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Primary vs Secondary Research: Differences, Methods, Sources, and More

Table of Contents

Primary vs Secondary Research – What’s the Difference?

In the search for knowledge and data to inform decisions, researchers and analysts rely on a blend of research sources. These sources are broadly categorized into primary and secondary research, each serving unique purposes and offering different insights into the subject matter at hand. But what exactly sets them apart?

Primary research is the process of gathering fresh data directly from its source. This approach offers real-time insights and specific information tailored to specific objectives set by stakeholders. Examples include surveys, interviews, and observational studies.

Secondary research , on the other hand, involves the analysis of existing data, most often collected and presented by others. This type of research is invaluable for understanding broader trends, providing context, or validating hypotheses. Common sources include scholarly articles, industry reports, and data compilations.

The crux of the difference lies in the origin of the information: primary research yields firsthand data which can be tailored to a specific business question, whilst secondary research synthesizes what's already out there. In essence, primary research listens directly to the voice of the subject, whereas secondary research hears it secondhand .

When to Use Primary and Secondary Research

Selecting the appropriate research method is pivotal and should be aligned with your research objectives. The choice between primary and secondary research is not merely procedural but strategic, influencing the depth and breadth of insights you can uncover.

Primary research shines when you need up-to-date, specific information directly relevant to your study. It's the go-to for fresh insights, understanding consumer behavior, or testing new theories. Its bespoke nature makes it indispensable for tailoring questions to get the exact answers you need.

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Secondary research is your first step into the research world. It helps set the stage by offering a broad understanding of the topic. Before diving into costly primary research, secondary research can validate the need for further investigation or provide a solid background to build upon. It's especially useful for identifying trends, benchmarking, and situating your research within the existing body of knowledge.

Combining both methods can significantly enhance your research. Starting with secondary research lays the groundwork and narrows the focus, whilst subsequent primary research delves deep into specific areas of interest, providing a well-rounded, comprehensive understanding of the topic.

Primary vs Secondary Research Methods

In the landscape of market research, the methodologies employed can significantly influence the insights and conclusions drawn. Let's delve deeper into the various methods underpinning both primary and secondary research, shedding light on their unique applications and the distinct insights they offer.

Primary Research Methods:

• Surveys: Surveys are a cornerstone of primary research, offering a quantitative approach to gathering data directly from the target audience. By employing structured questionnaires, researchers can collect a vast array of data ranging from customer preferences to behavioral patterns. This method is particularly valuable for acquiring statistically significant data that can inform decision-making processes and strategy development. The application of statistical approaches for analysing this data, such as key drivers analysis, MaxDiff or conjoint analysis can also further enhance any collected data.
• One on One Interviews: Interviews provide a qualitative depth to primary research, allowing for a nuanced exploration of participants' attitudes, experiences, and motivations. Conducted either face-to-face or remotely, interviews enable researchers to delve into the complexities of human behavior, offering rich insights that surveys alone may not uncover. This method is instrumental in exploring new areas of research or obtaining detailed information on specific topics.
• Focus Groups: Focus groups bring together a small, diverse group of participants to discuss and provide feedback on a particular subject, product, or idea. This interactive setting fosters a dynamic exchange of ideas, revealing consumers' perceptions, experiences, and preferences. Focus groups are invaluable for testing concepts, exploring market trends, and understanding the factors that influence consumer decisions.
• Ethnographic Studies: Ethnographic studies involve the systematic watching, recording, and analysis of behaviors and events in their natural setting. This method offers an unobtrusive way to gather authentic data on how people interact with products, services, or environments, providing insights that can lead to more user-centered design and marketing strategies.

Secondary Research Methods:

• Literature Reviews: Literature reviews involve the comprehensive examination of existing research and publications on a given topic. This method enables researchers to synthesize findings from a range of sources, providing a broad understanding of what is already known about a subject and identifying gaps in current knowledge.
• Meta-Analysis: Meta-analysis is a statistical technique that combines the results of multiple studies to arrive at a comprehensive conclusion. This method is particularly useful in secondary research for aggregating findings across different studies, offering a more robust understanding of the evidence on a particular topic.
• Content Analysis: Content analysis is a method for systematically analyzing texts, media, or other content to quantify patterns, themes, or biases . This approach allows researchers to assess the presence of certain words, concepts, or sentiments within a body of work, providing insights into trends, representations, and societal norms. This can be performed across a range of sources including social media, customer forums or review sites.
• Historical Research: Historical research involves the study of past events, trends, and behaviors through the examination of relevant documents and records. This method can provide context and understanding of current trends and inform future predictions, offering a unique perspective that enriches secondary research.

Each of these methods, whether primary or secondary, plays a crucial role in the mosaic of market research, offering distinct pathways to uncovering the insights necessary to drive informed decisions and strategies.

Primary vs Secondary Sources in Research

Both primary and secondary sources of research form the backbone of the insight generation process, when both are utilized in tandem it can provide the perfect steppingstone for the generation of real insights. Let’s explore how each category serves its unique purpose in the research ecosystem.

Primary Research Data Sources

Primary research data sources are the lifeblood of firsthand research, providing raw, unfiltered insights directly from the source. These include:

• Customer Satisfaction Survey Results: Direct feedback from customers about their satisfaction with a product or service. This data is invaluable for identifying strengths to build on and areas for improvement and typically renews each month or quarter so that metrics can be tracked over time.
• NPS Rating Scores from Customers: Net Promoter Score (NPS) provides a straightforward metric to gauge customer loyalty and satisfaction. This quantitative data can reveal much about customer sentiment and the likelihood of referrals.
• Ad-hoc Surveys: Ad-hoc surveys can be about any topic which requires investigation, they are typically one off surveys which zero in on one particular business objective. Ad-hoc projects are useful for situations such as investigating issues identified in other tracking surveys, new product development, ad testing, brand messaging, and many other kinds of projects.
• A Field Researcher’s Notes: Detailed observations from fieldwork can offer nuanced insights into user behaviors, interactions, and environmental factors that influence those interactions. These notes are a goldmine for understanding the context and complexities of user experiences.
• Recordings Made During Focus Groups: Audio or video recordings of focus group discussions capture the dynamics of conversation, including reactions, emotions, and the interplay of ideas. Analyzing these recordings can uncover nuanced consumer attitudes and perceptions that might not be evident in survey data alone.

These primary data sources are characterized by their immediacy and specificity, offering a direct line to the subject of study. They enable researchers to gather data that is specifically tailored to their research objectives, providing a solid foundation for insightful analysis and strategic decision-making.

Secondary Research Data Sources

In contrast, secondary research data sources offer a broader perspective, compiling and synthesizing information from various origins. These sources include:

• Books, Magazines, Scholarly Journals: Published works provide comprehensive overviews, detailed analyses, and theoretical frameworks that can inform research topics, offering depth and context that enriches primary data.
• Market Research Reports: These reports aggregate data and analyses on industry trends, consumer behavior, and market dynamics, providing a macro-level view that can guide primary research directions and validate findings.
• Government Reports: Official statistics and reports from government agencies offer authoritative data on a wide range of topics, from economic indicators to demographic trends, providing a reliable basis for secondary analysis.
• White Papers, Private Company Data: White papers and reports from businesses and consultancies offer insights into industry-specific research, best practices, and market analyses. These sources can be invaluable for understanding the competitive landscape and identifying emerging trends.

Secondary data sources serve as a compass, guiding researchers through the vast landscape of information to identify relevant trends, benchmark against existing data, and build upon the foundation of existing knowledge. They can significantly expedite the research process by leveraging the collective wisdom and research efforts of others.

By adeptly navigating both primary and secondary sources, researchers can construct a well-rounded research project that combines the depth of firsthand data with the breadth of existing knowledge. This holistic approach ensures a comprehensive understanding of the research topic, fostering informed decisions and strategic insights.

