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.
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.
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 ).
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.
Types of Research Synthesis | Definition | Data Types Used | Products | Examples |
1. Conventional Synthesis | Older forms of review with less-systematic examination, critique, and synthesis of the literature on a mature topic for re-conceptulization or on a new topic for preliminary conceptualization | , – | ||
2. Quantitative Synthesis | Combining, aggregating, or integrating quantitative empirical research with data expressed in numeric form | , – – – | ||
3. Qualitative Synthesis | Combining, aggregating, or integrating qualitative empirical research and/or theoretical work expressed in narrative form | – – , – , , – , – – , – – , – | ||
4. Emerging Synthesis | Newer syntheses that provide a systematic approach to synthesizing varied literature in a topic area that includes diverse data types | – – – – , , – |
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 .
4.1.1. 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.
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.
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).
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.
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.
4.3.1. 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.
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.
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.
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] .
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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] .
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.
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.
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.
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.
Literature reviews: synthesis.
So, how can you create paragraphs within your literature review that demonstrates your knowledge of the scholarship that has been done in your field of study?
You will need to present a synthesis of the texts you read.
Doug Specht, Senior Lecturer at the Westminster School of Media and Communication, explains synthesis for us in the following video:
Synthesising Texts
What is synthesis?
Synthesis is an important element of academic writing, demonstrating comprehension, analysis, evaluation and original creation.
With synthesis you extract content from different sources to create an original text. While paraphrase and summary maintain the structure of the given source(s), with synthesis you create a new structure.
The sources will provide different perspectives and evidence on a topic. They will be put together when agreeing, contrasted when disagreeing. The sources must be referenced.
Perfect your synthesis by showing the flow of your reasoning, expressing critical evaluation of the sources and drawing conclusions.
When you synthesise think of "using strategic thinking to resolve a problem requiring the integration of diverse pieces of information around a structuring theme" (Mateos and Sole 2009, p448).
Synthesis is a complex activity, which requires a high degree of comprehension and active engagement with the subject. As you progress in higher education, so increase the expectations on your abilities to synthesise.
How to synthesise in a literature review:
Identify themes/issues you'd like to discuss in the literature review. Think of an outline.
Read the literature and identify these themes/issues.
Critically analyse the texts asking: how does the text I'm reading relate to the other texts I've read on the same topic? Is it in agreement? Does it differ in its perspective? Is it stronger or weaker? How does it differ (could be scope, methods, year of publication etc.). Draw your conclusions on the state of the literature on the topic.
Start writing your literature review, structuring it according to the outline you planned.
Put together sources stating the same point; contrast sources presenting counter-arguments or different points.
Present your critical analysis.
Always provide the references.
The best synthesis requires a "recursive process" whereby you read the source texts, identify relevant parts, take notes, produce drafts, re-read the source texts, revise your text, re-write... (Mateos and Sole, 2009).
What is good synthesis?
The quality of your synthesis can be assessed considering the following (Mateos and Sole, 2009, p439):
Integration and connection of the information from the source texts around a structuring theme.
Selection of ideas necessary for producing the synthesis.
Appropriateness of the interpretation.
Elaboration of the content.
Original texts (fictitious):
Animal testing is necessary to save human lives. Incidents have happened where humans have died or have been seriously harmed for using drugs that had not been tested on animals (Smith 2008). | Animals feel pain in a way that is physiologically and neuroanatomically similar to humans (Chowdhury 2012). |
Animal testing is not always used to assess the toxicology of a drug; sometimes painful experiments are undertaken to improve the effectiveness of cosmetics (Turner 2015) | Animals in distress can suffer psychologically, showing symptoms of depression and anxiety (Panatta and Hudson 2016). |
Synthesis:
Animal experimentation is a subject of heated debate. Some argue that painful experiments should be banned. Indeed it has been demonstrated that such experiments make animals suffer physically and psychologically (Chowdhury 2012; Panatta and Hudson 2016). On the other hand, it has been argued that animal experimentation can save human lives and reduce harm on humans (Smith 2008). This argument is only valid for toxicological testing, not for tests that, for example, merely improve the efficacy of a cosmetic (Turner 2015). It can be suggested that animal experimentation should be regulated to only allow toxicological risk assessment, and the suffering to the animals should be minimised.
Mateos, M. and Sole, I. (2009). Synthesising Information from various texts: A Study of Procedures and Products at Different Educational Levels. European Journal of Psychology of Education, 24 (4), 435-451. Available from https://doi.org/10.1007/BF03178760 [Accessed 29 June 2021].
Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.
Learning objectives.
At the conclusion of this chapter, you will be able to:
7.1.1 putting the pieces together.
Combining separate elements into a whole is the dictionary definition of synthesis. It is a way to make connections among and between numerous and varied source materials. A literature review is not an annotated bibliography, organized by title, author, or date of publication. Rather, it is grouped by topic to create a whole view of the literature relevant to your research question.
Your synthesis must demonstrate a critical analysis of the papers you collected as well as your ability to integrate the results of your analysis into your own literature review. Each paper collected should be critically evaluated and weighed for “adequacy, appropriateness, and thoroughness” ( Garrard, 2017 ) before inclusion in your own review. Papers that do not meet this criteria likely should not be included in your literature review.
Begin the synthesis process by creating a grid, table, or an outline where you will summarize, using common themes you have identified and the sources you have found. The summary grid or outline will help you compare and contrast the themes so you can see the relationships among them as well as areas where you may need to do more searching. Whichever method you choose, this type of organization will help you to both understand the information you find and structure the writing of your review. Remember, although “the means of summarizing can vary, the key at this point is to make sure you understand what you’ve found and how it relates to your topic and research question” ( Bennard et al., 2014 ).
