Metasynthesis Of Qualitative Research

What is Metasynthesis?

Metasynthesis is a type of systematic review which synthesizes qualitative research findings from individual studies to generate new interpretations and advance a field of knowledge.

Metasynthesis is considered original research and uses previously published qualitative research reports as its database.

Although considered analogous to quantitative meta-analysis, metasynthesis has developed its own dimensions and directions.

There is, however, lively debate and disagreement regarding the appropriate methods for conducting metasynthesis and the types of conclusions drawn.

Purpose

Metasynthesis interprets, evaluates, and presents the similar and different aspects of the findings of qualitative studies in a particular field.

The outcomes often include theory development, higher-level abstraction, generalizability, and new knowledge development.

When is Metasynthesis Appropriate?

Qualitative metasynthesis is appropriate to answer research questions about human experiences when multiple qualitative studies on the topic are available.

The goal is to use a structured, transparent, and auditable method to advance knowledge in a field of study.

Qualitative metasynthesis is best suited to reinterpret meaning and generate new theories or explanations of interventions based on findings from multiple high-quality qualitative studies.

In This Article:

Conducting Qualitative Metasynthesis Research

Step 1: Formulating a Research Question for Qualitative Metasynthesis

The first step in any research project, including a qualitative metasynthesis, is posing a question. Although this sounds straightforward, it is a critical and nuanced process.

This question should be broad enough to be interesting but focused enough to be manageable.

As the researcher becomes more familiar with the body of literature, they can refine their question to guide them toward meaningful decisions about what to include in the metasynthesis.

Familiarize yourself with the literature: To begin deciding what you are looking for, you need to become familiar with the existing literature on your topic of interest.
Develop a flexible yet determined research question: As you engage with the literature, your goal is to develop a research question that is “both flexible and determined.” This means that the research question is flexible enough to allow you to approach most of the research literature within the area you wish to explore. At the same time, it needs to be specific enough that your eventual metasynthesis contributes something novel and does not simply reproduce a “catalogue of what is already known.”
The Research Question as Compass: The research question in this type of study is best understood “more like a compass than an anchor” because it helps guide you through the existing research toward meaningful decisions about what to include and exclude.

Examples

Metasynthesis research questions often seek to develop new theoretical understandings of human experiences by synthesizing findings from multiple qualitative studies.

What inductive theory can be built regarding clients’ experiences of their conjoint couple or family therapy?
The purposes of this systematic review and metasynthesis are first to synthesize qualitative studies documenting men’s breast cancer narratives into an empirically based explanatory framework, and second to compare men’s experience of breast cancer to women.
The goal of the current research is to synthesize qualitative research that focuses on the role of masculinities in close male friendships. Our analysis is guided by the following research question: How are masculine norms enacted within boys’ and men’s close friendships?
What are the potential common themes and psychological phenomena underpinning male suicide risk and recovery as perceived and experienced by men who are suicidal, and people bereaved by male suicide?

Step 2: Conducting a Systematic Literature Search

The next step is to conduct a systematic search of the qualitative literature using clearly defined search terms and databases.

This may include searching electronic databases, reviewing reference lists of relevant articles, and contacting experts in the field.

It’s important to be transparent about the search strategy and document all decisions for auditability. The goal is to identify all potentially relevant studies for consideration.

Both STARLITE (Standards for Reporting Literature searches) and PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) provide appropriate guidance for reporting qualitative literature searches.

Information Sources

To capture as much available data within certain parameters, an inclusive search strategy is recommended.

Specify all databases, registers, websites, organisations, reference lists and other sources searched or consulted to identify studies. Specify the date when each source was last searched or consulted.
PRISMA 2020 Checklist

An exhaustive, systematic search strategy is developed with the assistance of an expert librarian.

