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Qualitative Research Methods: Types, Analysis + Examples

Qualitative Research

Qualitative research is based on the disciplines of social sciences like psychology, sociology, and anthropology. Therefore, the qualitative research methods allow for in-depth and further probing and questioning of respondents based on their responses. The interviewer/researcher also tries to understand their motivation and feelings. Understanding how your audience makes decisions can help derive conclusions in market research.

What is qualitative research?

Qualitative research is defined as a market research method that focuses on obtaining data through open-ended and conversational communication .

This method is about “what” people think and “why” they think so. For example, consider a convenience store looking to improve its patronage. A systematic observation concludes that more men are visiting this store. One good method to determine why women were not visiting the store is conducting an in-depth interview method with potential customers.

For example, after successfully interviewing female customers and visiting nearby stores and malls, the researchers selected participants through random sampling . As a result, it was discovered that the store didn’t have enough items for women.

So fewer women were visiting the store, which was understood only by personally interacting with them and understanding why they didn’t visit the store because there were more male products than female ones.

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Types of qualitative research methods with examples

Qualitative research methods are designed in a manner that helps reveal the behavior and perception of a target audience with reference to a particular topic. There are different types of qualitative research methods, such as in-depth interviews, focus groups, ethnographic research, content analysis, and case study research that are usually used.

The results of qualitative methods are more descriptive, and the inferences can be drawn quite easily from the obtained data .

Qualitative research methods originated in the social and behavioral research sciences. Today, our world is more complicated, and it is difficult to understand what people think and perceive. Online research methods make it easier to understand that as it is a more communicative and descriptive analysis .

The following are the qualitative research methods that are frequently used. Also, read about qualitative research examples :

Types of Qualitative Research

1. One-on-one interview

Conducting in-depth interviews is one of the most common qualitative research methods. It is a personal interview that is carried out with one respondent at a time. This is purely a conversational method and invites opportunities to get details in depth from the respondent.

One of the advantages of this method is that it provides a great opportunity to gather precise data about what people believe and their motivations . If the researcher is well experienced, asking the right questions can help him/her collect meaningful data. If they should need more information, the researchers should ask such follow-up questions that will help them collect more information.

These interviews can be performed face-to-face or on the phone and usually can last between half an hour to two hours or even more. When the in-depth interview is conducted face to face, it gives a better opportunity to read the respondents’ body language and match the responses.

2. Focus groups

A focus group is also a commonly used qualitative research method used in data collection. A focus group usually includes a limited number of respondents (6-10) from within your target market.

The main aim of the focus group is to find answers to the “why, ” “what,” and “how” questions. One advantage of focus groups is you don’t necessarily need to interact with the group in person. Nowadays, focus groups can be sent an online survey on various devices, and responses can be collected at the click of a button.

Focus groups are an expensive method as compared to other online qualitative research methods. Typically, they are used to explain complex processes. This method is very useful for market research on new products and testing new concepts.

3. Ethnographic research

Ethnographic research is the most in-depth observational research method that studies people in their naturally occurring environment.

This method requires the researchers to adapt to the target audiences’ environments, which could be anywhere from an organization to a city or any remote location. Here, geographical constraints can be an issue while collecting data.

This research design aims to understand the cultures, challenges, motivations, and settings that occur. Instead of relying on interviews and discussions, you experience the natural settings firsthand.

This type of research method can last from a few days to a few years, as it involves in-depth observation and collecting data on those grounds. It’s a challenging and time-consuming method and solely depends on the researcher’s expertise to analyze, observe, and infer the data.

4. Case study research

T he case study method has evolved over the past few years and developed into a valuable quality research method. As the name suggests, it is used for explaining an organization or an entity.

This type of research method is used within a number of areas like education, social sciences, and similar. This method may look difficult to operate; however , it is one of the simplest ways of conducting research as it involves a deep dive and thorough understanding of the data collection methods and inferring the data.

5. Record keeping

This method makes use of the already existing reliable documents and similar sources of information as the data source. This data can be used in new research. This is similar to going to a library. There, one can go over books and other reference material to collect relevant data that can likely be used in the research.

6. Process of observation

Qualitative Observation is a process of research that uses subjective methodologies to gather systematic information or data. Since the focus on qualitative observation is the research process of using subjective methodologies to gather information or data. Qualitative observation is primarily used to equate quality differences.

Qualitative observation deals with the 5 major sensory organs and their functioning – sight, smell, touch, taste, and hearing. This doesn’t involve measurements or numbers but instead characteristics.

Explore Insightfully Contextual Inquiry in Qualitative Research

Qualitative research: data collection and analysis

A. qualitative data collection.

Qualitative data collection allows collecting data that is non-numeric and helps us to explore how decisions are made and provide us with detailed insight. For reaching such conclusions the data that is collected should be holistic, rich, and nuanced and findings to emerge through careful analysis.

  • Whatever method a researcher chooses for collecting qualitative data, one aspect is very clear the process will generate a large amount of data. In addition to the variety of methods available, there are also different methods of collecting and recording the data.

For example, if the qualitative data is collected through a focus group or one-to-one discussion, there will be handwritten notes or video recorded tapes. If there are recording they should be transcribed and before the process of data analysis can begin.

  • As a rough guide, it can take a seasoned researcher 8-10 hours to transcribe the recordings of an interview, which can generate roughly 20-30 pages of dialogues. Many researchers also like to maintain separate folders to maintain the recording collected from the different focus group. This helps them compartmentalize the data collected.
  • In case there are running notes taken, which are also known as field notes, they are helpful in maintaining comments, environmental contexts, environmental analysis , nonverbal cues etc. These filed notes are helpful and can be compared while transcribing audio recorded data. Such notes are usually informal but should be secured in a similar manner as the video recordings or the audio tapes.

B. Qualitative data analysis

Qualitative data analysis such as notes, videos, audio recordings images, and text documents. One of the most used methods for qualitative data analysis is text analysis.

Text analysis is a  data analysis method that is distinctly different from all other qualitative research methods, where researchers analyze the social life of the participants in the research study and decode the words, actions, etc. 

There are images also that are used in this research study and the researchers analyze the context in which the images are used and draw inferences from them. In the last decade, text analysis through what is shared on social media platforms has gained supreme popularity.

Characteristics of qualitative research methods

Characteristics of qualitative research methods - Infographics| QuestionPro

  • Qualitative research methods usually collect data at the sight, where the participants are experiencing issues or research problems . These are real-time data and rarely bring the participants out of the geographic locations to collect information.
  • Qualitative researchers typically gather multiple forms of data, such as interviews, observations, and documents, rather than rely on a single data source .
  • This type of research method works towards solving complex issues by breaking down into meaningful inferences, that is easily readable and understood by all.
  • Since it’s a more communicative method, people can build their trust on the researcher and the information thus obtained is raw and unadulterated.

Qualitative research method case study

Let’s take the example of a bookstore owner who is looking for ways to improve their sales and customer outreach. An online community of members who were loyal patrons of the bookstore were interviewed and related questions were asked and the questions were answered by them.

At the end of the interview, it was realized that most of the books in the stores were suitable for adults and there were not enough options for children or teenagers.

By conducting this qualitative research the bookstore owner realized what the shortcomings were and what were the feelings of the readers. Through this research now the bookstore owner can now keep books for different age categories and can improve his sales and customer outreach.

Such qualitative research method examples can serve as the basis to indulge in further quantitative research , which provides remedies.

When to use qualitative research

Researchers make use of qualitative research techniques when they need to capture accurate, in-depth insights. It is very useful to capture “factual data”. Here are some examples of when to use qualitative research.

  • Developing a new product or generating an idea.
  • Studying your product/brand or service to strengthen your marketing strategy.
  • To understand your strengths and weaknesses.
  • Understanding purchase behavior.
  • To study the reactions of your audience to marketing campaigns and other communications.
  • Exploring market demographics, segments, and customer care groups.
  • Gathering perception data of a brand, company, or product.

LEARN ABOUT: Steps in Qualitative Research

Qualitative research methods vs quantitative research methods

The basic differences between qualitative research methods and quantitative research methods are simple and straightforward. They differ in:

  • Their analytical objectives
  • Types of questions asked
  • Types of data collection instruments
  • Forms of data they produce
  • Degree of flexibility

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What is Qualitative in Qualitative Research

Patrik aspers.

1 Department of Sociology, Uppsala University, Uppsala, Sweden

2 Seminar for Sociology, Universität St. Gallen, St. Gallen, Switzerland

3 Department of Media and Social Sciences, University of Stavanger, Stavanger, Norway

What is qualitative research? If we look for a precise definition of qualitative research, and specifically for one that addresses its distinctive feature of being “qualitative,” the literature is meager. In this article we systematically search, identify and analyze a sample of 89 sources using or attempting to define the term “qualitative.” Then, drawing on ideas we find scattered across existing work, and based on Becker’s classic study of marijuana consumption, we formulate and illustrate a definition that tries to capture its core elements. We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. This formulation is developed as a tool to help improve research designs while stressing that a qualitative dimension is present in quantitative work as well. Additionally, it can facilitate teaching, communication between researchers, diminish the gap between qualitative and quantitative researchers, help to address critiques of qualitative methods, and be used as a standard of evaluation of qualitative research.

If we assume that there is something called qualitative research, what exactly is this qualitative feature? And how could we evaluate qualitative research as good or not? Is it fundamentally different from quantitative research? In practice, most active qualitative researchers working with empirical material intuitively know what is involved in doing qualitative research, yet perhaps surprisingly, a clear definition addressing its key feature is still missing.

To address the question of what is qualitative we turn to the accounts of “qualitative research” in textbooks and also in empirical work. In his classic, explorative, interview study of deviance Howard Becker ( 1963 ) asks ‘How does one become a marijuana user?’ In contrast to pre-dispositional and psychological-individualistic theories of deviant behavior, Becker’s inherently social explanation contends that becoming a user of this substance is the result of a three-phase sequential learning process. First, potential users need to learn how to smoke it properly to produce the “correct” effects. If not, they are likely to stop experimenting with it. Second, they need to discover the effects associated with it; in other words, to get “high,” individuals not only have to experience what the drug does, but also to become aware that those sensations are related to using it. Third, they require learning to savor the feelings related to its consumption – to develop an acquired taste. Becker, who played music himself, gets close to the phenomenon by observing, taking part, and by talking to people consuming the drug: “half of the fifty interviews were conducted with musicians, the other half covered a wide range of people, including laborers, machinists, and people in the professions” (Becker 1963 :56).

Another central aspect derived through the common-to-all-research interplay between induction and deduction (Becker 2017 ), is that during the course of his research Becker adds scientifically meaningful new distinctions in the form of three phases—distinctions, or findings if you will, that strongly affect the course of his research: its focus, the material that he collects, and which eventually impact his findings. Each phase typically unfolds through social interaction, and often with input from experienced users in “a sequence of social experiences during which the person acquires a conception of the meaning of the behavior, and perceptions and judgments of objects and situations, all of which make the activity possible and desirable” (Becker 1963 :235). In this study the increased understanding of smoking dope is a result of a combination of the meaning of the actors, and the conceptual distinctions that Becker introduces based on the views expressed by his respondents. Understanding is the result of research and is due to an iterative process in which data, concepts and evidence are connected with one another (Becker 2017 ).

Indeed, there are many definitions of qualitative research, but if we look for a definition that addresses its distinctive feature of being “qualitative,” the literature across the broad field of social science is meager. The main reason behind this article lies in the paradox, which, to put it bluntly, is that researchers act as if they know what it is, but they cannot formulate a coherent definition. Sociologists and others will of course continue to conduct good studies that show the relevance and value of qualitative research addressing scientific and practical problems in society. However, our paper is grounded in the idea that providing a clear definition will help us improve the work that we do. Among researchers who practice qualitative research there is clearly much knowledge. We suggest that a definition makes this knowledge more explicit. If the first rationale for writing this paper refers to the “internal” aim of improving qualitative research, the second refers to the increased “external” pressure that especially many qualitative researchers feel; pressure that comes both from society as well as from other scientific approaches. There is a strong core in qualitative research, and leading researchers tend to agree on what it is and how it is done. Our critique is not directed at the practice of qualitative research, but we do claim that the type of systematic work we do has not yet been done, and that it is useful to improve the field and its status in relation to quantitative research.

The literature on the “internal” aim of improving, or at least clarifying qualitative research is large, and we do not claim to be the first to notice the vagueness of the term “qualitative” (Strauss and Corbin 1998 ). Also, others have noted that there is no single definition of it (Long and Godfrey 2004 :182), that there are many different views on qualitative research (Denzin and Lincoln 2003 :11; Jovanović 2011 :3), and that more generally, we need to define its meaning (Best 2004 :54). Strauss and Corbin ( 1998 ), for example, as well as Nelson et al. (1992:2 cited in Denzin and Lincoln 2003 :11), and Flick ( 2007 :ix–x), have recognized that the term is problematic: “Actually, the term ‘qualitative research’ is confusing because it can mean different things to different people” (Strauss and Corbin 1998 :10–11). Hammersley has discussed the possibility of addressing the problem, but states that “the task of providing an account of the distinctive features of qualitative research is far from straightforward” ( 2013 :2). This confusion, as he has recently further argued (Hammersley 2018 ), is also salient in relation to ethnography where different philosophical and methodological approaches lead to a lack of agreement about what it means.

Others (e.g. Hammersley 2018 ; Fine and Hancock 2017 ) have also identified the treat to qualitative research that comes from external forces, seen from the point of view of “qualitative research.” This threat can be further divided into that which comes from inside academia, such as the critique voiced by “quantitative research” and outside of academia, including, for example, New Public Management. Hammersley ( 2018 ), zooming in on one type of qualitative research, ethnography, has argued that it is under treat. Similarly to Fine ( 2003 ), and before him Gans ( 1999 ), he writes that ethnography’ has acquired a range of meanings, and comes in many different versions, these often reflecting sharply divergent epistemological orientations. And already more than twenty years ago while reviewing Denzin and Lincoln’ s Handbook of Qualitative Methods Fine argued:

While this increasing centrality [of qualitative research] might lead one to believe that consensual standards have developed, this belief would be misleading. As the methodology becomes more widely accepted, querulous challengers have raised fundamental questions that collectively have undercut the traditional models of how qualitative research is to be fashioned and presented (1995:417).

According to Hammersley, there are today “serious treats to the practice of ethnographic work, on almost any definition” ( 2018 :1). He lists five external treats: (1) that social research must be accountable and able to show its impact on society; (2) the current emphasis on “big data” and the emphasis on quantitative data and evidence; (3) the labor market pressure in academia that leaves less time for fieldwork (see also Fine and Hancock 2017 ); (4) problems of access to fields; and (5) the increased ethical scrutiny of projects, to which ethnography is particularly exposed. Hammersley discusses some more or less insufficient existing definitions of ethnography.

The current situation, as Hammersley and others note—and in relation not only to ethnography but also qualitative research in general, and as our empirical study shows—is not just unsatisfactory, it may even be harmful for the entire field of qualitative research, and does not help social science at large. We suggest that the lack of clarity of qualitative research is a real problem that must be addressed.

Towards a Definition of Qualitative Research

Seen in an historical light, what is today called qualitative, or sometimes ethnographic, interpretative research – or a number of other terms – has more or less always existed. At the time the founders of sociology – Simmel, Weber, Durkheim and, before them, Marx – were writing, and during the era of the Methodenstreit (“dispute about methods”) in which the German historical school emphasized scientific methods (cf. Swedberg 1990 ), we can at least speak of qualitative forerunners.

Perhaps the most extended discussion of what later became known as qualitative methods in a classic work is Bronisław Malinowski’s ( 1922 ) Argonauts in the Western Pacific , although even this study does not explicitly address the meaning of “qualitative.” In Weber’s ([1921–-22] 1978) work we find a tension between scientific explanations that are based on observation and quantification and interpretative research (see also Lazarsfeld and Barton 1982 ).

If we look through major sociology journals like the American Sociological Review , American Journal of Sociology , or Social Forces we will not find the term qualitative sociology before the 1970s. And certainly before then much of what we consider qualitative classics in sociology, like Becker’ study ( 1963 ), had already been produced. Indeed, the Chicago School often combined qualitative and quantitative data within the same study (Fine 1995 ). Our point being that before a disciplinary self-awareness the term quantitative preceded qualitative, and the articulation of the former was a political move to claim scientific status (Denzin and Lincoln 2005 ). In the US the World War II seem to have sparked a critique of sociological work, including “qualitative work,” that did not follow the scientific canon (Rawls 2018 ), which was underpinned by a scientifically oriented and value free philosophy of science. As a result the attempts and practice of integrating qualitative and quantitative sociology at Chicago lost ground to sociology that was more oriented to surveys and quantitative work at Columbia under Merton-Lazarsfeld. The quantitative tradition was also able to present textbooks (Lundberg 1951 ) that facilitated the use this approach and its “methods.” The practices of the qualitative tradition, by and large, remained tacit or was part of the mentoring transferred from the renowned masters to their students.

This glimpse into history leads us back to the lack of a coherent account condensed in a definition of qualitative research. Many of the attempts to define the term do not meet the requirements of a proper definition: A definition should be clear, avoid tautology, demarcate its domain in relation to the environment, and ideally only use words in its definiens that themselves are not in need of definition (Hempel 1966 ). A definition can enhance precision and thus clarity by identifying the core of the phenomenon. Preferably, a definition should be short. The typical definition we have found, however, is an ostensive definition, which indicates what qualitative research is about without informing us about what it actually is :

Qualitative research is multimethod in focus, involving an interpretative, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives. (Denzin and Lincoln 2005 :2)

Flick claims that the label “qualitative research” is indeed used as an umbrella for a number of approaches ( 2007 :2–4; 2002 :6), and it is not difficult to identify research fitting this designation. Moreover, whatever it is, it has grown dramatically over the past five decades. In addition, courses have been developed, methods have flourished, arguments about its future have been advanced (for example, Denzin and Lincoln 1994) and criticized (for example, Snow and Morrill 1995 ), and dedicated journals and books have mushroomed. Most social scientists have a clear idea of research and how it differs from journalism, politics and other activities. But the question of what is qualitative in qualitative research is either eluded or eschewed.

We maintain that this lacuna hinders systematic knowledge production based on qualitative research. Paul Lazarsfeld noted the lack of “codification” as early as 1955 when he reviewed 100 qualitative studies in order to offer a codification of the practices (Lazarsfeld and Barton 1982 :239). Since then many texts on “qualitative research” and its methods have been published, including recent attempts (Goertz and Mahoney 2012 ) similar to Lazarsfeld’s. These studies have tried to extract what is qualitative by looking at the large number of empirical “qualitative” studies. Our novel strategy complements these endeavors by taking another approach and looking at the attempts to codify these practices in the form of a definition, as well as to a minor extent take Becker’s study as an exemplar of what qualitative researchers actually do, and what the characteristic of being ‘qualitative’ denotes and implies. We claim that qualitative researchers, if there is such a thing as “qualitative research,” should be able to codify their practices in a condensed, yet general way expressed in language.

Lingering problems of “generalizability” and “how many cases do I need” (Small 2009 ) are blocking advancement – in this line of work qualitative approaches are said to differ considerably from quantitative ones, while some of the former unsuccessfully mimic principles related to the latter (Small 2009 ). Additionally, quantitative researchers sometimes unfairly criticize the first based on their own quality criteria. Scholars like Goertz and Mahoney ( 2012 ) have successfully focused on the different norms and practices beyond what they argue are essentially two different cultures: those working with either qualitative or quantitative methods. Instead, similarly to Becker ( 2017 ) who has recently questioned the usefulness of the distinction between qualitative and quantitative research, we focus on similarities.

The current situation also impedes both students and researchers in focusing their studies and understanding each other’s work (Lazarsfeld and Barton 1982 :239). A third consequence is providing an opening for critiques by scholars operating within different traditions (Valsiner 2000 :101). A fourth issue is that the “implicit use of methods in qualitative research makes the field far less standardized than the quantitative paradigm” (Goertz and Mahoney 2012 :9). Relatedly, the National Science Foundation in the US organized two workshops in 2004 and 2005 to address the scientific foundations of qualitative research involving strategies to improve it and to develop standards of evaluation in qualitative research. However, a specific focus on its distinguishing feature of being “qualitative” while being implicitly acknowledged, was discussed only briefly (for example, Best 2004 ).

