Extracting
Learning Objectives
This chapter will help you:
- consider what data you need to extract.
- how to use extraction templates.
“Data extraction is key to demonstrating that you have followed a systematic approach and handled different studies in a consistent manner. Data extraction is core to the review process and requires intensive effort” (Booth et al., 2022, p. 197).
Data extraction, called charting in scoping reviews, is where you find the data from each included study that is needed to answer your review question. To reduce bias and inconsistencies, data extraction should be carried out independently by at least two reviewers who come together to resolve differences of opinion (Munn et al., 2014).
You should try to extract the same data from each study. This is easier if you are only looking at one type of study. If you can’t locate the data you need, you should try to contact the study authors. Items you may consider extracting are:
- descriptive data such as methodology, participants, intervention, type of study….
- the information you will need for critical appraisal or risk of bias assessment, such as the funding of the study (if you are doing a systematic review)
- outcomes including themes (qualitative research), findings, conclusions, recommendations, and limitations of the study (Caldwell & Bennett, 2020; MacMillan et al., 2019; Munn et al., 2014).
The Cochrane Handbook has extensive guidance on collecting data from included studies.
Extraction templates
Data extraction templates can be customised to suit your review. Using a template provides consistency and reliability in the data extracted across all included studies (MacMillan et al., 2019; Munn et al., 2014). It will also “make the process of reporting on extracted information narratively in your write-up, and the construction of summary information tables, quicker, easier, and more transparent for your co-authors” (MacMillan et al., 2019, p. 817). This template can be developed as a team. Some screening software, such as Covidence, provides customisable templates within the platform.
Test the data extraction form on a couple of studies to ensure it is reliable (Munn et al., 2014) and that the data extracted is relevant to save you from reading studies multiple times (MacMillan et al., 2019). Multiple reports of the same study must be located and you should explain how you dealt with that data (MacMillan et al., 2019). This is because not all reports include the same data and information. There are two approaches in this situation:
- Data can be extracted from each report separately and reported using multiple forms.
- Data can be extracted from each report and collated in one form (Li, et al., 2023).
This video by JBI discusses extracting and analysing data for scoping reviews.
JBI. (2023, March 20). Recommendations for the extraction, analysis and presentation of results in scoping reviews [Video]. YouTube. https://youtu.be/FPF9Jw118FE
Example
Click on the accordion button to see the data extraction process from the following systematic review.
Sullivan, O., Curtin, M., Flynn, R., Cronin, C., Mahony, J. O., & Trujillo, J. (2024). Telehealth interventions for transition to self-management in adolescents with allergic conditions: A systematic review. Allergy, 79, 861-883. https://doi.org/10.1111/all.15963
Further reading
Munn, Z., Tufanaru, C., & Aromataris, E. (2014). JBI’s systematic reviews: Data extraction and synthesis. The American Journal of Nursing, 114(7), 49–54. https://doi.org/10.1097/01.Naj.0000451683.66447.89
References
Booth, A., Sutton, A., Clowes, M., & Martyn-St James, M. (2022). Systematic approaches to a successful literature review (3rd ed.). SAGE.
Caldwell, P. H. Y., & Bennett, T. (2020). Easy guide to conducting a systematic review. Journal of Paediatrics Child Health, 56(6), 853-856. https://doi.org/10.1111/jpc.14853
Li, T., Higgins, J. P. T., & Deeks, J. J. (2023). Chapter 5: Collecting data. In J. P. T. Higgins, J. Thomas, J. Chandler, M. Cumpston, T. Li, M. J. Page, & V. A. Welch (Eds.), Cochrane handbook for systematic reviews of interventions (version 6.4). Cochrane. https://training.cochrane.org/handbook/current/chapter-05
MacMillan, F., McBride, K. A., Greorge, E. S., & Steiner, G. Z. (2019). Conducting a systematic review: A practical guide. In P. Liamputtong (Ed.), Handbook of research methods in health social sciences (pp. 805-826). Springer. https://doi.org/10.1007/978-981-10-5251-4
Munn, Z., Tufanaru, C., & Aromataris, E. (2014). JBI’s systematic reviews: Data extraction and synthesis. American Journal of Nursing, 114(7), 49-54. https://doi.org/10.1097/01.Naj.0000451683.66447.89
A systematic error or deviation from the truth in results.
How research is done, including how information is collected and analysed and why a particular method was chosen.
Something that aims to make a change and is tested through research.
The process of assessing and interpreting evidence, by systematically considering its validity, results and relevance to your own context.
The risk of a systematic error in the research that could detract from the truth.
The practical or theoretical shortcomings of a study that are often outside of the researcher's control.
