In this paper, the author reflects on his own experience of using NVivo. While the issue of mastering CAQDAS has received ample attention, little has been done to address the misconceptions associated with the use of CAQDAS.
#Remove coding from node in nvivo 12 software#
This may be due to the hassles that one has to go through to master the software and or the misconceptions that are associated with using CAQDAS 7. Although CAQDAS has been available since 1984, very few qualitative health researchers (16%) report using it 7. (Systematic Review and Meta-Analysis) 6 used NVivo to manage data for their respective different study designs. The software is not methodological-specific, it works well with wide range of qualitative research designs and data analysis methods such as discourse analysis, grounded theory, conversation analysis, ethnography, literature reviews, phenomenology, and mixed methods. Moreover, the strength of NVivo lies in its high compatibility to research designs. Additionally, NVivo also has in-built facilities that allow people from different geographical spaces to work on the same data files at the same time through a network. He stated that above and beyond NUD*IST, NVivo has features such as character-based coding, rich text capabilities and multimedia functions that are crucial for qualitative data management. In his paper, Tom Richards, the co-developer of the program, justified the birth of NVivo in the face of the reputation and long history of NUD*IST. The developers of the software have described it as an improved and expanded version of the NUD*IST 3. NVivo, one of the current popular qualitative data management programs, has its roots in the NUD*IST. The dawn of CAQDAS was marked by the development of a program called Non-numerical Unstructured Data Indexing Searching and Theorizing (NUD*IST), which was specifically designed for qualitative data management in 1980's. To lessen this burden, it is important that health researchers become aware of the possibilities of using Computer Assisted Qualitative Data Analysis Software (CAQDAS) such as ATLAS.ti, MAXqda, NVivo and N6.
The systematic and rigorous preparation and analysis of qualitative data is usually time consuming and labour intensive 2. Qualitative research usually produces large amounts of textual data in the form of transcripts and field notes. In recent years, there has been an increase in number of qualitative studies been carried out by health professionals. However, when we want to broaden or deepen our understanding of how things came to be the way they are in our social world, qualitative research has no substitute 1. Quantitative research tells us how often or how many behave in a certain way. CAQDAS are basically data management packages, which support the researcher during analysis. In other words, researchers must equally know that no software can analyse qualitative data.
The key message is that unlike statistical software, the main function of CAQDAS is not to analyse data but rather to aid the analysis process, which the researcher must always remain in control of. In this paper, the author reflects on his experience of interacting with one of the popular CAQDAS (NVivo) in order to provide evidence-based implications of using the software. While the issue of mastering CAQDAS has received ample attention, little has been done to address the misconceptions associated with CAQDAS. This may be due to the difficulties that one has to go through to master the software and the misconceptions that are associated with using CAQDAS. Although the CAQDAS has been there for decades, very few qualitative health researchers report using it. However, Computer Assisted Qualitative Data Analysis Software (CAQDAS) are increasingly being developed. For a long time, electronic data analysis has been associated with quantitative methods.
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