qualitative research methods unstructured

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• v.17(6); 2019 Nov

The 3 Cs of Content, Context, and Concepts: A Practical Approach to Recording Unstructured Field Observations

Michael d. fetters.

1 Mixed Methods Program, Department of Family Medicine, University of Michigan Medical School, Ann Arbor, Michigan

Ellen B. Rubinstein

2 Department of Sociology and Anthropology, North Dakota State University, Fargo, North Dakota

Most primary care researchers lack a practical approach for including field observations in their studies, even though observations can offer important qualitative insights and provide a mechanism for documenting behaviors, events, and unexpected occurrences. We present an overview of unstructured field observations as a qualitative research method for analyzing material surroundings and social interactions. We then detail a practical approach to collecting and recording observational data through a “3 Cs” template of content, context, and concepts. To demonstrate how this method works in practice, we provide an example of a completed template and discuss the analytical approach used during a study on informed consent for research participation in the primary care setting of Qatar.

INTRODUCTION

Clinical observation is a method well known to primary care physicians. It is the rare physician who takes a patient’s words at face value without also using contextual clues, such as the patient’s appearance and behavior, to construct a picture of the patient’s health. 1 Indeed, medical education has recently highlighted the need for physicians to be more observant through innovative curricula that teach observational skills by examining art. 2 , 3

Field observations offer insight into behaviors and the environment 4 and can play an important role in primary care research. A decades-long history of observational research in primary care has demonstrated how contextual factors both in and out of the clinic influence the effectiveness of interventions, as well as clinical outcomes. 5 – 9 A recent commentary in JAMA Internal Medicine has called for more “ethnographic and field studies” to capitalize on the “value of direct observation,” particularly in studies of patient safety. 10 (p1024)

Unfortunately, most primary care researchers lack a practical approach for including field observations in their studies. Here, we present an overview of unstructured field observations as a qualitative research method for analyzing material surroundings and social interactions, aimed at researchers new to unstructured observations. We then detail a practical approach to collecting and recording observational data through a “3 Cs” template of content, context, and concepts. To demonstrate how this method works in practice, we provide an example of a completed template and discuss the analytical approach used during a study on informed consent for research participation in the primary care setting of Qatar.

Observational field research has its roots in the social sciences and is most often associated with participant observation fieldwork in cultural anthropology and sociology, though it has spread to disciplines as diverse as nursing, education, and social work. 11 Although he was not the first to undertake fieldwork, the Polish anthropologist Bronislaw Malinowski has been ascribed with popularizing participant observation as a research method. 12 Unlike structured interview sessions, participant observation allows for more flexible interactions with research participants through social events, casual conversations, and semi-structured interviews conducted in settings that are a natural part of participants’ everyday lives. 13 There is some debate as to how much a researcher should “participate” in daily activities, 12 but it is often enough simply “to be tolerated as an unobtrusive observer.” 14 (p195)

Malinowski’s work was influenced by the scientific positivism of the era, but later social scientists launched an antipositivist (interpretivist) critique that shifted the focus of observational research from a search for social facts to an understanding of cultural meanings. 15 We follow an interpretivist approach in believing the purpose of observational research is to arrive at what the anthropologist Clifford Geertz called “thick description.” 16 In a famous example, Geertz explains how the same action (a quick blink of the right eye) holds different meanings based on the cultural context in which it occurs. 16 Only in a specific context will a blink be recognized as a wink—a conspiratorial signal to a friend—rather than as a meaningless twitch of the eye. Thick description, then, uses empirical data from multiple sources to contextualize individual behavior and interpret its meaning.

A crucial assumption in participant observation is that the researcher is the instrument of data collection. 17 This assumption means all data are filtered through the researcher, through his or her personal characteristics, background, and experiences. 18 The result is a different relationship to objectivity than that found in the natural sciences. Observational research does not seek objectivity through a conceptual separation between researcher and study participants and phenomena. 19 Researchers are not blank slates; instead, they use prior knowledge and experiences as either implicit or explicit bases of comparison to understand what they observe in the field. 20 Personal bias is not seen as a flaw but as part of data collection. 12 Qualitative researchers speak of using bias to explore hunches or ideas, as well as to seek out information contrary to their own views. 21 It is critical before going into the field for researchers to conduct a personal inventory and reflect on their preconceptions, as these will affect their interpretation of events. 21

Researchers must also remain aware of potential differences in status between themselves and their study participants, where higher status may be conferred by socioeconomic, educational, occupational, or other types of privilege, or some combination thereof. 19 Such differences create a certain power dynamic between researchers and participants that can influence data collection. 19 A reflective activity, such as journaling or freewriting, can help define the researcher’s lens and help the researcher recognize how he or she may be perceived in the field. 22

RATIONALE FOR COLLECTING FIELD OBSERVATIONS

Perhaps the most compelling reason for conducting observations is to understand behavior ( Table 1 ). Studies have suggested that nonverbal behavior plays a considerable role in communicating shared cultural meanings. 23 Furthermore, emotions are communicated more through facial expression and vocal tone and inflection than through spoken word. 24 , 25 Finally, as it pertains to health research, individuals tend to underreport their unhealthy or socially undesirable behaviors 26 , 27 and overreport the converse. 28 Observational research thus contributes to understanding human behavior in all of these scenarios.

Reasons for Conducting Observations in Primary Care Research, With Clinical Examples

Reasons to Observe	Clinical Examples
To understand behavior	Describe whether or how staff follow clinical guidelines or study protocols
To understand context	Understand environmental factors influencing uptake of an intervention
To understand process	Examine at baseline how clinical preventive services are delivered in offices
To recognize patterns	Examine variations in how clinical preventive services are implemented across multiple practices
To see what people are reluctant to discuss	Identify perceived cultural taboos, for example, parents reluctant to discuss HPV vaccination for prepubertal children
To gain direct personal experience and knowledge	Explore patient experiences of undergoing clinical procedures, for example, the experience of colonoscopy preparation
To move beyond selected perceptions	Observe how patients respond to universal screening questions, for example, depression screening, intimate personal violence screening

HPV = human papillomavirus.

Field observations can help researchers understand how the interactions and activities in a given setting inform behaviors and beliefs ( Table 1 ). 29 They contribute to uncovering the broader context of a given scenario, making observational research especially well suited for studying process. 19 In primary care, for example, observational research has deepened understanding of the clinical contexts in which practice transformation to patient-centered medical homes has occurred. 30 – 36 Field observations have also helped contextualize the (quantitative) results of randomized controlled trials, by providing insight into why certain randomized controlled trials have succeeded or failed. 9 , 37

Thus, field observations allow researchers to move beyond selected perceptions and protocols, and better understand the nature of particular activities, who performs them, and the contexts in which they occur.

Observational research may not always be appropriate, and under certain circumstances, participants will not tolerate an observer ( Table 2 ). Individuals who engage in socially undesirable or illegal behavior may be reluctant to have an observer present or be at risk personally 12 (although the opposite might also be true 38 ). Sometimes the presence of an observer might change participants’ behavior, a phenomenon known as the Hawthorne effect. 39 Research has shown this effect may not be as great as feared, 40 however, and multiple observations over the long term can be a mitigating factor. 29

Potential Reasons for Not Conducting Unstructured Observations in Primary Care Research, With Clinical Examples

Potential Reasons
Not to Observe	Clinical Examples
Research participants will not tolerate an observer	Research on illicit behaviors, such as drug abuse, or sexual practices relative to use of barrier devices or contraceptives
Participants will change	Possible change in adolescent bullying behaviors in presence
behavior if observer is present (Hawthorne effect )	of observer; altered communication behaviors of couples dealing with interpersonal violence; compromising of therapeutic rapport with the added presence of a stranger
Research will compromise participant decency, privacy	Research on physician-patient-family interactions that involves clinical examination of private areas; for example, breast, pelvic, male genital, rectal examinations may not be tolerable
Reporting observations would be stigmatizing or unethical	Risks of stigmatization, which are present for any socially marginalized population

UNSTRUCTURED AND STRUCTURED FIELD OBSERVATIONS

A central tenet of observational research is that observations must be recorded to count as data, 12 and it is only through the regular and systematic recording of field observations that researchers create texts for subsequent analysis. 41 Field observations can be structured, unstructured, or a combination of both. Structured observations use a template to record tabulations of specific behaviors that can be measured and analyzed statistically. 42 These observations often focus on highly specific issues and are indicated when the intent is to validly and reliably measure specific behaviors. Unstructured observational data use the researcher’s words for thick description of phenomena or events. These words emerge through the researcher’s experience in the field. 43 Even though unstructured, the observations are still focused because they address a research question or specific phenomenon. Within that focus, there is great latitude in what the researcher can choose to record ( Table 3 ).

The 3 Cs—Context, Content, and Concepts—Approach to Field Observations

Category	Definition	Focus
Context	The circumstances (both material and theoretical) under which observations are being conducted, as well as any historical, sociocultural, political, and other information that may directly (or indirectly) influence data collection	Who is there as observer?
		What is your reason for being there?
		Why this location?
		What is your state of mind (eg, confused, unhappy, tired, excited)?
		What are your key areas of (observational) interest based on your prior research experience and/or scholarly background?
Content	The matter or substance of what happened	Who are the participants? How are they related, if at all (eg, physicians and patients, work colleagues, friends or family members, cancer survivors)?
		How do participants interact?
		What actions/events are occurring?
		What is the timing/sequence of events?
		What quotes best capture the exchange that occurred?
Concepts	The larger theoretical context to which observations connect, either as evidence of or refutation of theory; theoretical insights that emerge from observations (as in grounded theory); directions for future research	What have you learned that you did not know before?
		Does this observation help support or refute your hypothesis/expectations?
		How is this observation related to prior observations or to your reading of the scholarly literature?
		What are some potential implications of what you have observed?
		What new questions (research or otherwise) arise from this observation?
		How do participants respond to the presence of an observer? (Are they excited, anxious, skeptical, wary, etc?)
		What historical or current events may influence this response?

To illustrate the potential of field observations, we introduce a study that relied heavily on observational data supplemented by interviews. The first author (M.D.F.) served as co–principal investigator on a multistage, mixed methods parent study in Qatar to develop a health care quality assessment instrument that was adapted for populations whose native languages were Arabic, English, Hindi, and Urdu. 44 A theoretical model, Cultural Construction of Clinical Reality developed by Kleinman et al, 45 guided the research. During the first stage of qualitative data collection, Qatari team members expressed concern about how potential participants would respond to recruitment strategies dictated by US–based institutional review boards. Existing literature had little guidance for recruiting participants in Arabian Gulf countries. We therefore conducted a study to explore how individuals in Qatar responded to in-person recruitment requests. 46 The 3 Cs template emerged from the need for institutional review board approval of data collection instruments and as a training instrument for research assistants.

THE 3 CS UNSTRUCTURED FIELD OBSERVATIONS TEMPLATE

The 3 Cs template provides an easy approach to collecting observational data. A full 3 Cs template (Supplemental Appendix 1, available at http://www.AnnFamMed.org/content/17/6/554/suppl/DC1/ ) includes the study metadata (details about the project), the research question, and the 3 Cs of context, content, and concepts.

Field Observation Metadata

The study metadata include information such as the project title, the study document type, the observer, the date and time, the location, and a participant description (eg, ID, descriptor if multiple individuals). The metadata from a single observation collected during the Qatar recruitment study are given in Supplemental Appendix 2, available at http://www.AnnFamMed.org/content/17/6/554/suppl/DC1/ . Additional information here included the language spoken by the researcher and participant.

Research Question

The research question keeps observations focused on the purpose of the study. Because there is bound to be individual variation in data collection (recalling that the researcher is the instrument of data collection), including the question on the template provides a focal point for recording details. As illustrated in Supplemental Appendix 2, there were both primary and secondary research questions for researchers to address.

Context, Content, and Concepts

The context, content, and concepts are summarized in Table 3 and explained in further detail below.

The first C, context, has a dual meaning: its most immediate referent is the circumstances in which the researcher is making observations (eg, who is doing the observation, where, and when). In a broader sense, context also refers to the researcher’s (or team’s) prior research experience, and could include knowledge gained from reading the scholarly literature, and additional information about a population, organization, or community—anything that speaks to the social surroundings and recent events that may influence the present interaction. 47 Context can act as a reminder of the researcher’s purpose in using observational methods—and may also include information about the researcher’s introduction to the field (eg, “invited by Dr A to observe her clinic” or “clinic recruited through practice manager”). Visuals, including sketches or photographs (if possible), may be useful, especially if certain structural features stand out (eg, small vs large waiting room; front staff behind an open desk vs behind a glass partition). This information can enable quick and easy comparisons between multiple locations.