In 2014 a theme issue was published in this journal on “Methods, Materials, and Meanings: Designing Cultural Analysis,” discussing central issues in (cultural) qualitative research (Berezin 2014 ; Biernacki 2014 ; Glaeser 2014 ; Lamont and Swidler 2014 ; Spillman 2014). We agree with many of the arguments put forward, such as the risk of methodological tribalism, and that we should not waste energy on debating methods separated from research questions. Nonetheless, a clarification of the relation to what is called “quantitative research” is of outmost importance to avoid misunderstandings and misguided debates between “qualitative” and “quantitative” researchers. Our strategy means that researchers, “qualitative” or “quantitative” they may be, in their actual practice may combine qualitative work and quantitative work.

In this article we accomplish three tasks. First, we systematically survey the literature for meanings of qualitative research by looking at how researchers have defined it. Drawing upon existing knowledge we find that the different meanings and ideas of qualitative research are not yet coherently integrated into one satisfactory definition. Next, we advance our contribution by offering a definition of qualitative research and illustrate its meaning and use partially by expanding on the brief example introduced earlier related to Becker’s work ( 1963 ). We offer a systematic analysis of central themes of what researchers consider to be the core of “qualitative,” regardless of style of work. These themes – which we summarize in terms of four keywords: distinction, process, closeness, improved understanding – constitute part of our literature review, in which each one appears, sometimes with others, but never all in the same definition. They serve as the foundation of our contribution. Our categories are overlapping. Their use is primarily to organize the large amount of definitions we have identified and analyzed, and not necessarily to draw a clear distinction between them. Finally, we continue the elaboration discussed above on the advantages of a clear definition of qualitative research.

In a hermeneutic fashion we propose that there is something meaningful that deserves to be labelled “qualitative research” (Gadamer 1990 ). To approach the question “What is qualitative in qualitative research?” we have surveyed the literature. In conducting our survey we first traced the word’s etymology in dictionaries, encyclopedias, handbooks of the social sciences and of methods and textbooks, mainly in English, which is common to methodology courses. It should be noted that we have zoomed in on sociology and its literature. This discipline has been the site of the largest debate and development of methods that can be called “qualitative,” which suggests that this field should be examined in great detail.

In an ideal situation we should expect that one good definition, or at least some common ideas, would have emerged over the years. This common core of qualitative research should be so accepted that it would appear in at least some textbooks. Since this is not what we found, we decided to pursue an inductive approach to capture maximal variation in the field of qualitative research; we searched in a selection of handbooks, textbooks, book chapters, and books, to which we added the analysis of journal articles. Our sample comprises a total of 89 references.

In practice we focused on the discipline that has had a clear discussion of methods, namely sociology. We also conducted a broad search in the JSTOR database to identify scholarly sociology articles published between 1998 and 2017 in English with a focus on defining or explaining qualitative research. We specifically zoom in on this time frame because we would have expect that this more mature period would have produced clear discussions on the meaning of qualitative research. To find these articles we combined a number of keywords to search the content and/or the title: qualitative (which was always included), definition, empirical, research, methodology, studies, fieldwork, interview and observation .

As a second phase of our research we searched within nine major sociological journals ( American Journal of Sociology , Sociological Theory , American Sociological Review , Contemporary Sociology , Sociological Forum , Sociological Theory , Qualitative Research , Qualitative Sociology and Qualitative Sociology Review ) for articles also published during the past 19 years (1998–2017) that had the term “qualitative” in the title and attempted to define qualitative research.

Lastly we picked two additional journals, Qualitative Research and Qualitative Sociology , in which we could expect to find texts addressing the notion of “qualitative.” From Qualitative Research we chose Volume 14, Issue 6, December 2014, and from Qualitative Sociology we chose Volume 36, Issue 2, June 2017. Within each of these we selected the first article; then we picked the second article of three prior issues. Again we went back another three issues and investigated article number three. Finally we went back another three issues and perused article number four. This selection criteria was used to get a manageable sample for the analysis.

The coding process of the 89 references we gathered in our selected review began soon after the first round of material was gathered, and we reduced the complexity created by our maximum variation sampling (Snow and Anderson 1993 :22) to four different categories within which questions on the nature and properties of qualitative research were discussed. We call them: Qualitative and Quantitative Research, Qualitative Research, Fieldwork, and Grounded Theory. This – which may appear as an illogical grouping – merely reflects the “context” in which the matter of “qualitative” is discussed. If the selection process of the material – books and articles – was informed by pre-knowledge, we used an inductive strategy to code the material. When studying our material, we identified four central notions related to “qualitative” that appear in various combinations in the literature which indicate what is the core of qualitative research. We have labeled them: “distinctions”, “process,” “closeness,” and “improved understanding.” During the research process the categories and notions were improved, refined, changed, and reordered. The coding ended when a sense of saturation in the material arose. In the presentation below all quotations and references come from our empirical material of texts on qualitative research.

Analysis – What is Qualitative Research?

In this section we describe the four categories we identified in the coding, how they differently discuss qualitative research, as well as their overall content. Some salient quotations are selected to represent the type of text sorted under each of the four categories. What we present are examples from the literature.

Qualitative and Quantitative

This analytic category comprises quotations comparing qualitative and quantitative research, a distinction that is frequently used (Brown 2010 :231); in effect this is a conceptual pair that structures the discussion and that may be associated with opposing interests. While the general goal of quantitative and qualitative research is the same – to understand the world better – their methodologies and focus in certain respects differ substantially (Becker 1966 :55). Quantity refers to that property of something that can be determined by measurement. In a dictionary of Statistics and Methodology we find that “(a) When referring to *variables, ‘qualitative’ is another term for *categorical or *nominal. (b) When speaking of kinds of research, ‘qualitative’ refers to studies of subjects that are hard to quantify, such as art history. Qualitative research tends to be a residual category for almost any kind of non-quantitative research” (Stiles 1998:183). But it should be obvious that one could employ a quantitative approach when studying, for example, art history.

The same dictionary states that quantitative is “said of variables or research that can be handled numerically, usually (too sharply) contrasted with *qualitative variables and research” (Stiles 1998:184). From a qualitative perspective “quantitative research” is about numbers and counting, and from a quantitative perspective qualitative research is everything that is not about numbers. But this does not say much about what is “qualitative.” If we turn to encyclopedias we find that in the 1932 edition of the Encyclopedia of the Social Sciences there is no mention of “qualitative.” In the Encyclopedia from 1968 we can read:

Qualitative Analysis. For methods of obtaining, analyzing, and describing data, see [the various entries:] CONTENT ANALYSIS; COUNTED DATA; EVALUATION RESEARCH, FIELD WORK; GRAPHIC PRESENTATION; HISTORIOGRAPHY, especially the article on THE RHETORIC OF HISTORY; INTERVIEWING; OBSERVATION; PERSONALITY MEASUREMENT; PROJECTIVE METHODS; PSYCHOANALYSIS, article on EXPERIMENTAL METHODS; SURVEY ANALYSIS, TABULAR PRESENTATION; TYPOLOGIES. (Vol. 13:225)

Some, like Alford, divide researchers into methodologists or, in his words, “quantitative and qualitative specialists” (Alford 1998 :12). Qualitative research uses a variety of methods, such as intensive interviews or in-depth analysis of historical materials, and it is concerned with a comprehensive account of some event or unit (King et al. 1994 :4). Like quantitative research it can be utilized to study a variety of issues, but it tends to focus on meanings and motivations that underlie cultural symbols, personal experiences, phenomena and detailed understanding of processes in the social world. In short, qualitative research centers on understanding processes, experiences, and the meanings people assign to things (Kalof et al. 2008 :79).

Others simply say that qualitative methods are inherently unscientific (Jovanović 2011 :19). Hood, for instance, argues that words are intrinsically less precise than numbers, and that they are therefore more prone to subjective analysis, leading to biased results (Hood 2006 :219). Qualitative methodologies have raised concerns over the limitations of quantitative templates (Brady et al. 2004 :4). Scholars such as King et al. ( 1994 ), for instance, argue that non-statistical research can produce more reliable results if researchers pay attention to the rules of scientific inference commonly stated in quantitative research. Also, researchers such as Becker ( 1966 :59; 1970 :42–43) have asserted that, if conducted properly, qualitative research and in particular ethnographic field methods, can lead to more accurate results than quantitative studies, in particular, survey research and laboratory experiments.

Some researchers, such as Kalof, Dan, and Dietz ( 2008 :79) claim that the boundaries between the two approaches are becoming blurred, and Small ( 2009 ) argues that currently much qualitative research (especially in North America) tries unsuccessfully and unnecessarily to emulate quantitative standards. For others, qualitative research tends to be more humanistic and discursive (King et al. 1994 :4). Ragin ( 1994 ), and similarly also Becker, ( 1996 :53), Marchel and Owens ( 2007 :303) think that the main distinction between the two styles is overstated and does not rest on the simple dichotomy of “numbers versus words” (Ragin 1994 :xii). Some claim that quantitative data can be utilized to discover associations, but in order to unveil cause and effect a complex research design involving the use of qualitative approaches needs to be devised (Gilbert 2009 :35). Consequently, qualitative data are useful for understanding the nuances lying beyond those processes as they unfold (Gilbert 2009 :35). Others contend that qualitative research is particularly well suited both to identify causality and to uncover fine descriptive distinctions (Fine and Hallett 2014 ; Lichterman and Isaac Reed 2014 ; Katz 2015 ).

There are other ways to separate these two traditions, including normative statements about what qualitative research should be (that is, better or worse than quantitative approaches, concerned with scientific approaches to societal change or vice versa; Snow and Morrill 1995 ; Denzin and Lincoln 2005 ), or whether it should develop falsifiable statements; Best 2004 ).

We propose that quantitative research is largely concerned with pre-determined variables (Small 2008 ); the analysis concerns the relations between variables. These categories are primarily not questioned in the study, only their frequency or degree, or the correlations between them (cf. Franzosi 2016 ). If a researcher studies wage differences between women and men, he or she works with given categories: x number of men are compared with y number of women, with a certain wage attributed to each person. The idea is not to move beyond the given categories of wage, men and women; they are the starting point as well as the end point, and undergo no “qualitative change.” Qualitative research, in contrast, investigates relations between categories that are themselves subject to change in the research process. Returning to Becker’s study ( 1963 ), we see that he questioned pre-dispositional theories of deviant behavior working with pre-determined variables such as an individual’s combination of personal qualities or emotional problems. His take, in contrast, was to understand marijuana consumption by developing “variables” as part of the investigation. Thereby he presented new variables, or as we would say today, theoretical concepts, but which are grounded in the empirical material.

Qualitative Research

This category contains quotations that refer to descriptions of qualitative research without making comparisons with quantitative research. Researchers such as Denzin and Lincoln, who have written a series of influential handbooks on qualitative methods (1994; Denzin and Lincoln 2003 ; 2005 ), citing Nelson et al. (1992:4), argue that because qualitative research is “interdisciplinary, transdisciplinary, and sometimes counterdisciplinary” it is difficult to derive one single definition of it (Jovanović 2011 :3). According to them, in fact, “the field” is “many things at the same time,” involving contradictions, tensions over its focus, methods, and how to derive interpretations and findings ( 2003 : 11). Similarly, others, such as Flick ( 2007 :ix–x) contend that agreeing on an accepted definition has increasingly become problematic, and that qualitative research has possibly matured different identities. However, Best holds that “the proliferation of many sorts of activities under the label of qualitative sociology threatens to confuse our discussions” ( 2004 :54). Atkinson’s position is more definite: “the current state of qualitative research and research methods is confused” ( 2005 :3–4).

Qualitative research is about interpretation (Blumer 1969 ; Strauss and Corbin 1998 ; Denzin and Lincoln 2003 ), or Verstehen [understanding] (Frankfort-Nachmias and Nachmias 1996 ). It is “multi-method,” involving the collection and use of a variety of empirical materials (Denzin and Lincoln 1998; Silverman 2013 ) and approaches (Silverman 2005 ; Flick 2007 ). It focuses not only on the objective nature of behavior but also on its subjective meanings: individuals’ own accounts of their attitudes, motivations, behavior (McIntyre 2005 :127; Creswell 2009 ), events and situations (Bryman 1989) – what people say and do in specific places and institutions (Goodwin and Horowitz 2002 :35–36) in social and temporal contexts (Morrill and Fine 1997). For this reason, following Weber ([1921-22] 1978), it can be described as an interpretative science (McIntyre 2005 :127). But could quantitative research also be concerned with these questions? Also, as pointed out below, does all qualitative research focus on subjective meaning, as some scholars suggest?

Others also distinguish qualitative research by claiming that it collects data using a naturalistic approach (Denzin and Lincoln 2005 :2; Creswell 2009 ), focusing on the meaning actors ascribe to their actions. But again, does all qualitative research need to be collected in situ? And does qualitative research have to be inherently concerned with meaning? Flick ( 2007 ), referring to Denzin and Lincoln ( 2005 ), mentions conversation analysis as an example of qualitative research that is not concerned with the meanings people bring to a situation, but rather with the formal organization of talk. Still others, such as Ragin ( 1994 :85), note that qualitative research is often (especially early on in the project, we would add) less structured than other kinds of social research – a characteristic connected to its flexibility and that can lead both to potentially better, but also worse results. But is this not a feature of this type of research, rather than a defining description of its essence? Wouldn’t this comment also apply, albeit to varying degrees, to quantitative research?

In addition, Strauss ( 2003 ), along with others, such as Alvesson and Kärreman ( 2011 :10–76), argue that qualitative researchers struggle to capture and represent complex phenomena partially because they tend to collect a large amount of data. While his analysis is correct at some points – “It is necessary to do detailed, intensive, microscopic examination of the data in order to bring out the amazing complexity of what lies in, behind, and beyond those data” (Strauss 2003 :10) – much of his analysis concerns the supposed focus of qualitative research and its challenges, rather than exactly what it is about. But even in this instance we would make a weak case arguing that these are strictly the defining features of qualitative research. Some researchers seem to focus on the approach or the methods used, or even on the way material is analyzed. Several researchers stress the naturalistic assumption of investigating the world, suggesting that meaning and interpretation appear to be a core matter of qualitative research.

We can also see that in this category there is no consensus about specific qualitative methods nor about qualitative data. Many emphasize interpretation, but quantitative research, too, involves interpretation; the results of a regression analysis, for example, certainly have to be interpreted, and the form of meta-analysis that factor analysis provides indeed requires interpretation However, there is no interpretation of quantitative raw data, i.e., numbers in tables. One common thread is that qualitative researchers have to get to grips with their data in order to understand what is being studied in great detail, irrespective of the type of empirical material that is being analyzed. This observation is connected to the fact that qualitative researchers routinely make several adjustments of focus and research design as their studies progress, in many cases until the very end of the project (Kalof et al. 2008 ). If you, like Becker, do not start out with a detailed theory, adjustments such as the emergence and refinement of research questions will occur during the research process. We have thus found a number of useful reflections about qualitative research scattered across different sources, but none of them effectively describe the defining characteristics of this approach.

Although qualitative research does not appear to be defined in terms of a specific method, it is certainly common that fieldwork, i.e., research that entails that the researcher spends considerable time in the field that is studied and use the knowledge gained as data, is seen as emblematic of or even identical to qualitative research. But because we understand that fieldwork tends to focus primarily on the collection and analysis of qualitative data, we expected to find within it discussions on the meaning of “qualitative.” But, again, this was not the case.

Instead, we found material on the history of this approach (for example, Frankfort-Nachmias and Nachmias 1996 ; Atkinson et al. 2001), including how it has changed; for example, by adopting a more self-reflexive practice (Heyl 2001), as well as the different nomenclature that has been adopted, such as fieldwork, ethnography, qualitative research, naturalistic research, participant observation and so on (for example, Lofland et al. 2006 ; Gans 1999 ).

We retrieved definitions of ethnography, such as “the study of people acting in the natural courses of their daily lives,” involving a “resocialization of the researcher” (Emerson 1988 :1) through intense immersion in others’ social worlds (see also examples in Hammersley 2018 ). This may be accomplished by direct observation and also participation (Neuman 2007 :276), although others, such as Denzin ( 1970 :185), have long recognized other types of observation, including non-participant (“fly on the wall”). In this category we have also isolated claims and opposing views, arguing that this type of research is distinguished primarily by where it is conducted (natural settings) (Hughes 1971:496), and how it is carried out (a variety of methods are applied) or, for some most importantly, by involving an active, empathetic immersion in those being studied (Emerson 1988 :2). We also retrieved descriptions of the goals it attends in relation to how it is taught (understanding subjective meanings of the people studied, primarily develop theory, or contribute to social change) (see for example, Corte and Irwin 2017 ; Frankfort-Nachmias and Nachmias 1996 :281; Trier-Bieniek 2012 :639) by collecting the richest possible data (Lofland et al. 2006 ) to derive “thick descriptions” (Geertz 1973 ), and/or to aim at theoretical statements of general scope and applicability (for example, Emerson 1988 ; Fine 2003 ). We have identified guidelines on how to evaluate it (for example Becker 1996 ; Lamont 2004 ) and have retrieved instructions on how it should be conducted (for example, Lofland et al. 2006 ). For instance, analysis should take place while the data gathering unfolds (Emerson 1988 ; Hammersley and Atkinson 2007 ; Lofland et al. 2006 ), observations should be of long duration (Becker 1970 :54; Goffman 1989 ), and data should be of high quantity (Becker 1970 :52–53), as well as other questionable distinctions between fieldwork and other methods:

Field studies differ from other methods of research in that the researcher performs the task of selecting topics, decides what questions to ask, and forges interest in the course of the research itself . This is in sharp contrast to many ‘theory-driven’ and ‘hypothesis-testing’ methods. (Lofland and Lofland 1995 :5)

But could not, for example, a strictly interview-based study be carried out with the same amount of flexibility, such as sequential interviewing (for example, Small 2009 )? Once again, are quantitative approaches really as inflexible as some qualitative researchers think? Moreover, this category stresses the role of the actors’ meaning, which requires knowledge and close interaction with people, their practices and their lifeworld.

It is clear that field studies – which are seen by some as the “gold standard” of qualitative research – are nonetheless only one way of doing qualitative research. There are other methods, but it is not clear why some are more qualitative than others, or why they are better or worse. Fieldwork is characterized by interaction with the field (the material) and understanding of the phenomenon that is being studied. In Becker’s case, he had general experience from fields in which marihuana was used, based on which he did interviews with actual users in several fields.

Grounded Theory

Another major category we identified in our sample is Grounded Theory. We found descriptions of it most clearly in Glaser and Strauss’ ([1967] 2010 ) original articulation, Strauss and Corbin ( 1998 ) and Charmaz ( 2006 ), as well as many other accounts of what it is for: generating and testing theory (Strauss 2003 :xi). We identified explanations of how this task can be accomplished – such as through two main procedures: constant comparison and theoretical sampling (Emerson 1998:96), and how using it has helped researchers to “think differently” (for example, Strauss and Corbin 1998 :1). We also read descriptions of its main traits, what it entails and fosters – for instance, an exceptional flexibility, an inductive approach (Strauss and Corbin 1998 :31–33; 1990; Esterberg 2002 :7), an ability to step back and critically analyze situations, recognize tendencies towards bias, think abstractly and be open to criticism, enhance sensitivity towards the words and actions of respondents, and develop a sense of absorption and devotion to the research process (Strauss and Corbin 1998 :5–6). Accordingly, we identified discussions of the value of triangulating different methods (both using and not using grounded theory), including quantitative ones, and theories to achieve theoretical development (most comprehensively in Denzin 1970 ; Strauss and Corbin 1998 ; Timmermans and Tavory 2012 ). We have also located arguments about how its practice helps to systematize data collection, analysis and presentation of results (Glaser and Strauss [1967] 2010 :16).

Grounded theory offers a systematic approach which requires researchers to get close to the field; closeness is a requirement of identifying questions and developing new concepts or making further distinctions with regard to old concepts. In contrast to other qualitative approaches, grounded theory emphasizes the detailed coding process, and the numerous fine-tuned distinctions that the researcher makes during the process. Within this category, too, we could not find a satisfying discussion of the meaning of qualitative research.

