An interviewer may bias research outcomes in any number of ways. For instance, he or she may allow personal beliefs or expectations to skew how questions are asked and/or responses are recorded. Or, the interviewer's physical characteristics (e.g., associated with gender, race, ethnicity, as well as manner of dress and demeanor) may weaken the interviewer-interviewee relationship and an otherwise trusting research environment which is essential to gaining accurate and useful qualitative data.
It is not, however, only interviewer bias that can lead to distorted outcomes but also interviewer inconsistency. This is an important distinction. An interviewer that has biased the results has done something to provoke false information from the interviewee in response to the research questions. Interviewer inconsistency, on the other hand, does not lead to inaccurate information from the interviewee but rather variation in the data that does not truly exist. A researcher, for example, conducting face-to-face interviews with public school teachers about their use of electronic media in the classroom may do nothing to elicit erroneous information from the teachers yet produce data suggesting a wide range of media use when, in fact, this is not the reality. The researcher might do this by: 1) not specifying what is included under "electronic media" for some participants; 2) defining it as audio and video recordings and PowerPoint presentations for other participants; and 3) defining electronic media as audio/video recordings, slide presentations, the Internet, television, radio, phone, and computer devices for yet another set of participants. The interviewer's inconsistent reference to "electronic media" will ultimately produce an unrealistic picture of what actually goes on in the classroom, a picture that suggests a greater variation in the use of electronic media than is true.
Inconsistency also presents problems in observational research (i.e., ethnography). Consider an ethnographic study involving the observation of passengers at major train stations on the East Coast, with a particular focus on observations related to 1) passengers waiting for a train, 2) unexpected delays in the train schedules, and 3) passengers boarding a train. An observer who (due to fatigue or for other reasons) fails to consistently observe these three target scenarios – e.g., observes all three situations at some stations, passengers waiting and unexpected delays at other stations, and only passengers boarding at still other stations – jeopardizes the research outcomes and ultimately provides data of little value.
Let's be clear. Qualitative research thrives on the flexibility and nimbleness of the researcher. This is an important quality that allows the researcher to reap all the complexity and context inherent in gaining meaning in qualitative research. But a good qualitative researcher understands that flexibility is not the same thing as an "anything goes" approach where no consideration is given to how the data are gathered. Like researcher bias, knowing when and how to avoid inconsistency – and add consistency – in data collection is an essential ingredient in the recipe for a quality qualitative research design.
Qualitative research is a good major. Few researchers understand the methodologies.