Iterative categorization (IC): a systematic technique for analysing qualitative data
Iterative categorization (IC): a systematic technique for analysing qualitative data
复制标题
DOI：
10.1111/add.13314
复制
发表时间：
2016-06-01
期刊：
影响因子：
6
通讯作者：
Neale, Joanne
中科院分区：
文献类型：
--
作者：
Neale, Joanne
分析定性数据的过程，特别是编码和发表之间的阶段，在成瘾科学和更广泛的研究中往往是模糊的和/或解释不清的。描述了一种简单但严格和透明的技术，用于分析成瘾领域内开发的定性文本数据。迭代分类（IC）技术适用于归纳和演绎代码，可以支持一系列常见的分析方法，例如主题分析、框架、持续比较、分析归纳、内容分析、会话分析、话语分析、解释性现象学分析和叙事分析。一旦数据被编码，唯一需要的软件就是一个标准的文字处理包。提供了工作示例。
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.