Defining Qualitative Research

In sum, our analysis shows that some notions reappear in the discussion of qualitative research, such as understanding, interpretation, “getting close” and making distinctions. These notions capture aspects of what we think is “qualitative.” However, a comprehensive definition that is useful and that can further develop the field is lacking, and not even a clear picture of its essential elements appears. In other words no definition emerges from our data, and in our research process we have moved back and forth between our empirical data and the attempt to present a definition. Our concrete strategy, as stated above, is to relate qualitative and quantitative research, or more specifically, qualitative and quantitative work. We use an ideal-typical notion of quantitative research which relies on taken for granted and numbered variables. This means that the data consists of variables on different scales, such as ordinal, but frequently ratio and absolute scales, and the representation of the numbers to the variables, i.e. the justification of the assignment of numbers to object or phenomenon, are not questioned, though the validity may be questioned. In this section we return to the notion of quality and try to clarify it while presenting our contribution.

Broadly, research refers to the activity performed by people trained to obtain knowledge through systematic procedures. Notions such as “objectivity” and “reflexivity,” “systematic,” “theory,” “evidence” and “openness” are here taken for granted in any type of research. Next, building on our empirical analysis we explain the four notions that we have identified as central to qualitative work: distinctions, process, closeness, and improved understanding. In discussing them, ultimately in relation to one another, we make their meaning even more precise. Our idea, in short, is that only when these ideas that we present separately for analytic purposes are brought together can we speak of qualitative research.

Distinctions

We believe that the possibility of making new distinctions is one the defining characteristics of qualitative research. It clearly sets it apart from quantitative analysis which works with taken-for-granted variables, albeit as mentioned, meta-analyses, for example, factor analysis may result in new variables. “Quality” refers essentially to distinctions, as already pointed out by Aristotle. He discusses the term “qualitative” commenting: “By a quality I mean that in virtue of which things are said to be qualified somehow” (Aristotle 1984:14). Quality is about what something is or has, which means that the distinction from its environment is crucial. We see qualitative research as a process in which significant new distinctions are made to the scholarly community; to make distinctions is a key aspect of obtaining new knowledge; a point, as we will see, that also has implications for “quantitative research.” The notion of being “significant” is paramount. New distinctions by themselves are not enough; just adding concepts only increases complexity without furthering our knowledge. The significance of new distinctions is judged against the communal knowledge of the research community. To enable this discussion and judgements central elements of rational discussion are required (cf. Habermas [1981] 1987 ; Davidsson [ 1988 ] 2001) to identify what is new and relevant scientific knowledge. Relatedly, Ragin alludes to the idea of new and useful knowledge at a more concrete level: “Qualitative methods are appropriate for in-depth examination of cases because they aid the identification of key features of cases. Most qualitative methods enhance data” (1994:79). When Becker ( 1963 ) studied deviant behavior and investigated how people became marihuana smokers, he made distinctions between the ways in which people learned how to smoke. This is a classic example of how the strategy of “getting close” to the material, for example the text, people or pictures that are subject to analysis, may enable researchers to obtain deeper insight and new knowledge by making distinctions – in this instance on the initial notion of learning how to smoke. Others have stressed the making of distinctions in relation to coding or theorizing. Emerson et al. ( 1995 ), for example, hold that “qualitative coding is a way of opening up avenues of inquiry,” meaning that the researcher identifies and develops concepts and analytic insights through close examination of and reflection on data (Emerson et al. 1995 :151). Goodwin and Horowitz highlight making distinctions in relation to theory-building writing: “Close engagement with their cases typically requires qualitative researchers to adapt existing theories or to make new conceptual distinctions or theoretical arguments to accommodate new data” ( 2002 : 37). In the ideal-typical quantitative research only existing and so to speak, given, variables would be used. If this is the case no new distinction are made. But, would not also many “quantitative” researchers make new distinctions?

Process does not merely suggest that research takes time. It mainly implies that qualitative new knowledge results from a process that involves several phases, and above all iteration. Qualitative research is about oscillation between theory and evidence, analysis and generating material, between first- and second -order constructs (Schütz 1962 :59), between getting in contact with something, finding sources, becoming deeply familiar with a topic, and then distilling and communicating some of its essential features. The main point is that the categories that the researcher uses, and perhaps takes for granted at the beginning of the research process, usually undergo qualitative changes resulting from what is found. Becker describes how he tested hypotheses and let the jargon of the users develop into theoretical concepts. This happens over time while the study is being conducted, exemplifying what we mean by process.

In the research process, a pilot-study may be used to get a first glance of, for example, the field, how to approach it, and what methods can be used, after which the method and theory are chosen or refined before the main study begins. Thus, the empirical material is often central from the start of the project and frequently leads to adjustments by the researcher. Likewise, during the main study categories are not fixed; the empirical material is seen in light of the theory used, but it is also given the opportunity to kick back, thereby resisting attempts to apply theoretical straightjackets (Becker 1970 :43). In this process, coding and analysis are interwoven, and thus are often important steps for getting closer to the phenomenon and deciding what to focus on next. Becker began his research by interviewing musicians close to him, then asking them to refer him to other musicians, and later on doubling his original sample of about 25 to include individuals in other professions (Becker 1973:46). Additionally, he made use of some participant observation, documents, and interviews with opiate users made available to him by colleagues. As his inductive theory of deviance evolved, Becker expanded his sample in order to fine tune it, and test the accuracy and generality of his hypotheses. In addition, he introduced a negative case and discussed the null hypothesis ( 1963 :44). His phasic career model is thus based on a research design that embraces processual work. Typically, process means to move between “theory” and “material” but also to deal with negative cases, and Becker ( 1998 ) describes how discovering these negative cases impacted his research design and ultimately its findings.

Obviously, all research is process-oriented to some degree. The point is that the ideal-typical quantitative process does not imply change of the data, and iteration between data, evidence, hypotheses, empirical work, and theory. The data, quantified variables, are, in most cases fixed. Merging of data, which of course can be done in a quantitative research process, does not mean new data. New hypotheses are frequently tested, but the “raw data is often the “the same.” Obviously, over time new datasets are made available and put into use.

Another characteristic that is emphasized in our sample is that qualitative researchers – and in particular ethnographers – can, or as Goffman put it, ought to ( 1989 ), get closer to the phenomenon being studied and their data than quantitative researchers (for example, Silverman 2009 :85). Put differently, essentially because of their methods qualitative researchers get into direct close contact with those being investigated and/or the material, such as texts, being analyzed. Becker started out his interview study, as we noted, by talking to those he knew in the field of music to get closer to the phenomenon he was studying. By conducting interviews he got even closer. Had he done more observations, he would undoubtedly have got even closer to the field.

Additionally, ethnographers’ design enables researchers to follow the field over time, and the research they do is almost by definition longitudinal, though the time in the field is studied obviously differs between studies. The general characteristic of closeness over time maximizes the chances of unexpected events, new data (related, for example, to archival research as additional sources, and for ethnography for situations not necessarily previously thought of as instrumental – what Mannay and Morgan ( 2015 ) term the “waiting field”), serendipity (Merton and Barber 2004 ; Åkerström 2013 ), and possibly reactivity, as well as the opportunity to observe disrupted patterns that translate into exemplars of negative cases. Two classic examples of this are Becker’s finding of what medical students call “crocks” (Becker et al. 1961 :317), and Geertz’s ( 1973 ) study of “deep play” in Balinese society.

By getting and staying so close to their data – be it pictures, text or humans interacting (Becker was himself a musician) – for a long time, as the research progressively focuses, qualitative researchers are prompted to continually test their hunches, presuppositions and hypotheses. They test them against a reality that often (but certainly not always), and practically, as well as metaphorically, talks back, whether by validating them, or disqualifying their premises – correctly, as well as incorrectly (Fine 2003 ; Becker 1970 ). This testing nonetheless often leads to new directions for the research. Becker, for example, says that he was initially reading psychological theories, but when facing the data he develops a theory that looks at, you may say, everything but psychological dispositions to explain the use of marihuana. Especially researchers involved with ethnographic methods have a fairly unique opportunity to dig up and then test (in a circular, continuous and temporal way) new research questions and findings as the research progresses, and thereby to derive previously unimagined and uncharted distinctions by getting closer to the phenomenon under study.

Let us stress that getting close is by no means restricted to ethnography. The notion of hermeneutic circle and hermeneutics as a general way of understanding implies that we must get close to the details in order to get the big picture. This also means that qualitative researchers can literally also make use of details of pictures as evidence (cf. Harper 2002). Thus, researchers may get closer both when generating the material or when analyzing it.

Quantitative research, we maintain, in the ideal-typical representation cannot get closer to the data. The data is essentially numbers in tables making up the variables (Franzosi 2016 :138). The data may originally have been “qualitative,” but once reduced to numbers there can only be a type of “hermeneutics” about what the number may stand for. The numbers themselves, however, are non-ambiguous. Thus, in quantitative research, interpretation, if done, is not about the data itself—the numbers—but what the numbers stand for. It follows that the interpretation is essentially done in a more “speculative” mode without direct empirical evidence (cf. Becker 2017 ).

Improved Understanding

While distinction, process and getting closer refer to the qualitative work of the researcher, improved understanding refers to its conditions and outcome of this work. Understanding cuts deeper than explanation, which to some may mean a causally verified correlation between variables. The notion of explanation presupposes the notion of understanding since explanation does not include an idea of how knowledge is gained (Manicas 2006 : 15). Understanding, we argue, is the core concept of what we call the outcome of the process when research has made use of all the other elements that were integrated in the research. Understanding, then, has a special status in qualitative research since it refers both to the conditions of knowledge and the outcome of the process. Understanding can to some extent be seen as the condition of explanation and occurs in a process of interpretation, which naturally refers to meaning (Gadamer 1990 ). It is fundamentally connected to knowing, and to the knowing of how to do things (Heidegger [1927] 2001 ). Conceptually the term hermeneutics is used to account for this process. Heidegger ties hermeneutics to human being and not possible to separate from the understanding of being ( 1988 ). Here we use it in a broader sense, and more connected to method in general (cf. Seiffert 1992 ). The abovementioned aspects – for example, “objectivity” and “reflexivity” – of the approach are conditions of scientific understanding. Understanding is the result of a circular process and means that the parts are understood in light of the whole, and vice versa. Understanding presupposes pre-understanding, or in other words, some knowledge of the phenomenon studied. The pre-understanding, even in the form of prejudices, are in qualitative research process, which we see as iterative, questioned, which gradually or suddenly change due to the iteration of data, evidence and concepts. However, qualitative research generates understanding in the iterative process when the researcher gets closer to the data, e.g., by going back and forth between field and analysis in a process that generates new data that changes the evidence, and, ultimately, the findings. Questioning, to ask questions, and put what one assumes—prejudices and presumption—in question, is central to understand something (Heidegger [1927] 2001 ; Gadamer 1990 :368–384). We propose that this iterative process in which the process of understanding occurs is characteristic of qualitative research.

Improved understanding means that we obtain scientific knowledge of something that we as a scholarly community did not know before, or that we get to know something better. It means that we understand more about how parts are related to one another, and to other things we already understand (see also Fine and Hallett 2014 ). Understanding is an important condition for qualitative research. It is not enough to identify correlations, make distinctions, and work in a process in which one gets close to the field or phenomena. Understanding is accomplished when the elements are integrated in an iterative process.

It is, moreover, possible to understand many things, and researchers, just like children, may come to understand new things every day as they engage with the world. This subjective condition of understanding – namely, that a person gains a better understanding of something –is easily met. To be qualified as “scientific,” the understanding must be general and useful to many; it must be public. But even this generally accessible understanding is not enough in order to speak of “scientific understanding.” Though we as a collective can increase understanding of everything in virtually all potential directions as a result also of qualitative work, we refrain from this “objective” way of understanding, which has no means of discriminating between what we gain in understanding. Scientific understanding means that it is deemed relevant from the scientific horizon (compare Schütz 1962 : 35–38, 46, 63), and that it rests on the pre-understanding that the scientists have and must have in order to understand. In other words, the understanding gained must be deemed useful by other researchers, so that they can build on it. We thus see understanding from a pragmatic, rather than a subjective or objective perspective. Improved understanding is related to the question(s) at hand. Understanding, in order to represent an improvement, must be an improvement in relation to the existing body of knowledge of the scientific community (James [ 1907 ] 1955). Scientific understanding is, by definition, collective, as expressed in Weber’s famous note on objectivity, namely that scientific work aims at truths “which … can claim, even for a Chinese, the validity appropriate to an empirical analysis” ([1904] 1949 :59). By qualifying “improved understanding” we argue that it is a general defining characteristic of qualitative research. Becker‘s ( 1966 ) study and other research of deviant behavior increased our understanding of the social learning processes of how individuals start a behavior. And it also added new knowledge about the labeling of deviant behavior as a social process. Few studies, of course, make the same large contribution as Becker’s, but are nonetheless qualitative research.

Understanding in the phenomenological sense, which is a hallmark of qualitative research, we argue, requires meaning and this meaning is derived from the context, and above all the data being analyzed. The ideal-typical quantitative research operates with given variables with different numbers. This type of material is not enough to establish meaning at the level that truly justifies understanding. In other words, many social science explanations offer ideas about correlations or even causal relations, but this does not mean that the meaning at the level of the data analyzed, is understood. This leads us to say that there are indeed many explanations that meet the criteria of understanding, for example the explanation of how one becomes a marihuana smoker presented by Becker. However, we may also understand a phenomenon without explaining it, and we may have potential explanations, or better correlations, that are not really understood.

We may speak more generally of quantitative research and its data to clarify what we see as an important distinction. The “raw data” that quantitative research—as an idealtypical activity, refers to is not available for further analysis; the numbers, once created, are not to be questioned (Franzosi 2016 : 138). If the researcher is to do “more” or “change” something, this will be done by conjectures based on theoretical knowledge or based on the researcher’s lifeworld. Both qualitative and quantitative research is based on the lifeworld, and all researchers use prejudices and pre-understanding in the research process. This idea is present in the works of Heidegger ( 2001 ) and Heisenberg (cited in Franzosi 2010 :619). Qualitative research, as we argued, involves the interaction and questioning of concepts (theory), data, and evidence.

Ragin ( 2004 :22) points out that “a good definition of qualitative research should be inclusive and should emphasize its key strengths and features, not what it lacks (for example, the use of sophisticated quantitative techniques).” We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. Qualitative research, as defined here, is consequently a combination of two criteria: (i) how to do things –namely, generating and analyzing empirical material, in an iterative process in which one gets closer by making distinctions, and (ii) the outcome –improved understanding novel to the scholarly community. Is our definition applicable to our own study? In this study we have closely read the empirical material that we generated, and the novel distinction of the notion “qualitative research” is the outcome of an iterative process in which both deduction and induction were involved, in which we identified the categories that we analyzed. We thus claim to meet the first criteria, “how to do things.” The second criteria cannot be judged but in a partial way by us, namely that the “outcome” —in concrete form the definition-improves our understanding to others in the scientific community.

We have defined qualitative research, or qualitative scientific work, in relation to quantitative scientific work. Given this definition, qualitative research is about questioning the pre-given (taken for granted) variables, but it is thus also about making new distinctions of any type of phenomenon, for example, by coining new concepts, including the identification of new variables. This process, as we have discussed, is carried out in relation to empirical material, previous research, and thus in relation to theory. Theory and previous research cannot be escaped or bracketed. According to hermeneutic principles all scientific work is grounded in the lifeworld, and as social scientists we can thus never fully bracket our pre-understanding.

We have proposed that quantitative research, as an idealtype, is concerned with pre-determined variables (Small 2008 ). Variables are epistemically fixed, but can vary in terms of dimensions, such as frequency or number. Age is an example; as a variable it can take on different numbers. In relation to quantitative research, qualitative research does not reduce its material to number and variables. If this is done the process of comes to a halt, the researcher gets more distanced from her data, and it makes it no longer possible to make new distinctions that increase our understanding. We have above discussed the components of our definition in relation to quantitative research. Our conclusion is that in the research that is called quantitative there are frequent and necessary qualitative elements.

Further, comparative empirical research on researchers primarily working with ”quantitative” approaches and those working with ”qualitative” approaches, we propose, would perhaps show that there are many similarities in practices of these two approaches. This is not to deny dissimilarities, or the different epistemic and ontic presuppositions that may be more or less strongly associated with the two different strands (see Goertz and Mahoney 2012 ). Our point is nonetheless that prejudices and preconceptions about researchers are unproductive, and that as other researchers have argued, differences may be exaggerated (e.g., Becker 1996 : 53, 2017 ; Marchel and Owens 2007 :303; Ragin 1994 ), and that a qualitative dimension is present in both kinds of work.

Several things follow from our findings. The most important result is the relation to quantitative research. In our analysis we have separated qualitative research from quantitative research. The point is not to label individual researchers, methods, projects, or works as either “quantitative” or “qualitative.” By analyzing, i.e., taking apart, the notions of quantitative and qualitative, we hope to have shown the elements of qualitative research. Our definition captures the elements, and how they, when combined in practice, generate understanding. As many of the quotations we have used suggest, one conclusion of our study holds that qualitative approaches are not inherently connected with a specific method. Put differently, none of the methods that are frequently labelled “qualitative,” such as interviews or participant observation, are inherently “qualitative.” What matters, given our definition, is whether one works qualitatively or quantitatively in the research process, until the results are produced. Consequently, our analysis also suggests that those researchers working with what in the literature and in jargon is often called “quantitative research” are almost bound to make use of what we have identified as qualitative elements in any research project. Our findings also suggest that many” quantitative” researchers, at least to some extent, are engaged with qualitative work, such as when research questions are developed, variables are constructed and combined, and hypotheses are formulated. Furthermore, a research project may hover between “qualitative” and “quantitative” or start out as “qualitative” and later move into a “quantitative” (a distinct strategy that is not similar to “mixed methods” or just simply combining induction and deduction). More generally speaking, the categories of “qualitative” and “quantitative,” unfortunately, often cover up practices, and it may lead to “camps” of researchers opposing one another. For example, regardless of the researcher is primarily oriented to “quantitative” or “qualitative” research, the role of theory is neglected (cf. Swedberg 2017 ). Our results open up for an interaction not characterized by differences, but by different emphasis, and similarities.

Let us take two examples to briefly indicate how qualitative elements can fruitfully be combined with quantitative. Franzosi ( 2010 ) has discussed the relations between quantitative and qualitative approaches, and more specifically the relation between words and numbers. He analyzes texts and argues that scientific meaning cannot be reduced to numbers. Put differently, the meaning of the numbers is to be understood by what is taken for granted, and what is part of the lifeworld (Schütz 1962 ). Franzosi shows how one can go about using qualitative and quantitative methods and data to address scientific questions analyzing violence in Italy at the time when fascism was rising (1919–1922). Aspers ( 2006 ) studied the meaning of fashion photographers. He uses an empirical phenomenological approach, and establishes meaning at the level of actors. In a second step this meaning, and the different ideal-typical photographers constructed as a result of participant observation and interviews, are tested using quantitative data from a database; in the first phase to verify the different ideal-types, in the second phase to use these types to establish new knowledge about the types. In both of these cases—and more examples can be found—authors move from qualitative data and try to keep the meaning established when using the quantitative data.

A second main result of our study is that a definition, and we provided one, offers a way for research to clarify, and even evaluate, what is done. Hence, our definition can guide researchers and students, informing them on how to think about concrete research problems they face, and to show what it means to get closer in a process in which new distinctions are made. The definition can also be used to evaluate the results, given that it is a standard of evaluation (cf. Hammersley 2007 ), to see whether new distinctions are made and whether this improves our understanding of what is researched, in addition to the evaluation of how the research was conducted. By making what is qualitative research explicit it becomes easier to communicate findings, and it is thereby much harder to fly under the radar with substandard research since there are standards of evaluation which make it easier to separate “good” from “not so good” qualitative research.

To conclude, our analysis, which ends with a definition of qualitative research can thus both address the “internal” issues of what is qualitative research, and the “external” critiques that make it harder to do qualitative research, to which both pressure from quantitative methods and general changes in society contribute.

Acknowledgements

Financial Support for this research is given by the European Research Council, CEV (263699). The authors are grateful to Susann Krieglsteiner for assistance in collecting the data. The paper has benefitted from the many useful comments by the three reviewers and the editor, comments by members of the Uppsala Laboratory of Economic Sociology, as well as Jukka Gronow, Sebastian Kohl, Marcin Serafin, Richard Swedberg, Anders Vassenden and Turid Rødne.