Examples of Primary and Secondary Research in Marketing

In the realm of marketing, both primary and secondary research methods play critical roles in understanding market dynamics, consumer behavior, and competitive landscapes. By comparing examples across both methodologies, we can appreciate their unique contributions to strategic decision-making.

Example 1: New Product Development

Primary Research: Direct Consumer Feedback through Surveys and Focus Groups

• Objective: To gauge consumer interest in a new product concept and identify preferred features.
• Process: Surveys distributed to a target demographic to collect quantitative data on consumer preferences, and focus groups conducted to dive deeper into consumer attitudes and desires.
• Insights: Direct insights into consumer needs, preferences for specific features, and willingness to pay. These insights help in refining product design and developing a targeted marketing strategy.

Secondary Research: Market Analysis Reports

• Objective: To understand the existing market landscape, including competitor products and market trends.
• Process: Analyzing published market analysis reports and industry studies to gather data on market size, growth trends, and competitive offerings.
• Insights: Provides a broader understanding of the market, helping to position the new product strategically against competitors and align it with current trends.

Example 2: Brand Positioning

Primary Research: Brand Perception Analysis through Surveys

• Objective: To understand how the brand is perceived by consumers and identify potential areas for repositioning.
• Process: Conducting surveys that ask consumers to describe the brand in their own words, rate it against various attributes, and compare it to competitors.
• Insights: Direct feedback on brand strengths and weaknesses from the consumer's perspective, offering actionable data for adjusting brand messaging and positioning.

Secondary Research: Social Media Sentiment Analysis

• Objective: To analyze public sentiment towards the brand and its competitors.
• Process: Utilizing software tools to analyze mentions, hashtags, and discussions related to the brand and its competitors across social media platforms.
• Insights: Offers an overview of public perception and emerging trends in consumer sentiment, which can validate findings from primary research or highlight areas needing further investigation.

Example 3: Market Expansion Strategy

Primary Research: Consumer Demand Studies in New Markets

• Objective: To assess demand and consumer preferences in a new geographic market.
• Process: Conducting surveys and interviews with potential consumers in the target market to understand their needs, preferences, and cultural nuances.
• Insights: Provides specific insights into the new market’s consumer behavior, preferences, and potential barriers to entry, guiding market entry strategies.

Secondary Research: Economic and Demographic Analysis

• Objective: To evaluate the economic viability and demographic appeal of the new market.
• Process: Reviewing existing economic reports, demographic data, and industry trends relevant to the target market.
• Insights: Offers a macro view of the market's potential, including economic conditions, demographic trends, and consumer spending patterns, which can complement insights gained from primary research.

By leveraging both primary and secondary research, marketers can form a comprehensive understanding of their market, consumers, and competitors, facilitating informed decision-making and strategic planning. Each method brings its strengths to the table, with primary research offering direct consumer insights and secondary research providing a broader context within which to interpret those insights.

What Are the Pros and Cons of Primary and Secondary Research?

When it comes to market research, both primary and secondary research offer unique advantages and face certain limitations. Understanding these can help researchers and businesses make informed decisions on which approach to utilize for their specific needs. Below is a comparative table highlighting the pros and cons of each research type.

Navigating the Pros and Cons

• Balance Your Research Needs: Consider starting with secondary research to gain a broad understanding of the subject matter, then delve into primary research for specific, targeted insights that are tailored to your precise needs.
• Resource Allocation: Evaluate your budget, time, and resource availability. Primary research can offer more specific and actionable data but requires more resources. Secondary research is more accessible but may lack the specificity or recency you need.
• Quality and Relevance: Assess the quality and relevance of available secondary sources before deciding if primary research is necessary. Sometimes, the existing data might suffice, especially for preliminary market understanding or trend analysis.
• Combining Both for Comprehensive Insights: Often, the most effective research strategy involves a combination of both primary and secondary research. This approach allows for a more comprehensive understanding of the market, leveraging the broad perspective provided by secondary sources and the depth and specificity of primary data.

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• Primary vs Secondary Research Methods: 15 Key Differences

When carrying out a systematic investigation, you can choose to be directly involved in the data collection process or to rely on already acquired information. While the former is described as primary research, the latter is known as secondary research. 

The distinguishing factor between primary research and secondary research is the degree of involvement of the research with the data gathering process . In this article, we’ll be detailing other key differences between primary and secondary research, and also show you how to conduct primary research with Formplus. 

What is Primary Research?

Primary research is a type of research that requires the researcher to participate directly in the data-gathering process. In primary research, the researcher does not depend on already existing data, rather he or she collects first-hand information which serves as research materials for the systematic investigation. 

This type of research gives the researcher absolute ownership of the data which is extremely important for businesses and organisations in fast-paced markets. These organisations utilise primary research to gather valuable information about consumer needs and preferences before launching a new product or service.  

Usually, primary research focuses on the specific needs of the research contexts. However, this type of research is expensive, time-consuming and it usually requires a lot of skilled resources that may not be readily available and this is why many businesses outsource this to 3rd party market research companies. 

What is Secondary Research?

Secondary research is a type of research approach in which the researcher relies solely on existing research materials rather than gather data directly for research. This research approach is less expensive and time-efficient unlike primary research.. 

Data for secondary research can be accessed from the internet, archive, libraries, educational institutions and organisational reports. However, extra care must be taken by the researcher to ensure that the data is valid as this can have a negative impact on the research process and outcomes. 

Differences Between Primary and Secondary Research

Primary research is a research approach that involves gathering data directly while secondary research is a research approach that involves relying on already existing data when carrying out a systematic investigation. 

This means that in primary research, the researcher is directly involved in the data collection and categorization process. In secondary research, on the other hand, the researcher simply depends on existing materials for the research without any need to collect raw information from the field. 

• Sources of Data

Surveys, interviews, focus groups and observation techniques are common sources of data in primary research. In secondary research, the researcher collects existing research materials through a number of sources like the internet, libraries and archives.

These data collection methods require some sort of interaction with the research subjects in order to gather first-hand information that will be useful in the research. Many times,secondary sources are free to access but some of them will require you to pay an access fee before you can make use of the information. 

• Other Names

Secondary research is also known as desk research because it does not necessarily require the researcher to move from one place to another. Meanwhile, primary research is also referred to as a field research design because it requires the researcher to get totally involved with the data collection process.

In secondary research, researchers can easily access information from the comfort of their desk; especially when using the internet to source for research materials. In some cases, the researcher would need to co-exist with the research subjects for a specific period of time in order to get information for the research. 

• Advantages of Primary Research over Secondary Research

Unlike secondary research, primary research gives the researcher 100% ownership of the research data which is extremely useful for organisations in highly competitive markets. Data from secondary research can be accessed by everyone and does not yield any specific benefits to organisations. 

Also, in primary research, the researcher can fully account for the authenticity of the data because he or she is an active participant in the data collection process. Because the researcher is not directly involved in gathering secondary research data, he or she cannot ascertain the authenticity of the research materials. 

• Advantages of Secondary Research over Primary Research.

Unlike primary research that is expensive and time-consuming, secondary research can be completed in limited time and with limited resources. Since the research data already exists, the secondary researcher does not need to invest time or resources to gather first-hand information. 

Also, secondary research helps to prevent knowledge repetition by mapping out already existing research efforts and this helps the primary researcher to concentrate on exploring new areas of knowledge. Hence, it is important for every research effort to begin with secondary research. 

Common tools used to collect data in secondary research include bots, internet-enabled devices like laptops, smartphones and tablets. On the other hand, surveys, questionnaires and interviews are common data gathering tools in primary research.

Secondary research devices help researchers to access sources of secondary data like libraries, archives and peer-reviewed journals; without needing to go to the field.  Primary research tools help the researcher to access first-hand information about the characteristics, dispositions and behaviours of research subjects in line with the context of the systematic investigation.  

Primary research makes use of real-time information while secondary research makes use of past or already existing research materials. During primary research, the research is ultimately concerned with gathering first-hand information about the research subjects and contexts while in secondary research, the researcher simply re-examines existing data. 