Databases: Searches should include seven key databases: CINAHL, Medline, APA PsycArticles, Psychology and Behavioral Sciences Collection, APA PsycInfo, SocINDEX with Full Text, and Web of Science: Core Collections.
Grey Literature: In addition to databases, forensic or ‘expansive’ searches can be conducted. This includes: conference proceedings, unpublished reports, theses, ongoing clinical trial databases, searches by names of authors of relevant publications.
Citation Searching: Reference lists often lead to highly cited and influential papers in the field, providing valuable context and background information for the review.

Other databases may also be worth searching, depending on the topic.

Search Strategy

Present the full search strategies for all databases, registers and websites, including any filters and limits used.
PRISMA 2020 Checklist

Keywords: Search terms should be relevant to the research questions, key variables, participants, and research design. Derivatives of the key variables AND “qualitative OR mixed-methods” can be used. Searches should include indexed terms, titles, and abstracts. Additionally, each database has specific indexed terms, so a targeted search strategy must be created for each database.
Synonyms: These are words or phrases with similar meanings to the keywords, as authors may use different terms to describe the same concepts. Including synonyms helps cover variations in terminology and increases the chances of finding all relevant studies. For example, a drug intervention may be referred to by its generic name or by one of its several proprietary names.
Truncation symbols: These broaden the search by capturing variations of a keyword. They function by locating every word that begins with a specific root. For example, if a user was researching interventions for smoking, they might use a truncation symbol to search for “smok*” to retrieve records with the words “smoke,” “smoker,” “smoking,” or “smokes.” This can save time and effort by eliminating the need to input every variation of a word into a database.
Boolean operators: The use of Boolean operators (AND/OR/NEAR/NOT) helps to combine these terms effectively, ensuring that the search strategy is both sensitive and specific. For instance, using “AND” narrows the search to include only results containing both terms, while “OR” expands it to include results containing either term.

When conducting these searches, it is important to combine browsing of texts (publications) with periods of more focused systematic searching. This iterative process allows the search to evolve as the review progresses.

Search guidance changes as databases and tools are updated, so it is worth checking current sources when planning a search.

Step 3: Screening and Selecting Appropriate Research Articles

Once the literature search is complete, the next step is to screen and select the studies that will be included in the metasynthesis.

This involves carefully reviewing each study to determine its relevance to the research question and its methodological quality.

The goal is to identify studies that are both relevant to the research question and of sufficient quality to contribute to a meaningful synthesis.

Eligibility criteria

Specify the inclusion and exclusion criteria for the review.
PRISMA 2020 Checklist

Eligibility criteria are a set of predefined characteristics used to determine which studies will be included or excluded from a metasynthesis.

These criteria are based on the research question and the specific goals of the metasynthesis. Clearly defining and specifying the eligibility criteria is essential to ensure that the included studies are relevant, appropriate, and able to contribute to the metasynthesis findings.

For example, researchers might choose to focus on a specific population group, a particular time period, or studies employing specific qualitative research methods.

When specifying the inclusion and exclusion criteria, consider the following aspects:

Research design: Specify the types of qualitative research designs that will be included, such as phenomenology, grounded theory, ethnography, or case studies. Determine whether mixed-method studies with a qualitative component will be included.
Participants or population: Define the characteristics of the participants or population of interest, such as age, gender, health condition, or socio-economic status.
Phenomena of interest: Clearly state the specific phenomena, experiences, or concepts that the metasynthesis aims to explore. For instance, if the metasynthesis is exploring the experiences of patients with chronic illnesses, the phenomena of interest might include coping mechanisms, social support systems, or perceptions of healthcare services.
Setting or context: Specify the setting or context in which the studies should have been conducted, such as healthcare settings, community settings, or specific geographical locations. This helps ensure that the included studies are contextually relevant to the research question.
Language: Determine which languages will be included in the metasynthesis, considering the language skills of the research team and the availability of resources for translation.
Time frame: Specify the time period within which the studies should have been conducted or published. For example, when studying a topic influenced by societal changes or technological advancements, researchers might choose a more recent timeframe to capture contemporary perspectives.
Publication status: Decide whether only published studies will be included or if unpublished works, such as dissertations or conference proceedings, will also be considered.
Methodological quality: Specify any criteria related to the methodological quality of the studies, such as the use of specific data collection or analysis techniques, or the assessment of study quality using established tools.

