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Ethnography: Number of Observations

The following is a modified excerpt from Applied Qualitative Research Design: A Total Quality Framework Approach (Roller & Lavrakas, 2015, pp. 199-201), a qualitative methods text covering in-depth interviews, focus group discussions, ethnography, qualitative content analysis, case study, and narrative research.

An important decision that ethnographic researchers need to make is the ethnographynumber of observations to conduct, or, more accurately, the number of:

  • Sites to observe.
  • People within sites to observe.
  • Observational events (e.g., how often to revisit a particular site).

Addressing this question can be complex—a process of both art and science—or fairly straightforward. In the simplest case, the number of sites to observe and observation events will be dictated by the (1) breadth and depth of the research objectives, (2) breadth and depth of the target population, and/or (3) practical realities of the research (e.g., the accessibility of the target participants, financial resources, and time available to complete the study). If, for example, the research objective is to examine the implementation of new procedures at a county free clinic, the number of sites to observe is just one (the clinic) and the frequency of observations will be determined by such factors as the fluctuation in the patient load (i.e., the slow- and high-volume hours in the clinic) and level of procedural details the observer wants to capture.

A more complex situation arises when the focus of the research is on a broad target population such as consumers. For instance, ethnographic research to study how consumers shop for vitamins would most likely require many observations of the same or different individuals within a variety of retail environments (e.g., supermarkets, drug stores, and superstores such as Read Full Text

Focus Groups: Heterogeneity vs. Homogeneity

The following is a modified excerpt from Applied Qualitative Research Design: A Total Quality Framework Approach (Roller & Lavrakas, 2015, pp. 107-109).

Heterogeneity

homogeneity

Fundamental to the design of a focus group study is group composition. Specifically, the researcher must determine the degree of homogeneity or heterogeneity that should be represented by the group participants. As shown below, there are many questions the researcher needs to contemplate, such as the extent of similarity or dissimilarity in participants’ demographic characteristics, as well as in their experiences and involvement with the subject matter.

Questions When Considering Heterogeneity vs. Homogeneity
A few of the questions the focus group researcher might consider when determining the desired heterogeneity or homogeneity among group participants include:

  • Should participants be in the same age range and/or stage of life?
  • Should participants be the same gender, race, and/or ethnicity?
  • Should participants be at a similar income, socio-economic, or educational level?
  • Should participants reside in the same community, be members of the same organization(s)?
  • Should participants have similar professions or jobs (including, job titles)?
  • Should participants have a similar involvement, experience, or knowledge with the research topic, e.g., the same types of problems with their 13 year old boys? the same healthcare service provider? the same purchase behavior? the same level of expertise with a new technology?

Whether or not—or the degree to which—group participants should be homogeneous in some or all characteristics has been at the center of debate for some years. On the one hand, Grønkjær, Curtis, Crespigny, and Delmar (2011) claim that at least some “homogeneity in focus group construction is considered essential for group interaction and dynamics” (p. 23)—for example, participants belonging to the same age group may have similar frames of reference and feel comfortable sharing their thoughts with people who have lived through the same experience. In the same vein, Read Full Text

The Qualitative Analysis Trap (or, Coding Until Blue in the Face)

There is a trap that is easy to fall into when conducting a thematic-style analysis of qualitative data. The trap revolves around coding and, specifically, the idea that after a general familiarization with the in-depth interview or focus group discussion content the researcher pores over the data scrupulously looking for anything deemed worthy of a code. If you think this process is daunting for the seasoned analyst who has categorized and themed many qualitative data sets, consider the newly initiated graduate student who is learning the process for the first time.

Recent dialog on social media suggests that graduate students, in particular, are susceptible to falling into the qualitative analysis trap, i.e., the belief that a well done analysis hinges on developing lots of codes and coding, coding, coding until…well, until the analyst is blue in the face. This is evident by overheard comments such as “I thought I finished coding but every day I am finding new content to code” and “My head is buzzing with all the possible directions for themes.”

Coding of course misses the point. The point of qualitative analysis is not to deconstruct the interview or discussion data into bits and pieces, i.e., codes, but rather to define the research question from participants’ perspectives Read Full Text