Hence, the type of data used in secondary research is described as “past data” because it reflects past occurrences and only provides insights into dealing with present situations. The role of the secondary researcher is primarily to specify how this past data informs his or her current research.

• Research Purpose

The purpose of primary research is to gather real-time data that will be useful in solving a specific problem. On the other hand, the purpose of secondary research is to gather existing research materials that may not directly address the problem at hand. 

The primary research process is carefully tailored towards the specific research problem from start to finish and this is why it relies on first-hand data. Secondary research is not tailored towards solving a specific problem rather, it provides general information that can prove useful for primary research. 

• When to Conduct Primary and Secondary Research

Primary or field research is usually carried out when an individual or organization needs to gather recent data that is useful for a specific research context. When organisations need to gather information on the changing needs of target markets, they typically employ primary research methods. 

Secondary research, on the other hand, is used when the researcher needs to identify existing knowledge that can provide useful insight in research. With this information, the researcher can identify knowledge gaps which would form the core of his or her research efforts. 

• Data Recency

Primary research relies on recent data for its systematic investigation because it addresses present situations. As earlier asserted, primary research efforts are ultimately tailored towards the needs of a specific research context from start to finish;hence, the primary researcher must gather real-time data in order to arrive at relevant research outcomes. 

Secondary research, on the other hand, makes use of past data in an attempt to understand existing research efforts, identify knowledge gaps and map out the recent research to fill these knowledge gaps. This, findings from secondary research do not necessarily apply to specific research contexts.  

• Feasibility

Secondary research is more feasible than primary research. For example, it may be improbable for a company to attempt to observe the buying culture of all the individuals in its target market. 

In this case, the researcher may have to depend on existing research findings that detail the buying culture of the target market. Alternatively, the researcher can use other sampling methods that would help him or her gather feedback from a section of the market. 

Examples of primary research data are student thesis, market research and first-person accounts of trauma survivors while examples of secondary research data include newspapers, books, academic journals and magazines. 

Secondary research data often represent an aggregation of already existing information with little or no additions while primary data contains new information. Usually, primary research collects data from the original source unlike secondary research that relies on reported information. For example, a student who wants to write a thesis would need to either interact with the research subjects in their natural environment or carry out an experiment. 

• Specificity

Primary research is more specific than secondary research because primary research is aimed at addressing issues peculiar to a business, organisation or institution. On the other hand, secondary research that does not cater to the specific needs of an organization. 

For example, when carrying out a primary research on consumer satisfaction for a product, the entirety of the research process is tailored towards the product in question. In secondary research, however, the data collected may not be exactly what the researcher needs. 

In primary research, the researcher has 100% ownership and control over the data and he or she can choose to make such information available to others or not. This means that the primary researcher has absolute discretion over the research materials. 

In secondary research, however, the researcher does not own the data and as such, he or she does not have absolute discretion over it. Secondary research can aptly be described as a “free-for-all” situation because everyone can gain access to the data. 

• Data Accuracy

Data gathered through primary research is more accurate than secondary research data. In primary research, the researcher is fully involved in the data collection process and he or she takes care to collect valid data that can be easily authenticated. 

The secondary researcher, on the other hand, has no control over the data and he or she cannot account for the validity of the research materials. For instance, there is a lot of inaccurate information on the internet which can affect research outcomes when used as the basis of a systematic investigation.  

Similarity between Primary and Secondary Research

Primary and secondary research makes use of quantitative and qualitative data. Quantitative data collection methods such as surveys and questionnaires are used to gather numerical data while qualitative data collection methods like observation are used to gather descriptive data . 

How to Conduct Primary Research with Formplus 

Primary research can be conducted with Formplus using a survey or questionnaire . Here is a step-by-step guide on how to go about this. 

• Sign into Formplus

With Formplus, you can create different types of surveys and questionnaires for primary research. Sign into your Formplus account to access the form builder where you can seamlessly add and modify different form fields for your primary research survey. 

Once you sign in, click on “create new form” to begin. 

In the builder page, you can specify your form title to be “Primary Research Survey” in the title box. Next, click on or drag your desired form fields into your survey form from the builder’s inputs section. 

• Edit fields
• Click on “Save”
• Preview form. 
• Form Customization

In the form customization section in the form builder, you can easily personalize your primary research survey by modifying its outlook to suit your needs. Formplus allows you to change your form theme, add background images and even change the font according to your needs. 

• Multiple Sharing Options

With Formplus, you can easily share your primary research survey with respondents using the available multiple sharing options. You can use the direct social media sharing buttons to share your form link to your organization’s social media pages. 

You can send out your survey form as email invitations to your research subjects too. If you wish, you can share your form’s QR code or embed it in your organization’s website for easy access. 

Conclusion   

Many times, researchers combine primary and secondary data collection methods in order to arrive at the most valid outcomes at the end of a systematic investigation. Usually, they start off with secondary research to effectively map out a relevant scope for their research effort, before proceeding to conduct primary research. 

It is important for you to consider the strengths and weaknesses of secondary and primary research before opting for any of these research methods. More importantly, you should pay attention to the overall aim of your systematic investigation as this is the fundamental determinator for choosing primary or secondary research.

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Qualitative Research: An Overview

• First Online: 24 April 2019

Cite this chapter

• Yanto Chandra 3 &
• Liang Shang 4  

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Qualitative research is one of the most commonly used types of research and methodology in the social sciences. Unfortunately, qualitative research is commonly misunderstood. In this chapter, we describe and explain the misconceptions surrounding qualitative research enterprise, why researchers need to care about when using qualitative research, the characteristics of qualitative research, and review the paradigms in qualitative research.

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Qualitative research is defined as the practice used to study things –– individuals and organizations and their reasons, opinions, and motivations, beliefs in their natural settings. It involves an observer (a researcher) who is located in the field , who transforms the world into a series of representations such as fieldnotes, interviews, conversations, photographs, recordings and memos (Denzin and Lincoln 2011 ). Many researchers employ qualitative research for exploratory purpose while others use it for ‘quasi’ theory testing approach. Qualitative research is a broad umbrella of research methodologies that encompasses grounded theory (Glaser and Strauss 2017 ; Strauss and Corbin 1990 ), case study (Flyvbjerg 2006 ; Yin 2003 ), phenomenology (Sanders 1982 ), discourse analysis (Fairclough 2003 ; Wodak and Meyer 2009 ), ethnography (Geertz 1973 ; Garfinkel 1967 ), and netnography (Kozinets 2002 ), among others. Qualitative research is often synonymous with ‘case study research’ because ‘case study’ primarily uses (but not always) qualitative data.

The quality standards or evaluation criteria of qualitative research comprises: (1) credibility (that a researcher can provide confidence in his/her findings), (2) transferability (that results are more plausible when transported to a highly similar contexts), (3) dependability (that errors have been minimized, proper documentation is provided), and (4) confirmability (that conclusions are internally consistent and supported by data) (see Lincoln and Guba 1985 ).

We classify research into a continuum of theory building — >   theory elaboration — >   theory testing . Theory building is also known as theory exploration. Theory elaboration refers to the use of qualitative data and a method to seek “confirmation” of the relationships among variables or processes or mechanisms of a social reality (Bartunek and Rynes 2015 ).

In the context of qualitative research, theory/ies usually refer(s) to conceptual model(s) or framework(s) that explain the relationships among a set of variables or processes that explain a social phenomenon. Theory or theories could also refer to general ideas or frameworks (e.g., institutional theory, emancipation theory, or identity theory) that are reviewed as background knowledge prior to the commencement of a qualitative research project.

For example, a qualitative research can ask the following question: “How can institutional change succeed in social contexts that are dominated by organized crime?” (Vaccaro and Palazzo 2015 ).

We have witnessed numerous cases in which committed positivist methodologists were asked to review qualitative papers, and they used a survey approach to assess the quality of an interpretivist work. This reviewers’ fallacy is dangerous and hampers the progress of a field of research. Editors must be cognizant of such fallacy and avoid it.