Selection Process

Specify the methods used to decide whether a study met the inclusion criteria of the review, including how many reviewers screened each record and each report retrieved, whether they worked independently, and if applicable, details of automation tools used in the process.
PRISMA 2020 Checklist

The selection process in qualitative metasynthesis involves multiple reviewers to ensure rigor and reliability.

Two reviewers should independently screen titles and abstracts, removing duplicates and irrelevant studies based on predefined inclusion and exclusion criteria.

Initial screening of titles and abstracts: After applying a strategy to search the literature, the next step involves screening the titles and abstracts of the identified articles against the predefined inclusion and exclusion criteria. During this initial screening, reviewers aim to identify potentially relevant studies while excluding those clearly outside the scope of the review. It is crucial to prioritize over-inclusion at this stage, meaning that reviewers should err on the side of keeping studies even if there is uncertainty about their relevance. This cautious approach helps minimize the risk of inadvertently excluding potentially valuable studies.
Retrieving and assessing full texts: For studies which a definitive decision cannot be made based on the title and abstract alone, reviewers need to obtain the full text of the articles for a comprehensive assessment against the predefined inclusion and exclusion criteria. This stage involves meticulously reviewing the full text of each potentially relevant study to determine its eligibility definitively.
Resolution of Disagreements: In cases of disagreement between reviewers regarding a study’s eligibility, a predefined strategy involving consensus-building discussions or arbitration by a third reviewer should be in place to reach a final decision. This collaborative approach ensures a fair and impartial selection process, further strengthening the review’s reliability.

Step 4: Evaluating the Quality of Studies

Data collection process

Specify the methods used to collect data from reports, including how many reviewers collected data from each report, whether they worked independently, any processes for obtaining or confirming data from study investigators, and if applicable, details of automation tools used in the process.
PRISMA 2020 Checklist

To gather data for the metasynthesis, researchers identify themes and findings already presented in the qualitative research reports included in the review.

Data extraction focuses on information relevant to the research question, such as risk or recovery factors related to a particular phenomenon.

Data is extracted from the findings, discussion, and conclusions of each primary study, including participant quotes and the authors’ interpretations.

It can be useful to focus on the authors’ interpretations of findings rather than individual participant quotes, as the latter lacks the full context of the original data.

Quality Appraisal Tools

Both the CASP and QARI tools give reviewers a structured way to judge the quality of the qualitative studies they are considering for inclusion. Several tools are available:

CASP: The Critical Appraisal Skills Programme (CASP) checklist judges study quality. The Cochrane Collaboration, a global network of researchers, professionals and patients, recommends it for metasyntheses.
QARI: The Qualitative Appraisal and Review Instrument (QARI) was developed by the Joanna Briggs Institute (JBI), an international research organisation promoting evidence-based healthcare.
Other tools: The Consolidated Criteria for Reporting Qualitative Research (COREQ) and the Evaluation Tool for Qualitative Studies (ETQS) are also used to appraise study quality.

Step 5: Extract Data, Including as Themes, Concepts, or Quotes

This step is critical, as it lays the foundation for the subsequent analysis and synthesis of the findings.

The focus during data extraction is identifying and documenting key concepts, themes, or interpretations from each study relevant to the metasynthesis research question.