The second C, content, is more focused than context, as it refers directly to what happens during the observation period. (We recommend that researchers record each observation period on a separate template, creating multiple shorter documents, for each episode of observing, rather than in a single long document, for later analysis.) Although observational research is often touted as holistic—that is, covering everything within the 5 senses during a given stretch of time—in truth, researchers continually make decisions about where to point their focus. The research question and the project’s theoretical orientation (the research questions, and the first C, context, described previously) are paramount here in guiding the observations.

The third C, concepts, is a space for the researcher to connect the minutiae of his or her field observations with the bigger picture, to think back to the research question or hypothesis and compare theory with practice. It can be used to reflect about the process of research, or procedural or ethical questions that arise in the field. It is a space for nascent analysis, where the researcher can try out new ideas based on insights gained in the field. Researchers may take note of emergent patterns or themes (as in grounded theory 48 ), may reflect on their experience in the field, or both. In this way, the third C provides a sort of running commentary on the field observations, which serves both as the foundation for later analysis and as an audit trail that demonstrates how observation, data collection, theory, and analysis are all intertwined. 15

USING THE 3 CS APPROACH IN THE FIELD

Recording field jottings.

There is never enough time in the field to write down everything one observes. Indeed, recording observations becomes even more difficult when the researcher participates in ongoing activities by, for example, engaging in conversation, directing a lost patient to the exit, or lending a hand to set up for a meeting. Furthermore, most of the time, a field researcher does not bring a computer into the field but rather relies on pen and paper, the latter being less obtrusive and easier to manage (although that has changed with the advent of smartphones and tablets). Generally speaking, therefore, no one writes actual field notes in the field. Rather, they capture field jottings—words, phrases, or drawings to jog their memories after the fact. 41 In the Qatar recruitment study, 46 the research assistants used a printed 3 Cs template for jotting down ideas as they occurred.

Expanding on Field Jottings

After leaving the field site, the observer has the opportunity to construct, from field jottings, a more extensive record of what was observed. 29 It is important to write these expanded field notes as soon as possible after the observation session (hours, not days, later); the more time that passes, the greater chance that the researcher will recall fewer details. A first pass should focus on writing descriptive text focusing on the “what” and “how” while avoiding summative or generalizing statements. The best field notes are rich with details that convey a sense of what it is like to be in the time and space described (ie, thick description). Expanded and edited notes can be found in Supplemental Appendix 2.

Working With a Research Team and Analyzing the Data

Primary care research is typically team based. The 3 Cs approach to field observations can facilitate iterative data collection and analysis. Field notes should be shared among team members both to encourage the entire team’s familiarity with the field and to identify salient points for future data collection and pattern recognition. The first few observational sessions should be the most detailed, as this is when the researcher is least familiar with the field. 15 Of course, not all details will ultimately prove relevant, but they can act as a starting point for more refined observations later on. Furthermore, after the researcher begins to recognize what counts as the norm in a given setting, he or she can then more easily identify deviations from that norm. Such surprises in the field can lead to unexpected insights that generate new directions for future research.

Field notes can be analyzed like any other qualitative text by, for example, searching for key words and coding for thematic content. Even if they are not formally analyzed, field notes may provide important context for understanding data derived from (time-limited) interviews and surveys. In the Qatar recruitment study, 46 the team conducted iterative analysis of the textual data from field observations and interviews, which led to the creation of a coding scheme in Atlas. ti (ATLAS.ti Scientific Software Development GmbH). The team also integrated numerical data from the demographic instrument and recruitment procedures, to create a narrative format for the results.

Finishing Field Observations in a Study

A final consideration is when to end the observational period or series. One possibility is to have a predetermined end point. In the Qatar recruitment study, 46 field observations continued until the study recruitment goals were met. An alternative is to seek data saturation. Guidelines for determining the saturation point in qualitative research vary, although a recent review calls for saturation to be operationalized in terms of research question(s), theoretical framework, and analytical goals. 49

Field observations are paramount in understanding contextual factors in any research project and have the potential to reveal important insights about the way actors and institutions work in a given place and time. Observational research is inductive and iterative, 15 and its greatest strength is its open-endedness. Because the researcher does not work in a controlled environment or with a standardized checklist or questionnaire, he or she is able to capture any data that do not fit into a priori categories. In such a setting, the research question serves as a guide, not a mandate, and it leaves room to address unexpected occurrences.

Although the 3 Cs template provides an excellent entrée for the use of field observations, there are other observational alternatives. Structured observations may be better indicated for inquiry exploring systematically the nature and metrics of phenomena, with integration across multiple observers for the purpose of statistical analysis. Another option is video recording, which yields multiple data sources, such as verbal, paraverbal, and nonverbal responses, and requires specific levels of skills and techniques for analysis. 50

The 3 Cs approach to unstructured field observations can be used when observation is the primary research method 46 or in tandem with another research method, such as qualitative interviews. 51 In the Qatar recruitment study, the observations were conducted more with the intent of being supplemental, but ultimately served as the primary source for a specific publication. 46 The template, which can be submitted for institutional review board approval, provides a straightforward mechanism for recording events and behaviors in almost any project involving human participants. As mixed methods gain increasing popularity in health services research, 52 unstructured field observations can play an important role in contextualizing other types of qualitative and quantitative data, resulting in more rigorous research designs and data collection.

Conflicts of interest: authors report none.

To read or post commentaries in response to this article, see it online at http://www.AnnFamMed.org/content/17/6/554 .

Previous presentations: Portions of the content of this article were presented at the 2012 North American Primary Care Research Group (NAPCRG) Annual Meeting; December 1-5, 2012; New Orleans, Louisiana; and at the 2013 NAPCRG Annual Meeting; November 9-13, 2013; Ottawa, Canada.

Supplemental Materials: Available at http://www.AnnFamMed.org/content/17/6/554/suppl/DC1/ .

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	© RWJF 2008 P.O. Box 2316 College Road East and Route 1 Princeton, NJ 08543	-->Citation: Cohen D, Crabtree B. "Qualitative Research Guidelines Project." July 2006.

Unstructured Interviews: When and How to Use Them

Introduction

Structured and unstructured interviews, the pros and cons of unstructured interviews, when would you use unstructured interviews, the unstructured interview process.

Of the three types of interviews in qualitative research , the unstructured interview is the most free-flowing. It provides the greatest flexibility in gathering participants' answers in a social interaction that resembles a natural conversation. While all interviews involve collecting data in the form of the respondents' own words as they answer the interviewer's questions, the unstructured interview offers researchers the most freedom to explore participants' responses as deeply as they need to meet their research objectives .

In this article, we will look at what researchers do to plan , conduct, and analyze unstructured interviews in qualitative studies.

An unstructured interview (sometimes known as a non-directive interview) stands in contrast to a structured interview . Structured interviews have a rigid protocol that includes a set of predetermined questions. The interviewer asks the same questions to all participants so they can have neatly organized and comparable data across participants.

Structured interviews are ideal when researchers have a clear notion of which questions should be asked and there is no need to stay open to exploring other potential directions which participants might bring up. Unstructured interviews, on the other hand, permit researchers to ask spontaneous probing questions to gain deeper understanding of unexpected things that could emerge during the interview.

Unstructured interview definition

An unstructured interview is a free-flowing conversation between a researcher and participant. The interviewer has a broad research question that guides their interest in conducting the interview , but the interview questions are not decided beforehand. Rather, the researcher poses questions to the participant in the moment, depending on the flow of the conversation.

Researchers who employ unstructured interviews acknowledge that each respondent will have different insights that can only be uncovered by asking questions tailored to each individual they interview. Unstructured interview questions are then determined over the course of the interview as researcher and respondent interact with each other. This allows the researcher to collect open-ended data and take advantage of opportunities that arise to probe further into respondents' perspectives or experiences about key topics or phenomena.

Keep in mind that a semi-structured interview can be a good compromise between structured and unstructured interviews. If you need the flexibility of a natural conversation setting and the structure provided by a set of predetermined questions, then semi-structured interviews might be the best option for your research.

The strategy that you adopt for conducting interviews is going to depend on the research questions in your study as well as the particular circumstances of the research context and interview respondents. Let's look at some of the key advantages and disadvantages of unstructured interviews.

Advantages of unstructured interviews

In a nutshell, an unstructured interview is an open-ended interaction that can move in any direction that arises as the researcher and participant engage in the conversation. To be sure, the interviewer has a set research objective in mind when conducting the interview. However, unstructured interviews have a natural flow and give interview respondents agency over the interaction. In situations where respondents feel they can control the interaction, they may be more open to providing more in-depth answers to interview questions.

As a result, the data collected from an unstructured interview can allow the researcher to dig deeper into the perspectives of respondents. The depth of the knowledge gained from unstructured interviews can prove valuable in gaining an insider perspective of social customs and cultural practices, especially when there is limited current understanding or theory that could meaningfully inform what kinds of questions are worth asking.

Disadvantages of unstructured interviews

Unstructured interviews flow in different and, oftentimes, unanticipated directions, which can pose challenges when it comes to analyzing all the data and making comparisons across participants. For example, each participant you interview may focus on different aspects of the phenomenon you are studying. While each of these aspects can contribute meaningful understanding to your phenomenon, integrating all these different perspectives into a coherent theory or story might be difficult.

On the other hand, since unstructured interviews can move in unexpected directions, there is also the risk that the interviewer loses the thread of an important research topic or the conversation explores unrelated tangents. Researchers should take care to balance the need for the interview to flow naturally and the objective of gathering valuable information from respondents.

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It is important to conduct interviews that are more suitable to your particular study and research objectives . This section looks at some of the considerations that you should keep in mind when deciding if an unstructured interview is best for your research.

Thick description through interviews

Unstructured interviews are best suited for exploratory research that adopts an inductive approach to developing theory. If the goal of your research is to establish a deep understanding of a culture or custom where there is insufficient theoretical development , then your study can engage in a concept known as thick description, which involves exploring the respondent's answers to grasp the nuances and interpretations of a particular social concept.

Matching research question to interview type

The influence of the interviewer plays a major role in using unstructured interviews. Think about an interview study that explores sensitive topics like hospice care or migrant work. A structured interview or even a semi-structured interview might not be the most appropriate form of interview when you are trying to gain the respondent's trust. After all, direct questions on controversial issues can make people hesitant to provide open, detailed answers.

If a prerequisite to collecting a respondent's answers is to establish rapport, then you could consider using interviews that don't rely on standardized questions to collect data . The flow of an unstructured interview has the potential to make the interview respondent comfortable with the interviewer, who can then judge in the moment of data collection when to ask probing questions or focus on building rapport.

When to consider other interview types

Structured interviews and semi-structured interviews offer more rigidity in terms of asking a set of predetermined questions. In cases where you have a collection of questions you want to ask, semi-structured interviews can be used to ask these same questions to all participants while remaining open to asking additional questions if the need arises. If you already know exactly which questions you want to ask and it is important to gather consistent data from all participants to aid subsequent comparisons, structured interviews can be the most appropriate approach.

Although unstructured interviews do not follow a predetermined flow, they also do not consist of simply talking with a respondent. In other words, unstructured interviews also depend on a clear research methodology . Indeed, as unrehearsed as they may seem, unstructured interviews are still an intentional research tool designed to collect data in a deliberate and rigorous manner. In this section, we'll look at the various stages of an unstructured interview study from design to research reporting .

Interview study design

As mentioned previously, the manner in which you conduct unstructured interviews depends on your research questions and interview respondents. If you are looking to explore a particular topic, it's important to define the object of inquiry as clearly as possible. What does existing scholarship say about the cultural practice you are looking to study? What is it about your given social phenomenon that you are trying to understand? Should your study look at the decisions people make about that phenomenon, the thinking behind it, or something else?

While an unstructured interview does not necessarily have a standardized set of questions to ask respondents, an interviewer should always have a set of topics in mind that are worth exploring. While there shouldn't be a set order to interview questions in an unstructured format, it benefits the interviewer to have a defined set of objectives to meet over the course of an interview.

The affective dimensions of an unstructured interview study are also important when considering how to conduct interviews . The unstructured format allows the researcher to decide when to be more direct or conservative in their questioning, depending on how open they think the respondent is in answering questions. When establishing who your respondents are and how they are likely to interact with you, you can make intentional and informed decisions about how to make the best of the conversational nature of unstructured interviews.

Conducting unstructured interviews

The data collection stage of an unstructured interview study can be the most fraught (and most interesting!) part of the research process. Without set questions in mind, the interview can explore any part of the respondent's experience or perspective that emerges. In an interaction that resembles an everyday conversation, it is up to the interviewer to successfully navigate a dynamic and fluid social situation to elicit valuable information from the respondent.

