The Devil is in the Details :-)

As our interviewers march forward and collect their four interviews, we continue to review their work to check for quality and adherence to required standards. It is no small task to locate potential participants, contact them, and eventually secure the interview. It is perhaps not surprising then, that by the time we get to the actual interviews - they are a bit of a relief, given how much work it took just to get to this point!

This said we need to remember to pay attention to detail when we are interviewing/collecting and recording data. As others have noted, the interviewer is in a unique position to obtain quality data (MacLin & Calder, 2006). As our protocol is about one hour long – there are a lot of seemingly minute steps to take before the data can be considered ‘collected’ and it is important to pace oneself while collecting so as to be sure we have done the best we can at this. Not only do all lines/spaces for data entry need to be clearly filled in, but it is helpful to see notes taken in the margins of the raw data so that we can get a more comprehensive look at our participants.

Data work, including data entry can be impacted by a variety of factors (Marson, Taylor, Ashby, & Cassell, 2005) – including training. Hopefully, the feedback we are providing our RAs will tighten our data collection and overall quality. Making sure we dot our i's and cross our t's is not as fun as interviewing itself and it is not as glamorous, so to speak, as seeing one's name in a journal publication or being able to describe the study that we have 'completed'. Detailed, precise data collection, however, *is* a necessary evil in order for the latter two events to occur and I would argue, it is the best way to respect the time and effort our participants have donated.

AES

MacLin, M.K. & Calder, J.C. (2006). Interviewers’ ratings of data quality in
household telephone surveys. North American Journal of Psychology,
8(1), 163-170.

Marson, R., Taylor, D.M., Ashby, K. & Cassell, E. (2005). Victoria Emergency
minimum dataset: Factors that impact upon the data quality. Emergency
Medicine Australasia, 17(2), 104-112.