Biographies

is professor of sociology at the Department of Sociology, Uppsala University and Universität St. Gallen. His main focus is economic sociology, and in particular, markets. He has published numerous articles and books, including Orderly Fashion (Princeton University Press 2010), Markets (Polity Press 2011) and Re-Imagining Economic Sociology (edited with N. Dodd, Oxford University Press 2015). His book Ethnographic Methods (in Swedish) has already gone through several editions.

is associate professor of sociology at the Department of Media and Social Sciences, University of Stavanger. His research has been published in journals such as Social Psychology Quarterly, Sociological Theory, Teaching Sociology, and Music and Arts in Action. As an ethnographer he is working on a book on he social world of big-wave surfing.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Patrik Aspers, Email: [email protected] .

Ugo Corte, Email: [email protected] .

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Qualitative Study

Affiliations.

  • 1 University of Nebraska Medical Center
  • 2 GDB Research and Statistical Consulting
  • 3 GDB Research and Statistical Consulting/McLaren Macomb Hospital
  • PMID: 29262162
  • Bookshelf ID: NBK470395

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. Instead of collecting numerical data points or intervene or introduce treatments just like in quantitative research, qualitative research helps generate hypotheses as well as further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much. It could be structured as a stand-alone study, purely relying on qualitative data or it could be part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and application of qualitative research.

Qualitative research at its core, ask open-ended questions whose answers are not easily put into numbers such as ‘how’ and ‘why’. Due to the open-ended nature of the research questions at hand, qualitative research design is often not linear in the same way quantitative design is. One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. Phenomena such as experiences, attitudes, and behaviors can be difficult to accurately capture quantitatively, whereas a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a certain time or during an event of interest. Quantifying qualitative data certainly is possible, but at its core, qualitative data is looking for themes and patterns that can be difficult to quantify and it is important to ensure that the context and narrative of qualitative work are not lost by trying to quantify something that is not meant to be quantified.

However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore ‘compete’ against each other and the philosophical paradigms associated with each, qualitative and quantitative work are not necessarily opposites nor are they incompatible. While qualitative and quantitative approaches are different, they are not necessarily opposites, and they are certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined that there is a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated together.

Examples of Qualitative Research Approaches

Ethnography

Ethnography as a research design has its origins in social and cultural anthropology, and involves the researcher being directly immersed in the participant’s environment. Through this immersion, the ethnographer can use a variety of data collection techniques with the aim of being able to produce a comprehensive account of the social phenomena that occurred during the research period. That is to say, the researcher’s aim with ethnography is to immerse themselves into the research population and come out of it with accounts of actions, behaviors, events, etc. through the eyes of someone involved in the population. Direct involvement of the researcher with the target population is one benefit of ethnographic research because it can then be possible to find data that is otherwise very difficult to extract and record.

Grounded Theory

Grounded Theory is the “generation of a theoretical model through the experience of observing a study population and developing a comparative analysis of their speech and behavior.” As opposed to quantitative research which is deductive and tests or verifies an existing theory, grounded theory research is inductive and therefore lends itself to research that is aiming to study social interactions or experiences. In essence, Grounded Theory’s goal is to explain for example how and why an event occurs or how and why people might behave a certain way. Through observing the population, a researcher using the Grounded Theory approach can then develop a theory to explain the phenomena of interest.

Phenomenology

Phenomenology is defined as the “study of the meaning of phenomena or the study of the particular”. At first glance, it might seem that Grounded Theory and Phenomenology are quite similar, but upon careful examination, the differences can be seen. At its core, phenomenology looks to investigate experiences from the perspective of the individual. Phenomenology is essentially looking into the ‘lived experiences’ of the participants and aims to examine how and why participants behaved a certain way, from their perspective . Herein lies one of the main differences between Grounded Theory and Phenomenology. Grounded Theory aims to develop a theory for social phenomena through an examination of various data sources whereas Phenomenology focuses on describing and explaining an event or phenomena from the perspective of those who have experienced it.

Narrative Research

One of qualitative research’s strengths lies in its ability to tell a story, often from the perspective of those directly involved in it. Reporting on qualitative research involves including details and descriptions of the setting involved and quotes from participants. This detail is called ‘thick’ or ‘rich’ description and is a strength of qualitative research. Narrative research is rife with the possibilities of ‘thick’ description as this approach weaves together a sequence of events, usually from just one or two individuals, in the hopes of creating a cohesive story, or narrative. While it might seem like a waste of time to focus on such a specific, individual level, understanding one or two people’s narratives for an event or phenomenon can help to inform researchers about the influences that helped shape that narrative. The tension or conflict of differing narratives can be “opportunities for innovation”.

Research Paradigm

Research paradigms are the assumptions, norms, and standards that underpin different approaches to research. Essentially, research paradigms are the ‘worldview’ that inform research. It is valuable for researchers, both qualitative and quantitative, to understand what paradigm they are working within because understanding the theoretical basis of research paradigms allows researchers to understand the strengths and weaknesses of the approach being used and adjust accordingly. Different paradigms have different ontology and epistemologies . Ontology is defined as the "assumptions about the nature of reality” whereas epistemology is defined as the “assumptions about the nature of knowledge” that inform the work researchers do. It is important to understand the ontological and epistemological foundations of the research paradigm researchers are working within to allow for a full understanding of the approach being used and the assumptions that underpin the approach as a whole. Further, it is crucial that researchers understand their own ontological and epistemological assumptions about the world in general because their assumptions about the world will necessarily impact how they interact with research. A discussion of the research paradigm is not complete without describing positivist, postpositivist, and constructivist philosophies.

Positivist vs Postpositivist

To further understand qualitative research, we need to discuss positivist and postpositivist frameworks. Positivism is a philosophy that the scientific method can and should be applied to social as well as natural sciences. Essentially, positivist thinking insists that the social sciences should use natural science methods in its research which stems from positivist ontology that there is an objective reality that exists that is fully independent of our perception of the world as individuals. Quantitative research is rooted in positivist philosophy, which can be seen in the value it places on concepts such as causality, generalizability, and replicability.

Conversely, postpositivists argue that social reality can never be one hundred percent explained but it could be approximated. Indeed, qualitative researchers have been insisting that there are “fundamental limits to the extent to which the methods and procedures of the natural sciences could be applied to the social world” and therefore postpositivist philosophy is often associated with qualitative research. An example of positivist versus postpositivist values in research might be that positivist philosophies value hypothesis-testing, whereas postpositivist philosophies value the ability to formulate a substantive theory.

Constructivist

Constructivism is a subcategory of postpositivism. Most researchers invested in postpositivist research are constructivist as well, meaning they think there is no objective external reality that exists but rather that reality is constructed. Constructivism is a theoretical lens that emphasizes the dynamic nature of our world. “Constructivism contends that individuals’ views are directly influenced by their experiences, and it is these individual experiences and views that shape their perspective of reality”. Essentially, Constructivist thought focuses on how ‘reality’ is not a fixed certainty and experiences, interactions, and backgrounds give people a unique view of the world. Constructivism contends, unlike in positivist views, that there is not necessarily an ‘objective’ reality we all experience. This is the ‘relativist’ ontological view that reality and the world we live in are dynamic and socially constructed. Therefore, qualitative scientific knowledge can be inductive as well as deductive.”

So why is it important to understand the differences in assumptions that different philosophies and approaches to research have? Fundamentally, the assumptions underpinning the research tools a researcher selects provide an overall base for the assumptions the rest of the research will have and can even change the role of the researcher themselves. For example, is the researcher an ‘objective’ observer such as in positivist quantitative work? Or is the researcher an active participant in the research itself, as in postpositivist qualitative work? Understanding the philosophical base of the research undertaken allows researchers to fully understand the implications of their work and their role within the research, as well as reflect on their own positionality and bias as it pertains to the research they are conducting.

Data Sampling

The better the sample represents the intended study population, the more likely the researcher is to encompass the varying factors at play. The following are examples of participant sampling and selection:

Purposive sampling- selection based on the researcher’s rationale in terms of being the most informative.

Criterion sampling-selection based on pre-identified factors.

Convenience sampling- selection based on availability.

Snowball sampling- the selection is by referral from other participants or people who know potential participants.

Extreme case sampling- targeted selection of rare cases.

Typical case sampling-selection based on regular or average participants.

Data Collection and Analysis

Qualitative research uses several techniques including interviews, focus groups, and observation. [1] [2] [3] Interviews may be unstructured, with open-ended questions on a topic and the interviewer adapts to the responses. Structured interviews have a predetermined number of questions that every participant is asked. It is usually one on one and is appropriate for sensitive topics or topics needing an in-depth exploration. Focus groups are often held with 8-12 target participants and are used when group dynamics and collective views on a topic are desired. Researchers can be a participant-observer to share the experiences of the subject or a non-participant or detached observer.

While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or in the environment of the participants, depending on the study goals and design. Qualitative research could amount to a large amount of data. Data is transcribed which may then be coded manually or with the use of Computer Assisted Qualitative Data Analysis Software or CAQDAS such as ATLAS.ti or NVivo.

After the coding process, qualitative research results could be in various formats. It could be a synthesis and interpretation presented with excerpts from the data. Results also could be in the form of themes and theory or model development.

Dissemination

To standardize and facilitate the dissemination of qualitative research outcomes, the healthcare team can use two reporting standards. The Consolidated Criteria for Reporting Qualitative Research or COREQ is a 32-item checklist for interviews and focus groups. The Standards for Reporting Qualitative Research (SRQR) is a checklist covering a wider range of qualitative research.

Examples of Application

Many times a research question will start with qualitative research. The qualitative research will help generate the research hypothesis which can be tested with quantitative methods. After the data is collected and analyzed with quantitative methods, a set of qualitative methods can be used to dive deeper into the data for a better understanding of what the numbers truly mean and their implications. The qualitative methods can then help clarify the quantitative data and also help refine the hypothesis for future research. Furthermore, with qualitative research researchers can explore subjects that are poorly studied with quantitative methods. These include opinions, individual's actions, and social science research.

A good qualitative study design starts with a goal or objective. This should be clearly defined or stated. The target population needs to be specified. A method for obtaining information from the study population must be carefully detailed to ensure there are no omissions of part of the target population. A proper collection method should be selected which will help obtain the desired information without overly limiting the collected data because many times, the information sought is not well compartmentalized or obtained. Finally, the design should ensure adequate methods for analyzing the data. An example may help better clarify some of the various aspects of qualitative research.

A researcher wants to decrease the number of teenagers who smoke in their community. The researcher could begin by asking current teen smokers why they started smoking through structured or unstructured interviews (qualitative research). The researcher can also get together a group of current teenage smokers and conduct a focus group to help brainstorm factors that may have prevented them from starting to smoke (qualitative research).

In this example, the researcher has used qualitative research methods (interviews and focus groups) to generate a list of ideas of both why teens start to smoke as well as factors that may have prevented them from starting to smoke. Next, the researcher compiles this data. The research found that, hypothetically, peer pressure, health issues, cost, being considered “cool,” and rebellious behavior all might increase or decrease the likelihood of teens starting to smoke.

The researcher creates a survey asking teen participants to rank how important each of the above factors is in either starting smoking (for current smokers) or not smoking (for current non-smokers). This survey provides specific numbers (ranked importance of each factor) and is thus a quantitative research tool.

The researcher can use the results of the survey to focus efforts on the one or two highest-ranked factors. Let us say the researcher found that health was the major factor that keeps teens from starting to smoke, and peer pressure was the major factor that contributed to teens to start smoking. The researcher can go back to qualitative research methods to dive deeper into each of these for more information. The researcher wants to focus on how to keep teens from starting to smoke, so they focus on the peer pressure aspect.

The researcher can conduct interviews and/or focus groups (qualitative research) about what types and forms of peer pressure are commonly encountered, where the peer pressure comes from, and where smoking first starts. The researcher hypothetically finds that peer pressure often occurs after school at the local teen hangouts, mostly the local park. The researcher also hypothetically finds that peer pressure comes from older, current smokers who provide the cigarettes.

The researcher could further explore this observation made at the local teen hangouts (qualitative research) and take notes regarding who is smoking, who is not, and what observable factors are at play for peer pressure of smoking. The researcher finds a local park where many local teenagers hang out and see that a shady, overgrown area of the park is where the smokers tend to hang out. The researcher notes the smoking teenagers buy their cigarettes from a local convenience store adjacent to the park where the clerk does not check identification before selling cigarettes. These observations fall under qualitative research.

If the researcher returns to the park and counts how many individuals smoke in each region of the park, this numerical data would be quantitative research. Based on the researcher's efforts thus far, they conclude that local teen smoking and teenagers who start to smoke may decrease if there are fewer overgrown areas of the park and the local convenience store does not sell cigarettes to underage individuals.

The researcher could try to have the parks department reassess the shady areas to make them less conducive to the smokers or identify how to limit the sales of cigarettes to underage individuals by the convenience store. The researcher would then cycle back to qualitative methods of asking at-risk population their perceptions of the changes, what factors are still at play, as well as quantitative research that includes teen smoking rates in the community, the incidence of new teen smokers, among others.

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What Is Qualitative Research? | Methods & Examples

Published on 4 April 2022 by Pritha Bhandari . Revised on 30 January 2023.

Qualitative research involves collecting and analysing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analysing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, and history.

  • How does social media shape body image in teenagers?
  • How do children and adults interpret healthy eating in the UK?
  • What factors influence employee retention in a large organisation?
  • How is anxiety experienced around the world?
  • How can teachers integrate social issues into science curriculums?

Table of contents

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography, action research, phenomenological research, and narrative research. They share some similarities, but emphasise different aims and perspectives.

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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

  • Observations: recording what you have seen, heard, or encountered in detailed field notes.
  • Interviews:  personally asking people questions in one-on-one conversations.
  • Focus groups: asking questions and generating discussion among a group of people.
  • Surveys : distributing questionnaires with open-ended questions.
  • Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
  • You take field notes with observations and reflect on your own experiences of the company culture.
  • You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
  • You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves ‘instruments’ in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analysing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

  • Prepare and organise your data. This may mean transcribing interviews or typing up fieldnotes.
  • Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
  • Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorise your data.
  • Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
  • Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analysing qualitative data. Although these methods share similar processes, they emphasise different concepts.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

  • Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

  • Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

  • Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

  • Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

Researchers must consider practical and theoretical limitations in analysing and interpreting their data. Qualitative research suffers from:

  • Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

  • Subjectivity

Due to the researcher’s primary role in analysing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

  • Limited generalisability

Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalisable conclusions because the data may be biased and unrepresentative of the wider population .

  • Labour-intensive

Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

There are five common approaches to qualitative research :

  • Grounded theory involves collecting data in order to develop new theories.
  • Ethnography involves immersing yourself in a group or organisation to understand its culture.
  • Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
  • Phenomenological research involves investigating phenomena through people’s lived experiences.
  • Action research links theory and practice in several cycles to drive innovative changes.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

  • Prepare and organise your data.
  • Review and explore your data.
  • Develop a data coding system.
  • Assign codes to the data.
  • Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

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Qualitative Research: Characteristics, Design, Methods & Examples

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“Not everything that can be counted counts, and not everything that counts can be counted“ (Albert Einstein)

Qualitative research is a process used for the systematic collection, analysis, and interpretation of non-numerical data (Punch, 2013). 

Qualitative research can be used to: (i) gain deep contextual understandings of the subjective social reality of individuals and (ii) to answer questions about experience and meaning from the participant’s perspective (Hammarberg et al., 2016).

Unlike quantitative research, which focuses on gathering and analyzing numerical data for statistical analysis, qualitative research focuses on thematic and contextual information.

Characteristics of Qualitative Research 

Reality is socially constructed.

Qualitative research aims to understand how participants make meaning of their experiences – individually or in social contexts. It assumes there is no objective reality and that the social world is interpreted (Yilmaz, 2013). 

The primacy of subject matter 

The primary aim of qualitative research is to understand the perspectives, experiences, and beliefs of individuals who have experienced the phenomenon selected for research rather than the average experiences of groups of people (Minichiello, 1990).

Variables are complex, interwoven, and difficult to measure

Factors such as experiences, behaviors, and attitudes are complex and interwoven, so they cannot be reduced to isolated variables , making them difficult to measure quantitatively.

However, a qualitative approach enables participants to describe what, why, or how they were thinking/ feeling during a phenomenon being studied (Yilmaz, 2013). 

Emic (insider’s point of view)

The phenomenon being studied is centered on the participants’ point of view (Minichiello, 1990).

Emic is used to describe how participants interact, communicate, and behave in the context of the research setting (Scarduzio, 2017).

Why Conduct Qualitative Research? 

In order to gain a deeper understanding of how people experience the world, individuals are studied in their natural setting. This enables the researcher to understand a phenomenon close to how participants experience it. 

Qualitative research allows researchers to gain an in-depth understanding, which is difficult to attain using quantitative methods. 

An in-depth understanding is attained since qualitative techniques allow participants to freely disclose their experiences, thoughts, and feelings without constraint (Tenny et al., 2022). 

This helps to further investigate and understand quantitative data by discovering reasons for the outcome of a study – answering the why question behind statistics. 

The exploratory nature of qualitative research helps to generate hypotheses that can then be tested quantitatively (Busetto et al., 2020).

To design hypotheses, theory must be researched using qualitative methods to find out what is important in order to begin research. 

For example, by conducting interviews or focus groups with key stakeholders to discover what is important to them. 

Examples of qualitative research questions include: 

  • How does stress influence young adults’ behavior?
  • What factors influence students’ school attendance rates in developed countries?
  • How do adults interpret binge drinking in the UK?
  • What are the psychological impacts of cervical cancer screening in women?
  • How can mental health lessons be integrated into the school curriculum? 

Collecting Qualitative Data

There are four main research design methods used to collect qualitative data: observations, interviews,  focus groups, and ethnography.

Observations

This method involves watching and recording phenomena as they occur in nature. Observation can be divided into two types: participant and non-participant observation.

In participant observation, the researcher actively participates in the situation/events being observed.

In non-participant observation, the researcher is not an active part of the observation and tries not to influence the behaviors they are observing (Busetto et al., 2020). 

Observations can be covert (participants are unaware that a researcher is observing them) or overt (participants are aware of the researcher’s presence and know they are being observed).

However, awareness of an observer’s presence may influence participants’ behavior. 

Interviews give researchers a window into the world of a participant by seeking their account of an event, situation, or phenomenon. They are usually conducted on a one-to-one basis and can be distinguished according to the level at which they are structured (Punch, 2013). 

Structured interviews involve predetermined questions and sequences to ensure replicability and comparability. However, they are unable to explore emerging issues.

Informal interviews consist of spontaneous, casual conversations which are closer to the truth of a phenomenon. However, information is gathered using quick notes made by the researcher and is therefore subject to recall bias. 

Semi-structured interviews have a flexible structure, phrasing, and placement so emerging issues can be explored (Denny & Weckesser, 2022).

The use of probing questions and clarification can lead to a detailed understanding, but semi-structured interviews can be time-consuming and subject to interviewer bias. 

Focus groups 

Similar to interviews, focus groups elicit a rich and detailed account of an experience. However, focus groups are more dynamic since participants with shared characteristics construct this account together (Denny & Weckesser, 2022).

A shared narrative is built between participants to capture a group experience shaped by a shared context. 

The researcher takes on the role of a moderator, who will establish ground rules and guide the discussion by following a topic guide to focus the group discussions.

Typically, focus groups have 4-10 participants as a discussion can be difficult to facilitate with more than this, and this number allows everyone the time to speak.

Ethnography

Ethnography is a methodology used to study a group of people’s behaviors and social interactions in their environment (Reeves et al., 2008).

Data are collected using methods such as observations, field notes, or structured/ unstructured interviews.

The aim of ethnography is to provide detailed, holistic insights into people’s behavior and perspectives within their natural setting. In order to achieve this, researchers immerse themselves in a community or organization. 

Due to the flexibility and real-world focus of ethnography, researchers are able to gather an in-depth, nuanced understanding of people’s experiences, knowledge and perspectives that are influenced by culture and society.

In order to develop a representative picture of a particular culture/ context, researchers must conduct extensive field work. 

This can be time-consuming as researchers may need to immerse themselves into a community/ culture for a few days, or possibly a few years.

Qualitative Data Analysis Methods

Different methods can be used for analyzing qualitative data. The researcher chooses based on the objectives of their study. 

The researcher plays a key role in the interpretation of data, making decisions about the coding, theming, decontextualizing, and recontextualizing of data (Starks & Trinidad, 2007). 

