Open AccessInductive and Deductive: Ambiguous Labels in Qualitative Content Analysis
Author(s) -
Mohammad Reza Armat,
Abdolghader Assarroudi,
Mostafa Rad,
Hassan Sharifi,
Abbas Heydari
Publication year - 2018
Publication title -
the qualitative report
Language(s) - English
Resource type - Journals
ISSN - 2160-3715
DOI - 10.46743/2160-3715/2018.2872
Subject(s) - qualitative research , dualism , qualitative analysis , ambiguity , content analysis , content (measure theory) , sort , epistemology , process (computing) , simple (philosophy) , computer science , psychology , information retrieval , sociology , mathematics , philosophy , social science , mathematical analysis , programming language , operating system
The propounded dualism in Content Analysis as quantitative and qualitative approaches is widely supported and justified in nursing literature. Nevertheless, another sort of dualism is proposed for Qualitative Content Analysis, suggesting the adoption of "inductive" and/or "deductive" approaches in the process of qualitative data analysis. These approaches have been referred and labelled as "inductive" or "conventional"; and "deductive" or "directed" content analysis in the literature. Authors argue that these labels could be fallacious, and may lead to ambiguity; as in effect, both approaches are employed with different dominancy during the process of any Qualitative Content Analysis. Thus, authors suggest more expressive, comprehensive, yet simple labels for this method of qualitative data analysis.