As you read through the material you gather, look for common themes as they may provide the structure for your literature review. And, remember, research is an iterative process: it is not unusual to go back and search information sources for more material.
At one extreme, if you are claiming, ‘There are no prior publications on this topic,’ it is more likely that you have not found them yet and may need to broaden your search. At another extreme, writing a complete literature review can be difficult with a well-trod topic. Do not cite it all; instead cite what is most relevant. If that still leaves too much to include, be sure to reference influential sources…as well as high-quality work that clearly connects to the points you make. ( Klingner, Scanlon, & Pressley, 2005 ).
Literature reviews can be organized sequentially or by topic, theme, method, results, theory, or argument. It’s important to develop categories that are meaningful and relevant to your research question. Take detailed notes on each article and use a consistent format for capturing all the information each article provides. These notes and the summary table can be done manually, using note cards. However, given the amount of information you will be recording, an electronic file created in a word processing or spreadsheet is more manageable. Examples of fields you may want to capture in your notes include:
Other fields that will be useful when you begin to synthesize the sum total of your research:
This short video demonstrates how a nursing researcher might create a summary table.
Summary tables can be organized by author or by theme, for example:
Author/Year | Research Design | Participants or Population Studied | Comparison | Outcome |
Smith/2010 | Mixed methods | Undergraduates | Graduates | Improved access |
King/2016 | Survey | Females | Males | Increased representation |
Miller/2011 | Content analysis | Nurses | Doctors | New procedure |
For a summary table template, see http://blogs.monm.edu/writingatmc/files/2013/04/Synthesis-Matrix-Template.pdf
An alternate way to organize your articles for synthesis it to create an outline. After you have collected the articles you intend to use (and have put aside the ones you won’t be using), it’s time to identify the conclusions that can be drawn from the articles as a group.
Based on your review of the collected articles, group them by categories. You may wish to further organize them by topic and then chronologically or alphabetically by author. For each topic or subtopic you identified during your critical analysis of the paper, determine what those papers have in common. Likewise, determine which ones in the group differ. If there are contradictory findings, you may be able to identify methodological or theoretical differences that could account for the contradiction (for example, differences in population demographics). Determine what general conclusions you can report about the topic or subtopic as the entire group of studies relate to it. For example, you may have several studies that agree on outcome, such as ‘hands on learning is best for science in elementary school’ or that ‘continuing education is the best method for updating nursing certification.’ In that case, you may want to organize by methodology used in the studies rather than by outcome.
Organize your outline in a logical order and prepare to write the first draft of your literature review. That order might be from broad to more specific, or it may be sequential or chronological, going from foundational literature to more current. Remember, “an effective literature review need not denote the entire historical record, but rather establish the raison d’etre for the current study and in doing so cite that literature distinctly pertinent for theoretical, methodological, or empirical reasons.” ( Milardo, 2015, p. 22 ).
As you organize the summarized documents into a logical structure, you are also appraising and synthesizing complex information from multiple sources. Your literature review is the result of your research that synthesizes new and old information and creates new knowledge.
Literature Reviews: Using a Matrix to Organize Research / Saint Mary’s University of Minnesota
Literature Review: Synthesizing Multiple Sources / Indiana University
Writing a Literature Review and Using a Synthesis Matrix / Florida International University
Sample Literature Reviews Grid / Complied by Lindsay Roberts
Select three or four articles on a single topic of interest to you. Then enter them into an outline or table in the categories you feel are important to a research question. Try both the grid and the outline if you can to see which suits you better. The attached grid contains the fields suggested in the video .
Author Date | Topic/Focus Purpose | Conceptual Theoretical Framework | Paradigm Methods | Context Setting Sample | Findings | Gaps |
Literature Reviews for Education and Nursing Graduate Students Copyright © by Linda Frederiksen is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.
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Paraphrasing and synthesis.
Synthesis is important in scholarly writing as it is the combination of ideas on a given topic or subject area. Synthesis is different from summary. Summary consists of a brief description of one idea, piece of text, etc. Synthesis involves combining ideas together.
Summary: Overview of important general information in your own words and sentence structure. Paraphrase: Articulation of a specific passage or idea in your own words and sentence structure. Synthesis: New interpretation of summarized or paraphrased details in your own words and sentence structure.
In the capstone, writers should aim for synthesis in all areas of the document, especially the literature review. Synthesis combines paraphrased information, where the writer presents information from multiple sources. Synthesis demonstrates scholarship; it demonstrates an understanding of the literature and information, as well as the writer’s ability to connect ideas and develop an argument.
From allan and zed (2012, p. 195).
Supervision, one practice in transactional leadership theory, is especially effective for small business owners. Improved retention not only contributes to an efficient workplace, but it promotes local commercial stability and cultural unity. Other management styles informed by transactional theory can also benefit communities.
Allan and Zed (2012) noted that supervision and other transactional leadership strategies provide advantages for small business owners and their surrounding communities.
This paraphrase DOES:
Synthesis is achieved by comparing and contrasting paraphrased information on a given topic. Discussions of the literature should be focused not on study-by-study summaries (see the Creating a Literature Review Outline SMRTguide). Writers should begin by using comparison language (indicated in bold and highlighted text in the examples below) to combine ideas on a given topic:
Again, the focus of synthesis is to combine ideas on a given topic and for the writer to use that to review the existing literature or support an overall argument (i.e., in the problem statement, rationale and justification for the method, etc.).
For more information and examples on synthesis, paragraph structure, and the MEAL Plan strategy for writing review additional Form and Style resources:
Departments.
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Chapter 9: summarizing study characteristics and preparing for synthesis.