A social enterprises (SE) is an organization that combines social welfare and commercial logics (Doherty et al. 2014 ), or that uses business principles to address social problems (Mair and Marti 2006 ); thus, qualitative research that reports that ‘social impact’ is important for SEs is too descriptive and, arguably, tautological. It is not uncommon to see authors submitting purely descriptive papers to scholarly journals.

Some qualitative researchers have conducted qualitative work using primarily a checklist (ticking the boxes) to show the presence or absence of variables, as if it were a survey-based study. This is utterly inappropriate for a qualitative work. A qualitative work needs to show the richness and depth of qualitative findings. Nevertheless, it is acceptable to use such checklists as supplementary data if a study involves too many informants or variables of interest, or the data is too complex due to its longitudinal nature (e.g., a study that involves 15 cases observed and involving 59 interviews with 33 informants within a 7-year fieldwork used an excel sheet to tabulate the number of events that occurred as supplementary data to the main analysis; see Chandra 2017a , b ).

As mentioned earlier, there are different types of qualitative research. Thus, a qualitative researcher will customize the data collection process to fit the type of research being conducted. For example, for researchers using ethnography, the primary data will be in the form of photos and/or videos and interviews; for those using netnography, the primary data will be internet-based textual data. Interview data is perhaps the most common type of data used across all types of qualitative research designs and is often synonymous with qualitative research.

The purpose of qualitative research is to provide an explanation , not merely a description and certainly not a prediction (which is the realm of quantitative research). However, description is needed to illustrate qualitative data collected, and usually researchers describe their qualitative data by inserting a number of important “informant quotes” in the body of a qualitative research report.

We advise qualitative researchers to adhere to one approach to avoid any epistemological and ontological mismatch that may arise among different camps in qualitative research. For instance, mixing a positivist with a constructivist approach in qualitative research frequently leads to unnecessary criticism and even rejection from journal editors and reviewers; it shows a lack of methodological competence or awareness of one’s epistemological position.

Analytical generalization is not generalization to some defined population that has been sampled, but to a “theory” of the phenomenon being studied, a theory that may have much wider applicability than the particular case studied (Yin 2003 ).

There are different types of contributions. Typically, a researcher is expected to clearly articulate the theoretical contributions for a qualitative work submitted to a scholarly journal. Other types of contributions are practical (or managerial ), common for business/management journals, and policy , common for policy related journals.

There is ongoing debate on whether a template for qualitative research is desirable or necessary, with one camp of scholars (the pluralistic critical realists) that advocates a pluralistic approaches to qualitative research (“qualitative research should not follow a particular template or be prescriptive in its process”) and the other camps are advocating for some form of consensus via the use of particular approaches (e.g., the Eisenhardt or Gioia Approach, etc.). However, as shown in Table 1.1 , even the pluralistic critical realism in itself is a template and advocates an alternative form of consensus through the use of diverse and pluralistic approaches in doing qualitative research.

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Chandra, Y., Shang, L. (2019). Qualitative Research: An Overview. In: Qualitative Research Using R: A Systematic Approach. Springer, Singapore. https://doi.org/10.1007/978-981-13-3170-1_1

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Types of data: qualitative and quantitative data; primary and secondary data, qualitative and quantitative.

model-answers-questionnaires-qual-quan-open-closed-doc-1

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If you have quantitative data; you need to know whether it is nominal, ordinal or interval/ratio; this handout will help to make sure!  levels-of-measurement-1-1 (1)

What is primary data?

What is secondary data, revision activity.

• Diagnosis given by duty psychiatrists in Rosenhan (1973)
• Information gathered in interviews in Vallentine et al
• Case histories and medical notes in the twin pairs in Gottesman and Shields (1966)
• Personality tests and analysis of tape recorded speech from semi-structured interviews with the twin pairs in Gottesman and Shields (1966)
• Diagnoses on admission and release in Pontizovsky et al’s (2006) study of reliability of diagnoses
• Information from standardised interviews with 1555 18-25 year old German women about what prescription drugs they were on and also used to diagnose mental disorders (Hach el al, 2004)
• Information provided by the doctors of the 1555 18-25 year old German women about diagnosis and prescriptions (Hach el al, 2004)

Learning Objective: Evaluate the use of primary and secondary data

Practice comparing primary and secondary data, share this:.

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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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Research Design Review

A discussion of qualitative & quantitative research design, secondary & primary qualitative content analysis: distinguishing between the two methods.

The following is a modified excerpt from Applied Qualitative Research Design: A Total Quality Framework Approach (Roller & Lavrakas, 2015, pp. 241-244).

Secondary Method

A systematic application of QCA as a secondary method* has been conducted across a variety of disciplines.  Health care researchers in particular have used content analysis in conjunction with other qualitative methods to investigate a broad range of topics.  For example, Söderberg and Lundman (2001) applied the content analysis method to analyze the results from 25 unstructured IDIs conducted with women inflicted with fibromyalgia, from which they isolated five areas in these women’s lives impacted by the onset of this condition. In a similar approach, Berg and Hansson (2000) examined the lived experiences of 13 nurses working in dementia care at a psychogeriatric clinic who received clinical group supervision and individually planned nursing care. Berg and Hansson conducted unstructured, open-ended IDIs with each nurse and executed a content analysis that revealed two principal and five subordinate themes indicating supportive needs at the personal and professional level. Kyngäs (2004) studied the support network among 40 teenagers suffering from a chronic disease, such as asthma or epilepsy, by way of semi-structured IDIs.  Content analysis in this instance showed six distinct social network categories for these adolescents, i.e., parents, peers, health care providers, school, technology, and pets.

Primary Method

The primary QCA method – which focuses on naturally occurring data – has also been used across a number of disciplines. These data sources are often textual in nature (i.e., written accounts of some kind, see below); however, this is not always the case. For instance, television content has been the focal point for public health researchers examining direct-to-consumer prescription drug commercials (Kaphingst, DeJong, Rudd, & Daltroy, 2004) as well as sociologists such as David Altheide (1987) who utilized content analysis to study television news coverage of the Iranian hostage crisis.  The analysis of patients’ “scribbles” from art psychotherapy sessions (Egberg-Thyme, Wiberg, Lundman, & Graneheim, 2013) as well as racism and the depiction of interracial relationships in U.S.-made films (Beeman, 2007) are other examples of using QCA as a primary method where the focus is on non-textual content.

Content analysis as a primary method to explore textual data has been used in: (a) sociological research to look at gender biases reflected in the Boy Scouts’ and Girl Scouts’ handbooks (Denny, 2011); (b) mass communication to study the portrayal of female immigrants in the Israeli media (Lemish, 2000); (c) sports marketing to investigate the social outreach programs among the four major professional leagues via a content analysis of their respective community website pages (Pharr & Lough, 2012); and (d) corporate management, including studies that analyze the content of corporate mission statements to understand “the messages communicated to organizational stakeholders” (Morris, 1994, p. 908).

Primary QCA is also used to study online content, including the examination of websites (such as Pharr & Lough, 2012, mentioned above) and the numerous ways people interact on social media. Once again, researchers in the health care industry have been particularly active using QCA to study social and other web-based phenomena.  As an example, Nordfeldt, Ängarne-Lindberg, and Berterö (2012) used the content analysis method to examine essays written by 18 diabetes health-care professionals concerning their experiences using a web portal designed for young diabetes type 1 patients and their significant others. The capabilities and use of social media, however, present qualitative researchers with new challenges.  Comments – made on blogs, networking sites, user groups, and content-sharing sites – and the use of hyperlinks are just two examples of how social media content is rarely isolated and, to the contrary, represent a highly integrated form of communication where finding themes or patterns from the multiplicity of interactions may present an extremely daunting task for the researcher. For this reason, information systems researchers such as Herring (2010) and Parker, Saundage, and Lee (2011) advocate a different, non-traditional way of thinking about the content analysis method in terms of developing units of analyses, categories, and patterns based on the realities of the interactive, linked world of online social media.

