step 3: Test the choices

Step 4: Select the choice that matches

Do two "passes" to eliminate choices!

Simplify the goal.

• Choice C emphasizes a difference between the two novels, not a similarity. We can eliminate choice C.
• Choice D also emphasizes a difference between the two novels, not a similarity. We can eliminate choice D.

Ignore the grammar

• Marine biologist Camille Jazmin Gaynus studies coral reefs.
• Coral reefs are vital underwater ecosystems that provide habitats to 25% of all marine species.
• Reefs can include up to 8,000 species of fish, such as toadfish, seahorses, and clown triggerfish.
• The Amazon Reef is a coral reef in Brazil.
• It is one of the largest known reefs in the world.
• (Choice A)   Providing homes to 25% of all marine species, including up to 8,000 species of fish, coral reefs are vital underwater ecosystems and thus of great interest to marine biologists. A Providing homes to 25% of all marine species, including up to 8,000 species of fish, coral reefs are vital underwater ecosystems and thus of great interest to marine biologists.
• (Choice B)   Marine biologist Camille Jazmin Gaynus studies coral reefs, vital underwater ecosystems that provide homes to 25% of all marine species. B Marine biologist Camille Jazmin Gaynus studies coral reefs, vital underwater ecosystems that provide homes to 25% of all marine species.
• (Choice C)   Camilla Jazmin Gaynus is a marine biologist who exclusively studies the Amazon Reef, a coral reef that is home to 8,000 different species of fish. C Camilla Jazmin Gaynus is a marine biologist who exclusively studies the Amazon Reef, a coral reef that is home to 8,000 different species of fish.
• (Choice D)   As Camille Jazmin Gaynus knows well, coral reefs are vital underwater ecosystems, providing homes to thousands of species of fish. D As Camille Jazmin Gaynus knows well, coral reefs are vital underwater ecosystems, providing homes to thousands of species of fish.
• Choice A doesn't mention the scientist at all. We can eliminate choice A.
• Remember to be strict : the goal is to introduce the scientist AND her field of study. Choice D names the scientist, but it doesn't introduce her field of study (it doesn't say she's a marine biologist). We can eliminate choice D.

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The 6 Levels of Questioning in the Classroom (+ Examples)

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The 6 levels of questioning in the classroom.

The goal of questioning in the classroom is not simply to determine whether students have learned something, but rather to guide them in their learning process. Unlike  tests, quizzes, and exams , questioning in the classroom should be used to teach students, not test them! 

Questions as tests

Teachers spend a great deal of classroom time testing students through questions. Observations of teachers at all levels of education reveal that most spend more than 90 percent of their instructional time testing students (through questioning). And most of the questions teachers ask are typically factual questions that rely on short-term memory.

Although questions are widely used and serve many functions, teachers tend to overuse factual questions such as “What is the capital of California?” Not surprising, as many teachers ask upward of 400 questions every school day! And approximately 80 percent of all the questions teachers ask are factual, literal, or knowledge-based questions.

The result is a classroom in which there is little creative thinking taking place.

What is Bloom's Taxonomy? 

Bloom's Taxonomy  is a hierarchical model used in education to classify educational learning objectives into levels of complexity and specificity. It's named after Benjamin Bloom, who chaired the committee of educators that devised it in the 1950s.

The taxonomy has six levels, designed to help educators create more effective learning objectives and engage students in higher levels of thinking. These levels are arranged in hierarchical form, moving from the lowest level of cognition to the highest level of cognition.

Bloom's Taxonomy was revised in 2001 to better reflect the different types of cognitive processes used in learning and understanding.

Why use Bloom's Taxonomy? 

Bloom's Taxonomy is a powerful tool in the K-12 classroom because it provides a structured approach to questioning that promotes higher levels of thinking. Instead of focusing on rote memorization, Bloom's Taxonomy encourages students to analyze, evaluate, and create. This level of questioning not only enhances students’ understanding of the material, but it also fosters critical thinking and problem-solving skills.