Joanne E McKenzie, Sue E Brennan, Rebecca E Ryan, Hilary J Thomson, Renea V Johnston
Cite this chapter as: McKenzie JE, Brennan SE, Ryan RE, Thomson HJ, Johnston RV. Chapter 9: Summarizing study characteristics and preparing for synthesis. In: Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.4 (updated August 2023). Cochrane, 2023. Available from www.training.cochrane.org/handbook .
Synthesis is a process of bringing together data from a set of included studies with the aim of drawing conclusions about a body of evidence. Most Cochrane Reviews on the effects of interventions will include some type of statistical synthesis. Most commonly this is the statistical combination of results from two or more separate studies (henceforth referred to as meta-analysis) of effect estimates.
An examination of the included studies always precedes statistical synthesis in Cochrane Reviews. For example, examination of the interventions studied is often needed to itemize their content so as to determine which studies can be grouped in a single synthesis. More broadly, synthesis of the PICO (Population, Intervention, Comparator and Outcome) elements of the included studies underpins interpretation of review findings and is an important output of the review in its own right. This synthesis should encompass the characteristics of the interventions and comparators in included studies, the populations and settings in which the interventions were evaluated, the outcomes assessed, and the strengths and weaknesses of the body of evidence.
Chapter 2 defined three types of PICO criteria that may be helpful in understanding decisions that need to be made at different stages in the review:
In this chapter, we focus on the PICO for each synthesis and the PICO of the included studies , as the basis for determining which studies can be grouped for statistical synthesis and for synthesizing study characteristics. We describe the preliminary steps undertaken before performing the statistical synthesis. Methods for the statistical synthesis are described in Chapter 10 , Chapter 11 and Chapter 12 .
Box 9.2.a A general framework for synthesis that can be applied irrespective of the methods used to synthesize results
Set up the comparisons ( and ).
Summarize the characteristics of each study in a ‘Characteristics of included studies’ table (see ), including examining the interventions to itemize their content and other characteristics (Section ). Determine which studies are similar enough to be grouped within each comparison by comparing the characteristics across studies (e.g. in a matrix) (Section ). . Determine what data are available for synthesis (Section ; extraction of data and conversion to the desired format is discussed in and ). Determine if modification to the planned comparisons or outcomes is necessary, or new comparisons are needed, noting any deviations from the protocol plans (Section ; and and ). Synthesize the characteristics of the studies contributing to each comparison (Section ).
Perform a statistical synthesis (if appropriate), or provide structured reporting of the effects (Section 9.5; and , and ). Interpret and describe the results, including consideration of the direction of effect, size of the effect, certainty of the evidence ( ), and the interventions tested and the populations in which they were tested. |
Box 9.2.a provides a general framework for synthesis that can be applied irrespective of the methods used to synthesize results. Planning for the synthesis should start at protocol-writing stage, and Chapter 2 and Chapter 3 describe the steps involved in planning the review questions and comparisons between intervention groups. These steps included specifying which characteristics of the interventions, populations, outcomes and study design would be grouped together for synthesis (the PICO for each synthesis: stage 1 in Box 9.2.a ).
This chapter primarily concerns stage 2 of the general framework in Box 9.2.a . After deciding which studies will be included in the review and extracting data, review authors can start implementing their plan, working through steps 2.1 to 2.5 of the framework. This process begins with a detailed examination of the characteristics of each study (step 2.1), and then comparison of characteristics across studies in order to determine which studies are similar enough to be grouped for synthesis (step 2.2). Examination of the type of data available for synthesis follows (step 2.3). These three steps inform decisions about whether any modification to the planned comparisons or outcomes is necessary, or new comparisons are needed (step 2.4). The last step of the framework covered in this chapter involves synthesis of the characteristics of studies contributing to each comparison (step 2.5). The chapter concludes with practical tips for checking data before synthesis (Section 9.4 ).
Steps 2.1, 2.2 and 2.5 involve analysis and synthesis of mainly qualitative information about study characteristics. The process used to undertake these steps is rarely described in reviews, yet can require many subjective decisions about the nature and similarity of the PICO elements of the included studies. The examples described in this section illustrate approaches for making this process more transparent.
9.3.1 summarize the characteristics of each study (step 2.1).
A starting point for synthesis is to summarize the PICO characteristics of each study (i.e. the PICO of the included studies, see Chapter 3 ) and categorize these PICO elements in the groups (or domains) pre-specified in the protocol (i.e. the PICO for each synthesis). The resulting descriptions are reported in the ‘Characteristics of included studies’ table, and are used in step 2.2 to determine which studies can be grouped for synthesis.
In some reviews, the labels and terminology used in each study are retained when describing the PICO elements of the included studies. This may be sufficient in areas with consistent and widely understood terminology that matches the PICO for each synthesis. However, in most areas, terminology is variable, making it difficult to compare the PICO of each included study to the PICO for each synthesis, or to compare PICO elements across studies. Standardizing the description of PICO elements across studies facilitates these comparisons. This standardization includes applying the labels and terminology used to articulate the PICO for each synthesis ( Chapter 3 ), and structuring the description of PICO elements. The description of interventions can be structured using the Template for Intervention Description and Replication (TIDIeR) checklist, for example (see Chapter 3 and Table 9.3.a ).
Table 9.3.a illustrates the use of pre-specified groups to categorize and label interventions in a review of psychosocial interventions for smoking cessation in pregnancy (Chamberlain et al 2017). The main intervention strategy in each study was categorized into one of six groups: counselling, health education, feedback, incentive-based interventions, social support, and exercise. This categorization determined which studies were eligible for each comparison (e.g. counselling versus usual care; single or multi-component strategy). The extract from the ‘Characteristics of included studies’ table shows the diverse descriptions of interventions in three of the 54 studies for which the main intervention was categorized as ‘counselling’. Other intervention characteristics, such as duration and frequency, were coded in pre-specified categories to standardize description of the intervention intensity and facilitate meta-regression (not shown here).