Grounded theory

Grounded theory is a qualitative method specifically designed to inductively generate theory from data. It was developed by Glaser and Strauss in 1967 (Glaser & Strauss, 2017).

 This methodology aims to develop theories (rather than test hypotheses) that explain a social process, action, or interaction (Petty et al., 2012). To inform the developing theory, data collection and analysis run simultaneously. 

There are three key types of coding used in grounded theory: initial (open), intermediate (axial), and advanced (selective) coding. 

Throughout the analysis, memos should be created to document methodological and theoretical ideas about the data. Data should be collected and analyzed until data saturation is reached and a theory is developed. 

Content analysis

Content analysis was first used in the early twentieth century to analyze textual materials such as newspapers and political speeches.

Content analysis is a research method used to identify and analyze the presence and patterns of themes, concepts, or words in data (Vaismoradi et al., 2013). 

This research method can be used to analyze data in different formats, which can be written, oral, or visual. 

The goal of content analysis is to develop themes that capture the underlying meanings of data (Schreier, 2012). 

Qualitative content analysis can be used to validate existing theories, support the development of new models and theories, and provide in-depth descriptions of particular settings or experiences.

The following six steps provide a guideline for how to conduct qualitative content analysis.
  • Define a Research Question : To start content analysis, a clear research question should be developed.
  • Identify and Collect Data : Establish the inclusion criteria for your data. Find the relevant sources to analyze.
  • Define the Unit or Theme of Analysis : Categorize the content into themes. Themes can be a word, phrase, or sentence.
  • Develop Rules for Coding your Data : Define a set of coding rules to ensure that all data are coded consistently.
  • Code the Data : Follow the coding rules to categorize data into themes.
  • Analyze the Results and Draw Conclusions : Examine the data to identify patterns and draw conclusions in relation to your research question.

Discourse analysis

Discourse analysis is a research method used to study written/ spoken language in relation to its social context (Wood & Kroger, 2000).

In discourse analysis, the researcher interprets details of language materials and the context in which it is situated.

Discourse analysis aims to understand the functions of language (how language is used in real life) and how meaning is conveyed by language in different contexts. Researchers use discourse analysis to investigate social groups and how language is used to achieve specific communication goals.

Different methods of discourse analysis can be used depending on the aims and objectives of a study. However, the following steps provide a guideline on how to conduct discourse analysis.
  • Define the Research Question : Develop a relevant research question to frame the analysis.
  • Gather Data and Establish the Context : Collect research materials (e.g., interview transcripts, documents). Gather factual details and review the literature to construct a theory about the social and historical context of your study.
  • Analyze the Content : Closely examine various components of the text, such as the vocabulary, sentences, paragraphs, and structure of the text. Identify patterns relevant to the research question to create codes, then group these into themes.
  • Review the Results : Reflect on the findings to examine the function of the language, and the meaning and context of the discourse. 

Thematic analysis

Thematic analysis is a method used to identify, interpret, and report patterns in data, such as commonalities or contrasts. 

Although the origin of thematic analysis can be traced back to the early twentieth century, understanding and clarity of thematic analysis is attributed to Braun and Clarke (2006).

Thematic analysis aims to develop themes (patterns of meaning) across a dataset to address a research question. 

In thematic analysis, qualitative data is gathered using techniques such as interviews, focus groups, and questionnaires. Audio recordings are transcribed. The dataset is then explored and interpreted by a researcher to identify patterns. 

This occurs through the rigorous process of data familiarisation, coding, theme development, and revision. These identified patterns provide a summary of the dataset and can be used to address a research question.

Themes are developed by exploring the implicit and explicit meanings within the data. Two different approaches are used to generate themes: inductive and deductive. 

An inductive approach allows themes to emerge from the data. In contrast, a deductive approach uses existing theories or knowledge to apply preconceived ideas to the data.

Phases of Thematic Analysis

Braun and Clarke (2006) provide a guide of the six phases of thematic analysis. These phases can be applied flexibly to fit research questions and data. 

Template analysis

Template analysis refers to a specific method of thematic analysis which uses hierarchical coding (Brooks et al., 2014).

Template analysis is used to analyze textual data, for example, interview transcripts or open-ended responses on a written questionnaire.

To conduct template analysis, a coding template must be developed (usually from a subset of the data) and subsequently revised and refined. This template represents the themes identified by researchers as important in the dataset. 

Codes are ordered hierarchically within the template, with the highest-level codes demonstrating overarching themes in the data and lower-level codes representing constituent themes with a narrower focus.

A guideline for the main procedural steps for conducting template analysis is outlined below.
  • Familiarization with the Data : Read (and reread) the dataset in full. Engage, reflect, and take notes on data that may be relevant to the research question.
  • Preliminary Coding : Identify initial codes using guidance from the a priori codes, identified before the analysis as likely to be beneficial and relevant to the analysis.
  • Organize Themes : Organize themes into meaningful clusters. Consider the relationships between the themes both within and between clusters.
  • Produce an Initial Template : Develop an initial template. This may be based on a subset of the data.
  • Apply and Develop the Template : Apply the initial template to further data and make any necessary modifications. Refinements of the template may include adding themes, removing themes, or changing the scope/title of themes. 
  • Finalize Template : Finalize the template, then apply it to the entire dataset. 

Frame analysis

Frame analysis is a comparative form of thematic analysis which systematically analyzes data using a matrix output.

Ritchie and Spencer (1994) developed this set of techniques to analyze qualitative data in applied policy research. Frame analysis aims to generate theory from data.

Frame analysis encourages researchers to organize and manage their data using summarization.

This results in a flexible and unique matrix output, in which individual participants (or cases) are represented by rows and themes are represented by columns. 

Each intersecting cell is used to summarize findings relating to the corresponding participant and theme.

Frame analysis has five distinct phases which are interrelated, forming a methodical and rigorous framework.
  • Familiarization with the Data : Familiarize yourself with all the transcripts. Immerse yourself in the details of each transcript and start to note recurring themes.
  • Develop a Theoretical Framework : Identify recurrent/ important themes and add them to a chart. Provide a framework/ structure for the analysis.
  • Indexing : Apply the framework systematically to the entire study data.
  • Summarize Data in Analytical Framework : Reduce the data into brief summaries of participants’ accounts.
  • Mapping and Interpretation : Compare themes and subthemes and check against the original transcripts. Group the data into categories and provide an explanation for them.

Preventing Bias in Qualitative Research

To evaluate qualitative studies, the CASP (Critical Appraisal Skills Programme) checklist for qualitative studies can be used to ensure all aspects of a study have been considered (CASP, 2018).

The quality of research can be enhanced and assessed using criteria such as checklists, reflexivity, co-coding, and member-checking. 

Co-coding 

Relying on only one researcher to interpret rich and complex data may risk key insights and alternative viewpoints being missed. Therefore, coding is often performed by multiple researchers.

A common strategy must be defined at the beginning of the coding process  (Busetto et al., 2020). This includes establishing a useful coding list and finding a common definition of individual codes.

Transcripts are initially coded independently by researchers and then compared and consolidated to minimize error or bias and to bring confirmation of findings. 

Member checking

Member checking (or respondent validation) involves checking back with participants to see if the research resonates with their experiences (Russell & Gregory, 2003).

Data can be returned to participants after data collection or when results are first available. For example, participants may be provided with their interview transcript and asked to verify whether this is a complete and accurate representation of their views.

Participants may then clarify or elaborate on their responses to ensure they align with their views (Shenton, 2004).

This feedback becomes part of data collection and ensures accurate descriptions/ interpretations of phenomena (Mays & Pope, 2000). 

Reflexivity in qualitative research

Reflexivity typically involves examining your own judgments, practices, and belief systems during data collection and analysis. It aims to identify any personal beliefs which may affect the research. 

Reflexivity is essential in qualitative research to ensure methodological transparency and complete reporting. This enables readers to understand how the interaction between the researcher and participant shapes the data.

Depending on the research question and population being researched, factors that need to be considered include the experience of the researcher, how the contact was established and maintained, age, gender, and ethnicity.

These details are important because, in qualitative research, the researcher is a dynamic part of the research process and actively influences the outcome of the research (Boeije, 2014). 

Reflexivity Example

Who you are and your characteristics influence how you collect and analyze data. Here is an example of a reflexivity statement for research on smoking. I am a 30-year-old white female from a middle-class background. I live in the southwest of England and have been educated to master’s level. I have been involved in two research projects on oral health. I have never smoked, but I have witnessed how smoking can cause ill health from my volunteering in a smoking cessation clinic. My research aspirations are to help to develop interventions to help smokers quit.

Establishing Trustworthiness in Qualitative Research

Trustworthiness is a concept used to assess the quality and rigor of qualitative research. Four criteria are used to assess a study’s trustworthiness: credibility, transferability, dependability, and confirmability.

Credibility in Qualitative Research

Credibility refers to how accurately the results represent the reality and viewpoints of the participants.

To establish credibility in research, participants’ views and the researcher’s representation of their views need to align (Tobin & Begley, 2004).

To increase the credibility of findings, researchers may use data source triangulation, investigator triangulation, peer debriefing, or member checking (Lincoln & Guba, 1985). 

Transferability in Qualitative Research

Transferability refers to how generalizable the findings are: whether the findings may be applied to another context, setting, or group (Tobin & Begley, 2004).

Transferability can be enhanced by giving thorough and in-depth descriptions of the research setting, sample, and methods (Nowell et al., 2017). 

Dependability in Qualitative Research

Dependability is the extent to which the study could be replicated under similar conditions and the findings would be consistent.

Researchers can establish dependability using methods such as audit trails so readers can see the research process is logical and traceable (Koch, 1994).

Confirmability in Qualitative Research

Confirmability is concerned with establishing that there is a clear link between the researcher’s interpretations/ findings and the data.

Researchers can achieve confirmability by demonstrating how conclusions and interpretations were arrived at (Nowell et al., 2017).

This enables readers to understand the reasoning behind the decisions made. 

Audit Trails in Qualitative Research

An audit trail provides evidence of the decisions made by the researcher regarding theory, research design, and data collection, as well as the steps they have chosen to manage, analyze, and report data. 

The researcher must provide a clear rationale to demonstrate how conclusions were reached in their study.

A clear description of the research path must be provided to enable readers to trace through the researcher’s logic (Halpren, 1983).

Researchers should maintain records of the raw data, field notes, transcripts, and a reflective journal in order to provide a clear audit trail. 

Discovery of unexpected data

Open-ended questions in qualitative research mean the researcher can probe an interview topic and enable the participant to elaborate on responses in an unrestricted manner.

This allows unexpected data to emerge, which can lead to further research into that topic. 

Flexibility

Data collection and analysis can be modified and adapted to take the research in a different direction if new ideas or patterns emerge in the data.

This enables researchers to investigate new opportunities while firmly maintaining their research goals. 

Naturalistic settings

The behaviors of participants are recorded in real-world settings. Studies that use real-world settings have high ecological validity since participants behave more authentically. 

Limitations

Time-consuming .

Qualitative research results in large amounts of data which often need to be transcribed and analyzed manually.

Even when software is used, transcription can be inaccurate, and using software for analysis can result in many codes which need to be condensed into themes. 

Subjectivity 

The researcher has an integral role in collecting and interpreting qualitative data. Therefore, the conclusions reached are from their perspective and experience.

Consequently, interpretations of data from another researcher may vary greatly. 

Limited generalizability

The aim of qualitative research is to provide a detailed, contextualized understanding of an aspect of the human experience from a relatively small sample size.

Despite rigorous analysis procedures, conclusions drawn cannot be generalized to the wider population since data may be biased or unrepresentative.

Therefore, results are only applicable to a small group of the population. 

Extraneous variables

Qualitative research is often conducted in real-world settings. This may cause results to be unreliable since extraneous variables may affect the data, for example:

  • Situational variables : different environmental conditions may influence participants’ behavior in a study. The random variation in factors (such as noise or lighting) may be difficult to control in real-world settings.
  • Participant characteristics : this includes any characteristics that may influence how a participant answers/ behaves in a study. This may include a participant’s mood, gender, age, ethnicity, sexual identity, IQ, etc.
  • Experimenter effect : experimenter effect refers to how a researcher’s unintentional influence can change the outcome of a study. This occurs when (i) their interactions with participants unintentionally change participants’ behaviors or (ii) due to errors in observation, interpretation, or analysis. 

What sample size should qualitative research be?

The sample size for qualitative studies has been recommended to include a minimum of 12 participants to reach data saturation (Braun, 2013).

Are surveys qualitative or quantitative?

Surveys can be used to gather information from a sample qualitatively or quantitatively. Qualitative surveys use open-ended questions to gather detailed information from a large sample using free text responses.

The use of open-ended questions allows for unrestricted responses where participants use their own words, enabling the collection of more in-depth information than closed-ended questions.

In contrast, quantitative surveys consist of closed-ended questions with multiple-choice answer options. Quantitative surveys are ideal to gather a statistical representation of a population.

What are the ethical considerations of qualitative research?

Before conducting a study, you must think about any risks that could occur and take steps to prevent them. Participant Protection : Researchers must protect participants from physical and mental harm. This means you must not embarrass, frighten, offend, or harm participants. Transparency : Researchers are obligated to clearly communicate how they will collect, store, analyze, use, and share the data. Confidentiality : You need to consider how to maintain the confidentiality and anonymity of participants’ data.

What is triangulation in qualitative research?

Triangulation refers to the use of several approaches in a study to comprehensively understand phenomena. This method helps to increase the validity and credibility of research findings. 

Types of triangulation include method triangulation (using multiple methods to gather data); investigator triangulation (multiple researchers for collecting/ analyzing data), theory triangulation (comparing several theoretical perspectives to explain a phenomenon), and data source triangulation (using data from various times, locations, and people; Carter et al., 2014).

Why is qualitative research important?

Qualitative research allows researchers to describe and explain the social world. The exploratory nature of qualitative research helps to generate hypotheses that can then be tested quantitatively.

In qualitative research, participants are able to express their thoughts, experiences, and feelings without constraint.

Additionally, researchers are able to follow up on participants’ answers in real-time, generating valuable discussion around a topic. This enables researchers to gain a nuanced understanding of phenomena which is difficult to attain using quantitative methods.

What is coding data in qualitative research?

Coding data is a qualitative data analysis strategy in which a section of text is assigned with a label that describes its content.

These labels may be words or phrases which represent important (and recurring) patterns in the data.

This process enables researchers to identify related content across the dataset. Codes can then be used to group similar types of data to generate themes.

What is the difference between qualitative and quantitative research?

Qualitative research involves the collection and analysis of non-numerical data in order to understand experiences and meanings from the participant’s perspective.

This can provide rich, in-depth insights on complicated phenomena. Qualitative data may be collected using interviews, focus groups, or observations.

In contrast, quantitative research involves the collection and analysis of numerical data to measure the frequency, magnitude, or relationships of variables. This can provide objective and reliable evidence that can be generalized to the wider population.

Quantitative data may be collected using closed-ended questionnaires or experiments.

What is trustworthiness in qualitative research?

Trustworthiness is a concept used to assess the quality and rigor of qualitative research. Four criteria are used to assess a study’s trustworthiness: credibility, transferability, dependability, and confirmability. 

Credibility refers to how accurately the results represent the reality and viewpoints of the participants. Transferability refers to whether the findings may be applied to another context, setting, or group.

Dependability is the extent to which the findings are consistent and reliable. Confirmability refers to the objectivity of findings (not influenced by the bias or assumptions of researchers).

What is data saturation in qualitative research?

Data saturation is a methodological principle used to guide the sample size of a qualitative research study.

Data saturation is proposed as a necessary methodological component in qualitative research (Saunders et al., 2018) as it is a vital criterion for discontinuing data collection and/or analysis. 

The intention of data saturation is to find “no new data, no new themes, no new coding, and ability to replicate the study” (Guest et al., 2006). Therefore, enough data has been gathered to make conclusions.

Why is sampling in qualitative research important?

In quantitative research, large sample sizes are used to provide statistically significant quantitative estimates.

This is because quantitative research aims to provide generalizable conclusions that represent populations.

However, the aim of sampling in qualitative research is to gather data that will help the researcher understand the depth, complexity, variation, or context of a phenomenon. The small sample sizes in qualitative studies support the depth of case-oriented analysis.

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Research Paper Guide

Qualitative Research Method

Nova A.

Qualitative Research - Methods, Types, and Examples

16 min read

Published on: Dec 25, 2017

Last updated on: Jan 11, 2024

Qualitative research

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There are various methods for conducting scientific research. The two broad approaches to data collection include qualitative and quantitative research methods. 

However, it is not easy to decide which one to choose while writing a research paper .

If you know the basic difference between both methods, you will produce a well-written and structured paper. 

In this blog, we have explored what is qualitative research, its nature, purpose, and methods of data collection. By reading this, students can gain a good understanding of qualitative research, enhancing their ability to conduct in-depth studies. 

So keep reading!

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What is Qualitative Research - Definition

Qualitative research is a research methodology that aims to explore and understand the complexities of human behavior, emotions, and experiences through non-numerical data.

Unlike quantitative research, which deals in numbers and statistics, qualitative research is all about revealing the stories, and perspectives that make us uniquely human.

Let's dive deeper and discover why it's a powerful tool in the researcher's arsenal.

Purpose of Qualitative Research Design

Qualitative research simplifies the understanding of complex human behavior and experiences. Its purpose is to:

  • Explore Complex Phenomena: Qualitative research allows us to delve deep into intricate human experiences and behaviors.
  • Understand Motivations: It helps uncover the 'whys' behind actions, shedding light on underlying motivations.
  • Capture Richness: By collecting narratives and stories, qualitative research captures the richness of human life.
  • Generate Hypotheses: It often serves as a foundation for hypothesis generation in further quantitative studies.
  • Inform Decision-Making: Qualitative findings guide decisions in fields like psychology, sociology, and market research.
  • Contextualize Quantitative Data: It provides context to quantitative data, explaining the 'how' and 'why' behind the numbers.

Characteristics of Qualitative Research

The following are the main characteristics of qualitative research.

  • The real-world setting is the first important characteristic. It involves various qualitative research methods to study the behavior of participants.
  • Researchers play an essential role in choosing a method and making a plan for conducting research.
  • All qualitative approaches have their significance and are used for different scenarios.
  • Qualitative research questions are beneficial for complex reasoning to get the right results.
  • It is also used to explain the outcome of quantitative research methods.
  • The role of participants is essential as it brings meaning to the study.
  • Qualitative research is flexible and can be changed at any stage of the research work.
  • It also describes the research problem by developing a complex cause-and-effect relationship between the variables. 
  • Data analysis in qualitative research is an ongoing process.
  • Conclusions can be drawn based on the outcomes of the research process.
  • Participants are selected from a particular and relevant group.

Qualitative Research Methods

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A detailed description of the major qualitative approaches to collecting data is given below.

In-depth Interview

In-depth interviews involve one-on-one conversations to gather detailed information about a specific topic. This method allows researchers to explore participants' motivations, inspirations, and body language.

Interviews can be conducted face-to-face, via email, or over the phone for flexibility.

Focus Groups

Focus groups consist of small group discussions (5-15 participants) on specific topics, ideal for 'what,' 'why,' and 'how' questions about society and the environment. They can be conducted in-person or online, offering versatility in data collection.

Direct Observation

Direct observation collects subjective data through the five senses without interference. It focuses on characteristics, not measurements, often in public settings where privacy isn't a concern.

Open-Ended Surveys

Open-ended surveys use structured or unstructured questions to collect information on respondents' opinions and beliefs, providing insights into their perspectives.

Participant Observation

Participant observation involves researchers actively participating in events while observing people in natural settings, offering firsthand experience and insights.

Literature Review

The literature review method interprets words and images from published works to analyze social life. It examines word usage in context to draw inferences and identify meanings.

Types of Qualitative Research

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The following is a comprehensive overview of the types of qualitative research methods.

The case study research method has now become the most valuable method of conducting research. It has evolved in recent years and is used to explain an entity in detail.

Moreover, it also involves a thorough understanding of different types of data sources. These include interviews, documents, reports, and observations.  Mainly, this research type is used in different areas like education, social sciences, etc.

Ethnographic Research

The ethnographic research method is the most familiar and in-depth observational method. It focuses on people and their behaviors in the natural environment.

Here, a researcher needs to adapt to the environment and society of the target audience to conduct better research. It helps to get a first-hand experience of the natural setting, including the customs, traditions, and culture of the subjects.

