Qualitative research can be used to thoroughly explore a new and unknown topic. It enables us to obtain a detailed view of a topic, while incorporating relevant complexities and subtleties connected to this topic. Qualitative research is often inductive, and can be used to develop new theories. Qualitative research enables us to study individuals in their natural settings or to examine certain programs, policies and events within a specific context.

1. Qualitative approaches/designs

Ethnography: Rooted in social and cultural anthropology, ethnography is about obtaining an understanding of a group of people through immersion; the researcher observes the participants in their natural setting and tries to see and interpret the world as it is perceived by these participants. Watching and listening must precede analysis and generalization of the findings. Ethnography is an inductive, interactive and holistic approach.

Phenomenology: The goal of phenomenological research is to describe, interpret and understand the meaning of someone’s lived experience. In public health, phenomenological research can help develop an understanding of how people experience their situation (e.g. being in a hospital, having diabetes, giving birth to a handicapped child, or being terminally ill).

Grounded theory: Grounded theory is used to scrutinize a process, action, or interaction with the intention of developing a theory. It utilizes the systematically collected and analysed data during the research process, and the research process is highly iterative; as a researcher you continuously interact with the research subject(s) until a level of knowledge and data saturation is reached. Grounded theory explains and shows depth of the researched phenomenon. It is a creative process which is used when there is no sufficient theory or knowledge related to the researched problem, and existing theories do not offer the solutions.

Case study: Case study research thoroughly investigates one or a small number of cases, focusing on numerous details within each case and the context. Case study research creates opportunities to elaborate on a situation holistically, capturing its complexity while incorporating multiple perspectives. Furthermore, case-study research is highly heuristic – as it provides opportunities for further learning, discovery, or problem solving – and has high conceptual validity, meaning that it enables one to ‘identify concepts that are of greatest interest and move toward their core or essential meaning in abstract theory’. Case study research does often incorporate an a priori theoretical framework.

Narrative: The narrative approach explores an individual story and describes someone’s life. It explores what the story means and what lessons can be drawn from it.

2. Methods of data collection

  • Participant observation
  • Interviews (semi-structured, structured, unstructured, in-depth)
  • Focus groups
  • Text/discourse analysis
  • Conversation/video analysis


3. Sampling in qualitative research

In qualitative research, it is often not the goal to obtain a representative sample drawn from a large number of cases. This does imply that findings cannot be used to produce inferences on a population level, but this is generally not the intention of qualitative research to begin with. For qualitative research we generally use a form of nonprobability sampling (also called non-random sampling). The following 8 sampling methods are all examples of nonprobability sampling:

Sampling methodElaboration
ConvenienceGet any cases in any manner that is convenient.
PurposiveUse a wide range of methods to get as many cases as possible fitting a certain profile. Often used to select members of a highly specific, hard-to-reach population (e.g. illegal immigrants).
SnowballBeginning with one or a few participants, the researcher identifies new participants based on information and referrals offered by those initial participants. As those new participants also provide new information and referrals, the number of potential participants generally grows exponentially.
Deviant CaseIdentify unusual and nonconforming cases to obtain an insight into social processes or a setting. The intention is to locate unusual and different cases that are not representative of the whole population. It can sometimes help to obtain unique insights to social developments. Similar to purposive sampling, we use a variety of techniques to locate cases.
SequentialQuite similar to purposive sampling, although with sequential sampling one continues to collect new cases/participants until a level of data saturation is reached (meaning no new information is obtained from including additional cases).
TheoreticalCases/participants are selected based on the expectation that they can help reveal features that are theoretically important for the specific setting and topic of a study. This sampling method is very compatible with a grounded theory approach.
AdaptiveIdentify a few cases of a hidden population (similar to purposive sampling). From here one, use a snowball sampling technique to identify additional cases and expand your research network. Adaptive sampling techniques can be useful to get in touch with hard-to-reach and concealed groups (often the case when studying a stigmatized, clandestine or socially disapproved phenomenon).
QuotaGet a fixed number of cases in each of several predetermined categories that will reflect the diversity of the population.

4. Analysis of qualitative data

There are various ways to analyse qualitative data. One frequently used method is the grounded theory approach of open, axial, and selective coding, as developed by Glaser and Strauss (1967). This inductive method is very thorough due to the three consecutive coding stages, but also very time-intensive, often requiring a verbatim transcription of all the data that were obtained.

For analysing qualitative interviews, one can also use the more time-saving method of directed content analysis. One important advantage of this method is that it does not necessarily require a verbatim transcription of the interview data, as it also allows for analysing data in verbal form. With a directed approach to content analysis one can validate or extend conceptually a theoretical framework or theory, as it works with prior formulated, theoretical derived aspects of analysis. This results in this form of content analysis being rather deductive in nature, and it is often applied in studies where the researcher adheres to a predetermined theoretical framework. This theoretical framework is useful for creating initial coding categories. Using these initial coding categories, relevant findings from an audio-recording or text can be transcribed (if needed) and categorised. Relevant data that cannot be coded immediately can then be identified and analysed to determine if they represent a new category or a subcategory of an existing code.

5. Strengths of qualitative research designs

The following characteristics can generally be perceived as strengths of qualitative research designs:

  • Obtain an in-depth understanding of a topic
  • Incorporation of the human element
  • Detailed view of a topic and its complexities, nuances and subtleties
  • Theories can be (further) developed
  • Often granting a certain degree of flexibility to continuously adjust and optimise the process of data collection


6.Weaknesses of qualitative research designs

The following characteristics can generally be perceived as weaknesses of qualitative research designs:

  • Very limited generalizability of findings
  • Volume and type of data often are difficult and complex to analyse
  • Limited reproducibility
  • Difficult to include a big sample



In qualitative research, the terms validity and reliability are not that often used. The following table illustrates how terminology in quantitative research relates to terminology in qualitative research.

Quantitative conceptEquivalent in qualitative research
ValidityCredibility / Truthfulness / Authenticity
ReliabilityDependability / Consistency

In qualitative research, the overarching theme is trustworthiness, meaning the degree of confidence researchers have in the data. The following criteria contribute to the overall trustworthiness of a study:

  • Credibility: Confidence in truth of the data and interpretations of them. The aim is to accurately capture and convey an inside view of how the people we study experience and interpret a phenomenon.
  • Dependability: Stability of data over time and over conditions so that the findings will be consistent and accurate.
  • Transferability: The extent to which the findings can be transferred to other settings or groups.
  • Confirmability: Objectivity of the results, that is, assuring that the findings are not the result of the researcher’s prior assumptions and preconceptions.