Moreover, this level of questioning in the classroom provides teachers with a clear framework to design their lessons and assess student learning effectively. This approach shifts the focus from merely testing students to facilitating meaningful learning experiences.

Levels of questioning in the classroom (+ examples)

Graphic used with permission by Vanderbilt University

Level 1: Remember

The first level of questioning in the classroom according to Bloom’s Taxonomy is "Remember" (previously: “Knowledge”). This base level involves recalling or recognizing information from memory. It's the most basic level of cognition, where students are asked to remember facts, terms, basic concepts, or answers without necessarily understanding what they mean.

Examples of this level of questioning in the classroom might include "What is the capital of France?" or "Who wrote 'To Kill a Mockingbird'?" Although this level is necessary, it's important to progress beyond it to promote higher levels of thinking.

Words often used in “Remember” questions often include  know ,  who ,  define ,  what ,  name ,  where ,  list , and  when .

Remembering question examples:

• "What is the date of the Declaration of Independence?"
• "Who is the author of 'Pride and Prejudice'?"
• "Can you list the planets in our solar system?"
• "What is the formula for the area of a rectangle?"
• "Who was the first president of the United States?"

Level 2: Understand 

The second level of questioning in the classroom is "Understand" (previously: “Comprehension”). At this stage, students are expected to comprehend the material, which means they can interpret, translate, and summarize the information.

This level goes beyond simple recall of facts and asks students to explain ideas or concepts in their own words.

Keywords often used in "Understand" questions include  explain ,  describe ,  identify ,  discuss , and  interpret .

Understanding questions examples:

• "Can you summarize the main events in the book in your own words?"
• "How would you interpret the author's intentions in this scene?"
• "Can you explain the concept of photosynthesis to a 5-year-old?"
• "What do you think the significance of this event in history is?"
• "How would you translate this sentence into your own words?"

Level 3: Apply

The third level of questioning in the classroom, according to Bloom’s Taxonomy, is "Apply" (previously: “Application”). At this stage, students are expected to use the information they have learned in new situations.

This stage involves problem-solving, implementing methods, and demonstrating how concepts can be used in real-world scenarios.

This level of questioning is important because it encourages students to go beyond simply recalling information and understanding concepts and to start applying this knowledge in practical ways. It promotes critical thinking and problem-solving skills and helps students see the relevance and applicability of what they are learning.

Keywords often used in "Apply" questions include  demonstrate ,  apply ,  solve ,  use , and  illustrate .

Applying question examples:

• "How would you use the Pythagorean theorem to determine the length of the hypotenuse in a right-angled triangle?"
• "Can you construct a model to demonstrate how the solar system works?"
• "Using what you've learned about the water cycle, can you explain why it rains?"
• "How can you apply the principles of democracy to set up a student council in your school?"
• "Can you create an experiment to test the law of conservation of energy?"

Level 4: Analyze 

The fourth level of questioning in the classroom is "Analyze" (previously: “Analysis”). This level involves breaking down information into its component parts for better understanding. Students are expected to differentiate, organize, and relate the parts to the whole.

This stage is crucial as it encourages students to examine information in a detailed way and to understand how different parts relate to one another. This level of questioning promotes critical thinking and a deeper understanding of the subject matter.

Keywords often used in "Analyze" questions include  compare ,  contrast ,  examine ,  classify , and  break down .

Analyzing questions examples

• "How does the protagonist's journey in the novel reflect societal issues?"
• "What are the similarities and differences between two political systems?"
• "How do the different elements of this artwork contribute to its overall impact?"
• "Explain the cause and effect relationship between events in a historical period."
• "How do the different theories of economics apply to this case study?"

Level 5: Evaluate 

The fifth level of questioning in the classroom is "Evaluate" (previously: “Evaluation”). At this stage, students are expected to form judgments about the value and worth of information based on criteria and standards. This involves appraising, judging, critiquing, and defending positions. This level encourages students to formulate their own opinions and make judgments based on their understanding and analysis of the information.