The general goal when conducting unstructured interviews is to encourage the respondent to craft as detailed a narrative as possible on the topic of interest. The interviewer's rapport with the respondent and the comfort level respondents have when the interviewer asks questions are crucial to eliciting relevant information in comprehensive detail. Direct questions have the potential to gather the more pertinent details, but it is also important to avoid leading questions that encourage socially desirable responses (e.g., "You've never shoplifted before, right?"). It is also helpful to begin with simpler questions to build rapport before moving on to potentially more sensitive questions. The interviewer should take care to balance the questions they ask to respondents depending on their relationship with them.

Reflecting on unstructured interviews

Because of the unrestricted nature of unstructured interviews, you have a lot of space to reflect on and make changes to your interview strategy as you interview further respondents. Perhaps you discovered there is a particular form of questioning that is more conducive to collecting rich answers from your respondents. Or maybe there is a certain topic that turned out to be more controversial or taboo than you first thought.

Because you are not bound to ask a predetermined set of questions in an unstructured interview format, you can benefit from reflecting on past data collection to inform future data collection as your study progresses. Utilize this opportunity to maximize the interview strategies that worked best and reconsider those that didn't work out. Ultimately, the goal of this reflection is to capture the richest data possible to generate a meaningful analysis.

How to analyze unstructured interviews

As you conduct interviews, you can simultaneously engage in data analysis . Your reflections of ongoing data collection will bring to mind key themes and preliminary insights that can inform subsequent data collection and analysis. Your notes during and after interviews can form the basis of a set of themes and topics that you can use to code your interview data. You can thus create a list of preliminary codes to guide your initial analysis, but you can still remain open to creating additional codes as you delve deeper into your analysis process.

Typically, interview data is transcribed so the researcher can comfortably search and segment the text for important phrases and meaningful insights. Working with interview transcriptions also makes it easier to manage all your data and draw connections across your different participants. That being said, with qualitative data analysis software such as ATLAS.ti, you can analyze both multimedia recordings and transcripts, and you can even sync the two together so you can fluidly move between the raw recording and the transcribed text.

The objective of data analysis is usually to explore and understand patterns across interview respondents. You might identify an interesting anecdote from one respondent or observe commonalities that are shared across multiple respondents.

You can choose the coding strategy that best suits your research question as you look at your interviews. For example, a thematic analysis can be followed to explore shared perspectives or experiences across respondents. Or, if you want to understand and compare how participants talk about the phenomenon you are studying, you can employ discursive coding to analyze how participants build their stories.

There are many coding approaches you can choose from, but it is always important to be systematic and transparent to persuade your research audience of the key insights in your interview data. As the name suggests, unstructured interviews are among the least predictable and most dynamic methods of qualitative research , so it is up to the researcher to develop a carefully crafted research study to identify key insights in an empirical manner.

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The decision to conduct interviews, and the type of interviewing to use, should flow from, or align with, the methodological paradigm chosen for your study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these).

• Structured Interview. Entry in The SAGE Encyclopedia of Social Science Research Methodsby Floyd J. Fowler Jr., Editors: Michael S. Lewis-Beck; Alan E. Bryman; Tim Futing Liao (Editor)  A concise article noting standards, procedures, and recommendations for developing and testing structured interviews. For an example of structured interview questions, you may view the Current Population Survey, May 2008: Public Participation in the Arts Supplement (ICPSR 29641), Apr 15, 2011 at https://doi.org/10.3886/ICPSR29641.v1 (To see the survey questions, preview the user guide, which can be found under the "Data and Documentation" tab. Then, look for page 177 (attachment 8).

Semi-Structured

• Semi-Structured Interview. Entry in The SAGE Encyclopedia of Qualitative Research Methodsby Lioness Ayres; Editor: Lisa M. Given  The semi-structured interview is a qualitative data collection strategy in which the researcher asks informants a series of predetermined but open-ended questions. The researcher has more control over the topics of the interview than in unstructured interviews, but in contrast to structured interviews or questionnaires that use closed questions, there is no fixed range of responses to each question.

Unstructured

• Unstructured Interview. Entry in The SAGE Encyclopedia of Qualitative Research Methodsby Michael W. Firmin; Editor: Lisa M. Given  Unstructured interviews in qualitative research involve asking relatively open-ended questions of research participants in order to discover their percepts on the topic of interest. Interviews, in general, are a foundational means of collecting data when using qualitative research methods. They are designed to draw from the interviewee constructs embedded in his or her thinking and rationale for decision making. The researcher uses an inductive method in data gathering, regardless of whether the interview method is open, structured, or semi-structured. That is, the researcher does not wish to superimpose his or her own viewpoints onto the person being interviewed. Rather, inductively, the researcher wishes to understand the participant's perceptions, helping him or her to articulate percepts such that they will be understood clearly by the journal reader.

Focus Groups

• "Focus Groups." Annual Review of Sociology 22 (1996): 129-1524.by David L. Morgan  Discusses the use of focus groups and group interviews as methods for gathering qualitative data used by sociologists and other academic and applied researchers. Focus groups are recommended for giving voice to marginalized groups and revealing the group effect on opinion formation.  
• Qualitative Research Methods: A Data Collector's Field Guide (See Module 4: "Focus Groups")by Mack, N., et al.  This field guide is based on an approach to doing team-based, collaborative qualitative research that has repeatedly proven successful in research projects sponsored by Family Health International (FHI) throughout the developing world. With its straightforward delivery of information on the main qualitative methods being used in public health research today, the guide speaks to the need for simple yet effective instruction on how to do systematic and ethically sound qualitative research. The aim of the guide is thus practical. In bypassing extensive discussion on the theoretical underpinnings of qualitative research, it distinguishes itself as a how-to guide to be used in the field.

In-Depth Interviews

• A Practical Introduction to in-Depth Interviewing by Alan Morris  Are you new to qualitative research or a bit rusty and in need of some inspiration? Are you doing a research project involving in-depth interviews? Are you nervous about carrying out your interviews? This book will help you complete your qualitative research project by providing a nuts and bolts introduction to interviewing. With coverage of ethics, preparation strategies and advice for handling the unexpected in the field, this handy guide will help you get to grips with the basics of interviewing before embarking on your research. While recognising that your research question and the context of your research will drive your approach to interviewing, this book provides practical advice often skipped in traditional methods textbooks.  
• Qualitative Research Methods: A Data Collector's Field Guide (See Module 3: "In-Depth Interviews") by Mack, N., et al.  This field guide is based on an approach to doing team-based, collaborative qualitative research that has repeatedly proven successful in research projects sponsored by Family Health International (FHI) throughout the developing world. With its straightforward delivery of information on the main qualitative methods being used in public health research today, the guide speaks to the need for simple yet effective instruction on how to do systematic and ethically sound qualitative research. The aim of the guide is thus practical. In bypassing extensive discussion on the theoretical underpinnings of qualitative research, it distinguishes itself as a how-to guide to be used in the field.

An interdisciplinary scientific program within the Institute for Quantitative Social Science which encourages and facilitates research and instruction in the theory and practice of survey research. The primary mission of PSR is to provide survey research resources to enhance the quality of teaching and research at Harvard.

• Internet, Phone, Mail, and Mixed-Mode Surveysby Don A. Dillman; Jolene D. Smyth; Leah Melani Christian  The classic survey design reference, updated for the digital age. The new edition is thoroughly updated and revised, and covers all aspects of survey research. It features expanded coverage of mobile phones, tablets, and the use of do-it-yourself surveys, and Dillman's unique Tailored Design Method is also thoroughly explained. This new edition is complemented by copious examples within the text and accompanying website. It includes: Strategies and tactics for determining the needs of a given survey, how to design it, and how to effectively administer it. How and when to use mail, telephone, and Internet surveys to maximum advantage. Proven techniques to increase response rates. Guidance on how to obtain high-quality feedback from mail, electronic, and other self-administered surveys. Direction on how to construct effective questionnaires, including considerations of layout. The effects of sponsorship on the response rates of surveys. Use of capabilities provided by newly mass-used media: interactivity, presentation of aural and visual stimuli. The Fourth Edition reintroduces the telephone--including coordinating land and mobile.
• The Ethnographic Interview by James P. Spradley  “Spradley wrote this book for the professional and student who have never done ethnographic fieldwork (p. 231) and for the professional ethnographer who is interested in adapting the author’s procedures (p. iv). Part 1 outlines in 3 chapters Spradley’s version of ethnographic research, and it provides the background for Part 2 which consists of 12 guided steps (chapters) ranging from locating and interviewing an informant to writing an ethnography. Most of the examples come from the author’s own fieldwork among U.S. subcultures . . . Steps 6 and 8 explain lucidly how to construct a domain and a taxonomic analysis” (excerpted from book review by James D. Sexton, 1980).  
• Fundamentals of Qualitative Research by Johnny Saldana (Series edited by Patricia Leavy)  Provides a soup-to-nuts overview of the qualitative data collection process, including interviewing, participant observation, and other methods.  
• Companion website to Bloomberg and Volpe's  Completing Your Qualitative Dissertation: A Road Map from Beginning to End,  4th ed Provides helpful templates and appendices featured in the book, as well as links to other useful dissertation resources.
• American Folklife Center at the Library of Congress. Folklife and Fieldwork: A Layman’s Introduction to Field Techniques Interviews gathered for purposes of folklore research are similar to standard social science interviews in some ways, but also have a good deal in common with oral history approaches to interviewing. The focus in a folklore research interview is on documenting and trying to understand the interviewee's way of life relative to a culture or subculture you are studying. This guide includes helpful advice and tips for conducting fieldwork in folklore, such as tips for planning, conducting, recording, and archiving interviews.
• American Folklife Center at the Library of Congress. Oral History Interviews Recommendations for planning an oral history project and tips for conducting interviews
• Oral History Research Guide, Harvard Library Consult this guide to access methodological handbooks and guides for oral history, selected projects, Harvard Library research guides for oral history, oral history collections at and beyond Harvard, and scholarship and commentary on oral history methodology.
• Indigenous Studies: Oral History Provides helpful information and resources to inform respectful understanding and citation of Indigenous oral histories.
• Oral History Association: Principles and Best Practices An invaluable document for maintaining an ethical stance as a researcher, with guidance on archiving interviews and managing rights/copyright.
• Oral History Methodology (Hajek A., 2014) The case study starts with a historical outline of the advent of oral history research in Western society, its strengths and its weaknesses, before it moves to a practical exploration of oral history methodology. It explains how to set up an oral history project, how to conduct interviews and what legal concerns to keep in mind. It also provides details on recording equipment and discusses a number of potential outputs of oral history data.
• The Oral History Reader (edited by Perks, R. and Thomson, A., 2015)   A comprehensive, international anthology combining major classic articles with cutting-edge pieces on the theory, method and use of oral history.
• Webinar: Introduction to Oral History and Interviewing , Centre for Oral History and Digital Storytelling, Concordia University

Research Site Selection

• Research interviews are used not only to furnish research data for theoretical analysis in the social sciences, but also to plan other kinds of studies. For example, interviews may allow researchers to screen appropriate research sites to conduct empirical studies (such as randomized controlled trials) in a variety of fields, from medicine to law. In contrast to interviews conducted in the course of social research, such interviews do not typically serve as the data for final analysis and publication.

UX at Harvard Library

• User Experience and Market Research interviews can inform the design of tangible products and services through responsive, outcome-driven insights. The  User Research Center  at Harvard Library specializes in this kind of user-centered design, digital accessibility, and testing. They also offer guidance and  resources  to members of the Harvard Community who are interested in learning more about UX methods. Contact [email protected] or consult the URC website for more information.
• User Interviews: The Beginner’s Guide (Chris Mears)
• Interviewing Users (Jakob Nielsen)
• Interviewing Users: How to Uncover Compelling Insights by Steve Portigal; Grant McCracken (Foreword by)  Interviewing is a foundational user research tool that people assume they already possess. Everyone can ask questions, right? Unfortunately, that's not the case. Interviewing Users provides invaluable interviewing techniques and tools that enable you to conduct informative interviews with anyone. You'll move from simply gathering data to uncovering powerful insights about people.
• Rapid Contextual Design by Jessamyn Wendell; Karen Holtzblatt; Shelley Wood  This handbook introduces Rapid CD, a fast-paced, adaptive form of Contextual Design. Rapid CD is a hands-on guide for anyone who needs practical guidance on how to use the Contextual Design process and adapt it to tactical projects with tight timelines and resources. Rapid Contextual Design provides detailed suggestions on structuring the project and customer interviews, conducting interviews, and running interpretation sessions. The handbook walks you step-by-step through organizing the data so you can see your key issues, along with visioning new solutions, storyboarding to work out the details, and paper prototype interviewing to iterate the design all with as little as a two-person team with only a few weeks to spare *Includes real project examples with actual customer data that illustrate how a CD project actually works.

