a researcher's literature review involves secondary data research

How To Do Secondary Research or a Literature Review

• Secondary Research
• Literature Review
• Step 1: Develop topic
• Step 2: Develop your search strategy
• Step 3. Document search strategy and organize results
• Systematic Literature Review Tips
• More Information

Before You Begin: Develop Search Terms

Developing search terms starts with developing a research question. There are many ways to develop a research question, and your assignment may dictate which format to use, but the PICO framework is a very common format used in the health field.

• About PICO Format Information about forming a health-based medical question in the PICO format ( P opulation, I ntervention, C omparison/Control, O utcome)

An example research question using the PICO criteria:

Does group therapy [ I ntervention] lower the number of panic attacks per year [ O utcome] when compared to drug therapy [ C omparison/ C ontrol] for teenagers diagnosed with panic disorders [ P opulation]?

After you establish a question, you can begin developing keywords for the four PICO criteria (or if you're not using PICO, the main themes of the question), including synonyms you can think of. It can help to break this up into a chart, like the example below. In this case, it's best to break up any compound criteria such as "teenagers diagnosed with panic disorders," into distinct concepts like simply "teenagers" and "panic disorder."

Where Do I Search?

For a psychology literature review, searching both PsycINFO and PubMed are your best bets. Both of these databases are very comprehensive. There will be some overlap between the two databases and some articles will appear during both searches, but you can filter for duplicates if you use a citation management program like Zotero (see later box about citation management). Searching tips for both databases follow.

PubMed Tips

How to search PubMed in a systematic way 

1. create a saved search for all of the terms that represent a concept.

The most comprehensive way to search PubMed is to create a separate but comprehensive search for each of the terms related to the concepts (step 1), then combining all of  those searches in a logical way (step 2). To do this, I would want to make one search string for all the potential terms used for each concept. I'll use the Intervention concept as an example. First, I will search for the first keyword I thought of to describe the concept, "group therapy."

Even though I searched just for "group therapy," the database interpreted my search in a different way. This is due to PubMed's algorithms. You can find the search details on the right side of the page: 

Because this is how the database interpreted my search, I'll want to copy and paste that into the upper search box. We'll look at why in a bit.

From here, I would continue like this, searching for each phrase of word that describes my concept separately. When done, go to the Advanced Search to see your history:

As you can see, the simple searches I entered have the same number of results as the more complicated, database code that I copied and pasted. The reason I did that is to preserve the actual details as run by the database. From here, I can combine the detailed searches by applying Boolean logic.  Because I want all possible terms that cover the same concept, the searches will be combined with OR. You can do this by clicking on the Add link next to searches 11 and 10, and separating by OR. Click search again and return to the search menu. There, you will have and you have one comprehensive list of all the terms related for one of your concepts (as number 12 below). 

Make sure to sign in and save this history to preserve it in case you need to make changes in the future. Click on the number of the search and choose Save to NCBI (if you don't have a free NCBI account, you will need to create one first):

Repeat this step for all of your concepts, combining each separate search into one comprehensive search for that concept and saving it.

2. Combine the concept searches logically

After you have created a comprehensive search for each concept, think about how the searches should be combined. Often, this will be simply combining all the concept searches with AND (so you get the overlap between all the terms), but not always.

For example, some researchers don't include textual searches for an age group as key terms; instead, they rely on the database filters for that. This is up to personal preference but you will likely have slightly different results depending on what you choose. 

For my sample question, I'm really researching two separate issues because I want to see both how group therapy works for panic attacks and also how drugs work, so that I can compare them. The reason I wouldn't want to search for ALL the concepts together in my example is that it's unlikely there are many articles explaining my exact issue (in other words, articles that compare the two therapies). 

To search for relevant articles about the intervention of group therapy question, I'd want to combine my comprehensive searches made for the Population, Intervention, and the Outcome concepts with AND by using the advanced search:

I click Search and end up with 184 relevant results. You should of course save this final search as well!

3. Modify as needed

If you think of other terms to include in your searches, you should modify each concept search individually and then re-combine them.

Other tips:

• Sign up for a free NCBI account. This will allow you to customize your search criteria, save searches and search history, and organize articles into folders.
• PubMed's search algorithm uses something called Automatic Term Mapping (ATM), which automatically groups phrases and searches different fields for a thorough search. This is useful for simpler searches or when you don't need to document search strategy, but for literature search documentation, it's best to look at the Search Details box, modify the search as needed, and record that as your actual search method.
• use Medical Subject Headings (MeSH) to help find targeted results. You can use MeSH terms and the corresponding subheadings to find targeted results.
• PubMed Search Strategies Blog A good place to start to find starting point strategies on a topic similar to yours.

PsycINFO Tips

• In addition to using keywords, take advantage of the Thesaurus, which uses indexed terms. See more info about the index terms on the PsycINFO guide .
• Create an EBSCO account. This is separate from your MyIIT login and allows you to save search history, set up search alerts, and organize research.
• Avoid using quotation marks when searching. By leaving them off, the database will automatically search for slight variations of your keywords, such as plural versions or alternate spellings. 
• Using the "Peer Reviewed" filter will limit results to only peer-reviewed journal articles. This will make up the majority of your literature, but if you'd like to also find items like books or conference proceedings, consider leaving that filter off.
• Note that your search results will vary by using Limiters, such as Age or Population Group, will provide you with different results than by using keywords for the same concept.

How to search PsycINFO in a systematic way

Similar to the PubMed strategy above, create a separate but comprehensive search for each of the terms related to the concepts (step 1), then combining all of  those searches in a logical way (step 2). To do this, I would want to make one search string for all the potential terms used for each concept. I'll use the Intervention concept as an example. First, I will search for the first keyword I thought of to describe the concept, "group therapy." PsycINFO differs from PubMed because the search you enter is the search you get (except the database will apply slight variants such as British spelling, plurals, etc.). You can choose whether to search all fields or a specific field such as the Title (See the More Tips section if you'd like to use the database subject terms).

Repeat for all of your terms:

When you are done searching for each individual term separately, click on the Search History link underneath the search boxes. From there, first clear any terms left in the boxes above and then combine your searches using the checkboxes and the "Search with OR" link.

This will create a combined search, but unlike PubMed PsycINFO does not list the details of the words used, so it can help to immediately save and rename the search to something more descriptive. To save your searches, click on the search(es) you'd like to save and click on Save Searches/Alerts. You will need to make a separate EBSCO account to do this.

Once you have created separate, comprehensive searches for each concept, then combine them following the same strategy listed above in the PubMed box but using the "Search with AND" box on the search history page.

Using Search History to Formulate Advanced Searches

As explained above, when conducting a comprehensive literature review, it's very important to use a systematic approach. This is especially important when submitting an article for publication, because you're often required to submit the search strategy you used. Instead of combining words/phrases into one search on the home page of the database, it's a good idea to use your Search History instead. This will help you be sure that your search terms are being combined properly and in the right order. See the links below for more background and alternative explanations: 

• PubMed Search Strategy For another explanation of searching PubMed, see this tutorial. The tutorial references "systematic reviews," but the search concept is similar to literature reviews.
• Example Search Methodology in an APA Paper Scroll to see a sample search method described in the Methodology section.
• Conducting a winning literature search Helpful article for finding health-based literature

What about Google Scholar?

In general, PsycINFO and PubMed are better bets to use than Google Scholar when conducting literature searches, because the search fields and algorithms are much more advancec. PsycINFO and PubMed also employ actual human indexers that review and categorize articles, whereas Google Scholar relies on keyword searching alone, so it's easier to get more complete and relevant results in PsycINFO or PubMed. It's also easier to keep track of your search strategy when using PubMed or PsycINFO.

Use a Citation Manager

• Zotero by IIT Galvin Library Last Updated Dec 21, 2023 2113 views this year

Using a citation manager requires a bit of a learning and adjustment period, but has a great payoff. Invest a bit of time to learn how to use one and you will benefit for the rest of your educational/professional career! Citation managers help you capture and organize references that you've found online, including the full text if available, and then help you to draft in-text citations and bibliographies. There are several available, but the library recommends Zotero if you aren't yet using a citation manager, because it is free, open-source, and very easy to use.