Keywords often used in "Evaluate" questions include  judge ,  rate ,  evaluate ,  defend , and  justify .

Evaluating question examples:

• "Was the ending of the novel satisfactory? Defend your position."
• "What do you think about the author's point of view?"
• "How would you rate this character's decisions throughout the story?"
• "Evaluate the effectiveness of the government's response in a historical event."
• "Can you justify your solution to this problem?"

Level 6: Create 

The final level of questioning in the classroom according to Bloom’s Taxonomy is "Create" (previously: “Synthesis”). At this stage, students are expected to use what they've learned to create something new or original. This could involve developing a plan or proposal, deriving a set of abstract relations, or presenting an original idea. This level of questioning encourages creativity and innovation, as students are asked to generate new ideas, products, or ways of viewing things. Keywords often used in "Create" questions include  design ,  construct ,  create ,  invent , and  compose .

Creating question examples:

• "Can you devise a way to ensure clean water access in developing countries?"
• "How would you design a fair and effective classroom behavior policy?"
• "Can you create a short story based on the themes we've discussed?"
• "Compose a poem that expresses your feelings about a current event."
• "Invent a new product that solves a problem you've identified."

It's elementary! 

Many teachers think primary-level students (Kindergarten through 2nd Grade) cannot handle higher-level questions. But nothing could be further from the truth! Challenging all students through higher-order questioning is one of the best ways to stimulate learning and enhance brain development, regardless of age.

If you only ask your students one level of questioning, your students might not be exposed to higher levels of thinking. If, for example, you only ask your students knowledge-based questions, they might think that learning a specific subject is nothing more than the ability to memorize a select number of facts.

The 6 levels of questioning in the classroom according to Bloom’s Taxonomy provide a structured shift from simple factual recall to more complex cognitive processes. This approach not only deepens students' understanding of the subject matter, but also fosters critical thinking, problem-solving skills, creativity, and innovation.

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Module 9: Genes and Proteins

Study guide: protein synthesis, study questions.

Objective: Illustrate the molecular processes described in the central dogma.

Use this page to check your understanding of the content.

• Transcription
• Translation

Study Guide Questions

• What is the central dogma of biology?
• Compare and contrast mRNA, rRNA, and tRNA.
• What is DNA polymerase?  What is RNA polymerase?
• How are mRNA transcripts modified before they exit the nucleus?
• Compare and contrast transcription and DNA replication.
• Compare and contrast transcription and translation.
• Compare and contrast introns and exons.
• What is a codon?  Compare this to an anticodon.
• Be able to use an amino acid/mRNA codon chart.
• Given a DNA template, be able to determine the mRNA base sequence, the tRNA anticodons, and the amino acids coded for (like in activity!)
• Know the structure of the ribosome.
• Know the significance of the E site, the P site and the A site in the ribosome.
• Know the structure of a tRNA molecule.
• Study Guide: Protein Synthesis. Authored by : Wendy Riggs. Provided by : College of the Redwoods. Project : Kaleidoscope. License : CC BY: Attribution

Critical Thinking Questions

Why are biological macromolecules considered organic?

What role do electrons play in dehydration synthesis and hydrolysis?

Amino acids have the generic structure seen below, where R represents different carbon-based side chains.

Describe how the structure of amino acids allows them to be linked into long peptide chains to form proteins.

Describe the similarities and differences between glycogen and starch.

Why is it impossible for humans to digest food that contains cellulose?

Draw the ketose and aldose forms of a monosaccharide with the chemical formula C 3 H 6 O 3 . How is the structure of the monosaccharide changed from one form to the other in the human body?

Explain at least three functions that lipids serve in plants and/or animals.

Why have trans fats been banned from some restaurants? How are they created?

Why are fatty acids better than glycogen for storing large amounts of chemical energy?

Part of cortisol’s role in the body involves passing through the plasma membrane to initiate signaling inside a cell. Describe how the structures of cortisol and the plasma membrane allow this to occur.