The following strategies can be used for data extraction:

Develop a data extraction form: Create a standardized form or template to consistently record the relevant information from each study, such as the study’s aim, participants, setting, data collection methods, analysis techniques, and key findings. This structured approach enhances the organization and management of extracted data.
Identify relevant data: Read through each study carefully, focusing on the results, discussion, and conclusion sections to identify the main themes, concepts, or interpretations that are pertinent to the metasynthesis research question.
Use a coding framework: Develop a coding framework based on the research question and the initial reading of the studies. This framework can include pre-defined codes or categories, as well as space for emergent codes that arise during the data extraction process.
Extract verbatim quotes: Identify and extract direct quotations from participants or authors that illustrate the key themes or concepts. These quotes can be used to support the metasynthesis findings and provide rich, contextual data.
Capture author interpretations: Extract the study authors’ interpretations and explanations of the findings, as these can provide valuable insights and contribute to the metasynthesis.
Maintain a clear audit trail: Document the data extraction process, including any decisions made, to ensure transparency and reproducibility. Maintaining a clear record of the process allows for scrutiny and enhances the credibility of the metasynthesis findings.
Collaborate with other researchers: Collaboration in data extraction is valuable, as it ensures consistency, minimizes bias, and captures a diverse range of perspectives. Multiple researchers can cross-check the extracted data, ensuring accuracy and reducing the risk of individual biases.

Automation Tools

The extracted data should be organised to help the analysis and synthesis that follows. A spreadsheet, qualitative data analysis software, or a structured summary table can all serve this purpose.

The tool matters less than the habit.

Researchers might record it in a Microsoft Excel spreadsheet, or use qualitative analysis software such as NVivo to organise and code the extracted information. This helps manage data from multiple sources.

Extraction should balance capturing the relevant data with keeping the context and richness of the original studies. The process is iterative, refined as the metasynthesis progresses and new insights emerge.

Step 6: Synthesizing Findings

Develop a new interpretation: Synthesize the findings to generate a new understanding or theory that goes beyond the individual studie

The goal of the synthesis step is to produce a meaningful, integrated understanding of the phenomena that goes beyond the sum of its parts.

This involves a thorough analysis of the contextual factors influencing the original studies and carefully considering the relationships between different concepts and themes.

Moving Beyond Description: The most impactful qualitative metasyntheses go beyond simply describing the findings of primary studies. They aim to generate new interpretations, develop theories, or offer practical implications for policy and practice.
Diversity of Metasynthesis Approaches: These approaches, including meta-ethnography, thematic synthesis, grounded theory, and others, each offer different ways of integrating and interpreting qualitative findings. The choice of approach depends on the research question, the nature of the available studies, and the aims of the review.

The synthesis process is iterative. Reaching a coherent, well-supported interpretation of the data often takes several rounds of analysis and refinement.

While there’s no standardized protocol, the qualitative synthesis methods often borrow from grounded theory, meta-ethnography, and meta-study:

Meta-ethnography

Meta-ethnography compares conceptual data across qualitative studies to build ideas that go beyond what any single study could show alone. Its aim is new interpretations, not summary.

This sets it apart from methods that aggregate findings without building new understanding. The core move is translation. It means carefully analysing the interpretations the primary studies’ authors already made, including their concepts and themes.

The process preserves each study’s original context and meaning, while still allowing comparison and new insight. Noblit and Hare, who developed meta-ethnography, outlined a seven-stage process for carrying it out.

Grounded Theory

By applying grounded theory to a qualitative metasynthesis, researchers can move beyond a simple aggregation of findings and generate a higher-level understanding of the phenomena being studied.

This approach allows for the development of new theories or the refinement of existing ones based on the collective findings of multiple qualitative studies.

When using grounded theory in a qualitative metasynthesis, the researcher follows these general steps:

Open coding: Carefully read through the findings and identify key concepts, themes, and categories that emerge from the data.
Constant comparison: Continuously compare the emerging concepts and categories to identify similarities, differences, and relationships between them.
Axial coding: Establish connections between the categories and subcategories, developing a more comprehensive understanding of the central phenomena.
Selective coding: Identify the core category or categories that represent the main theme(s) of the metasynthesis and systematically relate them to other categories.
Theory development: Develop a theoretical framework that explains the relationships between the categories and provides a coherent understanding of the phenomena under study.