Other Places to Search

If you have a novel topic or one that has not yet been empirically studied extensively via research articles, you may need to supplement with dissertations, theses, or books.

• I-Share Catalog Find books from IIT and other universities here.

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Literature Reviews

• Getting started

What is a literature review?

Why conduct a literature review, stages of a literature review, lit reviews: an overview (video), check out these books.

• Types of reviews
• 1. Define your research question
• 2. Plan your search
• 3. Search the literature
• 4. Organize your results
• 5. Synthesize your findings
• 6. Write the review
• Artificial intelligence (AI) tools
• Thompson Writing Studio This link opens in a new window
• Need to write a systematic review? This link opens in a new window

Contact a Librarian

Ask a Librarian

Definition: A literature review is a systematic examination and synthesis of existing scholarly research on a specific topic or subject.

Purpose: It serves to provide a comprehensive overview of the current state of knowledge within a particular field.

Analysis: Involves critically evaluating and summarizing key findings, methodologies, and debates found in academic literature.

Identifying Gaps: Aims to pinpoint areas where there is a lack of research or unresolved questions, highlighting opportunities for further investigation.

Contextualization: Enables researchers to understand how their work fits into the broader academic conversation and contributes to the existing body of knowledge.

tl;dr  A literature review critically examines and synthesizes existing scholarly research and publications on a specific topic to provide a comprehensive understanding of the current state of knowledge in the field.

What is a literature review NOT?

❌ An annotated bibliography

❌ Original research

❌ A summary

❌ Something to be conducted at the end of your research

❌ An opinion piece

❌ A chronological compilation of studies

The reason for conducting a literature review is to:

Literature Reviews: An Overview for Graduate Students

While this 9-minute video from NCSU is geared toward graduate students, it is useful for anyone conducting a literature review.

Writing the literature review: A practical guide

Available 3rd floor of Perkins

Writing literature reviews: A guide for students of the social and behavioral sciences

Available online!

So, you have to write a literature review: A guided workbook for engineers

Telling a research story: Writing a literature review

The literature review: Six steps to success

Systematic approaches to a successful literature review

Request from Duke Medical Center Library

Doing a systematic review: A student's guide

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Secondary research: definition, methods, & examples.

19 min read This ultimate guide to secondary research helps you understand changes in market trends, customers buying patterns and your competition using existing data sources.

In situations where you’re not involved in the data gathering process ( primary research ), you have to rely on existing information and data to arrive at specific research conclusions or outcomes. This approach is known as secondary research.

In this article, we’re going to explain what secondary research is, how it works, and share some examples of it in practice.

Free eBook: The ultimate guide to conducting market research

What is secondary research?

Secondary research, also known as desk research, is a research method that involves compiling existing data sourced from a variety of channels . This includes internal sources (e.g.in-house research) or, more commonly, external sources (such as government statistics, organizational bodies, and the internet).

Secondary research comes in several formats, such as published datasets, reports, and survey responses , and can also be sourced from websites, libraries, and museums.

The information is usually free — or available at a limited access cost — and gathered using surveys , telephone interviews, observation, face-to-face interviews, and more.

When using secondary research, researchers collect, verify, analyze and incorporate it to help them confirm research goals for the research period.

As well as the above, it can be used to review previous research into an area of interest. Researchers can look for patterns across data spanning several years and identify trends — or use it to verify early hypothesis statements and establish whether it’s worth continuing research into a prospective area.

How to conduct secondary research

There are five key steps to conducting secondary research effectively and efficiently:

1.    Identify and define the research topic

First, understand what you will be researching and define the topic by thinking about the research questions you want to be answered.

Ask yourself: What is the point of conducting this research? Then, ask: What do we want to achieve?

This may indicate an exploratory reason (why something happened) or confirm a hypothesis. The answers may indicate ideas that need primary or secondary research (or a combination) to investigate them.

2.    Find research and existing data sources

If secondary research is needed, think about where you might find the information. This helps you narrow down your secondary sources to those that help you answer your questions. What keywords do you need to use?

Which organizations are closely working on this topic already? Are there any competitors that you need to be aware of?

Create a list of the data sources, information, and people that could help you with your work.

3.    Begin searching and collecting the existing data

Now that you have the list of data sources, start accessing the data and collect the information into an organized system. This may mean you start setting up research journal accounts or making telephone calls to book meetings with third-party research teams to verify the details around data results.

As you search and access information, remember to check the data’s date, the credibility of the source, the relevance of the material to your research topic, and the methodology used by the third-party researchers. Start small and as you gain results, investigate further in the areas that help your research’s aims.

4.    Combine the data and compare the results

When you have your data in one place, you need to understand, filter, order, and combine it intelligently. Data may come in different formats where some data could be unusable, while other information may need to be deleted.

After this, you can start to look at different data sets to see what they tell you. You may find that you need to compare the same datasets over different periods for changes over time or compare different datasets to notice overlaps or trends. Ask yourself: What does this data mean to my research? Does it help or hinder my research?

5.    Analyze your data and explore further

In this last stage of the process, look at the information you have and ask yourself if this answers your original questions for your research. Are there any gaps? Do you understand the information you’ve found? If you feel there is more to cover, repeat the steps and delve deeper into the topic so that you can get all the information you need.

If secondary research can’t provide these answers, consider supplementing your results with data gained from primary research. As you explore further, add to your knowledge and update your findings. This will help you present clear, credible information.

Primary vs secondary research

Unlike secondary research, primary research involves creating data first-hand by directly working with interviewees, target users, or a target market. Primary research focuses on the method for carrying out research, asking questions, and collecting data using approaches such as:

• Interviews (panel, face-to-face or over the phone)
• Questionnaires or surveys
• Focus groups

Using these methods, researchers can get in-depth, targeted responses to questions, making results more accurate and specific to their research goals. However, it does take time to do and administer.

Unlike primary research, secondary research uses existing data, which also includes published results from primary research. Researchers summarize the existing research and use the results to support their research goals.

Both primary and secondary research have their places. Primary research can support the findings found through secondary research (and fill knowledge gaps), while secondary research can be a starting point for further primary research. Because of this, these research methods are often combined for optimal research results that are accurate at both the micro and macro level.

Sources of Secondary Research

There are two types of secondary research sources: internal and external. Internal data refers to in-house data that can be gathered from the researcher’s organization. External data refers to data published outside of and not owned by the researcher’s organization.

Internal data

Internal data is a good first port of call for insights and knowledge, as you may already have relevant information stored in your systems. Because you own this information — and it won’t be available to other researchers — it can give you a competitive edge . Examples of internal data include:

• Database information on sales history and business goal conversions
• Information from website applications and mobile site data
• Customer-generated data on product and service efficiency and use
• Previous research results or supplemental research areas
• Previous campaign results

External data

External data is useful when you: 1) need information on a new topic, 2) want to fill in gaps in your knowledge, or 3) want data that breaks down a population or market for trend and pattern analysis. Examples of external data include:

• Government, non-government agencies, and trade body statistics
• Company reports and research
• Competitor research
• Public library collections
• Textbooks and research journals
• Media stories in newspapers
• Online journals and research sites

Three examples of secondary research methods in action

How and why might you conduct secondary research? Let’s look at a few examples:

1.    Collecting factual information from the internet on a specific topic or market

There are plenty of sites that hold data for people to view and use in their research. For example, Google Scholar, ResearchGate, or Wiley Online Library all provide previous research on a particular topic. Researchers can create free accounts and use the search facilities to look into a topic by keyword, before following the instructions to download or export results for further analysis.

This can be useful for exploring a new market that your organization wants to consider entering. For instance, by viewing the U.S Census Bureau demographic data for that area, you can see what the demographics of your target audience are , and create compelling marketing campaigns accordingly.

2.    Finding out the views of your target audience on a particular topic

If you’re interested in seeing the historical views on a particular topic, for example, attitudes to women’s rights in the US, you can turn to secondary sources.

Textbooks, news articles, reviews, and journal entries can all provide qualitative reports and interviews covering how people discussed women’s rights. There may be multimedia elements like video or documented posters of propaganda showing biased language usage.

By gathering this information, synthesizing it, and evaluating the language, who created it and when it was shared, you can create a timeline of how a topic was discussed over time.