Explain what happens if even one amino acid is substituted for another in a polypeptide chain. Provide a specific example.

Describe the differences in the four protein structures.

Aquaporins are proteins embedded in the plasma membrane that allow water molecules to move between the extracellular matrix and the intracellular space. Based on its function and location, describe the key features of the protein’s shape and the chemical characteristics of its amino acids.

What are the structural differences between RNA and DNA?

What are the four types of RNA and how do they function?

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How to Tackle Organic Chemistry Synthesis Questions

November 10, 2016 By Leah4sci 4 Comments

It's not so scary at first, think about the simple acid/base deprotonation, an alkene reaction here, another there. Before you know it, you’re drowning in dozens upon dozens of reactions!

You’re asked to ‘memorize’ each one, to know what every reactant and reagent will do. And once you have it all down, don’t forget the dozen or so exceptions to the rule.

And once you have all THAT down, let’s put them all together: when you’re given molecule A and asked to come up with all 20 steps to produce product Z!

Ok, perhaps I’m exaggerating a bit…but really, just a tiny bit!

The average Organic Chemistry 1 or 2 exam synthesis question will range from two to five steps with intermediates.

How do you keep everything you learned straight?

And more importantly, how do you sift through the hundreds of data points in your head to produce the exact steps required to achieve the desired outcome?

As a kid, I was proud to call myself a nerd. Perhaps with a bit of OCD. I always looked for trends and found patterns where they didn’t exist. Perhaps that’s why I enjoy Orgo so much.

The SECRET to synthesis is simple:

A) Look for patterns, as we’ll explain below. B)  when you get stuck, remember there’s likely more than one way to reach your desired product.

Coming up with a proper synthesis requires a combination of forward and reverse thinking!

We’ll cover the reverse thinking in the Retrosynthesis tutorial . For this tutorial, we’ll focus on the shorter and simpler synthesis.

Let’s start by looking for patterns.

The following questions will help you understand what to pay close attention to.

Look out for the following:

• What functional group is present on the reactant ?
• What functional group is present on the product ?
• Which reactions do I know to convert from one to the other?
• Do I know of a reaction that produces an intermediate to the above product?

“What do I have in the reactant?” A reactive pi bond!

“ What do I have in the product?” An alcohol.

“Which reaction do I know can help me convert from an alkene to an alcohol?”

Well, there are many if you think about it. Let’s go in order from most obvious to less obvious:

• Acid catalyzed hydration
• Oxymercuration-demercuration
• Hydroboration-oxidation

But what if you weren’t given the alkene, or didn’t think of these alkene reactions? What about putting a halogen leaving group on the alkene through hydrohalogenation ? Or a radical halogenation if starting with an alkane?

What if it wasn’t that easy?

What if you’re asked to start with an alkyne?

This is where we introduce many options: –> If you reduce the alkyne to an alkene, you may use one of the following as already discussed above:

–> If you go from the alkyne to a carbonyl (ketone or aldehyde) you can follow up by reduction:

Do you see where we’re going with this?

A) Identify the patterns B) Ask yourself, “What do I know?” to recognize these patterns C) Go from there

Let’s start with a simple example for concept, then apply the same logic to something more complicated.

• What functional group is present on the reactant ? Reactive terminal alkyne
• What functional group is present on the product ? Ketone on carbon #2
• Which reactions do I know to convert from one to the other? Acid catalyzed hydration of alkynes will yield a ketone following Markovnikov’s Rule .

HOWEVER ,  in this example we’re starting with a 3-carbon chain yet ending with a 4-carbon chain.

4. Do I know of a reaction that produces an intermediate to the above product? Yes! Terminal alkynes easily undergo chain elongation via SN2.

We'll start with an acid/base reaction  to deprotonate the terminal alkyne forming a good nucleophile.

But wait, the product is an enol, not a ketone!!

And there we have it!