Meta-Study

A meta-study systematically analyses a collection of related studies to find common themes, patterns and conclusions across them. Applied to a metasynthesis, it can further synthesise and integrate findings already identified during the metasynthesis process.

The researcher moves beyond the individual findings and themes drawn from the primary sources. The goal is a coherent, higher-level understanding.

This means examining the relationships, patterns and connections between the different themes and concepts. Doing so builds a fuller understanding of the research topic.

The synthesis process in a meta-study of metasyntheses may involve:

Identifying overarching themes: The researcher looks for higher-order themes or concepts that encompass and connect the various findings and themes identified in the coding process. These overarching themes represent the core ideas or principles that emerge from the collective findings of the included metasyntheses.
Developing a theoretical framework: Based on the overarching themes and the relationships between them, the researcher may develop a new theoretical framework or model that explains the phenomena under study. This framework should integrate the key findings and insights from the included metasyntheses and provide a novel, comprehensive understanding of the research topic.
Comparing with existing literature: The researcher may also compare the emerging themes and theoretical framework with existing literature and theories in the field. This process can help to situate the findings within the broader context of the discipline and highlight how the meta-study contributes to or challenges current understanding.
Considering implications: As part of the synthesis process, the researcher may also consider the practical, methodological, and theoretical implications of the findings. This may involve discussing how the findings can inform policy, practice, or future research in the field.

Step 7: Present Synthesis of Findings Across Studies

When presenting the synthesis of findings across studies, consider the audience and use visuals such as charts, tables, and figures to represent the findings graphically.

Numbers can also be used, but it is important to present rich descriptions of the data, quotations, and the development of the conceptual model or working hypotheses drawn from the integration.

Disseminate the results: Share the metasynthesis findings through publications, presentations, or other means to contribute to the broader understanding of the topic.

The presentation of findings should include:

Introduction: Describe the problem and purpose.
Methods: Explain the sampling strategy, techniques and tools for appraising and comparing reports, classifying and synthesizing findings, and validity procedures.
Results: Present the findings from the analysis and synthesis.
Discussion: Explain the significance of the findings and connect findings back to the existing literature. Include limitations, strengths, and implications of the findings for research, practice, and policy.

Reporting Guidelines

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is a widely used reporting guideline, but it was built for systematic reviews and meta-analyses of quantitative studies.

Some of it still applies here. Guidance on reporting literature searches and selection strategies also works for qualitative evidence synthesis. This is not the whole story. PRISMA does not address the specific reporting needs of methods like meta-ethnography.

A reporting guideline built specifically for meta-ethnography, eMERGe (enhancing Meta-Ethnography Reporting Guidance), answers that need. The method is different from PRISMA.

It uses interpretive methods to translate findings from multiple studies into a new, overarching understanding of a phenomenon.

Meta-ethnography’s more complex analytical synthesis phases go beyond generic guidelines like ENTREQ. That gap is real. A dedicated guideline, eMERGe, was built to close it, improving the transparency and completeness of meta-ethnography reporting.

Ensuring Validity and Reliability

Ensuring the validity and reliability of a metasynthesis is crucial for producing high-quality, trustworthy findings that can contribute to the advancement of knowledge in a field.

1. Transparency and Rigor in Reporting

Transparency in reporting is essential for a metasynthesis to be valid and reliable. Researchers should give a clear, detailed account of their methods: the search strategy, the inclusion and exclusion criteria, the quality appraisal process, and the data analysis techniques.

This transparency allows other researchers to assess the rigor of the metasynthesis and replicate it if needed. The decision-making matters too. Researchers should be transparent about how they resolved disagreements among the team, and how they handled conflicting findings across studies.

A clear audit trail of the whole process makes the findings more credible and trustworthy.