3.    When you want to know the latest thinking on a topic

Educational institutions, such as schools and colleges, create a lot of research-based reports on younger audiences or their academic specialisms. Dissertations from students also can be submitted to research journals, making these places useful places to see the latest insights from a new generation of academics.

Information can be requested — and sometimes academic institutions may want to collaborate and conduct research on your behalf. This can provide key primary data in areas that you want to research, as well as secondary data sources for your research.

Advantages of secondary research

There are several benefits of using secondary research, which we’ve outlined below:

• Easily and readily available data – There is an abundance of readily accessible data sources that have been pre-collected for use, in person at local libraries and online using the internet. This data is usually sorted by filters or can be exported into spreadsheet format, meaning that little technical expertise is needed to access and use the data.
• Faster research speeds – Since the data is already published and in the public arena, you don’t need to collect this information through primary research. This can make the research easier to do and faster, as you can get started with the data quickly.
• Low financial and time costs – Most secondary data sources can be accessed for free or at a small cost to the researcher, so the overall research costs are kept low. In addition, by saving on preliminary research, the time costs for the researcher are kept down as well.
• Secondary data can drive additional research actions – The insights gained can support future research activities (like conducting a follow-up survey or specifying future detailed research topics) or help add value to these activities.
• Secondary data can be useful pre-research insights – Secondary source data can provide pre-research insights and information on effects that can help resolve whether research should be conducted. It can also help highlight knowledge gaps, so subsequent research can consider this.
• Ability to scale up results – Secondary sources can include large datasets (like Census data results across several states) so research results can be scaled up quickly using large secondary data sources.

Disadvantages of secondary research

The disadvantages of secondary research are worth considering in advance of conducting research :

• Secondary research data can be out of date – Secondary sources can be updated regularly, but if you’re exploring the data between two updates, the data can be out of date. Researchers will need to consider whether the data available provides the right research coverage dates, so that insights are accurate and timely, or if the data needs to be updated. Also, fast-moving markets may find secondary data expires very quickly.
• Secondary research needs to be verified and interpreted – Where there’s a lot of data from one source, a researcher needs to review and analyze it. The data may need to be verified against other data sets or your hypotheses for accuracy and to ensure you’re using the right data for your research.
• The researcher has had no control over the secondary research – As the researcher has not been involved in the secondary research, invalid data can affect the results. It’s therefore vital that the methodology and controls are closely reviewed so that the data is collected in a systematic and error-free way.
• Secondary research data is not exclusive – As data sets are commonly available, there is no exclusivity and many researchers can use the same data. This can be problematic where researchers want to have exclusive rights over the research results and risk duplication of research in the future.

When do we conduct secondary research?

Now that you know the basics of secondary research, when do researchers normally conduct secondary research?

It’s often used at the beginning of research, when the researcher is trying to understand the current landscape . In addition, if the research area is new to the researcher, it can form crucial background context to help them understand what information exists already. This can plug knowledge gaps, supplement the researcher’s own learning or add to the research.

Secondary research can also be used in conjunction with primary research. Secondary research can become the formative research that helps pinpoint where further primary research is needed to find out specific information. It can also support or verify the findings from primary research.

You can use secondary research where high levels of control aren’t needed by the researcher, but a lot of knowledge on a topic is required from different angles.

Secondary research should not be used in place of primary research as both are very different and are used for various circumstances.

Questions to ask before conducting secondary research

Before you start your secondary research, ask yourself these questions:

• Is there similar internal data that we have created for a similar area in the past?

If your organization has past research, it’s best to review this work before starting a new project. The older work may provide you with the answers, and give you a starting dataset and context of how your organization approached the research before. However, be mindful that the work is probably out of date and view it with that note in mind. Read through and look for where this helps your research goals or where more work is needed.

• What am I trying to achieve with this research?

When you have clear goals, and understand what you need to achieve, you can look for the perfect type of secondary or primary research to support the aims. Different secondary research data will provide you with different information – for example, looking at news stories to tell you a breakdown of your market’s buying patterns won’t be as useful as internal or external data e-commerce and sales data sources.

• How credible will my research be?

If you are looking for credibility, you want to consider how accurate the research results will need to be, and if you can sacrifice credibility for speed by using secondary sources to get you started. Bear in mind which sources you choose — low-credibility data sites, like political party websites that are highly biased to favor their own party, would skew your results.

• What is the date of the secondary research?

When you’re looking to conduct research, you want the results to be as useful as possible , so using data that is 10 years old won’t be as accurate as using data that was created a year ago. Since a lot can change in a few years, note the date of your research and look for earlier data sets that can tell you a more recent picture of results. One caveat to this is using data collected over a long-term period for comparisons with earlier periods, which can tell you about the rate and direction of change.

• Can the data sources be verified? Does the information you have check out?

If you can’t verify the data by looking at the research methodology, speaking to the original team or cross-checking the facts with other research, it could be hard to be sure that the data is accurate. Think about whether you can use another source, or if it’s worth doing some supplementary primary research to replicate and verify results to help with this issue.

We created a front-to-back guide on conducting market research, The ultimate guide to conducting market research , so you can understand the research journey with confidence.

In it, you’ll learn more about:

• What effective market research looks like
• The use cases for market research
• The most important steps to conducting market research
• And how to take action on your research findings

Download the free guide for a clearer view on secondary research and other key research types for your business.

Related resources

Market intelligence 10 min read, marketing insights 11 min read, ethnographic research 11 min read, qualitative vs quantitative research 13 min read, qualitative research questions 11 min read, qualitative research design 12 min read, primary vs secondary research 14 min read, request demo.

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Understanding Nursing Research

• Primary Research
• Qualitative vs. Quantitative Research
• Experimental Design
• Is it a Nursing journal?
• Is it Written by a Nurse?

Secondary Research and Systematic Reviews

Comparative table.

• Quality Improvement Plans

Secondary Research is when researchers collect lots of research that has already been published on a certain subject. They conduct searches in databases, go through lots of primary research articles, and analyze the findings in those pieces of primary research. The goal of secondary research is to pull together lots of diverse primary research (like studies and trials), with the end goal of making a generalized statement. Primary research can only make statements about the specific context in which their research was conducted (for example, this specific intervention worked in this hospital with these participants), but secondary research can make broader statements because it compiled lots of primary research together. So rather than saying, "this specific intervention worked at this specific hospital with these specific participants, a piece of secondary research can say, "This intervention works at hospitals that serve this population."

Systematic Reviews are a kind of secondary research. The creators of systematic reviews are very intentional about their inclusion/exclusion criteria, or which articles they'll include in their review and the goal is to make a generalized statement so other researchers can build upon the practices or interventions they recommend. Use the chart below to understand the differences between a systematic review and a literature review.

Check out the video below to watch the Nursing and Health Sciences librarian describe the differences between primary and secondary research.

• "Literature Reviews and Systematic Reviews: What Is the Difference?" This article explains in depth the differences between Literature Reviews and Systematic Reviews. It is from the journal RADIOLOGIC TECHNOLOGY, Nov/Dec 2013, v. 85, #2. It is one to which Bell Library subscribes and meets copyright clearance requirements through our subscription to CCC.
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Home » Secondary Data – Types, Methods and Examples

Secondary Data – Types, Methods and Examples

Table of Contents

Secondary Data

Definition:

Secondary data refers to information that has been collected, processed, and published by someone else, rather than the researcher gathering the data firsthand. This can include data from sources such as government publications, academic journals, market research reports, and other existing datasets.

Secondary Data Types

Types of secondary data are as follows:

• Published data: Published data refers to data that has been published in books, magazines, newspapers, and other print media. Examples include statistical reports, market research reports, and scholarly articles.
• Government data: Government data refers to data collected by government agencies and departments. This can include data on demographics, economic trends, crime rates, and health statistics.
• Commercial data: Commercial data is data collected by businesses for their own purposes. This can include sales data, customer feedback, and market research data.
• Academic data: Academic data refers to data collected by researchers for academic purposes. This can include data from experiments, surveys, and observational studies.
• Online data: Online data refers to data that is available on the internet. This can include social media posts, website analytics, and online customer reviews.
• Organizational data: Organizational data is data collected by businesses or organizations for their own purposes. This can include data on employee performance, financial records, and customer satisfaction.
• Historical data : Historical data refers to data that was collected in the past and is still available for research purposes. This can include census data, historical documents, and archival records.
• International data: International data refers to data collected from other countries for research purposes. This can include data on international trade, health statistics, and demographic trends.
• Public data : Public data refers to data that is available to the general public. This can include data from government agencies, non-profit organizations, and other sources.
• Private data: Private data refers to data that is not available to the general public. This can include confidential business data, personal medical records, and financial data.
• Big data: Big data refers to large, complex datasets that are difficult to manage and analyze using traditional data processing methods. This can include social media data, sensor data, and other types of data generated by digital devices.