• << Previous: Interview Research
• Next: Recruiting & Engaging Participants >>

Except where otherwise noted, this work is subject to a Creative Commons Attribution 4.0 International License , which allows anyone to share and adapt our material as long as proper attribution is given. For details and exceptions, see the Harvard Library Copyright Policy ©2021 Presidents and Fellows of Harvard College.

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• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on June 19, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Qualitative research involves collecting and analyzing 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 analyzing 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, history, etc.

• 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 organization?
• 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, other interesting articles, 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 emphasize different aims and perspectives.

Qualitative research approaches

Approach	What does it involve?
Grounded theory	Researchers collect rich data on a topic of interest and develop theories .
	Researchers immerse themselves in groups or organizations to understand their cultures.
Action research	Researchers and participants collaboratively link theory to practice to drive social change.
Phenomenological research	Researchers investigate a phenomenon or event by describing and interpreting participants’ lived experiences.
Narrative research	Researchers examine how stories are told to understand how participants perceive and make sense of their experiences.

Note that qualitative research is at risk for certain research biases including the Hawthorne effect , observer bias , recall bias , and social desirability bias . While not always totally avoidable, awareness of potential biases as you collect and analyze your data can prevent them from impacting your work too much.

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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 analyzing 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 organize 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 categorize 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 analyzing qualitative data. Although these methods share similar processes, they emphasize different concepts.

Qualitative data analysis

Approach	When to use	Example
	To describe and categorize common words, phrases, and ideas in qualitative data.	A market researcher could perform content analysis to find out what kind of language is used in descriptions of therapeutic apps.
	To identify and interpret patterns and themes in qualitative data.	A psychologist could apply thematic analysis to travel blogs to explore how tourism shapes self-identity.
	To examine the content, structure, and design of texts.	A media researcher could use textual analysis to understand how news coverage of celebrities has changed in the past decade.
	To study communication and how language is used to achieve effects in specific contexts.	A political scientist could use discourse analysis to study how politicians generate trust in election campaigns.

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 analyzing 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 analyzing 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 generalizability

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

• Labor-intensive

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

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.

• Chi square goodness of fit test
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

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 organization 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 organizations.

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

• Prepare and organize 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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• Published: 05 October 2018

Interviews and focus groups in qualitative research: an update for the digital age

• P. Gill 1 &
• J. Baillie 2  

British Dental Journal volume  225 ,  pages 668–672 ( 2018 ) Cite this article

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Highlights that qualitative research is used increasingly in dentistry. Interviews and focus groups remain the most common qualitative methods of data collection.

Suggests the advent of digital technologies has transformed how qualitative research can now be undertaken.

Suggests interviews and focus groups can offer significant, meaningful insight into participants' experiences, beliefs and perspectives, which can help to inform developments in dental practice.

Qualitative research is used increasingly in dentistry, due to its potential to provide meaningful, in-depth insights into participants' experiences, perspectives, beliefs and behaviours. These insights can subsequently help to inform developments in dental practice and further related research. The most common methods of data collection used in qualitative research are interviews and focus groups. While these are primarily conducted face-to-face, the ongoing evolution of digital technologies, such as video chat and online forums, has further transformed these methods of data collection. This paper therefore discusses interviews and focus groups in detail, outlines how they can be used in practice, how digital technologies can further inform the data collection process, and what these methods can offer dentistry.

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Interviews in the social sciences

Professionalism in dentistry: deconstructing common terminology

A review of technical and quality assessment considerations of audio-visual and web-conferencing focus groups in qualitative health research, introduction.

Traditionally, research in dentistry has primarily been quantitative in nature. 1 However, in recent years, there has been a growing interest in qualitative research within the profession, due to its potential to further inform developments in practice, policy, education and training. Consequently, in 2008, the British Dental Journal (BDJ) published a four paper qualitative research series, 2 , 3 , 4 , 5 to help increase awareness and understanding of this particular methodological approach.

Since the papers were originally published, two scoping reviews have demonstrated the ongoing proliferation in the use of qualitative research within the field of oral healthcare. 1 , 6 To date, the original four paper series continue to be well cited and two of the main papers remain widely accessed among the BDJ readership. 2 , 3 The potential value of well-conducted qualitative research to evidence-based practice is now also widely recognised by service providers, policy makers, funding bodies and those who commission, support and use healthcare research.

Besides increasing standalone use, qualitative methods are now also routinely incorporated into larger mixed method study designs, such as clinical trials, as they can offer additional, meaningful insights into complex problems that simply could not be provided by quantitative methods alone. Qualitative methods can also be used to further facilitate in-depth understanding of important aspects of clinical trial processes, such as recruitment. For example, Ellis et al . investigated why edentulous older patients, dissatisfied with conventional dentures, decline implant treatment, despite its established efficacy, and frequently refuse to participate in related randomised clinical trials, even when financial constraints are removed. 7 Through the use of focus groups in Canada and the UK, the authors found that fears of pain and potential complications, along with perceived embarrassment, exacerbated by age, are common reasons why older patients typically refuse dental implants. 7

The last decade has also seen further developments in qualitative research, due to the ongoing evolution of digital technologies. These developments have transformed how researchers can access and share information, communicate and collaborate, recruit and engage participants, collect and analyse data and disseminate and translate research findings. 8 Where appropriate, such technologies are therefore capable of extending and enhancing how qualitative research is undertaken. 9 For example, it is now possible to collect qualitative data via instant messaging, email or online/video chat, using appropriate online platforms.

These innovative approaches to research are therefore cost-effective, convenient, reduce geographical constraints and are often useful for accessing 'hard to reach' participants (for example, those who are immobile or socially isolated). 8 , 9 However, digital technologies are still relatively new and constantly evolving and therefore present a variety of pragmatic and methodological challenges. Furthermore, given their very nature, their use in many qualitative studies and/or with certain participant groups may be inappropriate and should therefore always be carefully considered. While it is beyond the scope of this paper to provide a detailed explication regarding the use of digital technologies in qualitative research, insight is provided into how such technologies can be used to facilitate the data collection process in interviews and focus groups.

In light of such developments, it is perhaps therefore timely to update the main paper 3 of the original BDJ series. As with the previous publications, this paper has been purposely written in an accessible style, to enhance readability, particularly for those who are new to qualitative research. While the focus remains on the most common qualitative methods of data collection – interviews and focus groups – appropriate revisions have been made to provide a novel perspective, and should therefore be helpful to those who would like to know more about qualitative research. This paper specifically focuses on undertaking qualitative research with adult participants only.

Overview of qualitative research

Qualitative research is an approach that focuses on people and their experiences, behaviours and opinions. 10 , 11 The qualitative researcher seeks to answer questions of 'how' and 'why', providing detailed insight and understanding, 11 which quantitative methods cannot reach. 12 Within qualitative research, there are distinct methodologies influencing how the researcher approaches the research question, data collection and data analysis. 13 For example, phenomenological studies focus on the lived experience of individuals, explored through their description of the phenomenon. Ethnographic studies explore the culture of a group and typically involve the use of multiple methods to uncover the issues. 14

While methodology is the 'thinking tool', the methods are the 'doing tools'; 13 the ways in which data are collected and analysed. There are multiple qualitative data collection methods, including interviews, focus groups, observations, documentary analysis, participant diaries, photography and videography. Two of the most commonly used qualitative methods are interviews and focus groups, which are explored in this article. The data generated through these methods can be analysed in one of many ways, according to the methodological approach chosen. A common approach is thematic data analysis, involving the identification of themes and subthemes across the data set. Further information on approaches to qualitative data analysis has been discussed elsewhere. 1

Qualitative research is an evolving and adaptable approach, used by different disciplines for different purposes. Traditionally, qualitative data, specifically interviews, focus groups and observations, have been collected face-to-face with participants. In more recent years, digital technologies have contributed to the ongoing evolution of qualitative research. Digital technologies offer researchers different ways of recruiting participants and collecting data, and offer participants opportunities to be involved in research that is not necessarily face-to-face.

Research interviews are a fundamental qualitative research method 15 and are utilised across methodological approaches. Interviews enable the researcher to learn in depth about the perspectives, experiences, beliefs and motivations of the participant. 3 , 16 Examples include, exploring patients' perspectives of fear/anxiety triggers in dental treatment, 17 patients' experiences of oral health and diabetes, 18 and dental students' motivations for their choice of career. 19

Interviews may be structured, semi-structured or unstructured, 3 according to the purpose of the study, with less structured interviews facilitating a more in depth and flexible interviewing approach. 20 Structured interviews are similar to verbal questionnaires and are used if the researcher requires clarification on a topic; however they produce less in-depth data about a participant's experience. 3 Unstructured interviews may be used when little is known about a topic and involves the researcher asking an opening question; 3 the participant then leads the discussion. 20 Semi-structured interviews are commonly used in healthcare research, enabling the researcher to ask predetermined questions, 20 while ensuring the participant discusses issues they feel are important.

Interviews can be undertaken face-to-face or using digital methods when the researcher and participant are in different locations. Audio-recording the interview, with the consent of the participant, is essential for all interviews regardless of the medium as it enables accurate transcription; the process of turning the audio file into a word-for-word transcript. This transcript is the data, which the researcher then analyses according to the chosen approach.

Types of interview

Qualitative studies often utilise one-to-one, face-to-face interviews with research participants. This involves arranging a mutually convenient time and place to meet the participant, signing a consent form and audio-recording the interview. However, digital technologies have expanded the potential for interviews in research, enabling individuals to participate in qualitative research regardless of location.

Telephone interviews can be a useful alternative to face-to-face interviews and are commonly used in qualitative research. They enable participants from different geographical areas to participate and may be less onerous for participants than meeting a researcher in person. 15 A qualitative study explored patients' perspectives of dental implants and utilised telephone interviews due to the quality of the data that could be yielded. 21 The researcher needs to consider how they will audio record the interview, which can be facilitated by purchasing a recorder that connects directly to the telephone. One potential disadvantage of telephone interviews is the inability of the interviewer and researcher to see each other. This is resolved using software for audio and video calls online – such as Skype – to conduct interviews with participants in qualitative studies. Advantages of this approach include being able to see the participant if video calls are used, enabling observation of non-verbal communication, and the software can be free to use. However, participants are required to have a device and internet connection, as well as being computer literate, potentially limiting who can participate in the study. One qualitative study explored the role of dental hygienists in reducing oral health disparities in Canada. 22 The researcher conducted interviews using Skype, which enabled dental hygienists from across Canada to be interviewed within the research budget, accommodating the participants' schedules. 22

A less commonly used approach to qualitative interviews is the use of social virtual worlds. A qualitative study accessed a social virtual world – Second Life – to explore the health literacy skills of individuals who use social virtual worlds to access health information. 23 The researcher created an avatar and interview room, and undertook interviews with participants using voice and text methods. 23 This approach to recruitment and data collection enables individuals from diverse geographical locations to participate, while remaining anonymous if they wish. Furthermore, for interviews conducted using text methods, transcription of the interview is not required as the researcher can save the written conversation with the participant, with the participant's consent. However, the researcher and participant need to be familiar with how the social virtual world works to engage in an interview this way.

Conducting an interview

Ensuring informed consent before any interview is a fundamental aspect of the research process. Participants in research must be afforded autonomy and respect; consent should be informed and voluntary. 24 Individuals should have the opportunity to read an information sheet about the study, ask questions, understand how their data will be stored and used, and know that they are free to withdraw at any point without reprisal. The qualitative researcher should take written consent before undertaking the interview. In a face-to-face interview, this is straightforward: the researcher and participant both sign copies of the consent form, keeping one each. However, this approach is less straightforward when the researcher and participant do not meet in person. A recent protocol paper outlined an approach for taking consent for telephone interviews, which involved: audio recording the participant agreeing to each point on the consent form; the researcher signing the consent form and keeping a copy; and posting a copy to the participant. 25 This process could be replicated in other interview studies using digital methods.

There are advantages and disadvantages of using face-to-face and digital methods for research interviews. Ultimately, for both approaches, the quality of the interview is determined by the researcher. 16 Appropriate training and preparation are thus required. Healthcare professionals can use their interpersonal communication skills when undertaking a research interview, particularly questioning, listening and conversing. 3 However, the purpose of an interview is to gain information about the study topic, 26 rather than offering help and advice. 3 The researcher therefore needs to listen attentively to participants, enabling them to describe their experience without interruption. 3 The use of active listening skills also help to facilitate the interview. 14 Spradley outlined elements and strategies for research interviews, 27 which are a useful guide for qualitative researchers:

Greeting and explaining the project/interview

Asking descriptive (broad), structural (explore response to descriptive) and contrast (difference between) questions

Asymmetry between the researcher and participant talking

Expressing interest and cultural ignorance

Repeating, restating and incorporating the participant's words when asking questions

Creating hypothetical situations

Asking friendly questions

Knowing when to leave.