Table 9.3.a Example of categorizing interventions into pre-defined groups
Definition of (selected) intervention groups from the PICO for each synthesis : “provide[s] motivation to quit, support to increase problem solving and coping skills, and may incorporate ‘transtheoretical’ models of change. … includes … motivational interviewing, cognitive behaviour therapy, psychotherapy, relaxation, problem solving facilitation, and other strategies.”* : “ women receive a financial incentive, contingent on their smoking cessation; these incentives may be gift vouchers. … Interventions that provided a ‘chance’ of incentive (e.g. lottery tickets) combined with counselling were coded as counselling.” : “interventions where the intervention explicitly included provision of support from a peer (including self-nominated peers, ‘lay’ peers trained by project staff, or support from healthcare professionals), or from partners ” (Chamberlain et al 2017). | |||
|
|
|
|
Study 1 | Counselling | Incentive | |
Study 2 | Routine prenatal advice on a range of health issues, from midwives and obstetricians plus: | Counselling | Social support |
Study 3 | Midwives received two and a half days of training on theory of transtheoretical model. Participants received a set of six stage-based self-help manuals ‘Pro-Change programme for a healthy pregnancy’. The midwife assessed each participant’s stage of change and pointed the woman to the appropriate manual. No more than 15 minutes was spent on the intervention. | Counselling | Nil |
* The definition also specified eligible modes of delivery, intervention duration and personnel.
While this example focuses on categorizing and describing interventions according to groups pre-specified in the PICO for each synthesis, the same approach applies to other PICO elements.
Once the PICO of included studies have been coded using labels and descriptions specified in the PICO for each synthesis, it will be possible to compare PICO elements across studies and determine which studies are similar enough to be grouped within each comparison.
Tabulating study characteristics can help to explore and compare PICO elements across studies, and is particularly important for reviews that are broad in scope, have diversity across one or more PICO elements, or include large numbers of studies. Data about study characteristics can be ordered in many different ways (e.g. by comparison or by specific PICO elements), and tables may include information about one or more PICO elements. Deciding on the best approach will depend on the purpose of the table and the stage of the review. A close examination of study characteristics will require detailed tables; for example, to identify differences in characteristics that were pre-specified as potentially important modifiers of the intervention effects. As the review progresses, this detail may be replaced by standardized description of PICO characteristics (e.g. the coding of counselling interventions presented in Table 9.3.a ).
Table 9.3.b illustrates one approach to tabulating study characteristics to enable comparison and analysis across studies. This table presents a high-level summary of the characteristics that are most important for determining which comparisons can be made. The table was adapted from tables presented in a review of self-management education programmes for osteoarthritis (Kroon et al 2014). The authors presented a structured summary of intervention and comparator groups for each study, and then categorized intervention components thought to be important for enabling patients to manage their own condition. Table 9.3.b shows selected intervention components, the comparator, and outcomes measured in a subset of studies (some details are fictitious). Outcomes have been grouped by the outcome domains ‘Pain’ and ‘Function’ (column ‘Outcome measure’ Table 9.3.b ). These pre-specified outcome domains are the chosen level for the synthesis as specified in the PICO for each synthesis. Authors will need to assess whether the measurement methods or tools used within each study provide an appropriate assessment of the domains ( Chapter 3, Section 3.2.4 ). A next step is to group each measure into the pre-specified time points. In this example, outcomes are grouped into short-term (<6 weeks) and long-term follow-up (≥6 weeks to 12 months) (column ‘Time points (time frame)’ Table 9.3.b ).
Variations on the format shown in Table 9.3.b can be presented within a review to summarize the characteristics of studies contributing to each synthesis, which is important for interpreting findings (step 2.5).
Table 9.3.b Table of study characteristics illustrating similarity of PICO elements across studies
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1 | Attention control | BEH | MON | CON | SKL | NAV | Pain | Pain VAS | 1 mth (short), 8 mths (long) | Mean, N / group | Yes | ||
Function | HAQ disability subscale | 1 mth (short), 8 mths (long) | Median, IQR, N / group | Maybe | |||||||||
2 | Acupuncture | BEH | EMO | CON | SKL | NAV | Pain | Pain on walking VAS | 1 mth (short), 12 mths (long) | MD from ANCOVA model, 95%CI | Yes | ||
Function | Dutch AIMS-SF | 1 mth (short), 12 mths (long) | Median, range, N / group | Maybe | |||||||||
4 | Information | BEH | ENG | EMO | MON | CON | SKL | NAV | Pain | Pain VAS | 1 mth (short) | MD, SE | Yes |
Function | Dutch AIMS-SF | 1 mth (short) | Mean, SD, N / group | Yes | |||||||||
12 | Information | BEH | SKL | Pain | WOMAC pain subscore | 12 mths (long) | MD from ANCOVA model, 95%CI | Yes | |||||
3 | Usual care | BEH | EMO | MON | SKL | NAV | Pain | Pain VAS* Pain on walking VAS | 1 mth (short) 1 mth (short) | Mean, SD, N / group | Yes | ||
5 | Usual care | BEH | ENG | EMO | MON | CON | SKL | Pain | Pain on walking VAS | 2 wks (short) | Mean, SD, N / group | Yes | |
6 | Usual care | BEH | MON | CON | SKL | NAV | Pain | Pain VAS | 2 wks (short), 1 mth (short)* | MD, t-value and P value for MD | Yes | ||
Function | WOMAC disability subscore | 2 wks (short), 1 mth (short)* | Mean, N / group | Yes | |||||||||
7 | Usual care | BEH | MON | CON | SKL | NAV | Pain | WOMAC pain subscore | 1 mth (short) | Direction of effect | No | ||
Function | WOMAC disability subscore | 1 mth (short) | Means, N / group; statistically significant difference | Yes | |||||||||
8 | Usual care | MON | Pain | Pain VAS | 12 mths (long) | MD, 95%CI | Yes | ||||||
9 | Usual care | BEH | MON | SKL | Function | Global disability | 12 mths (long) | Direction of effect, NS | No | ||||
10 | Usual care | BEH | EMO | MON | CON | SKL | NAV | Pain | Pain VAS | 1 mth (short) | No information | No | |
Function | Global disability | 1 mth (short) | Direction of effect | No | |||||||||
11 | Usual care | BEH | MON | SKL | Pain | WOMAC pain subscore | 1 mth (short), 12 mths (long) | Mean, SD, N / group | Yes |