This type of research is a challenging and time-consuming process as it can last from days to years. However, geographical constraints can be an issue while collecting data.

Grounded Theory

While other methods discuss and focus on an event or activity. The grounded theory method deeply looks into the explanation and the main theory behind the event.

It requires the researcher to observe the interviews and documents to build a theory. Moreover, it usually starts with a question or collection of data.  However, the sample sizes in this method are usually larger than in other methods. 

Phenomenological Method

This type is used in the description of an event, phenomenon, and activity. Here, methods like interviews, reading documents, visiting places, and watching videos are used.

This will help to add new insights to the existing data analysis by checking its reliability and validity.

Check out the video to learn more about the phenomenological method of qualitative research!

Narrative Method 

The narrative method is used to gather data from subjects through interviews or documents. Later, the gathered information is used to derive answers and suggestions for future research. 

Historical Method

The historical method involves the examination of past events to draw conclusions and predictions about the future. The steps included in the method are formulating a plan, gathering data, and analyzing the sources. 

Steps in Conducting Qualitative Research

Conducting qualitative research is a systematic process that involves several key steps to ensure the collection of meaningful data.

Here's a chronological guide to conducting qualitative research:

Step 1: Define Research Objectives

Begin by clearly defining the research objectives and questions. What do you want to learn, explore, or understand through your qualitative research? This step sets the direction for your study.

Step 2: Select a Research Design

Choose an appropriate research design based on your objectives. Common designs include case studies, ethnography, grounded theory, or phenomenology. The design informs your data collection and analysis methods.

Step 3: Sampling Methods

Decide on your sampling strategy. Will you use purposive sampling to select specific participants who are most relevant to your research question? Or will you employ snowball sampling to find participants through referrals?

Step 4: Data Collection Techniques

Determine the data collection techniques that align with your research design. Depending on your approach, this may involve conducting in-depth interviews, facilitating focus groups, observing participants, or analyzing existing documents and content.

Step 5: Plan Interviews and Questions

If conducting interviews, create interview guides with open-ended questions. These questions should allow participants to share their thoughts, experiences, and perspectives freely. Ensure that questions are related to your research objectives.

Step 6: Conducting Data Collection

Collect data according to your chosen methods. For interviews, arrange and conduct interviews with participants, ensuring a comfortable and open environment. If using other techniques, follow the procedures outlined in your research design.

Step 7: Data Recording and Management

Record data meticulously. This may involve audio or video recordings, note-taking, or transcribing interviews. Organize and store data securely to maintain confidentiality.

Step 8: Data Analysis

Qualitative data can be in the form of interviews, transcripts, surveys, videos, audio, etc. The steps involved in qualitative data analysis are given below.   

  • Organize the Data: This can be done by transcribing interviews or making detailed notes.
  • Review the Data: Examine the data, ideas, and patterns.
  • Establish a Data Coding System: Generate a set of codes that you can apply to classify your data.
  • Assign Codes to the Data: For qualitative survey analysis, create codes, and add them to your system.
  • Identify Themes: Link the codes together into cohesive themes.

Similarly, the following are different approaches to analyzing qualitative data. 

  • Content Analysis – It is used to categorize common words and ideas.
  • Thematic Analysis – thematic analysis in qualitative research is used to identify and interpret different themes and patterns.
  • Textual Analysis – This type of analysis is used to examine the structure, content, and design of text.
  • Discourse Analysis – It is used to study how a language is used to achieve specific results.

Step 9: Validity and Reliability

Ensure the validity and reliability of your findings. Consistently apply your chosen analysis methods and cross-check interpretations with colleagues or participants to validate your results.

Step 10: Ethical Considerations

Throughout the research process, uphold ethical principles. Protect the privacy and anonymity of participants, obtain informed consent, and address any ethical concerns that may arise.

Qualitative Research vs Quantitative Research

Qualitative and quantitative research are two distinct approaches to conducting research. Here are the main differences between qualitative vs. quantitative research.

Looking for a more detailed comparison between these 2 types of research? Check out our qualitative vs. quantitative research blog.

Qualitative Research Topics

To write an amazing qualitative research paper, here are some interesting topics for you.

  • The Impact of Parental Involvement on Children's Education
  • Social Isolation and Loneliness Among the Elderly
  • Factors Influencing Consumer Choices in Sustainable Fashion
  • Coping Mechanisms for Stress Among College Students
  • Experiences of Immigrant Workers in Low-Wage Jobs
  • The Role of Music in Expressing Emotions and Well-being
  • Perceptions of Mental Health Stigma in Ethnic Communities
  • Exploring the Transition to Parenthood: Challenges and Joys
  • How Cultural Differences Influence Conflict Resolution Styles
  • The Influence of Family Dynamics on Eating Habits and Nutrition in Children

We have also compiled a list of research paper topics in case you need more unique ideas.

Qualitative Research Examples

Check out the examples of qualitative research to get a better idea of writing a qualitative research study.

Qualitative Research Example

Qualitative Research Paper Sample

Qualitative Research Limitations

The following discussed are the qualitative research limitations. 

  • The qualitative research data involve fewer expenses and time. 
  • It does not have large-scale data.
  • It requires a lot of time to manage, gather, and analyze data.
  • It is not possible to verify the results as it is open-ended research. 
  • It is difficult to analyze the credibility and validity of data because of its subjective nature.
  • Expert knowledge of the area is necessary to understand the collected information.

In Conclusion, the qualitative research method shows the idea and perception of your targeted audience. However, not every student is able to choose the right approach while writing a research paper. It requires a thorough understanding of both qualitative research and quantitative research methods.

This is where the professional help from  MyPerfectWords.com comes in. We are a legit paper writing service that provides reliable help with your academic assignments. 

Contact our customer support and place " write my research paper " order today!

Frequently Asked Questions

What are the two methods in research study.

There are two types of studies that involve observing people during a study, participant observation and non-participant observation. 

Why is qualitative research better?

Because qualitative research includes the ability to gain unique insights through deep exploration. Survey respondents are able to disclose their experiences, thoughts, and feelings without constraint or influence from an outside source. 

Nova A. (Literature, Marketing)

Nova Allison is a Digital Content Strategist with over eight years of experience. Nova has also worked as a technical and scientific writer. She is majorly involved in developing and reviewing online content plans that engage and resonate with audiences. Nova has a passion for writing that engages and informs her readers.

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Qualitative Research Methods: Types, Examples, and Analysis

Qualitative Research Methods

In a universe swarming with data, numbers, and algorithms, lies a lesser-known realm where emotions, stories, and intimate revelations take center stage. When you want to get inside your customers’ heads to understand their thoughts, feelings, perceptions, beliefs, and emotions, numbers are unlikely to provide a complete picture.

Let’s set the scene: picture a cozy bakery buzzing with conversations. People from different walks of life gather, each carrying a unique story to tell. You observe that your sale of pancakes is more than that of pastries, numerical data will tell you that much. But numbers won’t tell you why.

This is exactly where qualitative surveys come into play; they take you right to the heart of people’s minds and experiences – the “why” behind the statistics.

Quantitative data may offer a bird’s-eye view of the crowd, but qualitative surveys open the doorways to your audience’s individual tales. In this blog, we are going to explore qualitative research, its types, analytical procedures, positive and negative aspects, and examples.

Here we go!

What Is Qualitative Research?

Qualitative research is a branch of market research that involves collecting and analyzing qualitative data through open-ended communication. The primary purpose of conducting qualitative research is to understand the individual’s thoughts, feelings, opinions, and reasons behind these emotions.

It is used to gather in-depth and rich insights into a particular topic. Understanding how your audience feels about a specific subject helps make informed decisions in research.

As opposed to quantitative research, qualitative research does not deal with the collection of numerical data for statistical analysis. The application of this research method is usually found in humanities and social science subjects like sociology, history, anthropology, health science, education, etc.

Types of Qualitative Research Methods

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Qualitative research methods are designed to understand the behavior and perception of the target audience about a particular subject.

Qualitative research methods include observations, one-on-one interviews, case study research, focus groups, ethnographic research, phenomenology, and grounded theory.

Let’s discuss them one by one.

1. Observations

Observation is one of the oldest qualitative methods of research used to collect systematic data using subjective methodologies. It is based on five primary sense organs – smell, sight, taste, touch, and hearing, and their functioning. This method focuses on characteristics and qualities rather than numbers.

The qualitative observation technique involves observing the interaction patterns in a particular situation. Researchers collect data by closely watching the behaviors of others. They rely on their ability to observe the target audience rather than communicating with people about their thoughts on a particular subject.

2. One-on-One Interviews

Conducting one-on-one interviews is one of the most common types of qualitative research methods. Although both open-ended and closed-ended questions can be a part of these interviews, open-ended conservation between researchers and participants related to a particular subject is still the preferred mode of communication. This is to gather in-depth qualitative data for the research purpose.

Here, the researcher asks pre-determined questions to the participants to collect specific information about their research topic. Interviews can be conducted face-to-face, by email, or by phone. The drawback of this method is that sometimes the participants feel uncomfortable sharing honest answers with the researcher.

3. Focus Groups

A Focus group involves collecting qualitative data by conducting a group discussion of 6-12 members along with a moderator related to a particular subject. Here the moderator asks respondents a set of predetermined questions so that they can interact with each other and form a group discussion. It helps researchers to collect rich qualitative data about their market research.

However, it is essential to ensure that the moderator asks open-ended questions like “how,” “what,” and “why” that will enable participants to share their thoughts and feelings.

Close-ended questions like “yes” and “no” should be avoided as they do not lead to engagement among participants.

4. Case Study Research

A case study is another example of qualitative research that involves a comprehensive examination of a particular subject, person, or event.

qualitative research sample

This method is used to obtain in-depth data and complete knowledge of the subject. The data is collected from various sources like interviews and observation to supplement the conclusion.

This qualitative approach is extensively used in the field of social sciences, law, business, and health. Many companies use this technique when marketing their products/services to new customers. It tells them how their business offerings can solve a particular problem. Let’s discuss an example of this method of qualitative research.

5. Digital Ethnography

This is an innovative form of qualitative research that focuses on understanding people and their cultures in the context of the digital realm. Digital ethnography aims to study individuals’ behavior, interactions, and social dynamics within online environments and digital communities.

In digital ethnography, the researcher acts as both an observer and a participant in these said online communities to gain firsthand insight into the lifestyles, cultures, and traditions of people navigating these digital landscapes.

Unlike traditional ethnography, digital ethnography is more efficient and accessible. The studies are conducted remotely, reducing the need for extended physical presence in a specific location, and the data collection process is often more streamlined.

6. Grounded Theory

This is another data collection method of qualitative research used across various disciplines. The Grounded Theory aims to provide the reasons, theories, and explanations behind an event. It focuses on why a course of action has happened the way it did.

The grounded theory model collects and analyzes the data to develop new theories about the subject. The data is collected using different techniques like observation, literature review, and document analysis.

This qualitative method is majorly used in business for conducting user satisfaction surveys to explain why a customer purchases a particular product or service. It helps companies in managing customer loyalty.

7. Phenomenology

Phenomenology is another qualitative research example that describes how an individual experiences or feels about a particular event. It also explores the experience of a specific event in a community.

Here, the researcher interviews people who have experienced a particular event to find similarities between their experiences. The researcher can also record what they learn from the target audience to maintain the credibility of the data.

Although this qualitative technique depends majorly on interviews, other data collection methods like observation, interviews, and survey questionnaires are also used to supplement the findings. The application of this method is found in psychology, philosophy, and education.

For example, to prompt a participant to share their experience around an event they encountered, you can ask:

“What was your experience like when you first encountered [a specific phenomenon or event]?”

8. Record Keeping

This approach involves using existing trustworthy documents and other reliable sources as the basis of data for new research. It’s comparable to visiting a library, where you can explore books and reference materials to gather relevant data that might be helpful for your research.

How Do You Analyze Qualitative Data?

Qualitative Data

1. Arranging the Data

Qualitative data is collected in different forms like audio recordings, interviews, video transcriptions, etc. This step involves arranging all the collected data in the text format in the spreadsheet. This can be done either manually or with the help of data analysis tools.

2. Organizing the Data

Even after putting the data into a spreadsheet, the data is still messy and hard to read. Due to this, the data needs to be organized in a readable and understandable pattern.

For example, you can organize data based on questions asked. Organize your data in such a way that it appears visually clear. Data organization can be tedious, but it is essential for the next step.

3. Assigning Codes

Developing codes for the data helps simplify the data analysis methods in qualitative research. Assigning code implies categorizing and setting patterns and properties to the collected data. It helps in compressing the vast amount of information collected. By developing codes for your data, you can gather deep insight into the data to make informed business decisions.

4. Analyzing the Data

Qualitative data cannot be analyzed based on any universally accepted equation like quantitative data. Qualitative data analysis depends on the thinking and logical skill of the researcher.

quantitative data. Qualitative

However, there are a few techniques by which you can easily interpret data by identifying themes and patterns between sample responses:

  • Checking the data for repetitive words and phrases commonly used by the audience in their answers.
  • Comparing the primary and secondary data collection to find the difference between them.
  • Scanning the data for expected information that has not been included in answers provided by respondents.

5. Summarizing the Data

The final stage is to link the qualitative data to the hypothesis. Highlight significant themes, patterns, and trends by using essential quotes from the data, as well as any possible contradictions.

Summarizing the Data

One of the main things about qualitative data is that there isn’t a single, formal way to collect and analyze data. Each research project will have its own set of methods and techniques that it needs to use.

The key is to look at the specific needs of each project and change the research method accordingly.

Also Read: How to Analyze Survey Data Like a Pro

Advantages and Limitations of Qualitative Research

Qualitative market research techniques offer a more comprehensive and complete picture of the subject than quantitative research, which focuses on specific and narrow areas. Other advantages of using qualitative research methods are:

  • Explore the subject in-depth: Qualitative research is personal and offers a deep understanding of the respondent’s feelings, thoughts, and actions so that the researcher can perform an in-depth analysis of the subject.
  • Promotes discussion: Qualitative research methods are open-ended in approach rather than rigorously following a predetermined set of questions. It adds context to the research rather than just numbers.
  • More flexibility: The interviewer can study and ask questions on the subject they feel is pertinent or had not previously thought about during the discussions. Moreover, open-ended questions enable respondents to be free to share their thoughts, leading to more information.
  • Capture trends as they change: Qualitative research can track how people’s feelings and attitudes change over time. Respondents’ opinions can change during the conversation, and qualitative research can show this.

With that being said, however, we do not mean that qualitative data is entirely devoid of flaws. Like most things, it, too, has its fair share of limitations, the prime among them being:

  • Subjectivity: Qualitative data can be influenced by the researcher’s bias or interpretation, potentially affecting the objectivity of the findings. The absence of strict guidelines in qualitative research can lead to variations in data collection and analysis too.
  • Time-Consuming & Resource-Intensive: Conducting qualitative research can be a lengthy process, from data collection through transcription and analysis. It also often requires skilled researchers, making it more resource-intensive compared to some quantitative methods.
  • Difficulty in Analysis: Analyzing qualitative data can be complex, as it involves coding, categorizing, and interpreting open-ended responses. This data category often does not lend itself well to traditional statistical tests, limiting the depth of statistical analysis as well.
  • Challenges in Replication: Replicating qualitative studies can be challenging due to the unique context and interactions involved.

Advantages of Using Website Surveys for Qualitative Research

The role of surveys and questionnaires in collecting quantitative data is pretty obvious, but how exactly would you use them to capture qualitative data, and why? Well, for starters, website surveys offer numerous advantages here, such as letting researchers explore diverse perspectives, collect rich and detailed data, conduct cost-effective and time-efficient studies, etc.

Let’s have a brief rundown of the significant benefits below:

Reach and Diversity: Website surveys enable researchers to engage with a diverse and global audience. They break geographical barriers, allowing participation from individuals residing in different regions, cultures, and backgrounds, leading to a richer pool of perspectives.

  • Cost-Effectiveness: Conducting traditional face-to-face qualitative research can be expensive and time-consuming. In contrast, website surveys are cost-effective, as they eliminate the need for travel, venue rentals, and other logistical expenses.
  • Convenience and Flexibility: Website surveys offer unparalleled convenience to both researchers and participants. Respondents can take part in the study at their own pace and preferred time, promoting higher response rates and reducing non-response bias.
  • Anonymity and Honesty: Participants often feel more comfortable expressing themselves honestly in online surveys. Anonymity ensures confidentiality, encouraging candid responses, and allowing researchers to gain deeper insights into personal experiences and opinions.
  • Rich Data Collection: Website surveys can accommodate various question types, including open-ended questions, allowing respondents to elaborate on their thoughts. This results in the collection of rich, detailed, and nuanced data, enriching the qualitative analysis.
  • Time-Efficient Data Collection: Website surveys facilitate efficient data collection, reaching a large number of participants in a short span. Researchers can access real-time data, enabling quick analysis and timely decision-making.
  • Ease of Analysis: Online survey platforms often provide tools for automated data analysis, simplifying the coding and categorization process. Researchers can swiftly identify themes and patterns, expediting the interpretation of qualitative findings.
  • Longitudinal Studies: Website surveys are well-suited for longitudinal studies, as they allow researchers to follow up with the same participants over an extended period. This longitudinal approach enables the exploration of changes in attitudes or behaviors over time.
  • Integration with Multimedia: Website surveys can seamlessly incorporate multimedia elements, such as images, videos, or audio clips, enabling respondents to provide more context and depth to their responses.
  • Eco-Friendly Approach: By reducing the need for paper and physical materials, website surveys promote a sustainable and eco-friendly approach to data collection, aligning with responsible research practices.

Most website survey tools are equipped with features that efficiently collect and analyze diverse perspectives, ultimately furthering your data collection process. For example:

  • Question Customization: These tools allow users to create and customize a wide range of questions, including open-ended, closed-ended, rating scale, and more. This flexibility allows participants to express their thoughts and feelings in their own words, paving the way for gathering diverse qualitative data.
  • Anonymity and Confidentiality: Ensuring confidentiality in qualitative research is crucial for building trust and obtaining more accurate and sensitive data. Participants can often remain anonymous when using website survey tools, which can encourage them to provide honest and candid responses.
  • Data Analysis Support: Many website survey tools offer built-in data analysis features, such as basic statistical summaries and visualizations. While these features are more suited for quantitative data, they can still aid in organizing and understanding qualitative responses, making the analysis process more manageable.
  • Flexibility in Survey Design: Researchers can use skip logic and branching features in these tools to create dynamic surveys that adapt based on participants’ responses. This can be greatly valuable in qualitative research, where participants’ experiences might vary widely.
  • Ease of Participation: Participants can access website surveys using various devices like computers, tablets, or smartphones, making it convenient and accessible for them to take part in the research. This ease of participation can contribute to a higher response rate and a more diverse participant pool.
  • Data Storage and Security: Many website survey tools offer secure data storage and backup, ensuring the safety of the collected qualitative data. This feature is essential for maintaining the confidentiality and integrity of participants’ responses.

Examples of Website Survey Questions for Qualitative Research

Crafting effective survey questions is crucial for qualitative research. Ensuring clarity, avoiding leading questions, and maintaining a balanced mix of question types is paramount if you are looking to gather comprehensive and valuable qualitative data.

With well-designed website survey questions, you can delve deep into participants’ thoughts, emotions, and experiences, providing a solid foundation for insightful qualitative analysis.

Let’s explore some of the prime examples:

1. Open-Ended Questions (Exploratory):

  • “Please describe your experience with our product/service in your own words.”
  • “What are the main challenges you face in your daily work?”

qualitative research sample

2.Multiple-Choice Questions (Categorization):

“Which age group do you belong to?”

  • 18-25 years
  • 26-35 years
  • 36-45 years
  • 46-55 years

qualitative research sample

3. Likert Scale Questions (Rating/Opinion): “On a scale of 1 to 5, how satisfied are you with our customer support?” 1 (Not satisfied at all) 2 (Slightly satisfied) 3 (Moderately satisfied) 4 (Very satisfied) 5 (Extremely satisfied)

qualitative research sample

4. Ranking Questions (Preference):

“Please rank the following factors in order of importance for choosing a smartphone:”

  • Battery life
  • Camera quality
  • Processor speed
  • Display resolution

5. Semantic Differential Questions (Contrast): “How would you describe our website’s user interface?”

  • Difficult _ Easy Unattractive Attractive
  • Confusing ___ Clear

6. Picture Choice Questions (Visual Feedback):

“Which logo do you find more appealing for our brand?”

