What is a Scoping Review and How to Conduct it
Making advancements in scientific research relies heavily on literature reviews. But it is important to identify the right kind of review that suits your research purpose. This blog helps you understand what a scoping review is and the best way to execute it.
Scoping Review vs. Systematic Review
How to Conduct a Scoping Review: Example
What is a Scoping Review?
Scoping reviews are conducted when you want to examine the breadth of a topic in a research field. Essentially, you are looking to answer the question: “What’s out there?” rather than dive into the quality of research conducted.
The purpose of a scoping review is to “scope” the literature just enough to identify knowledge gaps to determine likely future research directions. Often, the objective is to answer a broad research question like: “What is the role of AI in athlete training?” Such a scoping review may recognize existing AI models that are used in the field without evaluating which of them is the best one.
Although a specific research question is not answered, scoping reviews help researchers identify the existing knowledge gap, thus laying a foundation for formulating accurate research questions or even conduct systematic reviews.
Scoping Review vs. Systematic Review
A systematic review focuses on a specific research question and is used to analyze the depth of a research topic. Basically, systematic methods are used to research the existing research!
Systematic reviews are also often meta-analyses that involve data comparison. These reviews are conducted to identify, appraise, and synthesize existing knowledge from relevant studies. For example, if I were to continue on the topic of “The role of AI in athlete training,” I could consider one of the following research questions for my systematic review:
1. How effective are AI tools compared to traditional training methods in improving athlete performance and reducing risk of injuries?
2. What is the effectiveness of AI-driven wearable devices in monitoring and enhancing athletic performance compared to conventional monitoring methods?
3. Does the use of AI in athlete training programs improve injury prediction and prevention compared to standard coaching approaches?
Scoping Review Protocols
PRISMA-ScR
The PRISMA guidelines provide an extended checklist specifically for scoping reviews, referred to as the PRISMA-ScR1. This 22-item checklist outlines the reporting guidelines for a scoping review.
- The study should be identified as a scoping review in the title.
- The abstract should be a structured summary that includes (as applicable): background, objectives, eligibility criteria, sources of evidence, data charting methods, results, and conclusions that relate to the review questions and objectives.
- Describe the rationale behind the review and clearly state the objectives in the introduction section.
- The methods section should provide information on protocol and registration, rationale behind the eligibility criteria, search strategies used, how the sources of evidence were selected, and the data charting processes.
- The results section should include details of the inclusion and exclusion criteria for selecting the sources of evidence (preferably through a flow diagram), characteristics of sources of evidence (provide citations here), and the findings should be charted to individual sources as well as relevant research questions and objectives.
- In the discussion section, summarize the main findings and discuss the limitations of the scoping review process. Also, interpret the results and highlight the potential implications.
Scoping Review Framework
There’s also a methodological framework proposed by Arksey and O’Malley2. Although the framework has been refined over the years, the fundamental aspects remain the same:
- Identify the research question
- Shortlist studies for scoping
- Select relevant studies from the literature
- Chart the data
- Collect sufficient evidence
- Summarize and report the results
How to Conduct a Scoping Review: Example
Taking the example of examining the role of AI in athlete training, here’s an outline of how to conduct a scoping review.
| 1 | Identify the research question (and include sub-questions) |
| Main research question: What is known about AI use in athlete training and performance optimization? Sub-questions:
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| 2 | Scope databases for relevant studies |
a) Focus on athlete training and performance monitoring b) Papers published in English in the last 10 to 15 years c) Any study design (e.g., quantitative, qualitative, reviews, mixed research methods)
a) Studies focusing on general health and fitness without athlete context b) Opinion pieces without any empirical evidence. |
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| 3 | Select suitable studies |
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| 4 | Chart the data |
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The data can be extracted and tabulated considering:
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| 5 | Collating and summarizing results |
a) Monitoring & feedback (e.g., AI-based wearables to track training) b) Injury prevention (predicting risk from biomechanics data) c) Performance optimization (AI in strategizing personalized plans) d) Coaching support (AI-assisted video analysis and decision-making)
a) Lack of large-scale validation studies b) Over-reliance on small datasets c) Ethical considerations and data privacy issues
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| 6 | Reporting |
| Follow the PRISMA-ScR checklist to document the search strategy, include a flow diagram for study selection, and summarize findings in both tabular and narrative formats. |
References
1. PRISMA-ScR https://www.prisma-statement.org/scoping
2. Scoping review framework https://www.tandfonline.com/doi/abs/10.1080/1364557032000119616