Secondary Data Collection Methods

Secondary Data Collection Methods are as follows:

• Published sources: Researchers can gather secondary data from published sources such as books, journals, reports, and newspapers. These sources often provide comprehensive information on a variety of topics.
• Online sources: With the growth of the internet, researchers can now access a vast amount of secondary data online. This includes websites, databases, and online archives.
• Government sources : Government agencies often collect and publish a wide range of secondary data on topics such as demographics, crime rates, and health statistics. Researchers can obtain this data through government websites, publications, or data portals.
• Commercial sources: Businesses often collect and analyze data for marketing research or customer profiling. Researchers can obtain this data through commercial data providers or by purchasing market research reports.
• Academic sources: Researchers can also obtain secondary data from academic sources such as published research studies, academic journals, and dissertations.
• Personal contacts: Researchers can also obtain secondary data from personal contacts, such as experts in a particular field or individuals with specialized knowledge.

Secondary Data Formats

Secondary data can come in various formats depending on the source from which it is obtained. Here are some common formats of secondary data:

• Numeric Data: Numeric data is often in the form of statistics and numerical figures that have been compiled and reported by organizations such as government agencies, research institutions, and commercial enterprises. This can include data such as population figures, GDP, sales figures, and market share.
• Textual Data: Textual data is often in the form of written documents, such as reports, articles, and books. This can include qualitative data such as descriptions, opinions, and narratives.
• Audiovisual Data : Audiovisual data is often in the form of recordings, videos, and photographs. This can include data such as interviews, focus group discussions, and other types of qualitative data.
• Geospatial Data: Geospatial data is often in the form of maps, satellite images, and geographic information systems (GIS) data. This can include data such as demographic information, land use patterns, and transportation networks.
• Transactional Data : Transactional data is often in the form of digital records of financial and business transactions. This can include data such as purchase histories, customer behavior, and financial transactions.
• Social Media Data: Social media data is often in the form of user-generated content from social media platforms such as Facebook, Twitter, and Instagram. This can include data such as user demographics, content trends, and sentiment analysis.

Secondary Data Analysis Methods

Secondary data analysis involves the use of pre-existing data for research purposes. Here are some common methods of secondary data analysis:

• Descriptive Analysis: This method involves describing the characteristics of a dataset, such as the mean, standard deviation, and range of the data. Descriptive analysis can be used to summarize data and provide an overview of trends.
• Inferential Analysis: This method involves making inferences and drawing conclusions about a population based on a sample of data. Inferential analysis can be used to test hypotheses and determine the statistical significance of relationships between variables.
• Content Analysis: This method involves analyzing textual or visual data to identify patterns and themes. Content analysis can be used to study the content of documents, media coverage, and social media posts.
• Time-Series Analysis : This method involves analyzing data over time to identify trends and patterns. Time-series analysis can be used to study economic trends, climate change, and other phenomena that change over time.
• Spatial Analysis : This method involves analyzing data in relation to geographic location. Spatial analysis can be used to study patterns of disease spread, land use patterns, and the effects of environmental factors on health outcomes.
• Meta-Analysis: This method involves combining data from multiple studies to draw conclusions about a particular phenomenon. Meta-analysis can be used to synthesize the results of previous research and provide a more comprehensive understanding of a particular topic.

Secondary Data Gathering Guide

Here are some steps to follow when gathering secondary data:

• Define your research question: Start by defining your research question and identifying the specific information you need to answer it. This will help you identify the type of secondary data you need and where to find it.
• Identify relevant sources: Identify potential sources of secondary data, including published sources, online databases, government sources, and commercial data providers. Consider the reliability and validity of each source.
• Evaluate the quality of the data: Evaluate the quality and reliability of the data you plan to use. Consider the data collection methods, sample size, and potential biases. Make sure the data is relevant to your research question and is suitable for the type of analysis you plan to conduct.
• Collect the data: Collect the relevant data from the identified sources. Use a consistent method to record and organize the data to make analysis easier.
• Validate the data: Validate the data to ensure that it is accurate and reliable. Check for inconsistencies, missing data, and errors. Address any issues before analyzing the data.
• Analyze the data: Analyze the data using appropriate statistical and analytical methods. Use descriptive and inferential statistics to summarize and draw conclusions from the data.
• Interpret the results: Interpret the results of your analysis and draw conclusions based on the data. Make sure your conclusions are supported by the data and are relevant to your research question.
• Communicate the findings : Communicate your findings clearly and concisely. Use appropriate visual aids such as graphs and charts to help explain your results.

Examples of Secondary Data

Here are some examples of secondary data from different fields:

• Healthcare : Hospital records, medical journals, clinical trial data, and disease registries are examples of secondary data sources in healthcare. These sources can provide researchers with information on patient demographics, disease prevalence, and treatment outcomes.
• Marketing : Market research reports, customer surveys, and sales data are examples of secondary data sources in marketing. These sources can provide marketers with information on consumer preferences, market trends, and competitor activity.
• Education : Student test scores, graduation rates, and enrollment statistics are examples of secondary data sources in education. These sources can provide researchers with information on student achievement, teacher effectiveness, and educational disparities.
• Finance : Stock market data, financial statements, and credit reports are examples of secondary data sources in finance. These sources can provide investors with information on market trends, company performance, and creditworthiness.
• Social Science : Government statistics, census data, and survey data are examples of secondary data sources in social science. These sources can provide researchers with information on population demographics, social trends, and political attitudes.
• Environmental Science : Climate data, remote sensing data, and ecological monitoring data are examples of secondary data sources in environmental science. These sources can provide researchers with information on weather patterns, land use, and biodiversity.

Purpose of Secondary Data

The purpose of secondary data is to provide researchers with information that has already been collected by others for other purposes. Secondary data can be used to support research questions, test hypotheses, and answer research objectives. Some of the key purposes of secondary data are:

• To gain a better understanding of the research topic : Secondary data can be used to provide context and background information on a research topic. This can help researchers understand the historical and social context of their research and gain insights into relevant variables and relationships.
• To save time and resources: Collecting new primary data can be time-consuming and expensive. Using existing secondary data sources can save researchers time and resources by providing access to pre-existing data that has already been collected and organized.
• To provide comparative data : Secondary data can be used to compare and contrast findings across different studies or datasets. This can help researchers identify trends, patterns, and relationships that may not have been apparent from individual studies.
• To support triangulation: Triangulation is the process of using multiple sources of data to confirm or refute research findings. Secondary data can be used to support triangulation by providing additional sources of data to support or refute primary research findings.
• To supplement primary data : Secondary data can be used to supplement primary data by providing additional information or insights that were not captured by the primary research. This can help researchers gain a more complete understanding of the research topic and draw more robust conclusions.

When to use Secondary Data

Secondary data can be useful in a variety of research contexts, and there are several situations in which it may be appropriate to use secondary data. Some common situations in which secondary data may be used include:

• When primary data collection is not feasible : Collecting primary data can be time-consuming and expensive, and in some cases, it may not be feasible to collect primary data. In these situations, secondary data can provide valuable insights and information.
• When exploring a new research area : Secondary data can be a useful starting point for researchers who are exploring a new research area. Secondary data can provide context and background information on a research topic, and can help researchers identify key variables and relationships to explore further.
• When comparing and contrasting research findings: Secondary data can be used to compare and contrast findings across different studies or datasets. This can help researchers identify trends, patterns, and relationships that may not have been apparent from individual studies.
• When triangulating research findings: Triangulation is the process of using multiple sources of data to confirm or refute research findings. Secondary data can be used to support triangulation by providing additional sources of data to support or refute primary research findings.
• When validating research findings : Secondary data can be used to validate primary research findings by providing additional sources of data that support or refute the primary findings.