BEH = health-directed behaviour; CON = constructive attitudes and approaches; EMO = emotional well-being; ENG = positive and active engagement in life; MON = self-monitoring and insight; NAV = health service navigation; SKL = skill and technique acquisition. ANCOVA = Analysis of covariance; CI = confidence interval; IQR = interquartile range; MD = mean difference; SD = standard deviation; SE = standard error, NS = non-significant. Pain and function measures: Dutch AIMS-SF = Dutch short form of the Arthritis Impact Measurement Scales; HAQ = Health Assessment Questionnaire; VAS = visual analogue scale; WOMAC = Western Ontario and McMaster Universities Osteoarthritis Index. 1 Ordered by type of comparator; 2 Short-term (denoted ‘immediate’ in the review Kroon et al (2014)) follow-up is defined as <6 weeks, long-term follow-up (denoted ‘intermediate’ in the review) is ≥6 weeks to 12 months; 3 For simplicity, in this example the available data are assumed to be the same for all outcomes within an outcome domain within a study. In practice, this is unlikely and the available data would likely vary by outcome; 4 Indicates that an effect estimate and its standard error may be computed through imputation of missing statistics, methods to convert between statistics (e.g. medians to means) or contact with study authors. *Indicates the selected outcome when there was multiplicity in the outcome domain and time frame.
Once the studies that are similar enough to be grouped together within each comparison have been determined, a next step is to examine what data are available for synthesis. Tabulating the measurement tools and time frames as shown in Table 9.3.b allows assessment of the potential for multiplicity (i.e. when multiple outcomes within a study and outcome domain are available for inclusion ( Chapter 3, Section 3.2.4.3 )). In this example, multiplicity arises in two ways. First, from multiple measurement instruments used to measure the same outcome domain within the same time frame (e.g. ‘Short-term Pain’ is measured using the ‘Pain VAS’ and ‘Pain on walking VAS’ scales in study 3). Second, from multiple time points measured within the same time frame (e.g. ‘Short-term Pain’ is measured using ‘Pain VAS’ at both 2 weeks and 1 month in study 6). Pre-specified methods to deal with the multiplicity can then be implemented (see Table 9.3.c for examples of approaches for dealing with multiplicity). In this review, the authors pre-specified a set of decision rules for selecting specific outcomes within the outcome domains. For example, for the outcome domain ‘Pain’, the selected outcome was the highest on the following list: global pain, pain on walking, WOMAC pain subscore, composite pain scores other than WOMAC, pain on activities other than walking, rest pain or pain during the night. The authors further specified that if there were multiple time points at which the outcome was measured within a time frame, they would select the longest time point. The selected outcomes from applying these rules to studies 3 and 6 are indicated by an asterisk in Table 9.3.b .
Table 9.3.b also illustrates an approach to tabulating the extracted data. The available statistics are tabulated in the column labelled ‘Data’, from which an assessment can be made as to whether the study contributes the required data for a meta-analysis (column ‘Effect & SE’) ( Chapter 10 ). For example, of the seven studies comparing health-directed behaviour (BEH) with usual care, six measured ‘Short-term Pain’, four of which contribute required data for meta-analysis. Reordering the table by comparison, outcome and time frame, will more readily show the number of studies that will contribute to a particular meta-analysis, and help determine what other synthesis methods might be used if the data available for meta-analysis are limited.
Table 9.3.c Examples of approaches for selecting one outcome (effect estimate) for inclusion in a synthesis.* Adapted from López-López et al (2018)
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Random selection | Randomly select an outcome (effect estimate) when multiple are available for an outcome domain | Assumes that the effect estimates are interchangeable measures of the domain and that random selection will yield a ‘representative’ effect for the meta-analysis. |
Averaging of effect estimates | Calculate the average of the intervention effects when multiple are available for a particular outcome domain | Assumes that the effect estimates are interchangeable measures of the domain. The standard error of the average effect can be calculated using a simple method of averaging the variances of the effect estimates. |
Median effect estimate | Rank the effect estimates of outcomes within an outcome domain and select the outcome with the middle value | An alternative to averaging effect estimates. Assumes that the effect estimates are interchangeable measures of the domain and that the median effect will yield a ‘representative’ effect for the meta-analysis. This approach is often adopted in Effective Practice and Organization of Care reviews that include broad outcome domains. |
Decision rules | Select the most relevant outcome from multiple that are available for an outcome domain using a decision rule | Assumes that while the outcomes all provide a measure of the outcome domain, they are not completely interchangeable, with some being more relevant. The decision rules aim to select the most relevant. The rules may be based on clinical (e.g. content validity of measurement tools) or methodological (e.g. reliability of the measure) considerations. If multiple rules are specified, a hierarchy will need to be determined to specify the order in which they are applied. |
The previous steps may reveal the need to modify the planned comparisons. Important variations in the intervention may be identified leading to different or modified intervention groups. Few studies or sparse data, or both, may lead to different groupings of interventions, populations or outcomes. Planning contingencies for anticipated scenarios is likely to lead to less post-hoc decision making ( Chapter 2 and Chapter 3 ); however, it is difficult to plan for all scenarios. In the latter circumstance, the rationale for any post-hoc changes should be reported. This approach was adopted in a review examining the effects of portion, package or tableware size for changing selection and consumption of food, alcohol and tobacco (Hollands et al 2015). After preliminary examination of the outcome data, the review authors changed their planned intervention groups. They judged that intervention groups based on ‘size’ and those based on ‘shape’ of the products were not conceptually comparable, and therefore should form separate comparisons. The authors provided a rationale for the change and noted that it was a post-hoc decision.