For semi-structured interviews, a topic guide (also called an interview schedule) is used to guide the content of the interview – an example of a topic guide is outlined in Box 1 . The topic guide, usually based on the research questions, existing literature and, for healthcare professionals, their clinical experience, is developed by the research team. The topic guide should include open ended questions that elicit in-depth information, and offer participants the opportunity to talk about issues important to them. This is vital in qualitative research where the researcher is interested in exploring the experiences and perspectives of participants. It can be useful for qualitative researchers to pilot the topic guide with the first participants, 10 to ensure the questions are relevant and understandable, and amending the questions if required.

Regardless of the medium of interview, the researcher must consider the setting of the interview. For face-to-face interviews, this could be in the participant's home, in an office or another mutually convenient location. A quiet location is preferable to promote confidentiality, enable the researcher and participant to concentrate on the conversation, and to facilitate accurate audio-recording of the interview. For interviews using digital methods the same principles apply: a quiet, private space where the researcher and participant feel comfortable and confident to participate in an interview.

Box 1: Example of a topic guide

Study focus: Parents' experiences of brushing their child's (aged 0–5) teeth

1. Can you tell me about your experience of cleaning your child's teeth?

How old was your child when you started cleaning their teeth?

Why did you start cleaning their teeth at that point?

How often do you brush their teeth?

What do you use to brush their teeth and why?

2. Could you explain how you find cleaning your child's teeth?

Do you find anything difficult?

What makes cleaning their teeth easier for you?

3. How has your experience of cleaning your child's teeth changed over time?

Has it become easier or harder?

Have you changed how often and how you clean their teeth? If so, why?

4. Could you describe how your child finds having their teeth cleaned?

What do they enjoy about having their teeth cleaned?

Is there anything they find upsetting about having their teeth cleaned?

5. Where do you look for information/advice about cleaning your child's teeth?

What did your health visitor tell you about cleaning your child's teeth? (If anything)

What has the dentist told you about caring for your child's teeth? (If visited)

Have any family members given you advice about how to clean your child's teeth? If so, what did they tell you? Did you follow their advice?

6. Is there anything else you would like to discuss about this?

Focus groups

A focus group is a moderated group discussion on a pre-defined topic, for research purposes. 28 , 29 While not aligned to a particular qualitative methodology (for example, grounded theory or phenomenology) as such, focus groups are used increasingly in healthcare research, as they are useful for exploring collective perspectives, attitudes, behaviours and experiences. Consequently, they can yield rich, in-depth data and illuminate agreement and inconsistencies 28 within and, where appropriate, between groups. Examples include public perceptions of dental implants and subsequent impact on help-seeking and decision making, 30 and general dental practitioners' views on patient safety in dentistry. 31

Focus groups can be used alone or in conjunction with other methods, such as interviews or observations, and can therefore help to confirm, extend or enrich understanding and provide alternative insights. 28 The social interaction between participants often results in lively discussion and can therefore facilitate the collection of rich, meaningful data. However, they are complex to organise and manage, due to the number of participants, and may also be inappropriate for exploring particularly sensitive issues that many participants may feel uncomfortable about discussing in a group environment.

Focus groups are primarily undertaken face-to-face but can now also be undertaken online, using appropriate technologies such as email, bulletin boards, online research communities, chat rooms, discussion forums, social media and video conferencing. 32 Using such technologies, data collection can also be synchronous (for example, online discussions in 'real time') or, unlike traditional face-to-face focus groups, asynchronous (for example, online/email discussions in 'non-real time'). While many of the fundamental principles of focus group research are the same, regardless of how they are conducted, a number of subtle nuances are associated with the online medium. 32 Some of which are discussed further in the following sections.

Focus group considerations

Some key considerations associated with face-to-face focus groups are: how many participants are required; should participants within each group know each other (or not) and how many focus groups are needed within a single study? These issues are much debated and there is no definitive answer. However, the number of focus groups required will largely depend on the topic area, the depth and breadth of data needed, the desired level of participation required 29 and the necessity (or not) for data saturation.

The optimum group size is around six to eight participants (excluding researchers) but can work effectively with between three and 14 participants. 3 If the group is too small, it may limit discussion, but if it is too large, it may become disorganised and difficult to manage. It is, however, prudent to over-recruit for a focus group by approximately two to three participants, to allow for potential non-attenders. For many researchers, particularly novice researchers, group size may also be informed by pragmatic considerations, such as the type of study, resources available and moderator experience. 28 Similar size and mix considerations exist for online focus groups. Typically, synchronous online focus groups will have around three to eight participants but, as the discussion does not happen simultaneously, asynchronous groups may have as many as 10–30 participants. 33

The topic area and potential group interaction should guide group composition considerations. Pre-existing groups, where participants know each other (for example, work colleagues) may be easier to recruit, have shared experiences and may enjoy a familiarity, which facilitates discussion and/or the ability to challenge each other courteously. 3 However, if there is a potential power imbalance within the group or if existing group norms and hierarchies may adversely affect the ability of participants to speak freely, then 'stranger groups' (that is, where participants do not already know each other) may be more appropriate. 34 , 35

Focus group management

Face-to-face focus groups should normally be conducted by two researchers; a moderator and an observer. 28 The moderator facilitates group discussion, while the observer typically monitors group dynamics, behaviours, non-verbal cues, seating arrangements and speaking order, which is essential for transcription and analysis. The same principles of informed consent, as discussed in the interview section, also apply to focus groups, regardless of medium. However, the consent process for online discussions will probably be managed somewhat differently. For example, while an appropriate participant information leaflet (and consent form) would still be required, the process is likely to be managed electronically (for example, via email) and would need to specifically address issues relating to technology (for example, anonymity and use, storage and access to online data). 32

The venue in which a face to face focus group is conducted should be of a suitable size, private, quiet, free from distractions and in a collectively convenient location. It should also be conducted at a time appropriate for participants, 28 as this is likely to promote attendance. As with interviews, the same ethical considerations apply (as discussed earlier). However, online focus groups may present additional ethical challenges associated with issues such as informed consent, appropriate access and secure data storage. Further guidance can be found elsewhere. 8 , 32

Before the focus group commences, the researchers should establish rapport with participants, as this will help to put them at ease and result in a more meaningful discussion. Consequently, researchers should introduce themselves, provide further clarity about the study and how the process will work in practice and outline the 'ground rules'. Ground rules are designed to assist, not hinder, group discussion and typically include: 3 , 28 , 29

Discussions within the group are confidential to the group

Only one person can speak at a time

All participants should have sufficient opportunity to contribute

There should be no unnecessary interruptions while someone is speaking

Everyone can be expected to be listened to and their views respected

Challenging contrary opinions is appropriate, but ridiculing is not.

Moderating a focus group requires considered management and good interpersonal skills to help guide the discussion and, where appropriate, keep it sufficiently focused. Avoid, therefore, participating, leading, expressing personal opinions or correcting participants' knowledge 3 , 28 as this may bias the process. A relaxed, interested demeanour will also help participants to feel comfortable and promote candid discourse. Moderators should also prevent the discussion being dominated by any one person, ensure differences of opinions are discussed fairly and, if required, encourage reticent participants to contribute. 3 Asking open questions, reflecting on significant issues, inviting further debate, probing responses accordingly, and seeking further clarification, as and where appropriate, will help to obtain sufficient depth and insight into the topic area.

Moderating online focus groups requires comparable skills, particularly if the discussion is synchronous, as the discussion may be dominated by those who can type proficiently. 36 It is therefore important that sufficient time and respect is accorded to those who may not be able to type as quickly. Asynchronous discussions are usually less problematic in this respect, as interactions are less instant. However, moderating an asynchronous discussion presents additional challenges, particularly if participants are geographically dispersed, as they may be online at different times. Consequently, the moderator will not always be present and the discussion may therefore need to occur over several days, which can be difficult to manage and facilitate and invariably requires considerable flexibility. 32 It is also worth recognising that establishing rapport with participants via online medium is often more challenging than via face-to-face and may therefore require additional time, skills, effort and consideration.

As with research interviews, focus groups should be guided by an appropriate interview schedule, as discussed earlier in the paper. For example, the schedule will usually be informed by the review of the literature and study aims, and will merely provide a topic guide to help inform subsequent discussions. To provide a verbatim account of the discussion, focus groups must be recorded, using an audio-recorder with a good quality multi-directional microphone. While videotaping is possible, some participants may find it obtrusive, 3 which may adversely affect group dynamics. The use (or not) of a video recorder, should therefore be carefully considered.

At the end of the focus group, a few minutes should be spent rounding up and reflecting on the discussion. 28 Depending on the topic area, it is possible that some participants may have revealed deeply personal issues and may therefore require further help and support, such as a constructive debrief or possibly even referral on to a relevant third party. It is also possible that some participants may feel that the discussion did not adequately reflect their views and, consequently, may no longer wish to be associated with the study. 28 Such occurrences are likely to be uncommon, but should they arise, it is important to further discuss any concerns and, if appropriate, offer them the opportunity to withdraw (including any data relating to them) from the study. Immediately after the discussion, researchers should compile notes regarding thoughts and ideas about the focus group, which can assist with data analysis and, if appropriate, any further data collection.

Qualitative research is increasingly being utilised within dental research to explore the experiences, perspectives, motivations and beliefs of participants. The contributions of qualitative research to evidence-based practice are increasingly being recognised, both as standalone research and as part of larger mixed-method studies, including clinical trials. Interviews and focus groups remain commonly used data collection methods in qualitative research, and with the advent of digital technologies, their utilisation continues to evolve. However, digital methods of qualitative data collection present additional methodological, ethical and practical considerations, but also potentially offer considerable flexibility to participants and researchers. Consequently, regardless of format, qualitative methods have significant potential to inform important areas of dental practice, policy and further related research.

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Gill, P., Baillie, J. Interviews and focus groups in qualitative research: an update for the digital age. Br Dent J 225 , 668–672 (2018). https://doi.org/10.1038/sj.bdj.2018.815

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• Unstructured Interview | Definition, Guide & Examples

Unstructured Interview | Definition, Guide & Examples

Published on 4 May 2022 by Tegan George . Revised on 10 October 2022.

An unstructured interview is a data collection method that relies on asking participants questions to collect data on a topic. Also known as non-directive interviewing , unstructured interviews do not have a set pattern and questions are not arranged in advance.

In research, unstructured interviews are usually qualitative in nature, and they can be very helpful for social science or humanities research focusing on personal experiences.

An unstructured interview can be a particularly useful exploratory research tool. Known for being very informal and flexible, they can yield captivating responses from your participants.

• Structured interviews : The questions are predetermined in both topic and order.
• Semi-structured interviews : A few questions are predetermined, but other questions aren’t planned.
• Focus group interviews : The questions are presented to a group instead of one individual.

Table of contents

What is an unstructured interview, when to use an unstructured interview, advantages of unstructured interviews, disadvantages of unstructured interviews, unstructured interview questions, how to conduct an unstructured interview, how to analyse an unstructured interview, presenting your results, frequently asked questions about unstructured interviews.

An unstructured interview is the most flexible type of interview, with room for spontaneity. In contrast to a structured interview , the questions and the order in which they are presented are not set. Instead, the interview proceeds based on the participant’s previous answers.

Unstructured interviews are open-ended.This lack of structure can help you gather detailed information on your topic, while still allowing you to observe patterns in the analysis stage.

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It can be challenging to know what type of interview best fits your subject matter. Unstructured interviews can be very challenging to conduct and may not always be the best fit for your research question . Unstructured interviews are best used when:

• You are an experienced interviewer and have a very strong background in your research topic
• Your research question is exploratory in nature. While you may have developed hypotheses, you are open to discovering new or shifting viewpoints.
• You are seeking descriptive data, and are ready to ask questions that will deepen and contextualise your initial thoughts and hypotheses
• Your research depends on forming connections with your participants and making them feel comfortable revealing deeper emotions, thoughts, or lived experiences

Even more so than in structured or semi-structured interviews, it is critical that you remain organised and develop a system for keeping track of participant responses. Since the questions are not set beforehand, the data collection and analysis become more complex.

Differences between different types of interviews

Make sure to choose the type of interview that suits your research best. This table shows the most important differences between the four types.

Fixed questions
Fixed order of questions
Fixed number of questions
Option to ask additional questions

Unstructured interviews have a few advantages compared to other types of interviews.