Characteristics of Secondary Data

Secondary data have several characteristics that distinguish them from primary data. Here are some of the key characteristics of secondary data:

• Non-reactive: Secondary data are non-reactive, meaning that they are not collected for the specific purpose of the research study. This means that the researcher has no control over the data collection process, and cannot influence how the data were collected.
• Time-saving: Secondary data are pre-existing, meaning that they have already been collected and organized by someone else. This can save the researcher time and resources, as they do not need to collect the data themselves.
• Wide-ranging : Secondary data sources can provide a wide range of information on a variety of topics. This can be useful for researchers who are exploring a new research area or seeking to compare and contrast research findings.
• Less expensive: Secondary data are generally less expensive than primary data, as they do not require the researcher to incur the costs associated with data collection.
• Potential for bias : Secondary data may be subject to biases that were present in the original data collection process. For example, data may have been collected using a biased sampling method or the data may be incomplete or inaccurate.
• Lack of control: The researcher has no control over the data collection process and cannot ensure that the data were collected using appropriate methods or measures.
• Requires careful evaluation : Secondary data sources must be evaluated carefully to ensure that they are appropriate for the research question and analysis. This includes assessing the quality, reliability, and validity of the data sources.

Advantages of Secondary Data

There are several advantages to using secondary data in research, including:

• Time-saving : Collecting primary data can be time-consuming and expensive. Secondary data can be accessed quickly and easily, which can save researchers time and resources.
• Cost-effective: Secondary data are generally less expensive than primary data, as they do not require the researcher to incur the costs associated with data collection.
• Large sample size : Secondary data sources often have larger sample sizes than primary data sources, which can increase the statistical power of the research.
• Access to historical data : Secondary data sources can provide access to historical data, which can be useful for researchers who are studying trends over time.
• No ethical concerns: Secondary data are already in existence, so there are no ethical concerns related to collecting data from human subjects.
• May be more objective : Secondary data may be more objective than primary data, as the data were not collected for the specific purpose of the research study.

Limitations of Secondary Data

While there are many advantages to using secondary data in research, there are also some limitations that should be considered. Some of the main limitations of secondary data include:

• Lack of control over data quality : Researchers do not have control over the data collection process, which means they cannot ensure the accuracy or completeness of the data.
• Limited availability: Secondary data may not be available for the specific research question or study design.
• Lack of information on sampling and data collection methods: Researchers may not have access to information on the sampling and data collection methods used to gather the secondary data. This can make it difficult to evaluate the quality of the data.
• Data may not be up-to-date: Secondary data may not be up-to-date or relevant to the current research question.
• Data may be incomplete or inaccurate : Secondary data may be incomplete or inaccurate due to missing or incorrect data points, data entry errors, or other factors.
• Biases in data collection: The data may have been collected using biased sampling or data collection methods, which can limit the validity of the data.
• Lack of control over variables: Researchers have limited control over the variables that were measured in the original data collection process, which can limit the ability to draw conclusions about causality.

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Chapter Six: Reviewing the Secondary Literature / Types of Literature Reviews / Reading Like a Researcher

Reviewing the Secondary Literature

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Topics discussed on this page include:

What is the Purpose of the Review?

The annotated bibliography, the literature review, what do we mean by literature, what is the scope of the review.

The literature review provides your reader of an overview of the existing research about your topic or problem. Creating the literature review involves more than gathering citations. It is a qualitative process through which you will discover what is already known about your topic, and identify the key authorities, methods, and theoretical foundations so you can begin to position your contributions within the scholarly conversation.

Further, the literature review sharpens the focus of your research and demonstrates your knowledge and understanding of the scholarly conversation around your topic, which in turn helps establish your credibility as a researcher.

We suggest you begin putting your research together by making an annotated bibliography  (or  annotated list of sources ), then synthesize your research sources by looking for through lines in them (arguments, narratives, trends, etc.), then determine which type of literature review  works best for your project (we discuss these types on the following page). To help you gather annotated materials in one place, we provide a matrix tool   that helps you organize and synthesize your research. The annotated bibliography serves numerous purposes:

• It organizes your research findings in one place, and provides a handy reference while you are completing your research project.
• If you will be writing a literature review for your research project, compiling an annotated bibliography is a great first step.
• If you decide to include the annotated bibliography in your research project, it will allow readers to explore these sources on their own.

The annotated bibliography, unlike the literature review, does not need to be essayistic. To create an annotated bibliography, use either the matrix tool or write a separate paragraph for each entry. An annotated bibliography organizes sources alphabetically and explains not only a summary of each source, but also addresses the source’s credibility and explains its relevance to your research project. An example of an annotated bibliography , created by UCF student Dolores Batten, explains how her readings related to her research project (which was to develop methods for improving student writing).

Writing a literary studies research paper involves time and effort, with much of it going towards the development of a  literature review .  A literature review might fill several pages of your research paper and usually appears soon after an introduction and before you present your analysis. A literature review provides your audience with an overview of the available research about your area(s) of study, including the literary work, your theory, and methodology. The literature review demonstrates how these scholarly discussions have changed over time and it allows you to position your research in relation to research that has come before yours. Your aim is to narrate the discussion up to this point. Depending on the nature of the assignment, you may also include your critical commentary on prior research, noting among this material the weaker and stronger arguments, breakthroughs and dead ends, blind spots and opportunities, the invention of key terms and methods, mistakes as well as misreadings, and so on.

Once you have gathered the research materials you need for your literature review, you have yet another task in front of you: conducting an analysis on said research for your original contribution, which is the part where you discover and bring something new to the conversation. As the saying goes, “we are standing on the shoulders of giants.” Your job is to show a portrait to your audience of these giants and to show how your work relates to it.

Some beginning researchers try to tear down the work of other researchers in an effort to make their own work look good by comparison. It rarely works. First, it tends to make your audience justly skeptical of your claims. Second, it ignores the fact that even the mistakes, blind spots, and failures of other researchers contribute something to our knowledge. Albert Einstein didn’t trash Sir Isaac Newton by saying his theory of space was wrong and terrible and that his own theory was great by comparison. He built upon Newton’s work, showing how it could be improved. If, however, a researcher willfully set out to deceive others, then their work does not deserve such deference.

Before you begin work on your literature review, let’s discuss what we mean by “literature,” understand the purpose and scope of the review, establish criteria for selecting, organizing, and interpreting your findings, and, finally, discuss how to connect your findings to your research question.

When we use the word “literature” in the phrase “literature review,” we are not talking about literary writing such as novels, poems, and plays, but about scholarly research. Our objective is to tell the story of research up to the point when you add your own contribution. You should use this time to think about what types of information and resources you will need to complete your project. In the case of literary studies, we often start with peer-reviewed journal articles and scholarly monographs (books) that can be accessed through the library catalog and subject databases. These are both essential resources, but you may need more.

For Jada’s research project about James Baldwin’s ‘Sonny’s Blues,” we might also think about exploring newspapers and primary source collections related to civil rights, African American studies, and social activism. Other topics might require different types of media, data sets, case studies, etc.

More about searching for these sources will be discussed in the library resources portion. In the meantime, let’s break down the literature review a little further.

Defining the scope of your review will also help you establish criteria to determine the relevance of the sources you are finding. At this stage, you are not reading in-depth; you are taking snapshots of what has been published, identifying major concepts, theories, methodologies, and methods while identifying connections, tensions, and contradictions within what Michael Patton calls the “intellectual heritage” of your topic or problem.

This work involves building on the knowledge of others and understanding what methods, measures, and models we have inherited from previous researchers in our field.

For more about Dr. Patton’s thoughts on the literature review, watch this short video:

Video provided courtesy of the Center for Quality Research (CQR)

Before we take a look at types of reviews, here are some key Dos and Don’ts:

Strategies for Conducting Literary Research Copyright © 2021 by Barry Mauer & John Venecek is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Primary Research vs Secondary Research: A Comparative Analysis

Understand the differences between primary research vs secondary research. Learn how they can be used to generate valuable insights.

Primary research and secondary research are two fundamental approaches used in research studies to gather information and explore topics of interest. Both primary and secondary research offer unique advantages and have their own set of considerations, making them valuable tools for researchers in different contexts.