A final step, and one that is essential for interpreting combined effects, is to synthesize the characteristics of studies contributing to each comparison. This description should integrate information about key PICO characteristics across studies, and identify any potentially important differences in characteristics that were pre-specified as possible effect modifiers. The synthesis of study characteristics is also needed for GRADE assessments, informing judgements about whether the evidence applies directly to the review question (indirectness) and analyses conducted to examine possible explanations for heterogeneity (inconsistency) (see Chapter 14 ).
Tabulating study characteristics is generally preferable to lengthy description in the text, since the structure imposed by a table can make it easier and faster for readers to scan and identify patterns in the information presented. Table 9.3.b illustrates one such approach. Tabulating characteristics of studies that contribute to each comparison can also help to improve the transparency of decisions made around grouping of studies, while also ensuring that studies that do not contribute to the combined effect are accounted for.
Before embarking on a synthesis, it is important to be confident that the findings from the individual studies have been collated correctly. Therefore, review authors must compare the magnitude and direction of effects reported by studies with how they are to be presented in the review. This is a reasonably straightforward way for authors to check a number of potential problems, including typographical errors in studies’ reports, accuracy of data collection and manipulation, and data entry into RevMan. For example, the direction of a standardized mean difference may accidentally be wrong in the review. A basic check is to ensure the same qualitative findings (e.g. direction of effect and statistical significance) between the data as presented in the review and the data as available from the original study.
Results in forest plots should agree with data in the original report (point estimate and confidence interval) if the same effect measure and statistical model is used. There are legitimate reasons for differences, however, including: using a different measure of intervention effect; making different choices between change-from-baseline measures, post-intervention measures alone or post-intervention measures adjusted for baseline values; grouping similar intervention groups; or making adjustments for unit-of-analysis errors in the reports of the primary studies.
The focus of this chapter has been describing the steps involved in implementing the planned comparisons between intervention groups (stage 2 of the general framework for synthesis ( Box 9.2.a )). The next step (stage 3) is often performing a statistical synthesis. Meta-analysis of effect estimates, and its extensions have many advantages. 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. Available summary and synthesis methods, along with the questions they address and examples of associated plots, are described in Table 9.5.a . Chapter 10 and Chapter 11 discuss meta-analysis (of effect estimate) methods, while Chapter 12 focuses on the other statistical synthesis methods, along with approaches to tabulating, visually displaying and providing a structured presentation of the findings. An important part of planning the analysis strategy is building in contingencies to use alternative methods when the desired method cannot be used.
Table 9.5.a Overview of available methods for summary and synthesis
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| Text/Tabular | Vote counting | Combining P values | Summary of effect estimates | Pairwise meta-analysis | Network meta-analysis | Subgroup analysis/meta-regression |
| Narrative summary of evidence presented in either text or tabular form | Is there any evidence of an effect? | Is there evidence that there is an effect in at least one study? | What is the range and distribution of observed effects? | What is the common intervention effect? (fixed-effect model) What is the average intervention effect? (random effects model) | Which intervention of multiple is most effective? | What factors modify the magnitude of the intervention effects? |
| Forest plot (plotting individual study effects without a combined effect estimate) | Harvest plot Effect direction plot | Albatross plot | Box and whisker plot Bubble plot | Forest plot | Forest plot Network diagram Rankogram plots | Forest plot Box and whisker plot Bubble plot |
Authors: Joanne E McKenzie, Sue E Brennan, Rebecca E Ryan, Hilary J Thomson, Renea V Johnston
Acknowledgements: Sections of this chapter build on Chapter 9 of version 5.1 of the Handbook , with editors Jonathan Deeks, Julian Higgins and Douglas Altman. We are grateful to Julian Higgins, James Thomas and Tianjing Li for commenting helpfully on earlier drafts.
Funding: JM is supported by an NHMRC Career Development Fellowship (1143429). SB and RR’s positions are supported by the NHMRC Cochrane Collaboration Funding Program. HT is funded by the UK Medical Research Council (MC_UU_12017-13 and MC_UU_12017-15) and Scottish Government Chief Scientist Office (SPHSU13 and SPHSU15). RJ’s position is supported by the NHMRC Cochrane Collaboration Funding Program and Cabrini Institute.
Chamberlain C, O’Mara-Eves A, Porter J, Coleman T, Perlen SM, Thomas J, McKenzie JE. Psychosocial interventions for supporting women to stop smoking in pregnancy. Cochrane Database of Systematic Reviews 2017; 2 : CD001055.
Hollands GJ, Shemilt I, Marteau TM, Jebb SA, Lewis HB, Wei Y, Higgins JPT, Ogilvie D. Portion, package or tableware size for changing selection and consumption of food, alcohol and tobacco. Cochrane Database of Systematic Reviews 2015; 9 : CD011045.
