3.1.1.2 Sampling issues in qualitative research: who and how many?

Selection of participants

In qualitative research we select people who are likely to provide the most relevant information (Huston 1998). In order to design the sample and cover all variability around the research issue, the researchers must have an idea about the different perspectives that should be represented in the sample. This is called “field mapping” of the key players who have a certain interest in the problem under study. The role of this explicit “field mapping” is often underestimated but essential in order to build a purposive sample. It is possible that this “field map” evolves during the data collection. The notion of “representativeness” here is not understood in the statistical way. The idea of representation is seen as a “representation of perspectives, meanings, opinions and ideas” of different stakeholders in relation to the problem researched and their interest. In order to select the participants for interviews or focus groups, one should ask “do we expect that this person can talk about (represent) the perspectives (meanings given to the situation) of this stakeholder group”. The aim is to maximize the opportunity of producing enough data to answer the research question ^{(Green 2004)}.

Ideally there should be a mixture of different “population characteristics” to ensure that arguments and ideas of the participants represent the opinions and attitudes of the relevant population. Also the unit of analysis should be taken into account. This could be for example “individuals for their personal opinions/experience/expertise” or “individuals because they represent organizational perspectives”.

Moreover in order to make comparisons within and between types of participants, the sample design should take this already into account. In Table 9, two criteria for comparison, for example age and socio-economic status, are already included to allow comparative analysis between age or status groups.

Sampling approaches

There is a wide range of sampling approaches (e.g. Miles and Huberman 1994, Patton 2002, Strauss and Corbin 2008). It is not uncommon in qualitative research that the research team continues to make sampling decisions during the process of collecting and analysing data. However, a clear documentation of the sampling criteria is needed when doing qualitative research. These criteria should cover all relevant aspects of the research topic. The researcher should identify the central criteria and translate them in observable sample criteria. In addition, the chosen criteria should leave enough variation to explore the research topic ^{(Mortelmans, 2009)}. For example, in a research about factors influencing the decision to have or refrain from having a refractive eye surgery in the two last years, sampling criteria were:

1. To have experienced or to have considered a refractive surgery. We want to explore both the pro and cons.
2. To be older than 20 and younger than 70. Refractive eye surgery is not an option for those younger than 20 or older than 70.

In what follows we describe a number of sampling strategies. All the sampling strategies are non-probabilistic. A randomized sample is not useful in qualitative research, since generalizability to the general population is not the aim. Moreover with a random sample the researcher would run the risk of selecting people who have no link with the research subject and thus nothing to tell about it ^{(Mortelmans, 2009)}. In purposive sampling the point of departure are the sampling criteria as described above. There are different forms of purposive sampling:

• Stratified purposive sampling (Patton, 2002):      
  Purposive samples can be stratified (or nested) by selecting particular persons that vary according to a key dimension/characteristic (e.g. a sample of people from large hospitals, and a different sample with people from small hospitals) and the selection ideally represents the different positions within the ‘system’ or phenomenon under investigation. The stratification criteria are the equivalent of independent variables in quantitative research. The researcher should think ahead about independent variables which could provide new information regarding the research topic. For example, in the research project on refractive eye surgery we expected that reasons to chose or refrain from chosing for refractive eye surgery vary with age, with financial resources and can be different in the Dutch- and French-speaking part of the country. Therefore we added age, socio-economic status and region as criteria introducing heterogeneity. This results in the following matrix:
• Homogeneous sampling:   
  In the case of homogeneous sampling variation between respondents is minimised. Participants are chosen because they are alike, in order to focus on one particular process or situation they have in common ⁽Mortelmans, 2009) . However the homogenous character does not exclude comparisons between types of participants, because for example unanticipated dimensions might emerge from the data. It is also useful to take into account hierarchy, hence not to put for example nurses and specialists working in the same hospital together in a focus group, as this might create bias in the responses.This sampling strategy is used when the goal of the research is to develop an in-depth understanding and description of a particular group with similar characteristics or people on equal foot. For example for the KCE research project on alternative medicines ^48-50 only regular users were sampled.

