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Iterative categorization (IC): a systematic technique for analysing qualitative data

Addiction · 2016 · Vol. 111(6) · pp. 1096–1106
Joanne Neale

Abstract

The processes of analysing qualitative data, particularly the stage between coding and publication, are often vague and/or poorly explained within addiction science and research more broadly. A simple but rigorous and transparent technique for analysing qualitative textual data, developed within the field of addiction, is described. The technique, iterative categorization (IC), is suitable for use with inductive and deductive codes and can support a range of common analytical approaches, e.g. thematic analysis, Framework, constant comparison, analytical induction, content analysis, conversational analysis, discourse analysis, interpretative phenomenological analysis and narrative analysis. Once the data have been coded, the only software required is a standard word processing package. Worked examples are provided.

Substance Abuse Treatment and OutcomesCommunity Health and DevelopmentHIV, Drug Use, Sexual RiskCategorizationCoding (social sciences)Computer scienceThematic analysisQualitative researchContent analysisQualitative analysisNarrativeData scienceNatural language processing

MeSH terms

HumansQualitative Research

Funding

  • King's College London
Citations
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