Kroon FPB, van der Burg LRA, Buchbinder R, Osborne RH, Johnston RV, Pitt V. Self-management education programmes for osteoarthritis. Cochrane Database of Systematic Reviews 2014; 1 : CD008963.
López-López JA, Page MJ, Lipsey MW, Higgins JPT. Dealing with effect size multiplicity in systematic reviews and meta-analyses. Research Synthesis Methods 2018; 9 : 336–351.
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Synthesis essay generator.
A Synthesis Essay is a sophisticated form of writing that requires the integration of various sources and perspectives. Our resource provides a comprehensive look into this writing style, complete with insightful essay examples . These examples demonstrate how to effectively combine information from different texts, crafting a cohesive and well-argued narrative. Ideal for students and professionals alike, this guide will help you master the art of synthesizing diverse viewpoints into a single, compelling argument in your essays.
A synthesis essay is a written discussion that draws on one or more sources. It involves combining information from various sources to make a cohesive argument or presentation on a specific topic. This type of essay requires the writer to analyze information, derive insights, and present them in a structured and coherent manner. The key to a successful synthesis essay is not just summarizing the sources but integrating them to create a new perspective or argument. Writers must cite their sources accurately, showing how each piece of information contributes to and supports their thesis or main argument. Synthesis essays are common assignments in academic settings, especially in higher education, testing students’ abilities to research, evaluate, synthesize complex information, and articulate their findings effectively.
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Essays depict the standpoints of a writer on a certain topic or issue. An essay often presents a point and either convinces a reader to agree or disagree to a certain subject matter. An effective essay does what it is intended to do when a reader is convinced of the writer’s stand point. Common college essays include writing a synthesis essay. Examples of synthesis essay can be found in the page and made available for your reference. The examples can also be downloaded via the download link button below the sample in order to get a closer look.
Synthesis involves combining different pieces of information to form a cohesive understanding. For instance, if you gather insights from various experts about the impact of climate change and weave them into a comprehensive article or report, you are performing synthesis. This process is distinct from merely summarizing since it requires critical thinking to integrate ideas and form new connections, rather than just listing details or differences like in comparison and contrast.
It helps in presenting your argument clearly and persuasively. Here’s a typical structure for a synthesis essay:
Hook: Start with an engaging sentence to grab the reader’s attention. Background Information: Provide some context or background for the topic you will be discussing. Thesis Statement: Present your main argument or position on the topic, clearly stating how the different sources will support your thesis.
Each body paragraph should focus on a specific point or aspect of your thesis, integrating multiple sources to support each point.
Topic Sentence: Introduce the main idea of the paragraph that supports your thesis. Evidence and Analysis: Include information from your sources as evidence to back up your point. This could be quotations, summaries, or paraphrased material. Analyze the evidence, showing how it supports your argument. Synthesis: Discuss how the evidence from different sources relates to each other and to your thesis. This is where you combine (synthesize) the information to build your argument. Concluding Sentence: Summarize the main point of the paragraph and how it supports your overall thesis.
Consider including a paragraph that addresses potential counterarguments or opposing views. Refute these arguments and show how your thesis still stands.
Summary: Briefly summarize the key points you made in your body paragraphs. Thesis Restatement: Restate your thesis in a new way, reflecting the insights and arguments developed in your essay. Final Thoughts: Offer some final thoughts on the topic, possibly suggesting areas for further research or implications of your argument.
Include a list of all sources cited in your essay, formatted according to the required academic style guide (e.g., APA, MLA, Chicago).
Writing a synthesis essay involves gathering information from various sources and merging these insights to support a central thesis or argument. Here’s a step-by-step guide:
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Synthesis essays are used in different papers. Point is, a synthesis essay is used in creating a relationship between different sources and getting supplemental information from them to support the writer’s view point or make a coherent plan or proposal templates .
Essay examples in doc seen on the page offer more information regarding an essay. They are made available for your review by clicking on the individual link buttons under each sample.
Writing a synthesis essay is a pivotal skill for students, particularly in high school and college. This type of essay goes beyond simple summarization and requires critical thinking, a skill essential in essay writing. Here are some key tips to help students craft an effective synthesis essay:
The time to write a synthesis essay varies, typically ranging from several hours to a few days. This includes time for research, planning, writing, and revising. Effective time management and early start can help streamline the process.
Generally, avoid using “I” in a synthesis essay, especially in academic settings. Aim for an objective tone by presenting evidence and analysis without personal bias. Exceptions may apply if personal reflection or perspective is explicitly requested.
Writing a good synthesis essay involves thorough research, understanding your sources, creating a strong thesis, organizing your points logically, and synthesizing evidence from various sources to support your argument. Clear writing and proper citation are also crucial.
Start a synthesis essay with an engaging hook, followed by brief background information on your topic. Clearly state your thesis, outlining the main argument or perspective your essay will support, setting the stage for your synthesis.
Using first-person in a synthesis essay is generally discouraged in formal academic writing. It’s better to maintain an objective tone. However, if the assignment guidelines allow or if reflecting on personal experience, it may be acceptable.
Yes, you can directly quote in a synthesis essay to support your points, but do so sparingly. Focus on synthesizing information by paraphrasing and analyzing evidence from your sources. Ensure all quotes are properly cited according to the required citation style.
In conclusion, synthesis essays are key in developing critical thinking and analytical skills. For further guidance on writing synthesis essays, Colorado State University provides an in-depth guide , which can be accessed here. This resource offers valuable insights into the process of synthesizing information from diverse sources.
Text prompt
Write a Synthesis Essay on the integration of technology in education.
Create a Synthesis Essay comparing different leadership styles.