Very flexible

Respondents are more at ease, reduced risk of bias, more detail and nuance.

Unstructured interviews also have a few downsides compared to other data collection methods.

Low generalisability and reliability

Risk of leading questions, very time-consuming, risk of low internal validity.

It can be challenging to ask unstructured interview questions that get you the information you seek without biasing your responses. You will have to rely on the flow of the conversation and the cues you pick up from your participants.

Here are a few tips:

• Since you won’t be designing set questions ahead of time, it’s important to feel sufficiently comfortable with your topic that you can come up with questions spontaneously.
• Write yourself a guide with notes about your topic and what you’re seeking to investigate or gain from your interviews, so you have notes to refer back to.
• Try to ask questions that encourage your participant to answer at length. Avoid closed-ended questions that can be answered with a simple ‘yes’ or ‘no.’
• Relatedly, focus on ‘how’ questions rather than ‘why’ questions to help put your participants at ease and avoid any feelings of defensiveness or anxiety.
• Consider beginning the interview with an icebreaker or a “freebie” question, to start on a relaxed and comfortable note before delving into the more sensitive topics.

Here are a few possibilities for how your conversation could proceed:

Conversation A: 

• Interviewer: Do you go to the gym? How often?
• Participant: I go to the gym 5 times per week.
• Interviewer: What feelings does going to the gym bring out in you?
• Participant: I don’t feel like myself unless I go to the gym.

Since the participant hinted that going to the gym is important for their mental health, proceed with questions in that vein, such as:

• You say you ‘don’t feel like yourself.’ Can you elaborate?
• If you have to skip a gym day, how does that make you feel?
• Is there anything else that makes you feel the way going to the gym does?

Conversation B:

• Participant: No, I hate the gym.

Since the participant seems to have strong feelings against the gym, you can probe deeper.

• What makes you feel this way about the gym?
• What do you like to do instead?
• Do your feelings about the gym reflect on your feelings about exercise in general?

Once you’ve determined that an unstructured interview is the right fit for your research topic , you can proceed with the following steps.

Step 1: Set your goals and foundations

As you conceptualise your research question, consider starting with some guiding questions, such as:

• What are you trying to learn or achieve from an unstructured interview specifically?
• Why is an unstructured interview the best fit for your research, as opposed to a different type of interview or another research method?
• What is the guiding force behind your research? What topic will serve as the foundation for your unscripted and follow-up questions?

While you do not need to plan your questions ahead of time for an unstructured interview, this does not mean that no advanced planning is needed. Unstructured interviews actually require extensive planning ahead to ensure that the interview stage will be fruitful.

• Perhaps you have been studying it for quite some time, or you have previously conducted another type of research on a similar topic.
• Maybe you are seeking a bit more detail or nuance to confirm or challenge past results, or you are interested in delving deeper into a particular question that arose from past research.

Once you are feeling really solid about your research question, you can start brainstorming categories of questions you may ask. You can start with one broad, overarching question and brainstorm what paths the conversation could take.

Step 2: Assemble your participants

There are a few sampling methods you can use to recruit your interview participants, such as:

• Voluntary response sampling : For example, posting flyers in the dining hall and seeing who answers.
• Stratified sampling of a particular age, race, or gender identity that is relevant to your research.
• Convenience sampling of other students at your university, colleagues or friends.

Step 3: Decide on your setting

You should decide ahead of time whether your interview will be conducted in person, over the phone, or via video conferencing.

In-person, phone, or video interviews each have their own advantages and disadvantages.

• In general, live interviews can lead to nervousness or interviewer effects, where the respondent feels pressured to respond in a manner they perceive will please you.
• Videoconferencing specifically can feel awkward or stilted, which could affect your results. However, your participant may be more comfortable in their own home.
• Not being face to face with respondents, such as in a phone interview, could lead to more honest answers. However, there could be environmental conditions or distractions on the participant side that could affect their responses.
• Consent to video or audio recording
• Signature of a confidentiality agreement
• Signature of an agreement to anonymise or pseudonymise data

Step 4: Conduct your interviews

As you conduct your interviews, pay special attention to any environmental conditions that could bias your responses. This includes noises, temperature, and setting, but also your body language. Be careful to moderate your tone of voice and any responses to avoid interviewer effects.

Remember that one of the biggest challenges with unstructured interviews is to keep your questions neutral and unbiased. Strive for open-ended phrasing, and allow your participants to set the pace, asking follow-up questions that flow naturally from their last answer.

After you’re finished conducting your interviews, you move into the analysis phase. Don’t forget to assign each participant a pseudonym (such as a number or letter) to be sure you stay organised.

First, transcribe your recorded interviews. You can then conduct content or thematic analysis to create your categories, seeking patterns that stand out to you among your responses and testing your hypotheses .

Transcribing interviews

The transcription process can be quite lengthy for unstructured interviews due to their more detailed nature. One decision that can save you quite a bit of time before you get started is whether you will be conducting verbatim transcription or intelligent verbatim transcription.

• If you consider that laughter, hesitations, or filler words like ‘umm’ affect your analysis and research conclusions, you should conduct verbatim transcription and include them.
• If not, intelligent verbatim transcription allows you to exclude fillers and fix any grammar issues in your transcription. Intelligent verbatim transcription can save you some time in this step.

Transcribing has the added benefit of being a great opportunity for cleaning your data . While you listen, you can take notes of questions or inconsistencies that come up.

Note that in some cases, your supervisor may ask you to add the finished transcriptions in the appendix of your paper.

Coding unstructured interviews

After you’re finished transcribing, you can begin your thematic or content analysis . Here, you separate words, patterns, or recurring responses that stand out to you into labels or categories for later analysis. This process is called ‘coding’.

Due to the open-ended nature of unstructured interviews, you will most likely proceed with thematic analysis, rather than content analysis. In thematic analysis, you draw preliminary conclusions about your participants by identifying common topics, ideas, or patterns in their responses.

• After you have familiarised yourself sufficiently with your responses, you can separate them into different codes or labels.
• However, codes can be a bit too specific or niche for robust analysis. You can proceed by grouping similar codes into broader themes.
• After identifying your themes, be sure to double-check your responses to ensure that the themes you chose appropriately represent your data.

Analysing unstructured interviews

Once you’re confident with your preliminary thoughts, you can take either an inductive or a deductive approach in your analysis.

• An inductive approach is more open-ended, allowing your data to determine your themes.
• A deductive approach is the opposite, and involves investigating whether your data confirm preconceived themes or ideas.

Thematic analysis is quite subjective, which can lead to issues with the reliability of your results. The unstructured nature of this type of interview leads to greater dependence on your judgement and interpretations. Be extra vigilant about remaining objective here.

After your data analysis, you’re ready to combine your findings into a research paper .

• Your methodology section describes your data collection process (in this case, describing your unstructured interview process) and explains how you justified and conceptualised your analysis.
• Your discussion and results sections usually describe each of your coded categories, and give you the opportunity to showcase your argument.
• You can then conclude with your main takeaways and avenues for further study.
• Since unstructured interviews are predominantly exploratory in nature, you can add suggestions for future research in the discussion section .

Example of interview methodology for a research paper

Let’s say you are a history student particularly interested in the history of the town around your campus. The town has a long history dating back to the early 1600s, but town census data shows that many long-term residents have been moving away in recent years.

You identify a few potential reasons for this shift:

• People are moving away because there are better opportunities in the closest big city.
• The university has been aggressively purchasing real estate to build more student housing.
• The university has long been the main source of jobs for the town, and education budget cuts have led to a hiring freeze.
• The cost of living in the area has skyrocketed in recent years, and long-time residents can no longer afford their property taxes.

Anecdotally, you hypothesise that the increased cost of living is the predominant factor in driving away long-time residents. However, you cannot rule out the other options, specifically the lack of job options coupled with the university’s expansionist aims.

You feel very comfortable with this topic and oral histories in general. Since it is exploratory in nature but has the potential to become sensitive or emotional, you decide to conduct unstructured interviews with long-term residents of your town. Multi-generational residents are of particular interest.

To find the right mix of participants, you post in the Facebook group for town residents, as well as in the town’s NextDoor forum. You also post flyers in local cafés and even some postboxes.

Once you’ve assembled your participants, it’s time to proceed with your interviews. Consider starting out with an icebreaker, such as:

• What is your favorite thing about this town?
• Tell me about a memory of the town that you have that’s particularly special.

You can then proceed with the interview, asking follow-up questions relevant to your participants’ responses, probing their family history, ties to the community, or any stories they have to share – whether funny, touching, or sentimental.

Establishing rapport with your participants helps you delve into the reasoning behind the choice to stay or leave, and competing thoughts and feelings they may have as the interview goes on. Remember to try to structure it like a conversation, to put them more at ease with the emotional topics.

• Has increased cost of living led you to consider leaving the area? → The phrasing implies that you, the interviewer, think this is the case. This could bias your respondents, incentivising them to answer affirmatively as well.
• Are there any factors that would lead you to consider leaving the area? → This phrasing ensures the participant is giving their own opinion, and may even yield some surprising responses that enrich your analysis.

After conducting your interviews and transcribing your data, you can then conduct thematic analysis, coding responses into different categories. Since you began your research with several theories for why residents may be leaving that all seemed plausible, you would use the inductive approach.

After identifying the relevant themes from your data, you can draw inferences and conclusions. Your results section usually addresses each theme or pattern you found, describing each in turn, as well as how often you came across them in your analysis.

An unstructured interview is the most flexible type of interview, but it is not always the best fit for your research topic.

Unstructured interviews are best used when:

• You are an experienced interviewer and have a very strong background in your research topic, since it is challenging to ask spontaneous, colloquial questions
• Your research question is exploratory in nature. While you may have developed hypotheses, you are open to discovering new or shifting viewpoints through the interview process.
• Your research depends on forming connections with your participants and making them feel comfortable revealing deeper emotions, lived experiences, or thoughts

The four most common types of interviews are:

• Unstructured interviews : None of the questions are predetermined.

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 .

The interviewer effect is a type of bias that emerges when a characteristic of an interviewer (race, age, gender identity, etc.) influences the responses given by the interviewee.

There is a risk of an interviewer effect in all types of interviews , but it can be mitigated by writing really high-quality interview questions.

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Unstructured Problems and Development of Prescriptive Decision Making Methods

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Part of the book series: Nonconvex Optimization and Its Applications ((NOIA,volume 5))

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A class of unstructured decision making problems is under consideration. Unstructured problems are the problems with the majority of qualitative parameters with unknown quantitative dependencies. The peculiarities of these tasks are discussed, and requirements for decision aid tools are formulated: psychologically valid measurements and elicitation procedures, constistency testing, and possibility to communicate the result. Method ZAPROS is described as an example of the decision aid, meeting these requirements. Peculiarities of the method are illustrated on an example.

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Larichev, O.I., Moskovich, H.M. (1995). Unstructured Problems and Development of Prescriptive Decision Making Methods. In: Pardalos, P.M., Siskos, Y., Zopounidis, C. (eds) Advances in Multicriteria Analysis. Nonconvex Optimization and Its Applications, vol 5. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2383-0_4

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Using online methods to recruit participants into mental health clinical trials: considerations and recommendations from the RE-MIND study

• Mais Iflaifel 1 ,
• Charlotte L. Hall 2 , 3 ,
• Heidi R. Green 4 , 5 ,
• Andrew Willis 6 ,
• Stefan Rennick-Egglestone 3 , 7 ,
• Edmund Juszczak 1 ,
• Mark Townsend 8 ,
• Jennifer Martin 2 , 3 &
• Kirsty Sprange   ORCID: orcid.org/0000-0001-6443-7242 1  

Trials volume  25 , Article number:  596 ( 2024 ) Cite this article

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Ensuring diversity in clinical trials can be a challenge, which may be exacerbated when recruiting vulnerable populations, such as participants with mental health illness. As recruitment continues to be the major cause of trial delays, researchers are turning to online recruitment strategies, e.g. social media, to reach a wider population and reduce recruitment time and costs. There is mixed evidence for the use of online recruitment strategies; therefore, the REcruitment in Mental health trials: broadening the ‘net’, opportunities for INclusivity through online methoDs (RE-MIND) study aimed to identify evidence and provide guidance for use of online strategies in recruitment to mental health trials, with a focus on whether online strategies can enhance inclusivity. This commentary, as part of the RE-MIND study, focusses on providing recommendations for recruitment strategy selection in future research with the aim to improve trial efficiency.

