Secondary Data: The Hidden Pearls of Wisdom
Recognizing what you can do with secondary data is a bit like appreciating the real beauty of pearls. Perhaps you’ve never thought about buying them, because you regard them as “second best”. But secondary data aren’t less valuable than primary data, despite the meaning of the word “secondary”. Just because you don’t gather the data yourself, do not make them inferior. On the contrary, there’re the hidden pearls of wisdom, which are based on the integration of experience, knowledge, expertise and deep understanding of a topic of interest to discern the unknown. You may even find a rare pearl when inspecting data sets. Ethical reasons for using secondary data aren’t negligible either. These data reduce the burden on research participants, because they don’t have to be interviewed, or tested, again. Hence, I suggest that it’s a good idea to start with investigating secondary data when researching something. You can get a feel for what has already been researched in this way as well.
Admittedly, these type of data sources also have disadvantages, even though the benefits may outweigh their drawbacks. When you’re working in a non-academic setting, or aren’t part of a research team, collecting data for a study may not be easy, or even impossible. Using secondary (existing) data can therefore be a viable option. They’re also an alternative. If you don’t want to collect information yourself, utilize secondary data. Furthermore, they enable you to analyze large data sets. These are much larger than the data you could gather on your own, although this also means that the data are more complex. Often longitudinal studies, surveys, focus groups, health records, social media and journals are useful sources of information.
Additional advantages of secondary data sources are that you don’t have to spend time and money gathering them, so to use them is economical. Moreover, they may reduce unnecessary duplication. Provided that the original research was sound, replication is not required, even though results should be replicable.
There is a social aspect, too. Since the use of secondary data could involve communicating with organizations, you meet people, who share your interests. In addition, the quality of secondary data tends to be good when they’ve been collected by governments or prestigious (reputable) organizations. Proving the effectiveness of an intervention, or of something else, is another benefit, provided the secondary data are valid and reliable. Then they can be regarded as robust evidence. Expanding secondary data strengthens the evidence and contributes to demonstrating the effectiveness of an intervention. It also ensures that the data won’t be outdated.
Nevertheless, secondary data have limitations, because you may not exactly know how the data were gathered, collated and/or analyzed. Bias can be an issue. This means that you must check that your data source is dependable. Familiarizing yourself with the data, ethics, the Data Protection Act, as well as having sufficient research knowledge, are therefore a must. Or you need to ask someone else, who is knowledgeable and can advise you.
Obviously, the type of secondary data can restrict your choice of topic and your creativity. Unless you expand your primary data with a secondary data set, you’re reliant on data that were collected for a certain purpose. This may differ from what you’d like to research, although you can gain insight into what evidence is lacking regarding this topic or area.
Furthermore, the data set might not be in a suitable format. It may be presented in specific categories that you’re not interested in. For example, when ethnicity is reported instead of age. Another difficulty could arise when you need numerical data, but you only encounter categories.
Perhaps data sets are comparable to a large group. When you want to explore small group dynamics, you’ve to split it into small groups first. In other words, what you’re searching for may not be directly available, but is hidden in the secondary data.
Definitions of concepts might also not tally with yours. You’ve to be mindful of all these potential problems when utilizing secondary data. Furthermore, while government sources are mostly available without charge, data from organizations may not be freely accessible. Buying secondary data sets could be as costly as a rare pearl.
Be aware of potential confusion. Don’t mistake tertiary for secondary data. The former are third-party data which were collected from numerous sources by third parties for various purposes. So these data were not gathered for a specific goal. That’s the main difference between secondary and tertiary data. Tertiary data also tend to be unstructured. So stick to secondary data.
Remember that secondary analysis is an empirical exercise that applies the same basic principles as studies which utilize primary data. And the data can be analyzed both quantitatively and qualitatively. Obviously, it’s important that the secondary data are appropriate for your research aim. So you only include relevant data that are useful for your project.
When drawing on secondary data, the first step is to consider your purpose. This guides you. It ensures that you collect the ‘right’ data which are are suitable for your study. Then you think about your research questions. For example, if you want to find out how physical health impacts on mental health, you could devise a question, such as, “Which illnesses affect mental health?”. Focus on quantitative and disregard qualitative data when identifying and analyzing your sources of secondary data that relate to this question. For your analyses, you use the same methods and techniques that you would when analysing primary data.
If you prefer qualitative studies, you’ll find data from interviews in so-called ‘repositories’. Think about consent when re-using those data. So ensure that all participants consented that their data could be used by other researchers. And don’t violate principles of anonymity. Participants shouldn’t be recognizable and personal data mustn’t be transferred outside the country or economic territory, according to the Data Protection Act.
Many researchers have become reliant on secondary data over the years. A recent book with the title “Qualitative Secondary Analysis”, which was published in 2019 by Hughes and Tarrant, provides readers with knowledge about the research process when using qualitative secondary analysis.
You’ll find lots of videos and articles on the internet. This shows how popular secondary data sources are, even though you still may have to search for specific data, which aren’t immediately visible. It’s worth the effort and the moral of the story of secondary data is this: Don’t underestimate the wisdom of hidden pearls. They’re like groups. Both are gemstones that have developed from individual living creatures. I view them as the queens of gems because they are the world’s oldest gems. Go and find them in the ocean, amongst swarms of fish, and in other types of groups.
Merry Christmas & Seasonal greetings.