Analyze the impact of technology on education through synthesis.
Synthesize views on climate change from multiple sources.
Compare traditional vs. online learning in a synthesis essay.
Discuss the role of social media in politics synthesis.
Explore mental health effects of social isolation via synthesis.
Evaluate renewable energy sources' viability in a synthesis essay.
Synthesize historical perspectives on women's rights movement.
Examine the effects of globalization on culture through synthesis.
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Step 1 Organize your sources. Step 2 Outline your structure. Step 3 Write paragraphs with topic sentences. Step 4 Revise, edit and proofread. When you write a literature review or essay, you have to go beyond just summarizing the articles you've read - you need to synthesize the literature to show how it all fits together (and how your own ...
Example: Effective synthesis 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.
Describing how sources converse each other. Organizing similar ideas together so readers can understand how they overlap. Synthesis helps readers see where you add your own new ideas to existing knowledge. Critiquing a source. Simply comparing and contrasting sources. A series of summaries. Direct quotes without using your own voice.
Argumentative syntheses seek to bring sources together to make an argument. Both types of synthesis involve looking for relationships between sources and drawing conclusions. In order to successfully synthesize your sources, you might begin by grouping your sources by topic and looking for connections. For example, if you were researching the ...
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.
Citation tools can help organise, format, and insert citations with ease. Examples. Zotero: A free, open-source tool that helps you collect, organise, cite, and share research. Mendeley: A reference manager and academic social network that can help you organise your research, collaborate with others online, and discover the latest developments.
Synthesis Matrix. A synthesis matrix helps you record the main points of each source and document how sources relate to each other. After summarizing and evaluating your sources, arrange them in a matrix or use a citation manager to help you see how they relate to each other and apply to each of your themes or variables. By arranging your ...
The synthesis matrix is a chart that allows a researcher to sort and categorize the different arguments presented on an issue. Across the top of the chart are the spaces to record sources, and along the side of the chart are the spaces to record the main points of argument on the topic at hand. As you examine your first source, you will work ...
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 ...
A synthesis matrix visually represents your research by organizing your sources by themes: Theme #1 Theme #2 Theme #3; Source #1 : Source #2 : Source #3 : Sample Synthesis Matrix. Example provided by Ashford University Writing Center. << Previous: How to Review the Literature; Next: 7. Write literature review >>
Research synthesis is the overarching term we use to describe approaches to combining, aggregating, ... 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. ... open-ended format, and may shift and change through the process.
Synthesis is an important element of academic writing, demonstrating comprehension, analysis, evaluation and original creation. With synthesis you extract content from different sources to create an original text. While paraphrase and summary maintain the structure of the given source (s), with synthesis you create a new structure.
Structuring your synthesis essay by topic works best for more complicated ideas with different aspects that should be explored individually. Example outline: I. Introduction A. Thesis statement. II. Topic 1 A. Source A discussing Topic 1 1. A point or piece of evidence/data from Source A about Topic 1 2.
A literature review is not an annotated bibliography, organized by title, author, or date of publication. Rather, it is grouped by topic to create a whole view of the literature relevant to your research question. Figure 7.1. Your synthesis must demonstrate a critical analysis of the papers you collected as well as your ability to integrate the ...
Synthesizing qualitative research has become a useful and popular tool to inform policy- and evidence-based health care in recent years (Noyes, Popay, Pearson, Hannes, & Booth, 2008; Pope & Mays, 2006a).Systematic reviews can prove invaluable for busy practitioners as they combine results from many studies, provide up-to-date summarized evidence, and disseminate them in an unbiased and ...
Qualitative research synthesis is a diverse set of methods for combining the data or the results of multiple studies on a topic to generate new knowledge, theory and applications. Use of qualitative research synthesis is rapidly expanding across disciplines. Aggregative and interpretive models of qualitative research synthesis are defined and ...
The writing process for composing a good synthesis essay requires curiosity, research, and original thought to argue a certain point or explore an idea. Synthesis essay writing involves a great deal of intellectual work, but knowing how to compose a compelling written discussion of a topic can give you an edge in many fields, from the social sciences to engineering.
Get multiple synthesis essay examples covering a range of topics. Learn how to craft an introduction, thesis, outlines, or write your entire synthesis essay. ... When it comes to a synthesis essay, it is all about the research. You must take a stand, but that position needs to be backed up by credible sources. ... Formatting a Synthesis Essay.
When asked to synthesize sources and research, many writers start to summarize individual sources. However, this is not the same as synthesis. In a summary, you share the key points from an individual source and then move on and summarize another source. In synthesis, you need to combine the information from those multiple sources and add your ...
in in the source material. 2. Writing a Synthesis PaperOnce you have completed a grid of common points, you. an begin writing your paper. When you begin to write the body of the paper, you m. want to follow these steps: Select one common point and divide it into sub-topics that represen. unishment does deter crime, researchers' impressions ...
Although Mehmad (2012) suggested X, O'Donnell (2013) recommended a different approach. Again, the focus of synthesis is to combine ideas on a given topic and for the writer to use that to review the existing literature or support an overall argument (i.e., in the problem statement, rationale and justification for the method, etc.).
Box 9.2.a provides a general framework for synthesis that can be applied irrespective of the methods used to synthesize results. Planning for the synthesis should start at protocol-writing stage, and Chapter 2 and Chapter 3 describe the steps involved in planning the review questions and comparisons between intervention groups. These steps included specifying which characteristics of the ...
A synthesis essay is a written discussion that draws on one or more sources. It involves combining information from various sources to make a cohesive argument or presentation on a specific topic. This type of essay requires the writer to analyze information, derive insights, and present them in a structured and coherent manner.