A mixed-methods approach was employed involving three work packages: (I) an evidence review of a cohort of 97 recently published randomised controlled trials/feasibility or pilot studies in mental health to assess the impact of online versus offline recruitment; (II) a qualitative study investigating the experiences of n  = 23 key stakeholders on use of an online recruitment approach in mental health clinical trials; (III) combining the results of WP1 and WP2 to produce recommendations on the use of an online recruitment strategy in mental health clinical trials. The findings from WP1 and 2 have been published elsewhere; this commentary represents the results of the third work package.

For external validity, clinical trial participants should reflect the populations that will ultimately receive the interventions being tested, if proven effective. To guide researchers on their options for inclusive recruitment strategies, we have developed a list of considerations and practical recommendations on how to maximise the use of online recruitment methods.

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Introduction

Recruitment to clinical trials is challenging, and those in mental health research are no exception and people with mental health illness have been identified as an under-served group in health research [ 1 ]. The importance of broader representation of under-served populations in clinical trials is already well established to ensure they reflect the populations that stand to benefit from the intervention being tested [ 2 ]. The question is how do we improve recruitment when we already know that mental health service use is proportionately lower for the socioeconomically disadvantaged [ 3 ], males [ 4 ], people from ethnic minority backgrounds [ 5 ], and older participants or those living in more rural areas [ 6 ]. Traditionally, recruitment into mental health trials has been dependent upon face-to-face referrals and therefore limited to those individuals actively seeking service intervention, thus perpetuating the problem [ 7 ]. Furthermore, increasing pressures on mental health services has become an obstacle to the delivery of trials using this approach; however, technological advances are allowing researchers to be more creative and dynamic in their choice of recruitment strategies to target potential participants typically outside of services and reach wider groups of people [ 8 ]. Despite this potential, deciding upon what might be the best recruitment strategy for those living with mental health illness needs further careful consideration.

To help address, this we conducted a study, “REcruitment in Mental health trials: broadening the ‘net’, opportunities for Inclusivity through online methoDs’ (RE-MIND)” https://www.nctu.ac.uk/our-research/methodology.aspx . The objective was to explore the use of offline and online recruitment strategies with the aim of helping researchers improve recruitment reach and increase the efficiency of clinical trials of mental health interventions.

This project focussed on the recruitment strategy used to make the initial approach to potential participants, informing them about an active clinical trial. As our focus was on the initial stage in recruitment, we did not cover issues surrounding the consent process itself. Despite this, we acknowledge the importance of the methods of taking informed consent, and this should be considered when deciding on a recruitment strategy.

The RE-MIND study consisted of two work packages which have been published separately [ 9 , 10 ]. First is an evidence review of 97 recently published randomised controlled trials (RCTs) and randomised feasibility/pilot studies in mental health to assess the impact of online recruitment versus offline recruitment in clinical trials [ 9 ]. Second is a qualitative study investigating the experiences, opinions, and ideas of n  = 23 key stakeholders (research staff and patients and public involvement members with experience working in mental health research) on the use of online recruitment as an approach in mental health clinical trials [ 10 ]. The findings were then triangulated [ 11 ] by researchers MI, KS, and CLH to develop draft considerations and practical recommendations which then underwent a review process by the study Advisory Group (HRG, AW, SRE, EJ, MT, and JM) who have experience in digital research, design, and delivery of online and offline RCTs and equality, diversity, and inclusion resulting in the final recommendations.

Throughout the RE-MIND study, we used the following definitions to broadly categorise offline or online recruitment. These definitions describe an overarching strategy to recruitment:

Online recruitment strategies —the use of Internet technologies such as social media advertisements, Google search engine advertisements, and other website campaigns [ 12 ].

Offline recruitment strategies —in-clinic recruitment, approaching potential participants through mail and telephone using health records and registers, media campaigns, newspaper advertisements, and input during radio and television interviews [ 12 ].

In this commentary, we present a list of considerations and practical recommendations for research teams on the use of online recruitment of participants into mental health clinical trials with the aim to improve recruitment efficiency in clinical trials of mental health interventions. It is worth noting that although the RE-MIND study focussed on mental health interventions the findings may also be beneficial in wider clinical research.

• Recommendations

Complexity of mental illness

Severity of mental health illness has previously been identified as a barrier to participation in mental health research [ 13 , 14 ]. RE-MIND reported that the type of mental health illness, its stage, participants’ feelings about their illness, and carers’ responsibilities were key factors when selecting a recruitment strategy [ 10 ]. Alongside meaningful and authentic patient and public involvement (PPI) to guide and inform the recruitment strategy, using a multi-method approach to recruitment could improve accessibility and inclusivity, by supporting the diverse and changing needs of those living with mental health illness.

Considerations

Consider any relationships between recruitment strategy and mental health symptomatology:

For example, individuals with learning disabilities, autism, anxiety, or obsessive compulsive disorder may have difficulty interfacing in public and therefore may benefit from online recruitment.

Online recruitment may, however, be a barrier for other mental health illnesses such as low mood disorders, depression, personality disorders, and psychosis where an in-person approach offers more security, contact, and support to the individual.

Consider using the stage or severity of illness to inform recruitment method:

Will the person’s diagnostic and treatment experience impact on selection of recruitment method, for example, both patients and carers may be reluctant to talk about or need more time to process a diagnosis in the early stages?

Are personal cues, such as body language, important for communicating with your participants and supporting greater engagement in a trial, for example, recognising changes in mental health state, physical discomfort, increasing tics, loss of concentration, fatigue, etc.?

Is personal contact preferable or more encouraging, for example, for building rapport and trust with the individual?

Consider whether the recruitment method selected may impact on any experience of stigma around mental health:

Providing a virtual safe space (online) may be beneficial, but the safety of this space relies on participants having secure and private access to a safe space and a device that can access the Internet.

Consider the impact of the relationship between participants living with mental illness and the research team:

Trusting relationships are deemed important for both recruitment and retention of participants living with mental ill health. Knowing that a health care provider understands an illness and can offer personalised support can be reassuring.

Will your recruitment strategy choices contribute to maintaining or building trust with this group? Online recruitment, such as social media, can be seen as distant and disengaging compared to in-person recruitment. Regular trial updates and information sharing through short videos or live ‘chats’ may help ‘humanise’ the trial on digital platforms.

Develop your recruitment approach (offline/online/mixed) by working in partnership with potential participants and members of the public that share characteristics with your target population group. You can identify PPI contributors through your local employing organisation or through professional or existing research or public contributor groups such as Sprouting Minds https://digitalyouth.ac.uk/the-digital-youth-programme/about-sprouting-minds/ . Please note that most UK National Health Service (NHS) Trusts have established PPI Groups.

Build in flexibility where possible at the protocol development stage, to ensure that participants with fluctuating symptoms can remain engaged in a safe and supported way. This may be achieved in several ways, for example, by offering a mixed recruitment strategy to allow individuals to choose how they want to participate. Alternatively, you may select an online recruitment strategy via Facebook for the initial approach to participate but then build in telephone or in-person opportunities for eligibility checks or follow-ups. It is important to ensure participants know that these options exist at the earliest opportunity.

• Inclusivity

RE-MIND identified a number of specific challenges to inclusive recruitment into mental health clinical trials. Continuing stigma surrounding mental health was a significant factor on a political, cultural, community, and individual level, underpinned by lack of education and mistrust of services and research [ 10 ]. In addition, lack of researcher skills and experience in inclusive recruitment strategies has also been found to contribute to underrepresentation in clinical research [ 15 , 16 ]. This highlights the critical role of PPI in understanding a trial population’s needs. It is also vital to educate researchers on equality and diversity, to enable co-design and selection of suitable recruitment methods to improve representation in mental health clinical trials, for example, through better implementation of the UK’s National Institute for Health Research (NIHR) INCLUDE ethnicity framework [ 1 ].

Consider the impact of the relationship between participants from marginalised groups and the research team:

Will your recruitment strategy choices contribute to maintaining or building trust with this group, for example, those living with mental health illness in rural or under-served communities may benefit from an online recruitment strategy?

Can you develop relationships with local and/or national community groups to build trust in your research? Identify community group leaders who will advocate for your research.

Do you have connections with trusted members of the community to support the building and development of relationships to facilitate inclusive recruitment? This can be in-person or online for example. through administrators of Facebook groups, libraries, or leaders of interest groups.

Do you have a PPI member with lived experience on your research team who can advocate for your research with community groups? Establishing connections through shared experience can help break down barriers of mistrust and misunderstanding.

Consider which recruitment methods your target participant populations may prefer. Living with a mental health illness can be complex due to fluctuating health status or exacerbation of symptoms:

Think about what factors may be most important to them, e.g. if they are working, parents, carers, and/or attending school, then convenience may be the main factor to target.

Consider the range of media platforms available to target people who are educationally or socioeconomically diverse.

If local IT access, e.g. poor Internet access is known in a geographical area, consider using mixed methods for recruitment to improve inclusivity.

Consider information provision and accessibility when selecting your recruitment methods:

Consider whether the methods you are using to recruit and retain participants allow for language (written and/or spoken) needs to be met, e.g., using a translation service.

Consider whether the recruitment method selected allows you to adequately communicate what you need to your participants for example:

Social media platforms such as X (previously Twitter) or use of SMS text-based services have character limitations. Could any language or phrasing lead to misinterpretation or misunderstanding

Use of clinical or diagnostic terms, phrases and labels when considering issues of stigma.

If you are using offline methods, are they accessible for people in a physical sense? E.g., people with motor/mobility needs, or visual or auditory difficulties.

If you are using online methods, are the colours, font, and imagery that you are using inclusive? E.g., alt text for images, colour blindness, colour contrast and font readability.

Work in partnership with people with lived experience and members of the public that share characteristics with your target population group. Explore the needs of both the trial team and the target population group and select methods that are effective for both parties.

Greater sensitivities and confidentiality in mental health care mean that relationships and trust are critical, which may be easier to facilitate face-to-face. However, online recruitment may offer greater flexibility and convenience for participants, for example, by supporting those who may find in-person contact challenging due to their illness. When selecting a recruitment strategy , be mindful of both advantages and drawbacks of the strategy used.

Avoid stereotypes, particularly related to age, when thinking about online methods. For example, technology as a barrier is likely reduced with each generation as well as recent necessity to engage with digital communications (e.g. smartphones, WhatsApp, Facebook, videoconferencing platforms) due to the COVID pandemic.

Identify the main demographic characteristic(s) that is important to engage with your trial, and then consider how other characteristics may impact how they react to the recruitment strategy you have in mind. For example, if you know you want to include young people, consider using TikTok, whereas Facebook may be preferable for older participants. It is important to think about other characteristics that may impact if/how social media is used, e.g. mental health status, socioeconomic status, health status, gender.

There are a growing number of community-led mental illness specific support groups on social media. Can you access and/or engage these groups to help with recruitment? Care should be taken not to harm the safe spaces afforded by these groups, for example for a researcher joining a group purely for the purpose of trial promotion.

Data management

RE-MIND found that for people living with mental health illness, there remained a significant element of fear and mistrust in using online methods underpinned by the stigma and vulnerability of mental health illness with the potential for confidentiality to be broken [ 10 ]. Understanding safeguards for the range of digital platforms was particularly complex and in line with other research suggests better regulation is needed of digital platforms [ 17 ], which at times were not deemed as stringent as clinical trial requirements.

Consider putting appropriate safeguards in place for the recruitment methods selected, e.g. firewalls, General data Protection Regulation (GDPR), secure server.

Can you use a quick response (QR) code to improve security and safety. A QR code is an image scannable by a digital device that can impart information.

Does your organisation have data management policies for use of digital platforms such as social media that must be adhered to? Consider local policies required for multi-site trials.

Is your recruitment method a credible source, e.g. not mistaken for spam, phishing?

Allocate a moderator for engagement with online public groups to ensure safeguarding and wellbeing of people engaging with the content.

How will you inform potential participants about how their data will be shared and/or managed online?

Consider the resources required to adequately manage large numbers of enquiries generated by online strategies:

Do you have the resources to support the additional work associated with screening and monitoring of data quality?

Ensure that eligibility criteria are clearly communicated to potential participants.

Invest adequate time and resources in ensuring your data management systems are secure and safe for participants. You may want to make use restrictive software features for online methods.

Invest time to ensure security and safety methods are communicated clearly. You should work in partnership with potential participants and members of the public that share characteristics with your potential participant group to do this.

Staff training and support

The process of targeting recruitment using an online strategy has been considered as more time-efficient and cost-effective than traditional offline (in-person) recruitment [ 12 ]. However, knowledge of digital platforms and access to organisational and technical support and funding were the most common challenges researchers cited when selecting a recruitment strategy in the RE-MIND study [ 10 ]. It appears that despite advances in technology offering greater opportunity to reach wider audiences, many of these advances remain underutilised without adequate support and resources.

