Coding In-depth Semistructured Interviews

TLDR

Many social science studies rely on coded in‑depth semistructured interview transcripts, yet coding reliability is rarely reported and literature on this topic is sparse. The article proposes a procedure for developing coding schemes for coded in‑depth semistructured interview data. The procedure standardizes text units and refines the coding scheme’s discriminant capability to achieve acceptable intercoder reliability or agreement. The approach proves especially useful when a single knowledgeable coder codes all transcripts after the scheme is established, and it is also applicable to other qualitative data and contexts.

Abstract

Many social science studies are based on coded in-depth semistructured interview transcripts. But researchers rarely report or discuss coding reliability in this work. Nor is there much literature on the subject for this type of data. This article presents a procedure for developing coding schemes for such data. It involves standardizing the units of text on which coders work and then improving the coding scheme’s discriminant capability (i.e., reducing coding errors) to an acceptable point as indicated by measures of either intercoder reliability or intercoder agreement. This approach is especially useful for situations where a single knowledgeable coder will code all the transcripts once the coding scheme has been established. This approach can also be used with other types of qualitative data and in other circumstances.