Strategies for Achieving Transparency and Rigor:

Maintaining an Audit Trail: Documenting all decisions made throughout the research process, including rationales for inclusion and exclusion criteria, data analysis techniques, and interpretation of findings.
Negotiating Consensus Among the Research Team: Engaging in discussions and reaching agreement on key decisions to mitigate the influence of individual biases.
Consulting with Experts: Seeking input from information retrieval specialists, methodological experts, and practitioners to enhance the rigor and relevance of the metasynthesis.
Contacting Study Authors (If Needed): Communicating with authors of the primary studies to clarify ambiguous findings or gather missing information.
Using Reporting Guidelines: Following established reporting guidelines, such as ENTREQ (Enhancing Transparency in Reporting the Synthesis of Qualitative Research) or PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), helps ensure comprehensive and transparent reporting.
Publishing the Protocol: Publishing the study protocol in a publicly accessible repository, like PROSPERO (Prospective Register of Systematic Reviews), promotes transparency and allows for scrutiny of the research plan.

2. Use of Established Methods

Using established, well-recognised methods helps ensure a metasynthesis is valid and reliable. Researchers should follow a systematic approach, such as the steps set out by Noblit and Hare (1988) or the Joanna Briggs Institute (JBI) methodology for qualitative synthesis.

These methods give the synthesis a structured framework, covering the research question, study search and selection, quality appraisal, data extraction and analysis, and presenting the findings. Each stage has its own guidelines.

By adhering to these established methods, researchers keep their metasynthesis rigorous and standardised, which strengthens its validity and reliability.

3. Reflexivity of Researchers

Reflexivity is critical to a metasynthesis’s validity. Researchers should be aware of their own background, assumptions and biases, and of how these may shape their interpretations.

Engaging in reflexivity involves continuously examining one’s own role in the research process, questioning one’s assumptions, and considering alternative explanations for the findings.

This is not always comfortable.

Researchers should document their reflexive processes, such as keeping a reflexive journal or engaging in peer debriefing, to enhance the transparency and trustworthiness of the metasynthesis.

Reflexivity also involves being open to alternative interpretations and seeking out disconfirming evidence that may challenge one’s initial conclusions.

By actively engaging in reflexivity throughout the synthesis process, researchers can minimize the influence of their own biases. Reflexivity keeps findings grounded in data, not preconceptions.

Considerations for Reflexivity:

Study order: The order in which studies were incorporated into the metasynthesis.
Selection and sampling: How study selection and sampling influenced the findings.
Number of studies: A large volume of data may reduce the depth of analysis.
Context: The context of the metasynthesis.
Methodological changes: Any modifications made to Noblit and Hare’s (1988) original methodology.

Reviewers conducting a metasynthesis should explicitly describe the influence of these factors on their conclusions.

For instance, a large number of studies can be synthesised in smaller clusters. Doing so helps reviewers preserve conceptual richness and stay grounded in the data.

Contemporary Research

Since the mid-2010s, work in this area has shifted from establishing that qualitative findings can be synthesised toward making that synthesis process itself transparent and reproducible. One paper marks that shift.

Aim: Lewin et al. (2018) set out to give qualitative evidence an equivalent of GRADE, the system used to rate quantitative evidence. Their goal was simple: rate confidence transparently.

Method: Between 2015 and 2017, the authors worked iteratively through literature review, expert consultation and workshop feedback. They tested GRADE-CERQual across qualitative evidence syntheses in health and social care.

Results: GRADE-CERQual rates each review finding on four components: methodological limitations, coherence with the data, adequacy of the supporting data, and relevance to the review question. The four combine into one confidence rating. It ranges from high to very low.

Conclusion: CERQual makes an implicit judgement explicit, which is why guideline panels adopted it so readily. The paper has since been cited well over 800 times. It does not resolve whether reinterpreted qualitative findings can be graded for trustworthiness the way a quantitative effect size can.