* Not unlike the steps discussed in this 2015 Research Design Review article .

Beeman, A. K. (2007). Emotional segregation: A content analysis of institutional racism in US films, 1980–2001. Ethnic and Racial Studies , 30 (5), 687–712. https://doi.org/10.1080/01419870701491648

Berg, A., & Hansson, U. W. (2000). Dementia care nurses’ experiences of systematic clinical group supervision and supervised planned nursing care. Journal of Nursing Management , 8 (6), 357–368.

Denny, K. E. (2011). Gender in context, content, and approach: Comparing gender messages in Girl Scout and Boy Scout handbooks. Gender & Society , 25 (1), 27–47. https://doi.org/10.1177/0891243210390517

Egberg-Thyme, K., Wiberg, B., Lundman, B., & Graneheim, U. H. (2013). Qualitative content analysis in art psychotherapy research: Concepts, procedures, and measures to reveal the latent meaning in pictures and the words attached to the pictures. The Arts in Psychotherapy , 40 (1), 101–107. https://doi.org/10.1016/j.aip.2012.11.007

Herring, S. C. (2010). Web content analysis: Expanding the paradigm. In J. Hunsinger, L. Klastrup, & M. Allen (Eds.), International handbook of Internet research (pp. 233–249). Dordrecht, Netherlands: Springer.

Kaphingst, K. A., DeJong, W., Rudd, R. E., & Daltroy, L. H. (2004). A content analysis of direct-to-consumer television prescription drug advertisements. Journal of Health Communication , 9 (6), 515–528. https://doi.org/10.1080/10810730490882586

Kyngäs, H. (2004). Support network of adolescents with chronic disease: Adolescents’ perspective. Nursing and Health Sciences , 6 (4), 287–293. https://doi.org/10.1111/j.1442-2018.2004.00207.x

Lemish, D. (2000). The whore and the other: Israeli images of female immigrants from the former USSR. Gender & Society , 14 (2), 333–349. https://doi.org/10.1177/089124300014002007

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Conducting secondary analysis of qualitative data: Should we, can we, and how?

Nicole ruggiano.

School of Social Work, University of Alabama, USA

Tam E Perry

School of Social Work, Wayne State University, USA

While secondary data analysis of quantitative data has become commonplace and encouraged across disciplines, the practice of secondary data analysis with qualitative data has met more criticism and concerns regarding potential methodological and ethical problems. Though commentary about qualitative secondary data analysis has increased, little is known about the current state of qualitative secondary data analysis or how researchers are conducting secondary data analysis with qualitative data. This critical interpretive synthesis examined research articles (n = 71) published between 2006 and 2016 that involved qualitative secondary data analysis and assessed the context, purpose, and methodologies that were reported. Implications of findings are discussed, with particular focus on recommended guidelines and best practices of conducting qualitative secondary data analysis.

There has been increasing commentary in the literature regarding secondary data analysis (SDA) with qualitative data. Many critics assert that there are potential methodological and ethical problems regarding such practice, especially when qualitative data is shared and SDA is conducted by researchers not involved with data collection. However, less has been written on how sharing and SDA of qualitative data is actually conducted by scholars. To better understand this practice with qualitative research, this critical interpretive synthesis (CIS) appraised studies that have involved SDA with qualitative data, examining their context, analytical techniques, and methods applied to promote rigor and ethical conduct of research. Following this analysis, the strengths and weaknesses of such practice and strategies for promoting the advancement of science will be discussed in light of findings.

SDA involves investigations where data collected for a previous study is analyzed – either by the same researcher(s) or different researcher(s) – to explore new questions or use different analysis strategies that were not a part of the primary analysis ( Szabo and Strang, 1997 ). For research involving quantitative data, SDA, and the process of sharing data for the purpose of SDA, has become commonplace. Though not without its limitations, Hinds et al. (1997) argue that it is a “respected, common, and cost-effective approach to maximizing the usefulness of collected data” (p. 408). They describe four approaches to SDA: (1) research where SDA focuses on a different unit of analysis from that of the parent study; (2) research involving a more in-depth analysis of themes from the parent study with a subset of data from that study; (3) analyses of data from the parent study that appear important, but not sufficiently focused on in the primary analysis; and (4) analyses with a dataset that includes data from a parent study and newly-collected data that refines the parent study’s purpose or research questions ( Hinds et al., 1997 ).

Scholars have also promoted the practice of sharing data for the purpose of SDA, asserting that it may answer new research questions, as well as increase sample sizes and statistical power ( Perrino et al., 2013 ). Sharing data also allows for the generation of new knowledge without the costs of administration and implementation of additional data collection and maximizes the output of large-scale studies that are funded by public or private sources. Recognizing the value of sharing data, researchers and institutions have created an infrastructure to promote such practice by: making datasets more available through the process of archiving; making archived data available through a number of media, such as the internet, CD-ROMS, and other removable storage devices; and documenting and providing detailed information about the sampling, design, and data collection strategies from such parent studies so that researchers can better understand the qualities of the data they obtain for future use ( Hox and Boeije, 2005 ; Perrino et al., 2013 ).

Concerns about secondary data analysis when using qualitative data

The primary concerns about SDA with qualitative data surround rigor and ethics from a number of stakeholder perspectives, including research participants, funders, and the researchers themselves. Heaton (2004) suggests that a strength of secondary analysis of qualitative data is that it relieves the burden of participation from research participants and community partners who collaborate with researchers to identify, access, and recruit research participants. However, we must also consider how SDA fits within guidelines for duplicate publishing of qualitative research ( Morse, 2007 ) in an era of a quantity-driven publishing as one mark of scholarliness.

Debates regarding rigor in qualitative SDA.

Despite the demonstrated benefits from its practice in quantitative studies, sharing qualitative data for SDA has not been as widely promoted and even has received considerable criticisms in the literature. One criticism relates to the socio-cultural-political context under which qualitative studies are implemented. As highlighted by Walters (2009) , qualitative research involves the collection and interpretation of subjective data that often is shaped by the social, cultural, and political realities that are evident at the time of data collection. When such data are re-analyzed or reinterpreted during another time period, the changes in social, cultural and/or political norms may result in investigators exploring research questions or utilizing analysis strategies that are inappropriate or they may misinterpret the original data. Mauthner et al. (1998) assert that the process of re-analyzing data can be different even for researchers who are revisiting their own data that was collected at an earlier time. However, they also report that some researchers may find benefits to this process. For instance, some researchers may find themselves less emotionally invested in the data and therefore more objective, though, other researchers may find this emotional distance to result in less immersion in the data. Thorne (1994 ) has provided a number of approaches to increasing rigor in SDA, such as audit trails and critical and reflective constant comparison. However, it is unclear the extent to which such practices actually overcome challenges that compromise qualitative SDA, such as inappropriate coding and interpretation of data and/or lack of first-hand knowledge of data by SDA researchers ( Thorne, 1994 ).

Debates regarding ethics in qualitative secondary data analysis.

In addition to questions of methodological rigor, there are criticisms regarding ethical dilemmas posed by SDA of qualitative data. Many criticisms center on basic questions of research ethics – the risks to informed consent, confidentiality, and anonymity when such data are archived and/or shared ( Morrow et al., 2014 ). For instance, Parry and Mauthner (2004) argue that the in-depth nature of qualitative data may pose particular challenges to de-identifying data for the purpose of archiving it for shared use. The descriptiveness of the data alone may allow others to identify respondents, while removing such descriptors may compromise the quality of the data.