Understanding the distinctions between primary and secondary research is crucial for researchers to make informed decisions about the most suitable approach for their study objectives and available resources.

What is Primary Research?

Primary research refers to the collection and analysis of data directly from original sources. It involves gathering information directly to address specific research objectives and generate new insights. This research method conducts surveys, interviews, observations, experiments, or focus groups to obtain data that is relevant to the research question at hand. By engaging directly with subjects or sources, primary research provides firsthand and up-to-date information, allowing researchers to have control over the data collection process and adjust it to their specific needs.

Types of Primary Research

There are several types of primary research methods commonly used in various fields:

Surveys are the systematic collection of data through questionnaires or interviews, aiming to gather information from a large number of participants. Surveys can be conducted in person, over the phone, through mail, or online.

Interviews entail direct one-on-one or group interactions with individuals or key informants to obtain detailed information about their experiences, opinions, or expertise. Interviews can be structured (using predetermined questions) or unstructured (allowing for open-ended discussions).

Observations

Observational research carefully observes and documents behaviors, interactions, or phenomena in real-life settings. It can be done in a participant or non-participant manner, depending on the level of involvement of the researcher.

Data analysis

Examining and interpreting collected data, data analysis uncovers patterns, trends, and insights, providing a deeper understanding of the research topic. It enables drawing meaningful conclusions for decision-making and guides further research.

Focus groups

Focus groups facilitated group discussions with a small number of participants who shared their opinions, attitudes, and experiences on a specific topic. This method allows for interactive and in-depth exploration of a subject.

Benefits of Primary Research

Original and specific data: Primary research provides first hand data directly relevant to the research objectives, ensuring its freshness and specificity to the research context.

Control over data collection: Researchers have control over the design, implementation, and data collection process, allowing them to adapt the research methods and instruments to suit their needs.

Depth of understanding: Primary research methods, such as interviews and focus groups, enable researchers to gain a deep understanding of participants’ perspectives, experiences, and motivations.

Validity and reliability: By directly collecting data from original sources, primary research enhances the validity and reliability of the findings, reducing potential biases associated with using secondary or existing data.

Challenges of Primary Research

Time and Resource-intensive: Primary research requires careful planning, data collection, analysis, and interpretation. It may require recruiting participants, conducting interviews or surveys, and analyzing data, all of which require time and resources.

Sampling limitations: Primary research often relies on sampling techniques to select participants. Ensuring a representative sample that accurately reflects the target population can be challenging, and sampling biases may affect the generalizability of the findings.

Subjectivity: The involvement of researchers in primary research methods, such as interviews or observations, introduces the potential for subjective interpretations or biases that can influence the data collection and analysis process.

Limited generalizability: Findings from primary research may have limited generalizability due to the specific characteristics of the sample or context. It is essential to acknowledge the scope and limitations of the findings and avoid making broad generalizations beyond the studied sample or context.

What is Secondary Research?

It is a method of research that relies on data that is readily available, rather than gathering new data through primary research methods. Secondary research relies on reviewing and analyzing sources such as published studies, reports, articles, books, government databases, and online resources to extract relevant information for a specific research objective.

Sources of Secondary Research

Published studies and academic journals.

Researchers can review published studies and academic journals to gather information, data, and findings related to their research topic. These sources often provide comprehensive and in-depth analyses of specific subjects.

Reports and white papers

Reports and white papers produced by research organizations, government agencies, and industry associations provide valuable data and insights on specific topics or sectors. These documents often contain statistical data, market research, trends, and expert opinions.

Books and reference materials

Books and reference materials written by experts in a particular field can offer comprehensive overviews, theories, and historical perspectives that contribute to secondary research.

Online databases

Online databases, such as academic libraries, research repositories, and specialized platforms, provide access to a vast array of published research articles, theses, dissertations, and conference proceedings.

Benefits of Secondary Research

Time and Cost-effectiveness: Secondary research saves time and resources since the data and information already exist and are readily accessible. Researchers can utilize existing resources instead of conducting time-consuming primary research.

Wide range of data: Secondary research provides access to a wide range of data sources, including large-scale surveys, census data, and comprehensive reports. This allows researchers to explore diverse perspectives and make comparisons across different studies.

Comparative analyses: Researchers can compare findings from different studies or datasets, allowing for cross-referencing and verification of results. This enhances the robustness and validity of research outcomes.

Ethical considerations: Secondary research does not involve direct interaction with participants, which reduces ethical concerns related to privacy, informed consent, and confidentiality.

Challenges of Secondary Research

Data availability and quality: The availability and quality of secondary data can vary. Researchers must critically evaluate the credibility, reliability, and relevance of the sources to ensure the accuracy of the information used in their research.

Limited control over data: Researchers have limited control over the design, collection methods, and variables included in the secondary data. The data may not perfectly align with the research objectives, requiring careful selection and analysis.

Potential bias and outdated information: Secondary data may contain inherent biases or limitations introduced by the original researchers. Additionally, the data may become outdated, and newer information or developments may not be captured.

Lack of customization: Since secondary data is collected for various purposes, it may not perfectly align with the specific research needs. Researchers may encounter limitations in terms of variables, definitions, or granularity of data.

Comparing Primary and Secondary Research

Primary research vs secondary research, examples of primary and secondary research, examples of primary research.

• Conducting a survey to collect data on customer satisfaction and preferences for a new product directly from the target audience.
• Designing and conducting an experiment to test the effectiveness of a new teaching method by comparing the learning outcomes of students in different groups.
• Observing and documenting the behavior of a specific animal species in its natural habitat to gather data for ecological research.
• Organizing a focus group with potential consumers to gather insights and feedback on a new advertising campaign.
• Conducting interviews with healthcare professionals to understand their experiences and perspectives on a specific medical treatment.

Examples of Secondary Research

• Accessing a market research report to gather information on consumer trends, market size, and competitor analysis in the smartphone industry.
• Using existing government data on unemployment rates to analyze the impact of economic policies on employment patterns.
• Examining historical records and letters to understand the political climate and social conditions during a particular historical event.
• Conducting a meta-analysis of published studies on the effectiveness of a specific medication to assess its overall efficacy and safety.

How to Use Primary and Secondary Research Together

Having explored the distinction between primary research vs secondary research, the integration of these two approaches becomes a crucial consideration. By incorporating primary and secondary research, a comprehensive and well-informed research methodology can be achieved. The utilization of secondary research provides researchers with a broader understanding of the subject, allowing them to identify gaps in knowledge and refine their research questions properly.

Primary research methods, such as surveys or interviews, can then be employed to collect new data that directly address these research questions. The findings from primary research can be compared and validated against the existing knowledge obtained through secondary research. By combining the insights from both types of research, researchers can fill knowledge gaps, strengthen the reliability of their findings through triangulation, and draw meaningful conclusions that contribute to the overall understanding of the subject matter.

Ethical Considerations for Primary and Secondary Research

In primary research, researchers must obtain informed consent from participants, ensuring they are fully aware of the study’s purpose, procedures, and any potential risks or benefits involved. Confidentiality and anonymity should be maintained to safeguard participants’ privacy. Researchers should also ensure that the data collection methods and research design are conducted in an ethical manner, adhering to ethical guidelines and standards set by relevant institutional review boards or ethics committees.

In secondary research, ethical considerations primarily revolve around the proper and responsible use of existing data sources. Researchers should respect copyright laws and intellectual property rights when accessing and using secondary data. They should also critically evaluate the credibility and reliability of the sources to ensure the validity of the data used in their research. Proper citation and acknowledgment of the original sources are essential to maintain academic integrity and avoid plagiarism.

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Mentorship in Health Research Institutions in Africa: A Systematic Review of Approaches, Benefits, Successes, Gaps and Challenges

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Background In Africa, where the burden of diseases is disproportionately high, significant challenges arise from a shortage of skilled researchers, lack of research funding, and limited mentorship opportunities. The continent faces a substantial gap in research output largely attributed to the dearth of mentorship opportunities for early career researchers.

Objective To explore existing mentorship approaches, identify challenges, gaps, successes, and benefits, and provide insights for strengthening mentorship programs in African health research institutions.