  • Option A (Image)
  • Option B (Image)

7. Demographic Questions (Participant Profiling):

“Which of the following best describes your occupation?”

  • Professional

8. Dichotomous Questions (Yes/No):

  • “Have you ever purchased products from our online store?”

qualitative research sample

9. Follow-Up Probing Questions (In-depth Insight):

  • “You mentioned facing challenges at work. Could you please elaborate on the specific challenges you encounter?”

10. Experience-Based Questions (Narrative):

  • “Tell us about a memorable customer service experience you’ve had, whether positive or negative.”

View All Templates Here

Ready to Obtain Quality Data Using Qualitative Research?

So, there you have it all about qualitative research methods: their types, examples, use, and importance. Quantitative research is one of the most effective instruments to understand individuals’ thoughts and feelings or identify their needs and problems.

After figuring out the problem, quantitative research is used to make the conclusion and offer a reliable solution for business.

You can also supplement your qualitative market research with ProProfs Survey Maker to reach your target audience more effectively and in a shorter duration. Use the 15-day free trial to enhance your qualitative research – no commitment, no credit card details!

Jared Cornell

About the author

Jared cornell.

Jared is a customer support expert. He has been published in CrazyEgg , Foundr , and CXL . As a customer support executive at ProProfs, he has been instrumental in developing a complete customer support system that more than doubled customer satisfaction. You can connect and engage with Jared on Twitter , Facebook , and LinkedIn .

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16 Qualitative Methods Examples

qualitative research examples and definition, explained below

Qualitative research seeks to explore and understand individuals’ or groups’ experiences, behaviors, and social phenomena by collecting non-numerical data, such as text or images, and analyzing it in a narrative, descriptive manner.

Its strength is that it provides a deep understanding of human behavior, experiences, and social phenomena, enabling the exploration of nuances, contexts, and underlying factors that may not be evident through quantitative methods (Aurini, Heath & Howells, 2021 [ 1 ] ; Bhattacharya, 2017 [ 2 ] ).

However, its findings can be subjective, less generalizable due to smaller sample sizes, and may require a significant amount of time, effort, and expertise to collect and interpret the data accurately (Bhattacharya, 2017 [ 2 ] ; Hatch, 2023 [ 3 ] ).

Examples of qualitative research include conducting in-depth interviews to explore patients’ experiences with healthcare, utilizing focus groups to understand consumer perceptions of a product, engaging in ethnographic observation to study cultural practices, and employing case studies to investigate real-life phenomena in detail.

Qualitative Methods Examples

1. case studies.

A case study is a detailed investigation of a specific individual, group, or event over a defined period. It goes in depth in one specific case rather than achieving a broad range of participants or instances of a situation.

The main purpose of a case study is to provide an in-depth analysis and understanding of complex issues that cannot be fully captured through statistical models or broad sweeping quantitative approaches (Bhattacharya, 2017 [ 2 ] ; Lapan, Quartaroli & Riemer, 2011 [ 4 ] ).

This method often involves collecting and analyzing various forms of qualitative data such as interviews, observations, and documents.

The data is then used to construct a narrative about the case, identify themes or patterns, and draw conclusions. Case studies are often used in fields like psychology, business, and education, due to their ability to produce rich, detailed, and practical knowledge.

Real Case Study Example

Study: “Shoreline changes over last five decades and predictions for 2030 and 2040: a case study from Cuddalore, southeast coast of India.”

Explanation: This study is about estimating the shoreline changes over the past five decades in a part of the southeast coast of India at Cuddalore, and predicting the shoreline evolution for the years 2030 and 2040. This is a case study as it utilizes specific, localized data from Cuddalore to gain in-depth understanding and make future predictions about shoreline changes. However, as it’s a case study with only one location for analysis, it may not be applicable to other shorelines.

Citation: Natarajan, L., Sivagnanam, N., Usha, T., Chokkalingam, L., Sundar, S., Gowrappan, M., & Roy, P. D. (2021). Shoreline changes over last five decades and predictions for 2030 and 2040: a case study from Cuddalore, southeast coast of India.  Earth Science Informatics ,  14 , 1315-1325. ( Access Here )

See Also: Case Study Advantages and Disadvantages

2. Grounded Theory

Grounded theory is a research methodology that involves the collection and analysis of qualitative data with the aim of creating theories that are grounded in the data itself.

The defining feature of grounded theory is that it does not text a theory or hypothesis, unlike most other research approaches. Instead, it studies a phenomenon, allowing the theory to emerge naturally from the data (Atkinson, 2015 [ 5 ] ; Mills, Bonner & Francis, 2017 [ 6 ] ).

So, the study ends with a hypothesis by following the data rather than beginning with a hypothesis to be tested.

Researchers engaged in grounded theory begin with an area of study, then gather, code, and analyze the data, allowing the recurring patterns to evolve into a framework (Atkinson, 2015 [ 5 ] ; Mills, Bonner & Francis, 2017 [ 6 ] ).

This process continues up to the point of theoretical saturation, when no new information or themes are emerging from the data.

Real Grounded Theory Example

Study: “Developing a Leadership Identity.”

Developing a Leadership Identity  by Komives et al (2005) employs a grounded theory approach to develop a thesis based on the data rather than testing a hypothesis. The researchers studied the leadership identity of 13 college students taking on leadership roles. Based on their interviews, the researchers theorized that the students’ leadership identities shifted from a hierarchical view of leadership to one that embraced leadership as a collaborative concept.

Citation: Komives, S. R., Owen, J. E., Longerbeam, S. D., Mainella, F. C., & Osteen, L. (2005). Developing a leadership identity: A grounded theory.  Journal of college student development ,  46 (6), 593-611. ( Access Here )

See More Grounded Theory Examples Here

3. Ethnography

Ethnography is a research method often used in anthropology, in which the researcher immerses themselves in the community or culture they are studying (Hammersley, 2018 [ 7 ] ; Jones & Smith, 2017 [ 8 ] ).

The researcher observes, interacts, and records the daily lives, behaviors, and social interactions of the community members from their perspective.

The primary aim of ethnography is to provide rich, holistic insights into people’s views and actions, as well as the nature (i.e., sights, sounds) of the location they inhabit, through the collection of detailed observations and interviews.

During the ethnographic study, the researcher usually lives within the community, allowing them to get deeper insights than they would get from just having occasional contact (Hammersley, 2018 [ 7 ] ; Jones & Smith, 2017 [ 8 ] ).

The result is a detailed description of the community’s social practices, beliefs, and experiences, often looking at such aspects as rituals, ceremonies, interactions, and daily life.

Real Ethnography Example

Study: “Liquidated: An Ethnography of Wall.”

Liquidated: An Ethnography of Wall Street  by Karen Ho involves an anthropologist who embeds herself with Wall Street firms to study the culture of Wall Street bankers and how this culture affects the broader economy and world.

Citation: Ho, K. (2009). Liquidated: An Ethnography of Wall Street . Duke University Press. ( Access Here )

See More Ethnography Examples Here

4. Autoethnography

Autoethnography combines elements of autobiography and ethnography.

In autoethnography, researchers use their own personal experiences and reflections as the primary data source to gain insights into cultural, social, and individual phenomena (Pretorius & Cutri, 2019 [ 9 ] ).

The intent is to use personal narratives not only to understand the self, but also to understand the cultural context in which the self is situated.

By focusing on their own experiences, emotions, and responses within a specific cultural context, researchers seek to provide a rich, detailed, and personal account that sheds light on broader cultural norms , behaviors, and experiences (Pretorius & Cutri, 2019 [ 9 ] ).

This method is particularly common in social sciences and humanities, where understanding the complexity of human experiences and emotions is of principal importance.

Real Autoethnography Example

Study: “Living Without a Mobile Phone: An Autoethnography”

Living Without a Mobile Phone: An Autoethnography  by Andres Luccero (2018) is one of the more captivating academic studies I’ve engaged with in recent months. It explores themes related to the benefits and struggles of voluntarily foregoing mobile phones (including the safety fears Luccero goes through) after systematically collecting field notes over a number of years.

Citation: Lucero, A. (2018). Living without a mobile phone: An autoethnography. In  Proceedings of the 2018 Designing Interactive Systems Conference  (pp. 765-776). ( Access Here )

See More Autoethnography Examples Here

5. Phenomenology

Phenomenology is a method that focuses on the commonality of a lived experience within a particular group.

The central aim is to interpret and describe the meaning of these experiences in order to capture the ‘essence’ of the phenomenon (Neubauer, Witkop & Varpio, 2019 [ 10 ] ; Zahavi, 2018 [ 11 ] ).

Researchers utilizing this method typically gather data through interviews, written stories, artefacts or other forms of personal narratives from the individuals who have experienced the phenomenon firsthand.

Then, through a process of reflecting on these first-person descriptions, researchers aim to draw out the underlying structures and themes of the experience and thereby provide a richer and deeper understanding of the phenomenon (Neubauer, Witkop & Varpio, 2019 [ 10 ] ; Zahavi, 2018 [ 11 ] ).

Phenomenology is often used in social science, psychology, and health sciences research.

Real Phenomenology Example

Study: “A phenomenological approach to experiences with technology”

A phenomenological approach to experiences with technology  by Sebnem Cilesiz represents a good starting-point for formulating a phenomenological study. With its focus on the ‘essence of experience’, this piece presents methodological, reliability, validity, and  data analysis techniques  that phenomenologists use to explain how people experience technology in their everyday lives.

Citation: Cilesiz, S. (2011). A phenomenological approach to experiences with technology: Current state, promise, and future directions for research.  Educational Technology Research and Development ,  59 , 487-510. ( Access Here )

6. Narrative Research

Narrative research involves collecting and studying individuals’ lived experiences as told through their own stories. Detailed narratives help to produce detailed and nuanced accounts of phenomena (McAlpine, 2016 [ 12 ] .

This method is typically used when researchers want to capture detailed stories or life experiences related to the study’s focal area from the perspective of participants.

The research involves gathering data through methods such as interviews, diaries, personal notes, or letters, from which narratives are then constructed and analyzed for recurring themes and patterns (McAlpine, 2016 [ 12 ] .

A key value of narrative research is its emphasis on giving voice to participants’ experiences in their own words and context, making it a powerful approach to explore personal histories, cultural narratives, and complex social issues .

Real Narrative Research Example

Study: “Learning to Labour”

Learning to Labour  by Paul Willis is perhaps one of the most famous examples of narrative research. In this study, Willis explored the personal identity narratives that working-class English boys created around work and school, demonstrating their choices to reject formal education and its middle-class values while many of them embraced hard work ethic for types of work they valued, namely, creative and productive physical labor.

Citation: Willis, P. E. (1981). Learning to Labor: How Working Class Kids Get Working Class Jobs. Columbia University Press. ( Access Here )

7. Action Research

Action Research is a participatory, problem-solving method which aims to improve concrete situations through a cycle of action and reflection (Jacobs, 2018 [ 13 ] ).

The core idea is that the researcher is not a passive observer but actively involved in the phenomenon being studied, working collaboratively with participants to solve real-world problems.

The cycle typically includes problem identification, planning for improvement, implementation of change, observation of the effects, and reflection on the process and results to adjust and refine the plan for the next cycle (Jacobs, 2018 [ 13 ] ).

This type of research is usually employed in education, healthcare, community development, or organizational studies, where the goal is to make practical improvements while also expanding knowledge.

Action research, thus, blurs the boundary between researcher and participant, prioritizing experiential learning, shared decision making and equitable relationships.

Real Action Research Example

Study: “Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing”

Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing  by Ellison and Drew was a research study one of my research students completed in his own classroom under my supervision. He implemented a digital game-based approach to literacy teaching with boys and interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience.

Citation: Ellison, M., & Drew, C. (2020). Using digital sandbox gaming to improve creativity within boys’ writing.  Journal of Research in Childhood Education ,  34 (2), 277-287. ( Access Here )

See More Action Research Examples Here

8. Focus Group Research

Focus group research is a form of qualitative research where a group of people are asked about their attitudes, beliefs, experiences, and reactions to a specific subject, product, concept, or idea.

The interaction between the group members is observed and used for gathering data, as it can provide additional depth and complexity to the understanding of the topic being discussed (Guest, Namey & McKenna, 2017 [ 14 ] ; Kamberelis & Dimitriadis, 2013 [ 15 ] ).

Focus group usually involves 6-12 participants, led by a trained facilitator who guides the discussion and ensures everyone’s voice is heard.

Data collected in focus groups can be analyzed qualitatively to identify themes, patterns, or trends in people’s perceptions and experiences.

This research method is widely used in marketing, political studies, public health, and social sciences, due to its ability to provide rich, detailed and nuanced data.

Real Focus Group Example

Study: “Why people use herbal medicine: insights from a focus-group study in Germany.”

.This study investigates the reasons why people in Germany choose to use herbal medicine, including usage aims, factors associated with illness type, and sources of information. The study used a focus group approach, conducting six focus groups with 46 participants of varying ages, then analyzing the data using a content analysis method, which I’ll explain later in this article.

Citation: Welz, A. N., Emberger-Klein, A., & Menrad, K. (2018). Why people use herbal medicine: insights from a focus-group study in Germany.  BMC complementary and alternative medicine ,  18 , 1-9. ( Access Here )

See More Focus Group Examples Here

9. Semi-Structured Interviewing

Semi-structured interviewing is a common method of data collection in qualitative research where the interviewer directs the conversation using a predetermined set of open-ended questions, but with flexibility to explore topics in more depth (Aurini, Heath & Howells, 2021 [ 1 ] ; Bhattacharya, 2017 [ 2 ] ).

This type of interview does not follow a strict form, allowing the interviewee to express their thoughts and feelings more freely and the interviewer to adapt and probe further based on their responses.

Semi-structured interviews can cover a wide range of topics, gain detailed information, and provide a more nuanced understanding of the interviewee’s perspective and context.

While each interview is guided by a consistent list of topics (interview guide), the order can change depending on the flow of conversation, and additional questions can be asked for clarification or further exploration (Aurini, Heath & Howells, 2021 [ 1 ] .

Real Semi-Structured Interview Example

Study: “English professional football players concussion knowledge and attitude.”

The study examines the knowledge and attitude of English professional football players towards concussion and the misconceptions that exist about it. Semi-structured interviews were conducted to gather in-depth information about the players’ understanding of concussions and establish whether their intended behavior aligns with their knowledge.

Citation: Williams, J. M., Langdon, J. L., McMillan, J. L., & Buckley, T. A. (2016). English professional football players concussion knowledge and attitude.  Journal of sport and health science ,  5 (2), 197-204. ( Access Here )

10. Structured Interviewing

Structured interviewing is a quantitative research method where all participants are asked the same predetermined and standardized set of questions, with the same wording and in the same order (Aurini, Heath & Howells, 2021 [ 1 ] ; Bhattacharya, 2017 [ 2 ] ).

The structured interview format ensures that comparison and statistical analysis is possible since every respondent is asked exactly the same questions.

Response categories are also often predetermined and fixed, limiting the scope for exploring issues in depth, but permitting the gathering of consistent, comparable data (Aurini, Heath & Howells, 2021 [ 1 ] ; Bhattacharya, 2017 [ 2 ] ).

Structured interviewing reduces the potential impact of interviewer bias, enabling more objectivity in the responses.

This method is commonly used in large-scale surveys, market research, and social science research where researchers are interested in measuring trends, comparison between groups, or relationships between variables.

Real Structured Interview Example

Study: “Tell us about your leadership style: A structured interview approach for assessing leadership behavior constructs”

This study investigates the application of the structured interview method as a way to assess leadership behavior based on Yukl’s leadership taxonomy and examine its ability to predict leadership outcomes. The study uses structured interviews by having supervisors answer questions based on specific leadership constructs and situations, which are then analyzed and compared to other leadership measures such as self-assessments and subordinate ratings.

Citation: Heimann, A. L., Ingold, P. V., & Kleinmann, M. (2020). Tell us about your leadership style: A structured interview approach for assessing leadership behavior constructs.  The Leadership Quarterly ,  31 (4), 101364. ( Access Here )

11. Observational Research

Observational research is a qualitative research method where researchers observe participants in their natural setting without any direct involvement or intervention (Seim, 2021 [ 16 ] ; Lapan, Quartaroli & Riemer, 2011 [ 4 ] ).

The aim is to study people’s behavior, interactions, routines or events as they naturally occur, and as a result, gain a more authentic and holistic understanding of the phenomena being studied.

Methods of observation can vary vastly ranging from completely unobtrusive and passive observations, where participants are unaware they are being observed, to participant observations, where researchers immerse themselves into the groups to gain firsthand experience (Seim, 2021 [ 16 ] ).

The information gathered can be rich and detailed, including body language, expressions, and the context and sequence of events, offering insights that are not possible through traditional survey and experimental methods.

Real Observational Research Example

Study: “Influence of models’ reinforcement contingencies on the acquisition of imitative responses.”

The Bobo Doll Experiment  by Albert Bandura is the quintessential observational study. Bandura had children watch adults interacting with a doll. Half saw adults acting roughly with the doll, the other half saw parents acting carefully with the doll. Then, Bandura observed children playing with a doll. His observations revealed that children’s observations of adult actions affect how the children will subsequently treat the doll.

Citation: Bandura, A. (1965). Influence of models’ reinforcement contingencies on the acquisition of imitative responses.  Journal of Personality and Social Psychology, 1 (6), 589–595. ( Access Here )

See More Observational Research Examples Here

12. Delphi Method

The Delphi Method is a structured communication technique used in qualitative research that relies on a panel of experts (Brady, 2015 [ 17 ] ).

The process begins with researchers presenting a problem to the experts who respond individually, usually through a series of questionnaires or online surveys.

Responses are collected and summarized anonymously, then feedback is given to the group, allowing experts to revise their earlier answers based on the replies of their peers (Brady, 2015 [ 17 ] ).

Throughout multiple rounds, the group seeks to reach a consensus on the issue being investigated while minimizing bias because of group interaction.

The Delphi method is often used in predictive research, policy-making, decision-support, and system and technology forecasting where expert opinions are valuable.

Real Delphi Method Example

Study: “Assessing advisor competencies: A Delphi method study.”

This study aims to identify essential competencies for entry-level academic advisors. The Delphi method was employed through surveys administered to academic advisors with 5 or more years of experience, and their responses were analyzed to build consensus on the essential competencies for entry-level academic advisors. A consensus was reached on three essential competencies: Communication skills, interpersonal skills, and knowledge of university policies and resources.

Citation: Menke, D., Stuck, S., & Ackerson, S. (2018). Assessing advisor competencies: A Delphi method study.  The Journal of the National Academic Advising Association ,  38 (1), 12-21. ( Access Here )

13. Textual & Content Analysis

Textual analysis , also known as content analysis, is a qualitative research method used to interpret the content and meaning of textual material in a systematic way.

Researchers using this approach analyze the communication content (like books, essays, interviews, speeches, online posts, etc.) in order to decipher patterns, themes, biases, and other cultural, societal, or thematic elements.

A researcher might analyze the themes, symbols, motifs, dialogues, plot structures, or stylistic choices in a text, in an attempt to understand how these elements contribute to its overall meaning and potential effects on its audience.

I have a detailed explanation of how to conduct a qualitative content analysis in my article on inductive coding , and I also highly recommend Attride-Stirling’s (2001) [ 18 ] article on thematic network analysis for a step-by-step guide.

Textual analysis is commonly used in fields such as communication studies, literature, history, sociology, cultural studies, media studies, and more.

Real Textual Analysis Example

Study: “Making sense of “alternative”, “complementary”, “unconventional” and “integrative” medicine.”

This study analyzes the usage and evolution of terms like “alternative”, “complementary”, “unconventional” and “integrative” in medicine. It uses textual analysis by breaking down and examining the context, meaning, and usage of these terms in influential medical publications between 1970 and 2013 to understand their significance and implications in the discourse of unconventional medicine.

Citation: Ng, J. Y., Boon, H. S., Thompson, A. K., & Whitehead, C. R. (2016). Making sense of “alternative”, “complementary”, “unconventional” and “integrative” medicine: exploring the terms and meanings through a textual analysis.  BMC complementary and alternative medicine ,  16 (1), 1-18. ( Access Here )

See More Content Analysis Examples Here

14. Discourse Analysis

Discourse analysis is a qualitative research method used to analyze written, verbal, or sign language use or any significant semiotic event. It differs from textual analysis in its focus on the concept of emergent and dominant discourses , based on Foucauldian theory (Fairclough, 2013 [ 19 ] ).