There are also arguments that qualitative data is not created by researchers alone – they represent the “joint endeavor between respondent and researcher” and therefore allowing other researchers to re-use data poses significant ethical and legal dilemmas by disregarding the respondent’s ownership of the data ( Parry and Mauthner, 2004 : 142). Parry and Mauthner (2004) write that the collaborative effort of creating qualitative data also poses ethical dilemmas for qualitative researchers, who often offer personal information to respondents in an attempt to develop rapport. Therefore, they risk breeches in anonymity/confidentiality when such data are shared for future use.

To date, there has been increasing dialogue and controversy surrounding the practice of SDA with qualitative data. However, few studies have examined how qualitative SDA is being conducted or guidelines on conducting such investigations with high amounts of rigor and ethics. To address this issue, a CIS of studies identified as having qualitative SDA as a methodology was undertaken to address the following questions:

• What is the extent and context under which SDA is conducted with qualitative data?
• What are common approaches and purposes for conducting SDA with qualitative data?
• In what ways do researchers maintain rigor and ethics in qualitative SDA? and
• What limitations in qualitative SDA have been identified in practice?

Methodology

Although systematic reviews are commonly used to synthesize quantitative studies on a specific topic, Dixon-Woods et al. (2006) argue that the nature of systematic reviews and their focus on examining studies that emphasize testing theories is inappropriate when different types of evidence are being synthesized and/or there is a need for interpretation of studies. This review involved a CIS of literature that was identified through multiple search strategies. CIS differs from quantitative systematic reviews in several ways: (1) it uses broad review questions to guide the identification and analysis of studies, rather than specific hypotheses; (2) it relies on sources other than bibliographic databases to identify studies for inclusion; (3) it does not use a preconceived hierarchy of methods to guide study inclusion (e.g. only including randomized control trials, due to their perceived higher level of rigor); and (4) it uses ongoing inductive and interpretive strategies in the identification and analysis of studies, which may result in ongoing revision to the guiding review questions or revisiting search criteria and/or strategies ( Dixon-Woods et al., 2006 ). CIS differs from meta-ethnography in that the latter involves a more interpretive way of linking ethnographic findings from multiple studies, often on a specific topic ( Flemming, 2010 ). By contrast, the current analysis involves the interpretation and comparison of context and methodologies of studies focused on a wide variety of topics.

Eligibility criteria

This CIS identified and assessed research published in peer-reviewed, scholarly journals between the years 1996 and 2016. They also had to meet the following inclusion criteria: (a) involving analysis of data derived through qualitative methodologies; (b) research involving social or health-related research with human subjects; (c) use of SDA or repurposing of parent study data for subsequent analysis; and (d) research published in English. For the purpose of time sensitivity, unpublished dissertations were excluded from the final review. Given prior assertions that not all qualitative studies using SDA are identified as being such ( Hinds et al., 1997 ), the researchers cast a wide net and did not impose any additional exclusion criteria based on the perceived quality or approach to methodology, analysis, or focus area ( Dixon-Woods et al., 2006 ; Walsh and Downe, 2005 ).

Sources and process of search

Studies were identified between May and June of 2016 (see figure 1 ) by searching through the following eight databases: Expanded Academic ASAP, EBSCO Host, PsychInfo, PubMed, Social Services Abstracts, Social Work Abstracts, Sociological Abstracts, and Web of Science. The titles and/or abstracts were reviewed for more than 10,373 results that were yielded from the initial search. For each database, a search was conducted using combinations of the following search terms: qualitative research OR qualitative analysis OR qualitative study AND secondary data analysis OR secondary analysis OR combining data* OR sharing data* OR integrating data* OR two studies OR two field studies. Among these studies, 76 unduplicated studies were selected for full-text review. A second search strategy took place in September of 2016, where peer-reviewed journals that are dedicated to qualitative research and have impact factors (International Journal of Qualitative Methods, Qualitative Health Research, Qualitative Inquiry, Qualitative Research, Qualitative Social Work, and Qualitative Sociology) were searched. This subsequent search yielded 49 additional articles selected for full-text review. Among the 125 articles that were fully-reviewed, 54 did not meet the inclusion criteria and were excluded from the final analysis.

Search strategy and results for systematic review.

Appraisal of studies

The approach for appraising the included studies were derived from a number of recommendations in the literature ( Barnett-Page and Thomas, 2009 ; Schoenberg and McAuley, 2007 ; Walsh and Downe, 2005 ). Given that the current CIS focuses on an analysis of context and methodologies, rather than the findings of qualitative research on a specific topic, the appraisal of primary studies focused on the inclusion, description, and comparison/contrast of methods across the following categories:

• Relationship of researchers with parent study: Here, the extent to which researchers conducting the SDA were involved with the parent study or studies was assessed. The relationships were identified by: authors self-citing the parent study, authors describing their contribution to the parent study, and authors describing their use of other researchers’ data or archived data.
• Context of secondary analysis: For this category, articles were assessed by the context under which SDA took place. For instance, whether the data from parent study were analyzed post hoc, whether entire datasets or subsets were analyzed in the SDA, whether data from multiple studies were combined, or whether new research questions or analytical approaches were explicitly used. It was also assessed whether the secondary analysis aimed at advancing theory regarding a certain topic or methodology.
• Details about parent study: To understand the context under which the data were initially collected in the parent studies, articles were assessed for whether they included details about the parent studies, such as their: context and methodologies, IRB approval, funding sources, and process of sharing data (when applicable).
• Ethical considerations in secondary analysis: Articles were assessed for whether ethical considerations were described that were specific to secondary analysis. For instance, whether researchers made additional steps in the SDA to protect human subjects who participated in the parent study or descriptions of obtaining IRB approval for SDA.
• Methodological rigor in secondary analysis: Articles were assessed for whether the researchers described aspects specific to the secondary analysis that were used to increase rigor, including descriptions of the SDA process or specific strategies to improve rigor.
• Methodological challenges in secondary analysis: Articles were assessed for whether the researchers identified aspects of SDA that created challenges or limitations for their findings.

Both authors assessed each article independently and created a thematic chart based on these assessment criteria. Discrepancies in this assessment were resolved through discussion until agreement was reached. The authors acknowledge that the assessment is based on the published text, and thus, may not reflect further details outlined in other articles on the research or details not published. For instance, in cases where researchers did not identify obtaining IRB approval specifically for the SDA, that does not necessarily mean that the authors did not obtain IRB approval.

Seventy-one studies were included in this analysis. A table listing the studies and their appraisal using the criteria above can be accessed as an online supplementary appendix file. Most of the studies (n = 51, 71.8%) that met the inclusion criteria involved research focused on physical and mental health research, with fewer studies focused on social or economic issues.

Authors of these qualitative studies used a myriad of terms to describe their efforts to “repurpose parent study data for subsequent analysis,” including secondary data analysis, post hoc analysis, re-analysis, and supplemental analysis. Hence, the term qualitative secondary data analysis is not used consistently in the qualitative research literature. Through the appraisal of these studies, three central themes emerged that shed light on the current state of qualitative SDA and relate to current controversies to such practices within the literature: (1) the relationship of the SDA study to the parent study or studies ; (2) ethical considerations and human subject protections in qualitative SDA; and (3) attention given to methods and rigor in writing about primary and secondary studies . These themes, along with their sub-themes, are described in detail below. Please note that when interpreting these thematic findings that the articles were assessed based on what information they included or did not include in the reporting of their studies and that the findings should not be used to assess actual rigor or quality in methodologies of individual studies.

Relationship of the SDA study to the parent study or studies

In most cases (n = 60, 84.5%), qualitative SDA among the included studies involved researchers re-examining qualitative data from parent studies that they were involved with to explore new research questions or analytic strategies. Therefore, most were familiar with the methodologies and data of the parent studies and were able to write about the parent studies and quality of data in significant detail. Variation in relationships between parent and secondary studies was generally based on the following characteristics:

Involvement of researchers across studies.