Methods We registered the review protocol on the International Prospective Register of Systematic Reviews [CRD42021285018] and searched six electronic databases – EMBASE, AJOL, Web of Science, PubMed, DOAJ and JSTOR from inception to 10 November 2023, for studies published in English reporting on approaches of mentorship in health research in African countries. We also searched grey literature repositories, institutional websites, and reference lists of included studies for additional literature. Two independent reviewers conducted screening of titles and abstracts of identified studies, full-text screening, assessment of methodological quality, and data extraction. We assessed study quality against the Mixed Methods Appraisal Tool (MMAT). We resolved any disagreements through discussion and consensus. We employed a narrative approach to synthesize the findings.

Results We retrieved 1799 articles and after screening, included 21 studies in the review. The reviewers identified 20 mentorship programs for health researchers (N=1198) in 12 African countries mostly focusing on early career researchers and junior faculty members. A few included mid-career and senior researchers. We categorized the programs under three key mentoring approaches: international collaborative programs, regional and in-country collaborations, and specialized capacity-building initiatives. Our review highlighted the following successes and benefits of health research mentorship programs: the establishment of collaborations and partnerships, development of research programs and capacities, improvement of individual skills and confidence, increased publications, and successful grant applications. The gaps identified were limited funding, lack of a mentorship culture, negative attitudes towards research careers, and lack of prioritization of research mentorship.

Conclusion Our review highlights a diverse landscape of health research mentorship aspects predominantly targeting early career researchers and heavily driven by the North. There is a need for locally driven mentorship initiatives in Africa to strengthen mentorship in order to advance health research in the region.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This work received funding from the African Research Excellent Fund (AREF) through the Research and Related Capacity Strengthening (RRCS) unit at the African Population and Health Research Center. The funder had no role in the design, execution, synthesis, interpretation or decision to publish this manuscript.

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The article is a systematic review that synthesized secondary data. No ethical approval was required.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Data Availability

Data underlying the findings for this review has been provided as part of the submitted article in the supplementary information.

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• Iran J Public Health
• v.42(12); 2013 Dec

Secondary Data Analysis: Ethical Issues and Challenges

Research does not always involve collection of data from the participants. There is huge amount of data that is being collected through the routine management information system and other surveys or research activities. The existing data can be analyzed to generate new hypothesis or answer critical research questions. This saves lots of time, money and other resources. Also data from large sample surveys may be of higher quality and representative of the population. It avoids repetition of research & wastage of resources by detailed exploration of existing research data and also ensures that sensitive topics or hard to reach populations are not over researched ( 1 ). However, there are certain ethical issues pertaining to secondary data analysis which should be taken care of before handling such data.

Secondary data analysis

Secondary analysis refers to the use of existing research data to find answer to a question that was different from the original work ( 2 ). Secondary data can be large scale surveys or data collected as part of personal research. Although there is general agreement about sharing the results of large scale surveys, but little agreement exists about the second. While the fundamental ethical issues related to secondary use of research data remain the same, they have become more pressing with the advent of new technologies. Data sharing, compiling and storage have become much faster and easier. At the same time, there are fresh concerns about data confidentiality and security.

Issues in Secondary data analysis

Concerns about secondary use of data mostly revolve around potential harm to individual subjects and issue of return for consent. Secondary data vary in terms of the amount of identifying information in it. If the data has no identifying information or is completely devoid of such information or is appropriately coded so that the researcher does not have access to the codes, then it does not require a full review by the ethical board. The board just needs to confirm that the data is actually anonymous. However, if the data contains identifying information on participants or information that could be linked to identify participants, a complete review of the proposal will then be made by the board. The researcher will then have to explain why is it unavoidable to have identifying information to answer the research question and must also indicate how participants’ privacy and the confidentiality of the data will be protected. If the above said concerns are satisfactorily addressed, the researcher can then request for a waiver of consent.

If the data is freely available on the Internet, books or other public forum, permission for further use and analysis is implied. However, the ownership of the original data must be acknowledged. If the research is part of another research project and the data is not freely available, except to the original research team, explicit, written permission for the use of the data must be obtained from the research team and included in the application for ethical clearance.

However, there are certain other issues pertaining to the data that is procured for secondary analysis. The data obtained should be adequate, relevant but not excessive. In secondary data analysis, the original data was not collected to answer the present research question. Thus the data should be evaluated for certain criteria such as the methodology of data collection, accuracy, period of data collection, purpose for which it was collected and the content of the data. It shall be kept for no longer than is necessary for that purpose. It must be kept safe from unauthorized access, accidental loss or destruction. Data in the form of hardcopies should be kept in safe locked cabinets whereas softcopies should be kept as encrypted files in computers. It is the responsibility of the researcher conducting the secondary analysis to ensure that further analysis of the data conducted is appropriate. In some cases there is provision for analysis of secondary data in the original consent form with the condition that the secondary study is approved by the ethics review committee. According to the British Sociological Association’s Statement of Ethical Practice (2004) the researchers must inform participants regarding the use of data and obtain consent for the future use of the material as well. However it also says that consent is not a once-and-for-all event, but is subject to renegotiation over time ( 3 ). It appears that there are no guidelines about the specific conditions that require further consent.

Issues in Secondary analysis of Qualitative data

In qualitative research, the culture of data archiving is absent ( 4 ). Also, there is a concern that data archiving exposes subject’s personal views. However, the best practice is to plan anonymisation at the time of initial transcription. Use of pseudonyms or replacements can protect subject’s identity. A log of all replacements, aggregations or removals should be made and stored separately from the anonymised data files. But because of the circumstances, under which qualitative data is produced, their reinterpretation at some later date can be challenging and raises further ethical concerns.

There is a need for formulating specific guidelines regarding re-use of data, data protection and anonymisation and issues of consent in secondary data analysis.

Acknowledgements

The authors declare that there is no conflict of interest.

• Fielding NG, Fielding JL (2003). Resistance and adaptation to criminal identity: Using secondary analysis to evaluate classic studies of crime and deviance . Sociology , 34 ( 4 ): 671–689. [ Google Scholar ]
• Szabo V, Strang VR (1997). Secondary analysis of qualitative data . Advances in Nursing Science , 20 ( 2 ): 66–74. [ PubMed ] [ Google Scholar ]
• Statement of Ethical Practice for the British Sociological Association (2004). The British Sociological Association, Durham . Available at: http://www.york.ac.uk/media/abouttheuniversity/governanceandmanagement/governance/ethicscommittee/hssec/documents/BSA%20statement%20of%20ethical%20practice.pdf (Last accessed 24November2013)
• Archiving Qualitative Data: Prospects and Challenges of Data Preservation and Sharing among Australian Qualitative Researchers. Institute for Social Science Research, The University of Queensland, 2009 . Available at: http://www.assda.edu.au/forms/AQuAQualitativeArchiving_DiscussionPaper_FinalNov09.pdf (Last accessed 05September2013)

Understanding Artificial Intelligence with the IRB: Ethics and Advice

Understanding artificial intelligence with the irb: ethical considerations and advice for responsible research in the ai era, as ai tools become more accessible, tc irb discusses the ethics and considerations when using ai in research protocols..

With the surge of help from Generative AI research tools, nowadays is certainly “the most exciting time to be a researcher”, said Shwetak Patel, director of Google’s health technologies and a professor at the University of Washington (Jones, 2023). Researchers now have access to various platforms like Elicit and Consensus which curate a customized archive to assist with literature review, and even to a data analysis tool by ChatGPT. In the middle of this revolutionary era for AI research tools, researchers should consider the ethical impact of AI. This blog post will discuss the ethics and risks involved with using AI in research. We will discuss where the data comes from and the black box AI is utilizing. 

Where Does the Data that AI Use Comes From? To make AI generate answers, engineers first feed vast datasets to AI, a method known as machine learning. Data scraping is the stem of the datasets necessary for training machine learning models. Data scraping involves extracting information from sources such as social media pages and video-sharing sites. Large AI companies often deploy automatic data scraping technology extensively, raising ethical questions and doubts about the origin and usage of the collected data (Macapinlac, 2019). Two significant concerns are 1. the use of copyrighted material in AI training datasets, and 2. Violation of private data, both without proper permission.

