Open AccessImproving Data Quality and Avoiding Pitfalls of Online Text-Based Focus Groups: A Practical Guide
Author(s) -
Lilla Vicsek
Publication year - 2016
Publication title -
the qualitative report
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.335
H-Index - 35
ISSN - 2160-3715
DOI - 10.46743/2160-3715/2016.2368
Subject(s) - focus group , focus (optics) , computer science , quality (philosophy) , data science , advice (programming) , online discussion , qualitative research , data quality , psychology , internet privacy , world wide web , sociology , epistemology , engineering , social science , philosophy , physics , anthropology , optics , metric (unit) , operations management , programming language
Despite the fact that there are several practical advantages of online typed focus groups, this type of group questioning has not spread as widely as had been expected when it appeared as a new research option. One of the reasons for that might be that a major risk of these text-based focus groups is inadequate data quality. Unless certain measures are taken to prevent this, an analysis can face the problem of not being rich enough and not digging deep enough – which are often important criteria for good qualitative analysis. This article discusses how to deal with the problem and other possible pitfalls of this type of group discussion, and gives practical advice on how to obtain the best results from such discussions. It also gives suggestions which can be useful if a free chat platform is being used to conduct these groups. It argues that even nowadays with other online techniques available, online text-based focus groups can be useful – if executed properly.