In the majority of cases (n = 60, 84.5%), it was clear when the researchers conducting the SDA were involved in the parent study, as indicated by researchers self-citing their previous work on the parent study or directly referring to their participation in the parent study (e.g. We conducted in-depth interviews ...). However, it was not always clear when new investigators were included on the research team for SDA and therefore, the exact number of SDA researchers who were also involved with the parent study was not always easily determined. In some cases, the relationship could be assumed (but was not assumed for the current analysis), such as those where the SDA researchers did not explicitly indicate their involvement with the parent study, but described that the study was conducted at their institution and/or their IRB approved the study for research with human subjects (see Bergstrom et al., 2009 ). There were other cases where researchers shared their data with one another and combined data from independent parent studies for the purpose of SDA and indicated that they were involved with one or more of the studies that data were derived from, but not all of the studies (see Sallee and Harris, 2011 ; Taylor and Brown, 2011 ). Hence, the in-depth knowledge of parent study methodologies and data by each researcher was limited.

There were a smaller number of cases (n = 8, 11.3%) where researchers reported that they conducted an SDA with qualitative data derived from an qualitative data archive where the author(s) did not indicate having an affiliation with the archive team (see Kelly et al., 2013 ; Wilbanks et al., 2016 ). In these cases, it was common for SDA researchers to describe the methods used to collect the data for the archive, or at a minimum, describe the purpose and source of the data archive. Very few studies included in this analysis involved researchers conducting SDA using data that they were not involved with at all and/or not obtained through an archive. The most common case for this (n = 3, 4.3%) involved researchers who conducted analyses with data collected through program or government evaluations (see Hohl and Gaskell, 2008 ; Romero et al., 2012 ; Wint and Frank, 2006 ). One notable case involved an SDA using data collected by unrelated independent researchers to reanalyze classic sociological research ( Fielding and Fielding, 2000 ).

Context and purpose of SDA.

In almost all cases of research included in this analysis (n = 68, 95.7%), the SDA researchers provided the context and methodologies of the parent studies, though these descriptions varied in detail. Most were explicit in whether the data used in the SDA involved an entire dataset, a subset of data, or combination of data from the parent study or studies. The most common reason (n = 57, 80.2%) to conduct SDA was to explore new research questions post hoc that would advance theory in a particular area. In a smaller number of cases (n = 18, 25.4%), SDA was conducted post hoc to advance methodology. For instance, Myers and Lampropoulou (2016) conducted an SDA with data from several studies to examine the practice of identifying laughter in transcriptions of audio data. In other cases, SDA was conducted to demonstrate novel analytic approaches (see Henderson et al., 2012 ; Patel et al., 2015) or approaches to research (see Morse and Pooler, 2002 ; Schwartz et al., 2010 ).

Clarity in distinguishing between primary and secondary analyses.

While it was clear in most studies, there lacked consistency in the identification and description of SDA among the articles assessed. Some studies did not identify as being an SDA, but described methods and purposes that diverged from those of the parent studies and/or indicated that the analysis of the data for SDA was completed after the primary analysis in the parent study. In other cases, the researchers identified the research as being SDA, but it was not clear if the purpose or aims of the SDA diverged from the initial analysis or occurred subsequent to the parent study. For instance, Cortes et al. (2016) indicated that their study was considered SDA, because the theme that emerged wasn’t sufficiently explored before the IRB protocol period ended and therefore the findings being presented actually emerged during the primary analysis. In Coltart and Henwood’s (2012) study, they reported that they “routinely crossed conventional boundaries between primary and secondary analysis” (p. 39).

Ethical considerations and human subject protections in qualitative SDA

The articles assessed in this analysis also varied in the extent to which they discussed ethical considerations and protections of human subjects. The following is an analysis of the extent to which ethical issues were identified and/or addressed in the parent and/or SDA research presented in the articles.

Attention given to ethical safeguards in writing about primary and secondary studies.

For the majority of studies assessed, it was most common for researchers to provide information regarding IRB approval and/or ethical considerations given in the parent study methodology (n = 26, 36.6%) with fewer cases indicating that IRB approval or exemption was specifically obtained or ethical considerations were made in their effort to conduct SDA. Most articles indicated that IRB approval was obtained for the parent study with no mention about IRB review of the SDA (n = 19, 26.8%). In 17 cases (23.9%), the researchers indicated that IRB approval was obtained for the SDA study alone or for both the parent study and SDA. In one of these cases, a researcher using archived data reported that IRB approval was sought out, but not required for the scope of their study ( Heaton, 2015 ).

Examples of ethical procedures in secondary analysis.

Some researchers described steps for protecting human subjects that extended to the SDA, such as de-identifying data before SDA was conducted. Very few studies (n = 5, 7.0%) specifically indicated that participants in the parent studies consented to having their data available for SDA. Some researchers identified ethical considerations that are intrinsic to the nature of SDA, such as their efforts to conduct SDA in order to not overburden vulnerable populations that were participating in research (see Turcotte et al., 2015 ). Also less common was for researchers to report ethical dilemmas or concerns in conducting SDA, such as Coltart and Henwood’s (2012) research with longitudinal qualitative data, were the researchers presented concerns about anonymity and ethics regarding archived data.

Attention given to methods and rigor in writing about primary and secondary studies

Finally, articles varied in the extent to which they described issues of rigor and limitations stemming specifically from the SDA. There was variation on the attention researchers gave to describing methods and rigor in the parent and SDA studies, their approaches to increasing rigor in SDA, and the limitations they identified that were specific from conducting an SDA.

Attention and focus of parent and secondary studies.

For most of the articles appraised (n = 60, 84.5%), researchers provided detail on the methodologies used to collect and analyze data in the parent study. The level of detail of these descriptions varied significantly, with some researchers providing a few sentences on the overall methodological approach to data collection in the parent study with little to no detail on primary analysis, to extensive sections of research articles being dedicated to the methods of the parent studies. Some researchers also reported the funding sources of the parent studies (n = 28, 39.4%), which may further help readers assess bias in the SDA. Many studies also described the process of SDA as being distinctively different from primary analysis, though in some articles, it was difficult to assess how SDA different from primary data analysis.

Examples of rigor in secondary analysis.

Some studies presented strategies used by researchers to increase rigor in the SDA study. Many studies (n = 25, 35.2%) reported common practices in qualitative data analysis to increase rigor, such as member checking, memoing, triangulation, peer debriefing, inter-rater agreement, and maintaining audit trails. In some articles, researchers indicated inclusion of members of the parent study research team or new researchers with expertise in the area of focus for the SDA with the intent of increasing rigor. Other articles asserted that the research questions explored through SDA were “a good fit” with those of the parent study, and therefore increased the trustworthiness of findings. Only a few studies reported that steps were taken in SDA to analyze data with a lens that was not influenced by the researchers’ involvement with the parent study, such as using clean, uncoded transcripts from parent study (see Williams and Collins, 2002 ) or purposefully reading transcripts with new perspective (see Moran and Russo-Netzer, 2016 ). Some articles reported that a strength in the SDA was that the researchers involved were very familiar with the parent study methodology and data. In one case ( Volume and Farris, 2000 ), the researchers indicated that one source of rigor was that emerging findings during analysis could not influence future interviews, since the data were already all collected, which may minimize bias.

Identification of limitations in secondary analysis.

Most articles reported limitations in their studies that are often reported in qualitative research (e.g. small samples, not generalizable), though most of these descriptions did not relate specifically to SDA. About half (n = 36, 50.7%) of articles identified limitations in their study that resulted from the nature of their SDA, such as: not being able to return to participants for member checking or conduct further interviews to clarify or validate thematic findings in the SDA; conducting research with one purpose using data that were collected for another purpose, which limited the number of cases or extent to which a thematic finding could be identified; and conducting qualitative research with data that may not be as relevant as when it was first collected, given changes in context and/or time that may have influenced the data if collected in present day.

In response to growing dialogue and criticisms about conducting SDA with qualitative data, this CIS set out to better understand the context of qualitative SDA in practice, with particular attention given to issues of methodological rigor and ethical principles. Overall, 71 articles met the inclusion criteria and were appraised, a number that is expectedly dwarfed by the number of quantitative studies that are identified as using SDA. However, thematic findings in this assessment address controversies in the literature and also raise issues in conducting SDA with qualitative data that can be used to guide future research and assessment of qualitative SDA studies.