Table 9 – Example of stratified purposive sample

• Heterogeneous or maximum variation sampling :
  In the case of heterogeneous sampling variation between repondents is maximised, relevant to the research question.
• Extreme or deviant cases sampling:
  For some purposes it can be useful to search for outliers or highly unusual persons or representatives of opinions. A selection of persons that, emerging from an analysis, appear to be the 'exception to the rule' could be considered to get a better understanding of these outliers or “negative cases”. The process of identifying extreme or deviant cases occurs after of the data collection and analysis have been partially completed. Therefore it is a sampling strategy which is always conducted as complementary to other sampling strategies.
• Typical case:         
  Cases are selected from which it is expected that they will provide information about a typical situation. This strategy is used in case of a new research area. If knowledge about a research topic is completely absent, a typical case can provide the basic knowledge necessary to construct theoretical explanations, preparatory to the search for more variation in cases. The typical case is one that occurs frequently ⁽Mortelmans, 2009).
• Critical case sampling:       
  This sampling is especially used in case studies, a research strategy “to understand social phenomena within a single or small number of naturally occurring settings. The purpose may be to provide description through a detailed example (…)” (Bloor and Wood, 2006, p. 27). It can be used when time or resource constraints limit the possibilities to recruit participants. A small number of important cases is selected to "yield the most information and have the greatest impact on the development of knowledge" (Patton, 2002, p. 236). It is crucial that the research team identifies the dimensions that make the participants “critical”. Snowball sampling can be used to identify critical informants who can provide a great deal of information about a phenomenon.
• Theory-based or theoretical sampling:         
  Theoretical sampling refers to the process of selecting "incidents, slices of life, time periods, or people on the basis of their potential manifestation or representation of important theoretical constructs" (Patton, 1999, p. 238).
• Confirming and disconfirming cases:          
  Identification of confirming and disconfirming case occurs after data collection and analysis has partially been completed. Cases are sought to lend further support to an initial analysis or theory (confirming cases), or to disconfirm the theory and provide rival explanations (disconfirming cases). Researchers seek out confirming and disconfirming cases in order to develop a richer, more in-depth understanding of a phenomenon and to lend credibility to one's research account.

Recruitment strategies

In order to achieve the expected sample, several ways to find and recruit participants could be suggested:

• Convenience sampling:      
  It is a pragmatic solution, i.e. selecting respondents based on ease, speed, and low cost, without any in-depth considerations on the selection of the participants. This strategy should ideally be avoided ³³, but in some cases it is the only feasible option due to practical reasons (such as time, costs, etc.). A good description of the sample is especially important with convenience sampling, so that the reader can know how the results came about.
• Snowball sampling:
  This strategy is especially used when the researcher has no clear idea about where to search for respondents or who could provide him with the information he envisions. Hence the researcher searches for one or a few respondents and asks them who else they know could provide information. These individuals are contacted and in their turn asked whether they know other potential respondents. Once indivuals the same names are mentioned, the sample has reached his maximum size ⁽Mortelmans, 2009) .
• At random, but still purposive:
  As already mentioned above a random selection as such is not useful in qualitative research. However, there is one exception: random selection can be used when the researcher by using one of the sampling strategies mentioned above, gets more cases than he can interview or observe with his available time and resources. In that situation randomness can be an additional selection criterion ⁽Mortelmans, 2009).

Sample size

“Determining adequate sample size in qualitative research is ultimately a matter of judgement and experience in evaluating the quality of the information collected against the uses to which it will be put, the particular research method and purposeful sampling strategy employed, and the research product intended” (Sandelowski, 1995, p. 199).

Typically, in qualitative research one should continue sampling until saturation is reached– this is the point at which no new information or themes are emerging from the data³⁵. Therefore sampling goes hand in hand with data analysis and cannot be planned totally in advance. In reality in every research institution, the sample size is also determined in function of the budget, the time and human resources available. This means often practical aspects of the research project may constrain the size of the sample before theoretical saturation is reached. This is also true for KCE working practice, since budgets and time schedules are limited and fixed.

Beware that saturation can be reached prematurely if one's sampling frame is too narrow, if one's analytical perspective is biased or limited; if the data collection method is not resulting in rich, in-depth information or when the researcher is unable to get beyond the surface.

First contact with a respondent

• The first contact with a respondent is often made by telephone. It is very important as it will set the tone for the rest of the interviewing. During this telephone conversation the researcher must convince the respondent of the importance of the research and his participation. To convince the researcher could search for arguments that are important in the eyes of the respondent, rather than arguments in function of the importance of the research. Not too much information should be provided during this first contact. Additional information can be provided by means of an information letter. Box 1 presents information that can be provided during the invitation to participate.

Box 1: Information to be given during first contact

Source: Adapted from Emans, 1986 cited by: Mortelmans, 2009

It is important that people understand that participation in interviews or focus groups is completely voluntary, and that they may choose to leave at any time during the discussion. In addition, it is imperative that participants are aware that they will receive no tangible benefit for participation. That is why the question on offering incentives is often rather contentious ^{(Green et al., 2009)}. Nevertheless their traveling costs could be reimbursed or they can receive a slight compensation or a small gift.

Also it is recommended to leave the choice of place (where the interview will take place) up to the respondent, in order to facilitate his participation. The context in which the interview takes place determines partly the interactions during the interview. For example a patient at home or in the waiting room of a hospital will disclose other kinds of information, not only because he/she feels more or less comfortable, but also because the setting triggers other associations and thoughts. The interviewer/researcher should be well aware of and anticipate the impact the interview location is likely to have on the data generated.

The same accounts for the characteristics of the interviewer. In the qualitative interview the researcher empathizes with his or her respondents and views their situation from their own points of view⁵³. In general this empathic stance as well as gaining trust from the respondent, is facilitated if the interviewer resembles the respondent in terms of race or other characteristics relevant to the research topic. Gender however is an exception to this rule. There is a debate in the literature about whether same sex or opposite sex is preferable in order to achieve rapport during interviews. Some argue that men are more comfortable in talking with women (especially about intimate topics) that they are with other men ^{(Williams, 1993)}.