Data extraction is the process of collecting relevant information from studies and organising it in a way that with help with data analysis and synthesis. Data extraction can be challenging. It requires you to go back to your chosen articles and highlighting the relevant information that will answer your research question. Normally this involves extracting the data related to your chosen framework and its components e.
To standardise and improve the validity of the results, it's crucial to create a data extraction form or table Bettany-Saltikov, , p. Data extraction is the process of extracting the relevant pieces of information from the studies you have assessed for eligibility in your review and organizing the information in a way that will help you synthesize the studies and draw conclusions. Boland, A.
Author, Country. Research Design. Aim of Research. Sample Size. Main findings. Sarkisian et al. Qualitative study; focus group. Reasons for appointments. Physical function, cognitive function, social function, pain. Older adult expressed that they felt like numbers not people, not involved in decision-making.
GP stared at computer throughout conversation with no eye contact. Bastiaens et al. Qualitative study; interviews. Explores the views of older adult aged 70 and over on their involvement in primary healthcare in 11 European Countries. Older adults want to be involved in their care and decision-making.
The study stressed the importance of good communication, interest in their problems, clear information, being reliable and supportive. You may have read or seen some of the data extraction software available e. Unfortunately, we currently do not have any licences for this software at University of Dundee. Alternative options include creating a table, form manually that suits your review - e. Dissertation Subject Guide including systematic reviews, literature reviews and scoping reviews.
