Supporting Observational Research

The following is a modified excerpt from Applied Qualitative Research Design: A Total Quality Framework Approach (Roller & Lavrakas, 2015, pp. 217-219) which is a qualitative methods text covering in-depth interviews, focus group discussions, ethnography, qualitative content analysis, case study, and narrative research.

An important element in the Total Quality Framework Analyzability component is Verification, i.e., taking steps to establish some level of support for the data gathered in order to move the researcher closer to achieving high quality outcomes. The verificationSupporting qualitative data tools at the ethnographer’s disposal go beyond those identified for the in-depth interview (IDI) and group discussion methods in that they include the technique of expanded observation. For example, Lincoln and Guba (1985) stated that it is “more likely that credible findings and interpretations” will come from ethnographic data with “prolonged engagement” in the field and “persistent observation” (p. 301). The former refers to spending adequate time at an observation site to experience the breadth of stimuli and activities relevant to the research, and the purpose of the latter (i.e., persistent observation) is “to identify those characteristics and elements in the situation that are most relevant to the problem or issue” (p. 304)—that is, to provide a depth of understanding of the “salient factors.” Both prolonged engagement and persistent observation speak to the idea of expanding observation in terms of time as well as diligence in exploring variables as they emerge in the observation. Although expanding observations in this way may be unrealistic due to the realities of deadlines and research funding, it is an important verification approach unique to ethnography. When practicable, it is recommended that researchers maximize the time allotted for observation and train observers to look for the unexpected or examine more closely seemingly minor occurrences or variables that may ultimately support (or contradict) the observer’s dominant understanding.

The ultimate usefulness of expanded observation is not unlike deviant or negative case analysis (see earlier link). In both instances, the goal is to identify and investigate observational events (or particular variables in these events) that defy explanation or otherwise contradict the general patterns or themes that appear to be emerging from the data. For example, a researcher conducting in-home nonparticipant observations of young mothers may find that infants are typically put back in the crib when they begin to cry, which seems to be a routine behavior among the mothers observed. The observer may come to the assumption that mothers equate crying with fatigue and place their infants in the crib so they can rest. But observations of mothers who do not respond to their crying infants yet put them to bed at similar times of the day may give the observer a different point of view and lead her to explore other factors, such as, the mother’s fatigue and need to be away from the baby. It is this ability to always question assumptions and look for factors that disprove these assumptions that enhance the quality and ultimate usefulness of ethnographic research.

As in all qualitative research, triangulation is an important procedure for investigating support of observational data. The purpose of triangulation, similar to deviant case analysis, is to integrate other ways of looking at the data into the analysis. One example is researcher triangulation, which might include collaborating with other members of the research team in the data collection and processing phases, or asking someone on the research team to review transcripts or the observer’s reflexive journal to give her/his own assessment. As with deviant case analysis, any differences that may surface between the researcher’s and the colleague’s interpretations should be treated as an opportunity to learn more about the underlying meanings from the observations.

Another triangulation-like consideration is offered by Dicks, Soyinka, and Coffey (2006), who discuss the variation of meanings in ethnographic research derived from different media. The idea is that the meaning of an observed event is transformed by the different modes of capturing the data. So, for instance, the researcher needs to consider what meaning in the data is lost or gained by listening to the spoken word in an audio recording compared to reading the written word in text. This “media triangulation” becomes particularly complex in an online context, where hyperlinking makes it nearly impossible to decipher the participant’s experience. For example, as Dicks et al. state, “How does a piece of video film change when linked to a piece of written text? And what kind of reading or interpretation is produced by that linkage when the reader can pursue an almost infinite number of traversals and linkages of his/her own?” (p. 94).


Dicks, B., Soyinka, B., & Coffey, A. (2006). Multimodal ethnography. Qualitative Research, 6(1), 77–96.

Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Beverly Hills, CA: Sage Publications.


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