First, is the issue of copyright infringement. When collecting large amounts of data to train AI, especially through automated methods, there's a risk of overlooking copyright issues due to the massive volume of data (Riley, 2018). With the rise of generative AI for profit, some decided to tackle this process. An example is Stability AI's Stable Diffusion, a text-to-image generator, which uses datasets from a non-profit organization funded by Stability AI. An investigation revealed that their dataset contained over a million images from sources like Pinterest, WordPress blogs, Flickr, Getty, and DeviantArt without permission, raising questions about copyright infringement. As a result, Getty Images filed a lawsuit against Stability AI over using their copyright issues (Vincent, 2023). This does not only go for companies but is way more critical for individual content creators, who often rely on the integrity and proper use of their work for their livelihood.

In addition to the concerns of copyright infringement, there’s the pressing issue of privacy violation in data scraping. When the data is scrapped from people’s private social media to train the AI model, the data inevitably contains “private information, including personally identifiable information, from hundreds of millions of internet users, including children of all ages, without their informed consent or knowledge.” (Reily, 2023). OpenAI, the company that created chat GPT, is facing a lawsuit for scraping private information from millions of internet users thereby breaching privacy without consent. “They’re taking personal data that has been shared for one purpose and using it for a completely different purpose without the consent of those who shared the data,” said Timothy Edgar, professor of practice of computer science at Brown University. “It is by definition, a privacy violation, or at least an ethical violation, and it might be a legal violation.” This not only is a privacy violation but stems further into a deeper problem when it’s generative AI. The generated answers when a random user asks questions could include private information, and it’ll be difficult to claw back the violated data (Reily, 2023). Considering the ethical conundrum of AI, researchers utilizing generative AI tools must be mindful of these ethical considerations, ensuring they respect copyright laws and the rights of content creators. 

The Black Box Problem: How Does AI Make Decisions?

Now that we understand the ethical challenges associated with the types of data used to train AI, there's another crucial aspect that remains unclear. How do these AI models function once they are trained with vast amounts of data? What processes do they use to make decisions? Many AIs operate as "black boxes". This “black box problem”, while the term itself is still undefined and under discussion, occurs whenever the reasons why an AI decision-maker has arrived at its decision are not understandable because the system itself is not understandable (Wadden, 2023). This issue can lead to complex ethical issues, as seen in 2015 when the Mount Sinai Hospital research team’s use of deep learning on patient records led to the development of Deep Patient (Miotto et al., 2016). The Deep Patient system could predict psychiatric disorders like schizophrenia without revealing how it reached these conclusions, leaving doctors puzzled about its decision-making process. This case raises ethical concerns about how physicians can confidently inform patients about potential health issues without understanding the AI's reasoning.

Using black box technology creates a worse issue when used in contexts without transparency. Since the training data contains human bias, AI can reproduce or even exacerbate the bias leading to social issues. For instance, an AI was used to predict the likelihood of committing a future crime, and a black male with a previous record of petty theft was rated higher than a white male who had been convicted of armed robbery, mirroring the prevalent social bias (Angwin et al., 2016). Of course, we cannot blame AI for magnifying the bias as it is rather a reflection of human bias. However, since AI is hidden under a black veil and we can’t trace the system's thought process and see why it made this decision (Blouin, 2023), researchers should be extra cautious in using AI in their research. Researchers should double-check if their research result using AI is a result of strengthened bias, especially toward a vulnerable population. 

Additionally, the emergence of generative AI raises questions about ownership and commercialization rights. When human creators generate digital art using AI systems, the issue of ownership becomes complex, especially when regulations struggle to keep pace with technological advancements (Riley, 2023). Academia is facing the same challenges. There is a consensus amongst journals and research communities that AI models “cannot meet the requirements for authorship as they cannot take responsibility for submitted work. As non-legal entities, they cannot assert the presence or absence of conflicts of interest nor manage copyright and license agreements,” (Committee on Publication Ethics [COPE], 2023). While AI is not perceived as an ‘author’, researchers should always disclose the usage of AI in their research. Plus, users must assume responsibility and accountability for the content generated by these tools.

Advice for Using AI in Research

As researchers can rely on AI to assist them in their research, participants can also utilize AI tools. They can create bots that can take online surveys for them and receive compensation. Bot infiltration can be seen frequently when conducting online research and requires time and resources to clean the responses (Griffin et al., 2021). Though there is the convenience of using AI, it also comes with risks in securing privacy for online data management. Disclosing participants’ data outside the study can result in severe consequences and may result in damaging researchers’ careers if they avoid using AI safety protocols. Thus, here are a few tips to decrease the risk of or possibly prevent these adverse events.

1) Know the limits of the AI’s privacy

AI can be used to organize data for research and help with general analysis. However, because AI is evolving, most tools use the data inputted by the user to improve its model. It is best to assume that any information shared with the AI will be shown again in the future. To prevent this, researchers should make sure that any data that interacts with the AI is de-identified. Some AI tools may have privacy and confidentiality policies (i.e. users can turn off chat history) but it may not be safe to rely on this information. Never share any personal information. 

2) Use AI to enhance rather than replace your study

It can be tempting to use AI when researchers are in a bind or do not have the time to write protocols. However, this creates disingenuity to the study if researchers allow these tools to do their work. Just as AI tools are improving and becoming more frequent, some tools detect AI usage. Thus, AI should be used to enhance a study, as researchers can receive information they may have missed when conducting initial research and engage in critical thinking. It’s best not to rely on online tools if researchers do not have secure access to them all the time. Researchers should start with their draft and reread it after using AI. We advise you to use AI as a reviewer, not a creator. When it comes to the consent form and other formal documents, try to read aloud what is AI-generated or reviewed before you proceed, to ensure integrity and clarity. Always keep this in mind: AI can “hallucinate”.

3) Know the institutions’ guidelines on using AI

As AI is quite new, some institutions may not be familiar with or accept the usage of AI. It may violate its code of conduct and result in negative outcomes for the researcher’s career if used carelessly. Thus, it is important to ensure that the AI is approved by institutions and their IRB.  Researchers should consult the “Considerations for IRB Review of Research Involving Artificial Intelligence” resource as it provides guidance for IRB reviewers on how to engage with researchers who propose the use of AI in their studies.

Case: Koko Care’s -  Always disclose and receive consent for AI usage

In January 2023, Rob Morris, co-founder of the online emotional support service Koko, shared results from a contentious experiment. He had GPT-3, an AI, compose responses fully or partially for about 4,000 people seeking mental and emotional support, who believed they were communicating with human volunteers. Although initial satisfaction was high, it plummeted once users learned responses were AI-generated, perceived as 'inauthentic and empty.' Criticism arose not from the result, but because of the process. Users, often in mental health crises, weren't informed they were interacting with AI and could not opt out except by ignoring the responses. “People in mental pain could be made to feel worse, especially if the AI produces biased or careless text that goes unreviewed”, said Leslie Wolf, a Georgia State University law professor (Ingram, 2023). Following the backlash, Morris noted Koko's plans to implement a third-party IRB (Institutional Review Board) process for reviewing product changes. This incident underscores the ethical importance of informed consent in research, especially with AI's inherent biases and privacy concerns. It is a reminder for researchers to responsibly use AI, particularly in studies involving vulnerable groups, and consult resources like “Considerations for IRB Review of Research Involving Artificial Intelligence” for guidance.

Final Thoughts

In conclusion, the growing role of AI in research brings both unparalleled opportunities and significant ethical considerations. While AI tools offer invaluable assistance, researchers must navigate the ethical landscape carefully. Key aspects like data origin, privacy, and the black-box nature of AI decision-making necessitate a thoughtful approach to ensure ethical compliance and respect for individual rights. Remember, only humans can infuse elements of care, intuition, and at times, illogical but necessary decisions into research. Therefore, AI should be viewed not as a replacement but as a supportive tool, augmenting human insight and diligence in the pursuit of knowledge.

Accessible version of the infographic

— Jooyoung Jeon, M.A. & Diana Bae, B.A.

Published Tuesday, May 7, 2024

Institutional Review Board

Address: Russell Hall, Room 13

* Phone: 212-678-4105 * Email:   [email protected]

Appointments are available by request . Make sure to have your IRB protocol number (e.g., 19-011) available.  If you are unable to access any of the downloadable resources, please contact  OASID via email [email protected] .