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Qualitative Data Analysis in Systematic Reviews

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A systematic review is a rigorous research method that involves a systematic approach of collecting, assessing, and synthesizing relevant unpublished, and published literature to answer a well-defined research question. It can either be quantitative or qualitative; the former includes studies with numerical data while the latter includes qualitative studies that derive their data from observation and analysis of interviews and verbal interactions. Primarily, quantitative means are used in analyzing study data in a quantitative systematic review. Qualitative, thematic, or narrative analysis is used in analyzing data from studies in a qualitative systematic review. Some systematic reviews can also be both qualitative and quantitative (i.e. mixed methods). Here, we’ll discuss qualitative systematic reviews, and how aggregate or interpretative approaches to reviewing literature can provide valuable insights, which is especially useful in evidence-based medicine.

What Is A Qualitative Systematic Review?

A qualitative systematic review aggregates integrates and interprets data from qualitative studies, which is collected through observation, interviews, and verbal interactions. Included studies may also use other qualitative methodologies of data collection in the relevant literature. The use of qualitative systematic reviews analyzes the information and focuses on the meanings derived from it.

A qualitative systematic review generally follows the same steps as indicated by most systematic review guidelines, including the application of eligibility criteria in systematic reviews, and the steps for searching and screening available literature. All of these then conclude in the final write-up, which involves tabulating the data into a summary of findings table in the systematic review, and reporting on findings and conclusions. Qualitative systematic reviews are different in that, they incorporate qualitative studies and use only qualitative methods in analyzing and synthesizing data.

Why Are Qualitative Systematic Reviews Valuable?

Apart from the rigorous, methodical, and reproducible process used, qualitative systematic reviews derive their conclusions from qualitative data, they bring a human perspective into the process of answering the focused research question. This brings valuable findings, which cannot be expressed in quantitative means, into the view of the reader. Results that are better stated that calculated, like feelings of compliance or satisfaction following treatment using a new anti-depressant.

Another example, if a systematic review that deals with pain associated with a certain drug considers qualitative data, it can come up with conclusions that consider how subjects feel when taking the medicine, e.g., the level of pain and tolerance, etc.

Types Of Qualitative Systematic Reviews

Pioneers of qualitative systematic reviews suggest that qualitative systematic reviews can be segregated into two types: aggregated and interpretive.

Aggregated Systematic Review

An aggregated systematic review simply summarizes the collected data. It generates a summary of the studies using aggregate data obtained from individual studies within the scoped literature.

Interpretive Systematic Review

An interpretive systematic review, which is the more common of the two types, analyzes the data. From the analysis, researchers can derive a new understanding that may lead to the development of a theory and can help understand or predict behavior as it relates to the topic of the review.

Interpretive systematic reviews can be further broken down into meta-ethnography, critical interpretive synthesis, realist synthesis, and narrative synthesis.

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How to Analyze Data in a Qualitative Systematic Review

Qualitative systematic reviews deal with a lot of textual studies. This is why undertaking one requires a well-planned, systematic, and sustainable approach, as defined in your protocol. It also helps to employ literature review software like DistillerSR to take out a significant amount of manual labor, as it automates key stages in the entire methodology.

Here are four steps to take for qualitative data analysis in systematic reviews.

Collect and Review the Data

Based on your eligibility criteria, search and screen the studies relevant to your review. This involves scouring libraries and databases, gathering documents, and printing or saving transcripts. You can also check for studies in the reference lists of already eligible studies. The recommendation of similar articles by databases during searching should also be checked.

Once you’ve collected your data, get a sense of what it contains by reading the collected studies (you’ll likely need to do this several times).

This step can be easier with systematic review software, such as DistillerSR which gives you access to more sources and applies AI to identify the literature you need.

Create And Identify Codes

Connect your data by creating and identifying common ideas. Highlight keywords, and categorize information; it may even be helpful to create concept maps for easy reference.

Develop Themes

Combine your codes and revise them into themes, recognizing recurring concepts, language, opinions, beliefs, etc.

Derive Conclusions and Summarize Findings

Present the themes that you’ve collected in a cohesive manner, using them to answer your review’s research question. Finally, derive conclusions from the data, and summarize your findings in a report.


Qualitative systematic reviews are a valuable research approach that presents a different, more human perspective to the methodology, allowing high-quality conclusions and solutions to be derived in the process. Undertaking it, however, requires a lot of work, particularly in the collection, extraction, and analysis of qualitative data. That said, these tasks may be streamlined with the help of literature review software like DistillerSR, which lifts a lot of the manual labor required in doing a qualitative systematic review.

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