A second strand of work closes a different gap. Noblit and Hare’s (1988) seven-stage procedure names what each phase involves without saying, procedurally, how to carry it out.

France et al. (2019a) reviewed 57 publications on meta-ethnography practice and found researchers had operationalised the method in markedly inconsistent ways. No study had directly compared its three recognised synthesis techniques, reciprocal, refutational and line-of-argument translation, against each other.

The gap was real. Their advice: use all three together. This avoids treating them as a single either/or choice. Sattar et al. (2021) then built on this evidence base with a step-by-step, practitioner-facing guide to the seven phases for researchers approaching meta-ethnography for the first time.

Advantages

Qualitative metasynthesis offers a valuable approach to strengthening and deepening the understanding of a particular field of study, such as early childhood intervention.

This systematic process of analyzing and interpreting data across qualitative studies provides a unique and important contribution to bridging the gap between research and practice.

Enhanced Understanding and Knowledge Development: Qualitative metasynthesis goes beyond simply summarizing the findings of individual studies to interpret patterns and insights across investigations, offering a richer, more complete, and conceptually robust understanding of the phenomenon under investigation. This method can identify common themes, compare and contrast different perspectives, and generate new theoretical insights or practical implications.
Increased Generalizability: While individual qualitative studies are often limited in their generalizability due to factors such as sample size and context, metasynthesis enables researchers to synthesize findings from multiple studies, potentially leading to more generalizable conclusions. By integrating findings from studies conducted in diverse settings and with different populations, metasynthesis can provide broader insights into the phenomenon of interest.
Identification of Research Gaps and Future Directions: By systematically reviewing the existing body of qualitative research on a specific topic, metasynthesis can help researchers identify gaps and omissions in the literature, highlighting areas where further investigation is needed. This, in turn, can inform future research agendas and guide the development of new interventions or policies.
Enhanced Impact on Policy and Practice: By synthesizing qualitative research findings in a rigorous and accessible manner, metasynthesis can provide a strong foundation for evidence-based practice and policy development. For example, metasynthesis can inform the development, implementation, and evaluation of support strategies or interventions.
Integration of Diverse Perspectives: Qualitative metasynthesis allows researchers to consider and integrate the beliefs, values, and experiences of various stakeholders, including families, practitioners, administrators, policy makers, and researchers. This can lead to more comprehensive and nuanced understandings of complex issues.

Advantages Over Other Research Methods:

Unlike narrative literature reviews, qualitative metasynthesis employs systematic and rigorous methods to analyze and synthesize research findings. This systematic approach enhances the trustworthiness and credibility of the findings.
Unlike qualitative secondary analysis, which involves re-analyzing raw data from primary qualitative studies, qualitative metasynthesis focuses on analyzing and interpreting the findings and interpretations presented in published research reports.
Unlike meta-analysis, which is designed for quantitative studies, qualitative metasynthesis uses interpretive methods to synthesize findings from qualitative research, allowing for a deeper exploration of the meaning and complexity of human experiences

Disadvantages

Oversimplification and Decontextualization: Qualitative metasyntheses may result in findings being stripped of the critical context found in the original qualitative studies, sacrificing the rich description central to qualitative research.

Combining many studies in a qualitative metasynthesis may also create a superficial synthesis that loses grounding in the detailed study accounts. To address this issue, researchers suggest providing a framework with contextual information about the setting and participants of the studies included in the metasynthesis.
Misrepresentation of Original Studies: Trying to summarize the findings of qualitative studies in a metasynthesis may be inappropriate both epistemologically and ethically, as it risks misrepresenting the potential value of a body of research on health and illness.
Limited Impact on Policy and Practice: If a systematic process for integrating and synthesizing qualitative studies is not implemented, significant bodies of research may have limited influence on policy and practice.
Difficulty in Setting Boundaries: Due to the open-ended nature of qualitative studies, the permeable boundaries around the types of phenomena they examine can make setting limits on a metasynthesis challenging.