The need for better and consistent definitions of qualitative SDA

Revisiting Hinds et al.’s (1997 ) approaches to qualitative SDA described earlier, most qualitative SDA studies identified and appraised through this CIS best reflect the approaches of conducting a more in-depth analysis of themes from the parent study with a subset of data from that study and conducting an analysis of data from the parent study that appear important, but not sufficiently focused on in the primary analysis , though all four approaches they identified were observed among studies. However, the main concern that arose from this CIS was that researchers often failed to describe the differences between primary and secondary analysis (or at least the relationship between the two analyses). Many described SDA strategies that were similar in scope and appeared to have been conducted in close timing to the primary analysis. As a result, it was not always clear cut if findings were more related to primary analysis than an actual secondary analysis.

There were also cases where researchers described conducting qualitative SDA, but did not label it as such. As a result, one of the primary limitations of this CIS is that the extent to which qualitative SDA studies were excluded from search results and therefore not included in this synthesis is unclear. Scholars can improve this issue by explicitly referring to qualitative SDA as such and describing the study methods in a way that make clear how SDA differed from primary analysis in scope, context, and/or methodology. Otherwise, given the fluid and/or emerging nature of many qualitative analyses and the fact that many researchers conduct qualitative SDA with their own data, there are limitations on the extent to which audiences can fully appraise such research.

Maintaining ethical standards in qualitative SDA

It is generally accepted that almost all research involving human subjects, including research involving SDA, should be reviewed by an IRB and determined if the study is exempt from further review or approved based on its treatment of human subjects. However, the majority of articles included in this analysis reported that IRB approval was obtained for the parent study with no mention of whether review was sought for the SDA or if the SDA was included under the same protocol. In the case of quantitative SDA, this issue may be more clearly explained in research reporting, since data is often shared among researchers who were not involved with the parent study and therefore SDA researchers would not be able to claim to be covered under the protocol approval for the parent study. As was found through this CIS, many qualitative SDA researchers are conducting analysis with their own data and may feel that the SDA is covered under the original protocol approval. However, it is unclear if this is always appropriate, given that many SDA investigations involve new research questions, unit of analysis, or focus from which the participants of the parent study may have consented to.

In addition, specific safeguards aimed at protecting human subjects should always be taken in qualitative SDA and described in the research reporting. For researchers who are interested in conducting studies that may be open to SDA in the future, this may mean taking specific steps that would make additional IRB review unnecessary (when the same researchers are conducting further analysis) or eligible for exemption. For instance, qualitative researchers should have participants consent to SDA of their data during the recruitment process or explain to participants during the consent process that researchers may report findings from their data that are unexpectedly derived and therefore not feasibly explained in the purpose and goals of the study through the initial consent form. They can also design interview and focus group guides that could more easily be de-identified for researchers to use later and think critically about whether additional safeguards should be in place to protect the participants in primary studies. Researchers should report about these procedures so that their audience can adequately access the ethical considerations taken in their research.

Ways to move forward

Promoting qualitative data sharing..

While much of the literature on the topic has criticized the use of qualitative data for SDA, some scholars have recognized its potential benefit to the state of science and have offered suggestions to promote this practice. Drawing upon the literature, Dargentas (2006) identified several ways of advancing the practice of SDA of qualitative data, including: increasing access to archived qualitative data, training researchers on using computer assisted qualitative analysis software, and addressing issues related to qualitative methodologies (p. 3). Such efforts have initiated, but have been slower to develop than those for quantitative data. Examples include the UK Data Service, the Timescapes Archive (University of Leeds) and The Oxford Health Experiences Research Group (University of Oxford).

Arguments have also been made that qualitative researchers can deploy strategies to collect data that is suitable and appropriate for SDA by other investigators. Walters (2009) asserts that through effective use of reflexivity, qualitative researchers can collect data that identifies and documents the socio-cultural-political context under which the data are collected so the dataset is relevant and important for future use by other researchers. However, Parry and Mauthner (2004) caution that researchers who develop plans at the beginning of their projects to collect qualitative data that may be shared in the future may run the risk of restraining themselves, through the questions that they ask, data collection strategies, or even their own contributions to creating the data (e.g. offering personal information to respondents to develop rapport) in a way that they would not if they were creating the data for solely their own use. This could compromise the quality of the data.

Recommendations

After our review of the literature, we offer three sets of recommendations to give SDA common anchors in qualitative research, designed to stress its strengths and reveal its limitations.

1. Increasing clarity and transparency in SDA.

We recommend a clearer and consistent definition of qualitative SDA where some or all of the following information is included in manuscripts. This includes: (1a) describing if and how the SDA researchers were involved with the parent study or studies; and (1b) a distinction between primary and secondary analysis should be provided so that the readers can determine if findings reflect the emerging nature of qualitative research findings or a new approach or purpose for re-analysis. Such descriptions will help readers evaluate the researchers’ familiarity of the parent study methods, sample, data, and context. This will also help readers evaluate whether findings were the result of the emerging process of qualitative analysis, as opposed to SDA, which ideally would be a new analysis with a different purpose or approach from the parent study, even if the researchers remain the same across studies. A number of exemplary studies were identified that helped create clear and transparent understandings about the difference between the parent and SDA studies, including: Molloy et al. (2015) , Myers and Lampropoulou’s (2016) , and Pleschberger et al. (2011) .

2. Ethics in conducting qualitative SDA studies.

The ethics of conducting qualitative SDA is one of the most common topics written about in the literature about this practice. Hence, it was surprising that many studies in this CIS did not discuss IRB approval or strategies for protecting human subjects in the SDA study. It may be that researchers and peer reviewers assume that IRB approval was given or extended from the parent study’s protocol. However, researchers should take responsibility to report their efforts in protecting human subjects through qualitative SDA. Some specific recommendations include: (2a) clarity about how the researchers obtained approval or exemption for the SDA; and (2b) methods to protect human subjects in the SDA, such as de-identified data, or consent forms that outlined SDA.

3. Increasing rigor and identifying our limitations in qualitative SDA.

Researchers are expected to maximize rigor in their research methodologies and identify limitations in their studies that may influence their audience’s interpretation of findings. However, in this CIS it was found that only about half of the articles identified how the nature of SDA may affect their findings. Some recommendations for increasing rigor and transparency include: (3a) employing and describing strategies for increasing rigor within the SDA, such as including research team members from the parent study, including new research team members with specific expertise or fresh perspectives uninfluenced by the primary analysis, conducting SDA with uncoded transcripts, or other methods (audit trails, peer debriefing, member checking); and (3b) identifying limitations in qualitative SDA, such as how time or context may have changed the relevance of the data and/or the extent to which the goals and purpose of the SDA research were a good fit with those of the parent study. Examples of SDA studies that described rigor include: Borg et al. (2013) , Chau et al.’s (2008 ), and Mayer and Rosenfeld (2006) .

Qualitative research often involves long data collection sessions and/or participants who share intimate, sensitive and detailed information about themselves with researchers to promote the goal of generating new knowledge that may benefit society. SDA of qualitative research is one way to advance this goal while minimizing the burden of research participants. Although SDA of qualitative data may not be appropriate or ethical in all cases, researchers should take the responsibility of recognizing when qualitative data are appropriate and safe to conduct SDA and/ or find creative ways that new studies may be designed that promote SDA. In such efforts, researchers should also take responsibility for identifying ways of promoting rigor and ethical research practices in SDA and clearly identify and describe these efforts so that the academic community can appropriately appraise such work while also learn from one another to advance methodology.

Acknowledgments

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Contributor Information

Nicole Ruggiano, School of Social Work, University of Alabama, USA.

Tam E Perry, School of Social Work, Wayne State University, USA.

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