Scoping review analysis methods should match the type of data you extract and the purpose of your review while remaining within the descriptive remit of scoping review methodology. Depending on your data, appropriate approaches include descriptive numerical analysis, inductive content analysis and deductive content analysis.

What can you and cannot do in scoping review analysis?

A scoping review maps and charts the landscape of research. Think of yourself as a tour guide pointing out clusters of studies, gaps in the evidence, where the field is heading and how research has evolved.

You do not zoom in and analyse the detailed composition of the evidence. Your role is to map rather than interpret, evaluate or synthesise.

This means methods such as meta-analysis, meta-ethnography and meta-aggregation are outside the remit of a scoping review. You also do not judge quality, weigh evidence or recommend the “best” intervention.

The analytical approaches suited to scoping reviews remain descriptive:

• Descriptive analysis — numerical summaries.

• Inductive content analysis.

• Deductive content analysis — including framework-supported approaches.

The distinction from thematic analysis is important. Inductive content analysis organises repeated ideas into categories, while thematic analysis involves interpretation based on the importance or “keyness” of themes. That interpretive depth moves beyond mapping.

How should your extracted data guide your analysis method?

Before choosing an analysis method, examine the type of data you are extracting. Your research question tells you what you are looking for, while your extraction sheet determines what you actually have to work with.

Ask yourself: What will my extracted data look like?

1. Mostly structured, numerical data → Descriptive analysis

If your extraction sheet contains publication years, countries or regions, study designs, sample characteristics, intervention types or outcome categories, your dataset is structured and quantitative.

Use descriptive numerical analysis such as counts, percentages, frequencies, simple tables or charts. This gives readers a clear overview of the research landscape.

2. Textual or conceptual data without a pre-existing framework → Inductive content analysis

If you extract authors’ definitions, descriptions of experiences, reported barriers or facilitators, or key concepts, use inductive content analysis. This organises the data into categories that emerge from the information itself.

3. Textual or conceptual data mapped to a framework → Deductive content analysis

If you have qualitative data and an existing framework, such as TIDieR or a socioecological model, deductive content analysis allows you to map the data onto pre-defined categories.

Can you use more than one analysis method in a scoping review?

Scoping reviews often involve extracting a range of data, so you may find that multiple analytical methods are appropriate.

For example, Hoppe et al. examined attitudes and experiences and extracted mainly descriptive statements from included studies. They used inductive content analysis, organising findings into seven categories such as pharmacists’ knowledge and attitudes. Some frequency counts were included, but the analysis remained focused on summarising and collating the findings.

Another example extracted structured data about intervention features and reproducibility elements and mapped these onto an existing framework. The authors reported percentages and numerical distributions and used visual displays such as bar charts. Deductive content analysis was one component alongside numerical descriptive analysis.

A further review relied entirely on descriptive numerical analysis, reporting how many studies used particular outcomes and which intervention types appeared most often. This was appropriate because the extracted data were highly structured.

How do you decide which analysis method to use?

Analysis in scoping reviews is not a single choice. It can be viewed as a sliding scale, and you need to decide where your review sits on that scale.

Most scoping reviews naturally combine descriptive analysis with one form of content analysis. Your choice should be based on three things:

• the nature of your data;

• the purpose of your review; and

• staying within the descriptive remit of scoping review methodology.

The guiding principle is simple:

• Numerical and structured → descriptive analysis

• Textual or conceptual, with emerging categories → inductive content analysis

• Textual or conceptual, with an existing framework → deductive content analysis

Take a close look at your extraction sheet before deciding. The appropriate choice should reflect the data you have and keep your analysis within the descriptive remit of a scoping review.

How should you explain your scoping review analysis?

Once you have decided on your analytical approach, explain your analytical steps clearly in the methods section so readers can follow your logic.

The analysis method should connect with the data you extracted and the purpose of your review. The choice is part of the wider research design, so it needs to make sense within the study as a whole.

A useful way to approach this is to work backwards from your extraction sheet. Identify the nature of the data you have collected, consider what you want your analysis to show, and then select an approach that allows you to describe that research landscape without moving beyond what a scoping review is designed to do.

If you're applying this to your own scoping review and want a second pair of eyes: research support