The broad nature of metasynthesis findings doesn’t offer much insight into how to predict specific phenomena like male suicide, and the findings often overlap with those for other phenomena like depression or addiction

Real-World Applications

Metasynthesis findings are used less as an academic exercise than as a way of feeding the qualitative literature on a topic into decisions made outside the review itself. Those decisions range from clinical guidelines to service design.

Clinical and Nursing Practice

Because a metasynthesis draws on published qualitative reports rather than raw participant data, it suits questions about everyday illness and care. One small study cannot answer these questions alone.

Tong et al. (2008) synthesised qualitative studies of parents caring for a child with chronic kidney disease. The result is a fuller picture of the practical and emotional demands of paediatric renal care than any single clinic study could offer.

The work was intended to inform how nephrology teams support families, not only patients.

A second study did the same for autism care.

Douglas et al. (2022) took the same approach to the barriers and benefits caregivers of autistic children report when seeking medical care. They identified recurring obstacles, such as communication breakdowns with clinicians and sensory-unfriendly environments, that a service could act on directly.

Guideline Development and Health Policy

This is not only a clinical concern.

The GRADE-CERQual framework discussed above exists for a reason. International guideline panels, including the World Health Organization, had begun using qualitative evidence syntheses without stating how much weight a finding should carry (Lewin et al., 2018).

Altree’s (2005) metasynthesis of parenting support in the context of poverty applies the same logic at the level of social policy, rather than a formal clinical guideline.

It synthesises findings across studies of low-income families to identify what kind of support parents themselves report as helpful, rather than what services simply assume they need.

In both cases, the goal is the same. Give decision-makers and policymakers a trustworthy account of what the people affected actually say they need, not what outsiders assume.

Early Intervention and Disability Services

Erwin et al. (2011) note that metasynthesis is used repeatedly in early childhood intervention research. The qualitative studies available on any one sub-question are often too few and too varied in context for a single study to generalise.

Synthesising across studies and settings is one of the few ways to build a broadly applicable account of what families and practitioners in this field actually experience.

A related question concerns disability services.

Kramer et al. (2012) applied the same logic to synthesise the perspectives of young people with disabilities on their environment and participation. The aim was to inform how services and physical spaces are designed around what disabled young people themselves report, rather than around assumptions made on their behalf.

Not every early application was clinical.

Education and Service Planning

Peck et al. (1989) is one of the earliest examples of the method, applied well before the term “metasynthesis” was in wide use. It synthesised qualitative accounts of resistance among parents, administrators and teachers to the integration of preschools.

That timing matters.

The aim was to help such programmes anticipate stakeholder resistance during rollout, rather than only address it after it appears. That the method predates its own name shows how naturally it fits this kind of practical question.

The pattern repeats.

Across these fields, metasynthesis is reached for specifically when the practical question is not whether an intervention works, but what it actually means for the people living through it.

That holds whether the setting is a preschool, a hospital ward, or a national policy office.

Key Takeaways

Definition: Metasynthesis interprets and synthesises findings across published qualitative studies to build new interpretations, unlike a meta-analysis, which pools numerical effects.
Seven Steps: The process runs from formulating a research question through systematic search, screening, quality appraisal, data extraction, synthesis and reporting.
Synthesis Approaches: Researchers typically draw on meta-ethnography, grounded theory or meta-study to move beyond describing each study and build new understanding.
Quality Appraisal: Tools such as CASP and QARI help reviewers judge which qualitative studies are strong enough to include.
Rigor and Reflexivity: Transparency, a documented audit trail and ongoing researcher reflexivity are what make a metasynthesis trustworthy.
Confidence Ratings: The GRADE-CERQual framework, developed from 2015, lets reviewers state transparently how much confidence a synthesis finding deserves.
Real-World Use: Metasynthesis findings inform clinical guidelines, health policy and service design, not only academic theory.