Even scarier than a synthesis by itself is the following exam question/request:

“Propose a reasonable mechanism to carry out the following synthesis.”

This is where you’re given one reactant, one product, and ONE or TWO sets of reagents. In other words, you’re given all the steps but asked to show how the different molecules work together.

While the question is completely different, the concept is the same .

We’ll modify the initial questions slightly:

• WHERE IS THE REACTIVITY ON THE STARTING MOLECULE? As in, where do I start the mechanism?

A student recently showed me this exam question for which not a single student in his class got full credit.

Let me preface this by saying YES, this is a tough question. BUT, if you think through it logically, you’ll realize that if you studied the individual steps and recognize them, you should be able to follow along.

In fact, I challenge you to give this a try and see how far you get before reading on.

Propose a reasonable mechanism for the following reaction. show all intermediates and formal charges. is this reaction sn1 sn2 e1 e2 .

What do you think? Did you get it?

Here's a video with a step by step solution: 

No matter how well you prepare, you'll still get caught off-guard by one tricky step or another.

And when you get stuck?

Chances are, there’s more than one way to derive your product!

When I took my first weekly Organic Chemistry 2 quiz, I inadvertently set a trend of scoring top of the class, but it was a fluke. I didn’t realize we had weekly quizzes…

We were asked to outline a step by step procedure to separate two similar molecules with different functional groups. The process involved a series of reactions to prepare one molecule for extraction.

I remembered that there were about six steps, but I could only confidently answer four. I’d already bombed, then aced Orgo 1, and didn’t want to do that again!

No matter what I did, I couldn’t come up with the other steps. So instead, I crossed out my four and a half steps and wrote a detailed step by step procedure for carrying out fractional distillation.

My TA very reluctantly gave me full credit with an amused warning. No one else came close.

Am I asking you to outsmart the question?

Just recognize that the more reactions you learn, the more options you have for creating a single functional group.

If you're stuck on a certain pathway or can’t fully describe the steps, Ask yourself, “Is there another way to create the same functional group?”

Think back to the many alcohol formation reactions we discussed above. If you forgot one option, simply use another.

Here are a few interesting patterns and alternates to consider.

–> Chain Elongation ‘Go-To’ reactions

• Use alkynes in Orgo 1
• Use grignards or condensation in Orgo 2

–> Adding carboxylic acids or carbonyls

• Alcohol -> oxidation
• Oxidative cleavage using KMnO4 or O3 (smaller chain)
• Grignard and CO2 (longer chain)

–> ‘Moving’ Reactivity so that you can start/react at a different portion of the molecule compared to the current location of the active group.

Active groups include leaving groups, pi bonds, nucleophilic centers susceptible to attack and more.

• Move the Pi bond intermediate then apply a Markovnikov or Anti-Markovnikov addition .
• No pi bond? Radical halogenation to introduce a leaving group and THEN eliminate.

These are just SOME of the tricks you can utilize.

Maximizing Partial Credit On Your Exam

Gaining bonus points on exams is one thing, but here’s the best part:

The average synthesis question is worth anywhere from 10-30 points. And the average professor WILL give partial credit. So, if you can only remember four of five steps, DO NOT leave it blank to receive zero points!

Instead, write the four steps and add in as much relevant information as possible. Then VERY CONFIDENTLY fake the fifth step.

Do not write “ Magic! ”   (yes, I’ve seen this on a student exam).

Make up something that appears to be just a ‘careless’ mistake. Your professor will be impressed by your work and hopefully give you an 80% for the question.

This also applies to reagents!

If you only remember the steps, but don’t remember which reagents will get you there, start by drawing out the molecules:

A –> B –> C

This has two benefits:

• It helps you think without distractions so you can clearly see how the molecule and functional groups change/evolve from step to step.
• Now that you have a clear picture of where you’re doing, you should be able to retrace your steps and fill in the required reagents!

Of course if Reagents are giving you trouble with this, here's a video on  ‘Memorizing’ Organic Chemistry Reagents .