The main purpose is to understand how language is used in real-life situations and uncover the social, cultural, and psychological structures that underlie the text or talk in its specific context (i.e. the discourses).

Discourse analysis considers language at several levels, such as sounds, words, sentences, speech acts, conversations, and narratives, and explores how these elements shape and are shaped by social practices, identities, relationships, and power dynamics.

It also looks beyond explicit meaning to explore implicit messages, underlying assumptions, and ideological standpoints that are conveyed through language.

This method is applied in a wide range of disciplines, including linguistics, psychology, sociology, anthropology, communication studies, and cognitive and cultural studies.

Real Discourse Analysis Example

Study: “How is Islam portrayed in western media? A critical discourse analysis perspective.”

How is Islam Portrayed in Western Media?  By Poorebrahim and Zarei (2013) represents a typical critical discourse analysis. This study combs through a corpus of western media texts to explore the language forms that are used in relation to Islam and Muslims, finding that they are overly stereotyped, which may represent anti-Islam bias or failure to understand the Islamic world.

Citation: Poorebrahim, F., & Zarei, G. (2013). How is Islam portrayed in western media? A critical discourse analysis perspective.  International Journal of Foreign Language Teaching and Research ,  1 (2), 57-75. ( Access Here )

See More Discourse Analysis Examples Here

15. Life History Research

Life history research is a qualitative methodology that focuses on understanding people’s lives and experiences through their personal narratives over a prolonged period, usually their entire life (Goodson & Sykes, 2016 [ 20 ] ) .

The objective is to gain in-depth insight into the subjective experiences, cultural contexts, identity development, decision-making processes, and changes over time.

Methods commonly used in life history research include interviews, diaries, photo elicitation or other artifacts, aiming to capture a rich, detailed, and holistic account of the person’s life (Goodson & Sykes, 2016 [ 20 ] ).

In interpreting the data, researchers pay attention to how the individual makes sense of their life trajectory, the pivotal moments, their relationships, and how historical and sociocultural contexts influence their life events and perceptions.

The life history method is suitable for research in diverse fields such as education, psychology, sociology, anthropology, and health sciences, particularly when studying themes like identity, resilience, transformation, and moral development over time.

Study: “The study of life history: Gandhi.”

The Study of Life History: Gandhi  by David Mandelbaum conducts a life history analysis of Gandhi by exploring his biographies and texts about his life. Through this analysis, Mandelbaum contextualized Gandhi’s life achievements and decisions in the banal experiences of fatherhood an nationhood, with an attempt to humanize the Indian hero and re-imagine his role in the development of modern India.

Citation: Mandelbaum, D. G. (1973). The study of life history: Gandhi.  Current anthropology ,  14 (3), 177-206. ( Access Here )

16. Semiotic Analysis

Semiotic analysis is like textual analysis, but has its own range of methods for examining how multimodal texts (images, video, movements) convey meaning in cultural contexts (Andersen et al., 2015 [ 21 ] ; Gualberto & Kress, 2019 [ 22 ] ).

The approach acknowledges that things (signs) can stand for something else and carry a particular meaning, especially within a social or cultural contexts.

So, this approach involves examining the signs and symbols that are used in various forms of communication, such as language, imagery, body language, music, and even things like fashion and food (Gualberto & Kress, 2019 [ 22 ] ).

The process of this method typically includes identifying the signs, exploring the system or code that organizes these signs (syntax), and interpreting how these signs work to inform or influence our ideas and beliefs (semantics).

By providing these insights, semiotic analysis helps researchers understand societal norms, cultural values , power relations, ideological beliefs, and more.

Study: “Visualizing teens and technology: A social semiotic analysis of stock photography and news media imagery.”

This study provides an analysis of how teenagers and their usage of digital media are visually represented in stock photography and news media imagery. Semiotic analysis is used to discern the meanings embedded in these visual representations and identify recurring patterns through the exploration of representational, compositional, and interpersonal meanings to uncover the underlying ideologies at play.

Citation: Thurlow, C., Aiello, G., & Portmann, L. (2020). Visualizing teens and technology: A social semiotic analysis of stock photography and news media imagery.  New media & society ,  22 (3), 528-549. ( Access Here )

Pros and Cons of Qualitative Research

Qualitative research offers a profound understanding of human behaviors , experiences, and the underlying factors driving these phenomena, which often cannot be achieved through quantitative methods.

By employing methods like in-depth interviews, focus groups, or ethnographic studies, most types of qualitative research allow for a detailed exploration of complex issues , providing rich, contextual insights (Bhattacharya, 2017 [ 2 ] ; Merriam & Tisdell, 2015 [ 23 ] ).

Furthermore, the flexible design of qualitative research enables researchers to adjust their approaches as new themes or patterns emerge during the study, allowing for a more nuanced understanding of the research topic.

However, one of the significant disadvantages of qualitative research is its potential for subjectivity (Hatch, 2023 [ 3 ] ; Weaver-Hightower, 2018 [ 24 ] ). The researcher’s perspectives and interactions with participants can influence the data collection and interpretation, possibly leading to biased or skewed findings.

Additionally, the inherent nature of qualitative research, which often relies on small, non-random samples, may result in findings that are not easily generalizable to a larger population (Bhattacharya, 2017 [ 2 ] ; Lapan, Quartaroli & Riemer, 2011 [ 4 ] ). This lack of generalizability can be a drawback when the goal is to make broader inferences or when comparing findings across different groups or settings.

The following table summarizes the pros and cons:

Read More about Qualitative Research Here

Before you Go

When doing qualitative research, you’ll need to know about qualitative variables. So, read my guide to qualitative variables next – it’ll help with writing your methodology section in your dissertation!

[1] Aurini, J. D., Heath, M., & Howells, S. (2021). The How To of Qualitative Research . SAGE Publications.

[2] Bhattacharya, K. (2017). Fundamentals of Qualitative Research: A Practical Guide . Taylor & Francis.

[3] Hatch, J. A. (2023). Doing Qualitative Research in Education Settings, Second Edition . State University of New York Press.

[4] Lapan, S. D., Quartaroli, M. T., & Riemer, F. J. (2011). Qualitative Research: An Introduction to Methods and Designs . Wiley.

[5] Atkinson, P. (2015). Grounded theory and the constant comparative method: Valid qualitative research strategies for educators.  Journal of Emerging Trends in Educational Research and Policy Studies, 6 (1), 83-86. ( Source )

[6] Mills, J., Bonner, A., & Francis, K. (2017). Adopting a Constructivist Approach to Grounded Theory: Implications for Research Design.  International Journal of Nursing Practice, 13 (2), 81-89. ( Source )

[7] Hammersley, M. (2018). What is ethnography? Can it survive? Should it?.  Ethnography and education ,  13 (1), 1-17. ( Source )

[8] Jones, J., & Smith, J. (2017). Ethnography: challenges and opportunities.  Evidence-Based Nursing ,  20 (4), 98-100. ( Source )

[9] Pretorius, L., & Cutri, J. (2019). Autoethnography: Researching personal experiences.  Wellbeing in doctoral education: Insights and guidance from the student experience , 27-34. ( Source )

[10] Neubauer, B. E., Witkop, C. T., & Varpio, L. (2019). How phenomenology can help us learn from the experiences of others.  Perspectives on medical education ,  8 , 90-97. ( Source )

[11] Zahavi, D. (2018).  Phenomenology: the basics . Routledge.

[12] McAlpine, L. (2016). Why might you use narrative methodology? A story about narrative.  Eesti Haridusteaduste Ajakiri. Estonian Journal of Education ,  4 (1), 32-57. ( Source )

[13] Jacobs, S. D. (2018). A history and analysis of the evolution of action and participatory action research.  The Canadian Journal of Action Research ,  19 (3), 34-52. ( Source )

[14] Guest, G., Namey, E., & McKenna, K. (2017). How many focus groups are enough? Building an evidence base for nonprobability sample sizes.  Field methods ,  29 (1), 3-22. ( Source )

[15] Kamberelis, G., & Dimitriadis, G. (2013). Focus Groups: From Structured Interviews to Collective Conversations . London: Routledge.

[16] Seim, J. (2021). Participant observation, observant participation, and hybrid ethnography.  Sociological Methods & Research , 0049124120986209. ( Source )

[17] Brady, S. R. (2015). Utilizing and adapting the Delphi method for use in qualitative research.  International Journal of Qualitative Methods ,  14 (5), 1609406915621381.

[18] Attride-Stirling, J. (2001). Thematic networks: an analytic tool for qualitative research.  Qualitative research ,  1 (3), 385-405.

[19] Fairclough, N. (2013).  Critical discourse analysis: The critical study of language . London: Routledge.

[20] Goodson, I., & Sikes, P. (2016). Techniques for doing life history. In  The Routledge international handbook on narrative and life history  (pp. 82-98). Routledge.

[21] Andersen, T. H., Boeriis, M., Maagerø, E., & Tonnessen, E. S. (2015).  Social semiotics: Key figures, new directions . Routledge.

[22] Gualberto, C., & Kress, G. (2019). Social semiotics.  The international encyclopedia of media literacy , 1-9.

[23] Merriam, S. B., & Tisdell, E. J. (2015). Qualitative Research: A Guide to Design and Implementation . Wiley.

[24] Weaver-Hightower, M. B. (2018). How to Write Qualitative Research . Taylor & Francis.

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  • Questionnaire Design | Methods, Question Types & Examples

Questionnaire Design | Methods, Question Types & Examples

Published on July 15, 2021 by Pritha Bhandari . Revised on June 22, 2023.

A questionnaire is a list of questions or items used to gather data from respondents about their attitudes, experiences, or opinions. Questionnaires can be used to collect quantitative and/or qualitative information.

Questionnaires are commonly used in market research as well as in the social and health sciences. For example, a company may ask for feedback about a recent customer service experience, or psychology researchers may investigate health risk perceptions using questionnaires.

Table of contents

Questionnaires vs. surveys, questionnaire methods, open-ended vs. closed-ended questions, question wording, question order, step-by-step guide to design, other interesting articles, frequently asked questions about questionnaire design.

A survey is a research method where you collect and analyze data from a group of people. A questionnaire is a specific tool or instrument for collecting the data.

Designing a questionnaire means creating valid and reliable questions that address your research objectives , placing them in a useful order, and selecting an appropriate method for administration.

But designing a questionnaire is only one component of survey research. Survey research also involves defining the population you’re interested in, choosing an appropriate sampling method , administering questionnaires, data cleansing and analysis, and interpretation.

Sampling is important in survey research because you’ll often aim to generalize your results to the population. Gather data from a sample that represents the range of views in the population for externally valid results. There will always be some differences between the population and the sample, but minimizing these will help you avoid several types of research bias , including sampling bias , ascertainment bias , and undercoverage bias .

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Questionnaires can be self-administered or researcher-administered . Self-administered questionnaires are more common because they are easy to implement and inexpensive, but researcher-administered questionnaires allow deeper insights.

Self-administered questionnaires

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or through mail. All questions are standardized so that all respondents receive the same questions with identical wording.

Self-administered questionnaires can be:

  • cost-effective
  • easy to administer for small and large groups
  • anonymous and suitable for sensitive topics

But they may also be:

  • unsuitable for people with limited literacy or verbal skills
  • susceptible to a nonresponse bias (most people invited may not complete the questionnaire)
  • biased towards people who volunteer because impersonal survey requests often go ignored.

Researcher-administered questionnaires

Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents.

Researcher-administered questionnaires can:

  • help you ensure the respondents are representative of your target audience
  • allow clarifications of ambiguous or unclear questions and answers
  • have high response rates because it’s harder to refuse an interview when personal attention is given to respondents

But researcher-administered questionnaires can be limiting in terms of resources. They are:

  • costly and time-consuming to perform
  • more difficult to analyze if you have qualitative responses
  • likely to contain experimenter bias or demand characteristics
  • likely to encourage social desirability bias in responses because of a lack of anonymity

Your questionnaire can include open-ended or closed-ended questions or a combination of both.

Using closed-ended questions limits your responses, while open-ended questions enable a broad range of answers. You’ll need to balance these considerations with your available time and resources.

Closed-ended questions

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. Closed-ended questions are best for collecting data on categorical or quantitative variables.

Categorical variables can be nominal or ordinal. Quantitative variables can be interval or ratio. Understanding the type of variable and level of measurement means you can perform appropriate statistical analyses for generalizable results.

Examples of closed-ended questions for different variables

Nominal variables include categories that can’t be ranked, such as race or ethnicity. This includes binary or dichotomous categories.

It’s best to include categories that cover all possible answers and are mutually exclusive. There should be no overlap between response items.

In binary or dichotomous questions, you’ll give respondents only two options to choose from.

White Black or African American American Indian or Alaska Native Asian Native Hawaiian or Other Pacific Islander

Ordinal variables include categories that can be ranked. Consider how wide or narrow a range you’ll include in your response items, and their relevance to your respondents.

Likert scale questions collect ordinal data using rating scales with 5 or 7 points.

When you have four or more Likert-type questions, you can treat the composite data as quantitative data on an interval scale . Intelligence tests, psychological scales, and personality inventories use multiple Likert-type questions to collect interval data.

With interval or ratio scales , you can apply strong statistical hypothesis tests to address your research aims.

Pros and cons of closed-ended questions

Well-designed closed-ended questions are easy to understand and can be answered quickly. However, you might still miss important answers that are relevant to respondents. An incomplete set of response items may force some respondents to pick the closest alternative to their true answer. These types of questions may also miss out on valuable detail.

To solve these problems, you can make questions partially closed-ended, and include an open-ended option where respondents can fill in their own answer.

Open-ended questions

Open-ended, or long-form, questions allow respondents to give answers in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered. For example, respondents may want to answer “multiracial” for the question on race rather than selecting from a restricted list.

  • How do you feel about open science?
  • How would you describe your personality?
  • In your opinion, what is the biggest obstacle for productivity in remote work?

Open-ended questions have a few downsides.

They require more time and effort from respondents, which may deter them from completing the questionnaire.

For researchers, understanding and summarizing responses to these questions can take a lot of time and resources. You’ll need to develop a systematic coding scheme to categorize answers, and you may also need to involve other researchers in data analysis for high reliability .

Question wording can influence your respondents’ answers, especially if the language is unclear, ambiguous, or biased. Good questions need to be understood by all respondents in the same way ( reliable ) and measure exactly what you’re interested in ( valid ).

Use clear language

You should design questions with your target audience in mind. Consider their familiarity with your questionnaire topics and language and tailor your questions to them.

For readability and clarity, avoid jargon or overly complex language. Don’t use double negatives because they can be harder to understand.

Use balanced framing

Respondents often answer in different ways depending on the question framing. Positive frames are interpreted as more neutral than negative frames and may encourage more socially desirable answers.

Use a mix of both positive and negative frames to avoid research bias , and ensure that your question wording is balanced wherever possible.

Unbalanced questions focus on only one side of an argument. Respondents may be less likely to oppose the question if it is framed in a particular direction. It’s best practice to provide a counter argument within the question as well.

Avoid leading questions

Leading questions guide respondents towards answering in specific ways, even if that’s not how they truly feel, by explicitly or implicitly providing them with extra information.

It’s best to keep your questions short and specific to your topic of interest.

  • The average daily work commute in the US takes 54.2 minutes and costs $29 per day. Since 2020, working from home has saved many employees time and money. Do you favor flexible work-from-home policies even after it’s safe to return to offices?
  • Experts agree that a well-balanced diet provides sufficient vitamins and minerals, and multivitamins and supplements are not necessary or effective. Do you agree or disagree that multivitamins are helpful for balanced nutrition?

Keep your questions focused

Ask about only one idea at a time and avoid double-barreled questions. Double-barreled questions ask about more than one item at a time, which can confuse respondents.

This question could be difficult to answer for respondents who feel strongly about the right to clean drinking water but not high-speed internet. They might only answer about the topic they feel passionate about or provide a neutral answer instead – but neither of these options capture their true answers.

Instead, you should ask two separate questions to gauge respondents’ opinions.

Strongly Agree Agree Undecided Disagree Strongly Disagree

Do you agree or disagree that the government should be responsible for providing high-speed internet to everyone?

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You can organize the questions logically, with a clear progression from simple to complex. Alternatively, you can randomize the question order between respondents.

Logical flow

Using a logical flow to your question order means starting with simple questions, such as behavioral or opinion questions, and ending with more complex, sensitive, or controversial questions.

The question order that you use can significantly affect the responses by priming them in specific directions. Question order effects, or context effects, occur when earlier questions influence the responses to later questions, reducing the validity of your questionnaire.

While demographic questions are usually unaffected by order effects, questions about opinions and attitudes are more susceptible to them.

  • How knowledgeable are you about Joe Biden’s executive orders in his first 100 days?
  • Are you satisfied or dissatisfied with the way Joe Biden is managing the economy?
  • Do you approve or disapprove of the way Joe Biden is handling his job as president?

It’s important to minimize order effects because they can be a source of systematic error or bias in your study.

Randomization

Randomization involves presenting individual respondents with the same questionnaire but with different question orders.

When you use randomization, order effects will be minimized in your dataset. But a randomized order may also make it harder for respondents to process your questionnaire. Some questions may need more cognitive effort, while others are easier to answer, so a random order could require more time or mental capacity for respondents to switch between questions.

Step 1: Define your goals and objectives

The first step of designing a questionnaire is determining your aims.

  • What topics or experiences are you studying?
  • What specifically do you want to find out?
  • Is a self-report questionnaire an appropriate tool for investigating this topic?

Once you’ve specified your research aims, you can operationalize your variables of interest into questionnaire items. Operationalizing concepts means turning them from abstract ideas into concrete measurements. Every question needs to address a defined need and have a clear purpose.

Step 2: Use questions that are suitable for your sample

Create appropriate questions by taking the perspective of your respondents. Consider their language proficiency and available time and energy when designing your questionnaire.

  • Are the respondents familiar with the language and terms used in your questions?
  • Would any of the questions insult, confuse, or embarrass them?
  • Do the response items for any closed-ended questions capture all possible answers?
  • Are the response items mutually exclusive?
  • Do the respondents have time to respond to open-ended questions?

Consider all possible options for responses to closed-ended questions. From a respondent’s perspective, a lack of response options reflecting their point of view or true answer may make them feel alienated or excluded. In turn, they’ll become disengaged or inattentive to the rest of the questionnaire.

Step 3: Decide on your questionnaire length and question order

Once you have your questions, make sure that the length and order of your questions are appropriate for your sample.

If respondents are not being incentivized or compensated, keep your questionnaire short and easy to answer. Otherwise, your sample may be biased with only highly motivated respondents completing the questionnaire.

Decide on your question order based on your aims and resources. Use a logical flow if your respondents have limited time or if you cannot randomize questions. Randomizing questions helps you avoid bias, but it can take more complex statistical analysis to interpret your data.

Step 4: Pretest your questionnaire

When you have a complete list of questions, you’ll need to pretest it to make sure what you’re asking is always clear and unambiguous. Pretesting helps you catch any errors or points of confusion before performing your study.

Ask friends, classmates, or members of your target audience to complete your questionnaire using the same method you’ll use for your research. Find out if any questions were particularly difficult to answer or if the directions were unclear or inconsistent, and make changes as necessary.

If you have the resources, running a pilot study will help you test the validity and reliability of your questionnaire. A pilot study is a practice run of the full study, and it includes sampling, data collection , and analysis. You can find out whether your procedures are unfeasible or susceptible to bias and make changes in time, but you can’t test a hypothesis with this type of study because it’s usually statistically underpowered .

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

  • Student’s  t -distribution
  • Normal distribution
  • Null and Alternative Hypotheses
  • Chi square tests
  • Confidence interval
  • Quartiles & Quantiles
  • Cluster sampling
  • Stratified sampling
  • Data cleansing
  • Reproducibility vs Replicability
  • Peer review
  • Prospective cohort study

Research bias

  • Implicit bias
  • Cognitive bias
  • Placebo effect
  • Hawthorne effect
  • Hindsight bias
  • Affect heuristic
  • Social desirability bias

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analyzing data from people using questionnaires.

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviors. It is made up of 4 or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with 5 or 7 possible responses, to capture their degree of agreement.

You can organize the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomization can minimize the bias from order effects.

Questionnaires can be self-administered or researcher-administered.

Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

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