Consider identifying trials involving similar participant populations to learn from their experience of recruitment:

For example, information on trials can be accessed from ClinicalTrials.Gov, PubMed, etc.

Remember that this relies on adequate reporting of recruitment strategy.

Think about how previous trials could have been improved.

Consider the impact of researchers/recruiters being in/adequately trained and knowledgeable on how to use the online recruitment methods you have chosen:

If you are using social media, does your organisation have policies and/or expertise that can be used to support engagement on specific platforms

Does your organisation have procedures for payment for social media promotion?

Do you have local services available to support at an organisational level when things go wrong, e.g. IT, marketing, or communications teams?

Ensure your recruitment methods are appropriately funded, for example, advertising costs per click; do you need a professional designer to produce visual summaries of the research, such as infographics?

Do you have lived experience patient and public input on the selection of recruitment strategy, including content and presentation?

Make a conscious effort to learn from previous trials aimed at the populations you are intending to recruit. Reflect upon how these trials may differ from yours and how that may impact your selection of recruitment process (e.g., severity or stage of mental health illness, intervention type, locality, country, setting, healthcare system, culture).

Ensure research teams are adequately trained on systems and software, and that they know where to go when systems fail, or if they have unanswered questions.

Conclusions

This list of considerations and recommendations is based on the experiences of key partners and the findings from the RE-MIND project, outlining factors to consider when planning recruitment strategies in mental health research/clinical trials. It should be used as a starting point for discussions among the trial team. We acknowledge the potential limitations of each consideration in context of individual and/or organisational capacity, funding and resources available.

The process of selecting a suitable recruitment method should give due consideration to the study population as well as the resources (including staff time and training) needed to implement that method. The ideal juncture to do this is when writing a trial grant funding proposal to ensure adequate resourcing. However, we encourage trial teams that are struggling to recruit to use our considerations and recommendations to re-evaluate their approach to recruitment.

The considerations are designed to be used flexibly based on the target population to be recruited. Greater consideration should be given to using online or mixed methods recruitment strategies that adopt a tailored approach, offering flexibility and choice, to enable wider participation. For future work, we recommend revisiting and re-evaluating these considerations after they have been implemented in practical settings. This process of reassessment will allow us to gain valuable insights into the real-world impact and effectiveness of our proposed strategies. It will also enable us to make necessary adjustments, fine-tune our recommendations, and ensure their continued relevance and success in evolving contexts.

Availability of data and materials

The data collected, used, and/or analysed during the current study are available from the Nottingham Clinical Trials Unit (NCTU) via the corresponding author on reasonable request.

Abbreviations

General Data Protection Regulation

Patient and public involvement

Nottingham Clinical Trials Unit

National health Service

National Institute for Health and Care Research

Quick response

Randomised controlled trial

Short message service

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Acknowledgements

The study authors would like to thank all our focus group and interview participants and the UK Clinical Research Collaboration for their support of the project culminating in these recommendations for future practice.

This project is funded by the National Institute for Health and Care Research (NIHR) CTU Support Funding scheme. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. Open Access funding provided by The University of Nottingham. Stefan Rennick-Egglestone and Charlotte L Hall were supported by the NIHR Nottingham Biomedical Research Centre (NIHR203310).

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Nottingham Clinical Trials Unit, University of Nottingham, Nottingham, UK

Mais Iflaifel, Edmund Juszczak & Kirsty Sprange

Institute of Mental Health, School of Medicine, NIHR MindTech MedTech HRC, Mental Health and Clinical Neurosciences, University of Nottingham, Innovation Park, Triumph Road, Nottingham, UK

Charlotte L. Hall & Jennifer Martin

Institute of Mental Health, NIHR Nottingham Biomedical Research Centre, University of Nottingham, Innovation Park, Triumph Road, Nottingham, UK

Charlotte L. Hall, Stefan Rennick-Egglestone & Jennifer Martin

Health Services Research Unit, University of Aberdeen, Aberdeen, UK

Heidi R. Green

COUCH Health, Manchester, UK

Leicester/Diabetes Research Centre, Centre for Ethnic Health Research, University of Leicester, Leicester, UK

Andrew Willis

School of Health Sciences, Institute of Mental Health, University of Nottingham, Nottingham, UK

Stefan Rennick-Egglestone

NIHR Evaluation, Trials and Studies Coordinating Centre (NETSCC), Southampton, UK

Mark Townsend

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Contributions

All authors contributed to designing the RE-MIND study. All authors contributed to the selection and refinement of the recommendations. MI and KS drafted the initial manuscript. All authors reviewed and edited drafts of the manuscript. All authors accepted the final version of the manuscript.

Corresponding author

Correspondence to Kirsty Sprange .

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Ethics approval and consent to participate.

The RE-MIND study received approval from the University of Nottingham Research Ethics Committee (FMHS 13–0422) on 13 June 2022.

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The authors declare no competing interests.

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Iflaifel, M., Hall, C.L., Green, H.R. et al. Using online methods to recruit participants into mental health clinical trials: considerations and recommendations from the RE-MIND study. Trials 25 , 596 (2024). https://doi.org/10.1186/s13063-024-08435-9

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DOI : https://doi.org/10.1186/s13063-024-08435-9

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Nominal, Ordinal, Interval & Ratio Data

Levels of measurement: explained simply (with examples).

By: Derek Jansen (MBA) | Expert Reviewed By Dr. Eunice Rautenbach | November 2020

If you’re new to the world of quantitative data analysis and statistics, you’ve most likely run into the four horsemen of levels of measurement : nominal, ordinal, interval and ratio . And if you’ve landed here, you’re probably a little confused or uncertain about them.

Don’t stress – in this post, we’ll explain nominal, ordinal, interval and ratio levels of measurement in simple terms , with loads of practical examples .

Overview: Levels of measurement

Here’s what we’ll be covering in this post. Click to skip directly to that section.

• What are levels of measurement in statistics?
• Nominal data
• Ordinal data
• Interval data
• Why does this matter?
• Recap & visual summary

Levels of Measurement 101

When you’re collecting survey data (or, really any kind of quantitative data) for your research project, you’re going to land up with two types of data –  categorical  and/or  numerical . These reflect different levels of measurement.

Categorical data  is data that reflect characteristics or categories (no big surprise there!). For example, categorical data could include variables such as gender, hair colour, ethnicity, coffee preference, etc. In other words, categorical data is essentially a way of assigning numbers to qualitative data (e.g. 1 for male, 2 for female, and so on). 

Numerical data , on the other hand, reflects data that are inherently numbers-based and quantitative in nature. For example, age, height, weight. In other words, these are things that are naturally measured as numbers (i.e. they’re quantitative), as opposed to categorical data (which involves assigning numbers to qualitative characteristics or groups).

Within each of these two main categories, there are two levels of measurement:

• Categorical data – n ominal and o rdinal
• Numerical data – i nterval and r atio

Let’s take look at each of these, along with some practical examples.

Need a helping hand?

What is nominal data?

As we’ve discussed, nominal data is a categorical data type, so it describes qualitative characteristics or groups, with no order or rank between categories. Examples of nominal data include:

• Gender, ethnicity, eye colour, blood type
• Brand of refrigerator/motor vehicle/television owned
• Political candidate preference, shampoo preference, favourite meal

In all of these examples, the data options are categorical , and there’s no ranking or natural order . In other words, they all have the same value – one is not ranked above another. So, you can view nominal data as the most basic level of measurement , reflecting categories with no rank or order involved.

What is ordinal data?

Ordinal data kicks things up a notch. It’s the same as nominal data in that it’s looking at categories, but unlike nominal data, there is also a meaningful order or rank between the options. Here are some examples of ordinal data:

• Income level (e.g. low income, middle income, high income)
• Level of agreement (e.g. strongly disagree, disagree, neutral, agree, strongly agree)
• Political orientation (e.g. far left, left, centre, right, far right)

As you can see in these examples, all the options are still categories, but there is an ordering or ranking difference between the options . You can’t numerically measure the differences between the options (because they are categories, after all), but you can order and/or logically rank them. So, you can view ordinal as a slightly more sophisticated level of measurement than nominal.

What is interval data?

As we discussed earlier, interval data are a numerical data type. In other words, it’s a level of measurement that involves data that’s naturally quantitative (is usually measured in numbers). Specifically, interval data has an order (like ordinal data), plus the spaces between measurement points are equal (unlike ordinal data). 

Sounds a bit fluffy and conceptual? Let’s take a look at some examples of interval data:

• Credit scores (300 – 850)
• GMAT scores (200 – 800)
• The temperature in Fahrenheit

Importantly, in all of these examples of interval data, the data points are numerical , but the zero point is arbitrary . For example, a temperature of zero degrees Fahrenheit doesn’t mean that there is no temperature (or no heat at all) – it just means the temperature is 10 degrees less than 10. Similarly, you cannot achieve a zero credit score or GMAT score. 

In other words, interval data is a level of measurement that’s numerical (and you can measure the distance between points), but that doesn’t have a meaningful zero point – the zero is arbitrary. 

Long story short – interval-type data offers a more sophisticated level of measurement than nominal and ordinal data, but it’s still not perfect. Enter, ratio data…

What is ratio data?

Ratio-type data is the most sophisticated level of measurement. Like interval data, it is ordered/ranked and the numerical distance between points is consistent (and can be measured). But what makes it the king of measurement is that the zero point reflects an absolute zero (unlike interval data’s arbitrary zero point). In other words, a measurement of zero means that there is nothing of that variable.

Here are some examples of ratio data:

• Weight, height, or length
• The temperature in Kelvin (since zero Kelvin means zero heat)
• Length of time/duration (e.g. seconds, minutes, hours)

In all of these examples, you can see that the zero point is absolute . For example, zero seconds quite literally means zero duration. Similarly, zero weight means weightless. It’s not some arbitrary number. This is what makes ratio-type data the most sophisticated level of measurement. 

With ratio data, not only can you meaningfully measure distances between data points (i.e. add and subtract) – you can also meaningfully multiply and divide . For example, 20 minutes is indeed twice as much time as 10 minutes. You couldn’t do that with credit scores (i.e. interval data), as there’s no such thing as a zero credit score. This is why ratio data is king in the land of measurement levels.

Why does it matter?

At this point, you’re probably thinking, “Well that’s some lovely nit-picking nerdery there, Derek – but why does it matter?”. That’s a good question. And there’s a good answer .

The reason it’s important to understand the levels of measurement in your data – nominal, ordinal, interval and ratio – is because they directly impact which statistical techniques you can use in your analysis. Each statistical test only works with certain types of data. Some techniques work with categorical data (i.e. nominal or ordinal data), while others work with numerical data (i.e. interval or ratio data) – and some work with a mix . While statistical software like SPSS or R might “let” you run the test with the wrong type of data, your results will be flawed at best , and meaningless at worst. 

The takeaway – make sure you understand the differences between the various levels of measurement before you decide on your statistical analysis techniques. Even better, think about what type of data you want to collect at the survey design stage (and design your survey accordingly) so that you can run the most sophisticated statistical analyses once you’ve got your data.

Let’s recap.

In this post, we looked at the four levels of measurement – nominal, ordinal, interval and ratio . Here’s a visual summary of each.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

17 Comments

Clear, concise with examples. PLUS in your videos you include other names or terms that could apply to the topic you are reviewing. This is so important! You are fantastic! It has been many, many, many moons ago that these were learned. They are now necessary again as the nursing profession progresses deeper into evidence based practice.

Thanks for the feedback, Diana 🙂

Good explanation.. I came here after giving 5 marks for each question in a quiz n wondering that the data is not continuous and how to analyse it further.. Understood it is ratio and i can use mean/ median accordingly

Glad it helped!

Bloody good! You saved my homework (:

Happy to help 🙂

High quality of education stuff, thank you very much.

great knowledge shared here. I had problem understanding this at the undergraduate school but very clear now. Thanks to GRADCOACH

What type of data would age be? Ratio or interval?

It would be ratio. However, if you are using age ranges (e.g. 18 – 25, 26 – 35, etc.), this wouldn’t be the case.

What is age ranges considered?

What measurement scale is ideal to use when measuring “knowledge” and the acceptable responses are “yes,” “no,” or “not sure”? What kind of analytical test is suitable in this situation?

I watched your youtube tutorial on quantitative analysis and it was really informative.

However, I’m trying to navigate your blog to find the post that discusses the different inferential statistical methods and the data type they support.

Kindly forward this link to my email : [email protected]

Scores from a performance test are ratio data?

It is an excellent discussion about levels of measurement.

Pretty! This was an incredibly wonderful article. Thanks for providing this info.

Thank you so much for this information! The study material was vague.

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