And if you can’t remember them, invent something rather than leave it blank.  try to use a reagent that has the groups you’re adding..

Are they correct? Not quite! Both will cleave the alkyne.

BUT, I’ve seen enough students use this as a legitimate mistake that your professor may think the same and hopefully give you partial credit.

Again, I’m not asking you to invent on your exam.

But, guessing logically on a multi-step problem where you’ve already earned sufficient points will help you get closer to full credit.

I’ve done this successfully on my orgo exams and come out top of the class, despite missing half a point here and there on multiple questions. My Study Hall members and tutoring clients do the same thing to squeeze in a few extra points, bringing them to the top.

Bottom line, make sure you learn and UNDERSTAND all of the required reactions!

But even the best of us forget some things under pressure.

That’s when you can utilize the tips above to help you try your best and you’ll have an advantage with most professors. They'll hopefully give you the benefit of the doubt when answers are questionable or not exactly what they were seeking.

Ready to start thinking backwards? That's where the more difficult topic of  Retrosynthetic Analysis or simply retrosynthesis  comes into play.

I’d love to hear from you

Do you feel better about synthesis and knowing what to do when you are stuck? Let me know in the comments below

September 26, 2018 at 12:42 pm

its too much difficult topic I can’t understand….infact i can’t thnk too much like that to propose a mechanism………Wt should I do? paper b ha?

March 1, 2018 at 8:23 am

why in this case the pi bond forms in C1 and C2 and not in C2 and C3 (more substitued alkene) https://leah4sci.com/wp-content/uploads/2016/11/Moving-Reactivity-can-help-react-a-different-portion-of-the-molecule-using-intermediates-and-then-Mark-or-Anti-Markovnikov-addition.jpg

December 23, 2017 at 1:21 pm

Great post!!This article will be extremely helpful for students. Thank you for sharing this great guide it is really well written and very easy to understand with some great tips for chemistry. Nice work!

April 23, 2017 at 12:18 pm

I can’t explain how much this just helped me for my Ochem exam this thursday! THANK YOU

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This page contains resource questions and discussion points designed to further conversation on the subject of gene expression.

A Review of Protein Synthesis

1. Protein synthesis is a two-stage process involving transcription and translation . Explain what happens in each stage of protein synthesis.

2. Scientists talk about coding and non‐coding DNA. What do these terms mean?

3. What does the term gene expression mean?

4. Describe the relationship between DNA, RNA, and proteins and explain how mutations can impact on phenotype.

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6. Describe a situation where the effect of environment on phenotype can be observed and cannot be reversed if the environment changes.

Important Vocabulary: Test Yourself

Related topic: bisphenol a.

(Links to Curriculum Level Eight and Achievement Standard: AS91602 3.2: Integrate Biological Knowledge to Develop an Informed Response to a Socio-Scientific Issue)

Epigenetics is also linked to a current international issue that is becoming more widely known in New Zealand. Bisphenol A, a chemical found in many plastics including baby bottles, fillings that dentists use, linings for tin cans and much more has been shown to be linked with premature puberty and breast cancer. In Canada, the use of plastics containing Bisphenol A in baby bottles has been banned. Internationally, there is much debate over this issue. 

The New Zealand Food Safety authority is monitoring the situation. Professor Ian Shaw, a toxicologist from Canterbury University and Principal Investigator for the National Research Centre for Growth and Development is an expert in this field. He is also a consultant to the NZ Food Safety authority.  

This is a contemporary biological issue for which different groups in society hold differing viewpoints. You may wish to consider this issue for Biology 3.2. 

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Watch Professor Ian Shaw talking about this issue for TEDx (November, 2010)

Breast Cancer Link to Plastic (Sunday Star Times, 31 January, 2009)

Dangers Lurking in Everyday Plastic (Taranaki Daily News, 10 July, 2009)

Greens Say NZ Should Ban Plastic Baby Bottles (Stuff, 31 Jan, 2009)

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