My question is how we can increase transparency in qualitative research, especially when it comes to single case studies. Robert Yin (2009) suggests that we use a study protocol, but I haven't really understood what this means and how it increases the transparency of a scientific paper.
I think a good option is Open Data philosophy. For example, publishing your fieldwork notes, interview transcripts or data base in the institutional repository of your university/research center.
This, together with making reference to the process of data production, and your position in relation to the research problem, should be enough to make your qualitative study "transparent"
Dear Beltrán, I agree with you. Thank you for your comments.
Regards.
Yin has an another book, on Application of Case Study, which includes lots of examples. Also, I believe that the newest edition of his basic book now has applications integrated into it.
The main objective in implementing a study protocol in qualitative research is to provide a detailed account of the hypothesis, rationale and methodology of the study. By describing the background, rationale, objectives, design, methodology, statistical considerations, and organization of the case under scrutiny, we can make the confirmability and credibility of the outcomes more transparent. The following links can hopefully provide you with more details in this regard:
www.labquality.be/.../Eriksen_2004_How%20to%20write%20a%20study%20Protoco...
orrp.osu.edu/files/2011/10/GuidelinesforWritingaResearchProtocol.pdf
in.bgu.ac.il/humsos/soc-ant/DocLib/...examples/Protocol_Form_Examples.pdf
Best of luck,
R. Biria
Dear all, thank you for taking your time to answer my question. They have all been very helpful.
I find that it is much harder to discuss the researcher's transparency in a qualitative research that has not been based on field work, such as interviews -but instead only on analysis of written sources. Do you believe that the lack of transparency in qualitative research, based on an analysis of written sources, is something that we just have to take granted for or are there any recommendations on how to handle this issue?
Best,
In addition to being transparent about methods and data, I think self-reflexivity is essential. Denzin and Goodall have written well about the role of self-reflexivity and developing a transparent, authentic and trustworthy voice in qualitative writing. Also you could check out R. Hertz's edited volume published with Sage, _Reflexivity & Voice.
A good way to guarantee the transparency of your qualitative study is to pre-register it on an open science platform. You prepare a protocol, upload it, stick to your plan and if need be, report any changes to the protocol that were necessary to the research process. Some journals will even guarantee publication if you follow this process. A good platform to do this is OSF (http://help.osf.io/m/registrations/l/524205-register-your-project). Pre-registration encourages transparency, good practice and reduces the temptation of reporting bias.
As qualitative research explores perception, opinion, and experiences of peoples in a specific socio-cultural, political and geographical settings, hence absolute objectivity in social and behavioural sciences is impossible. Most of qualitative researchers (feminists)believe that subjective experience of a group are significant to understand the problem associated to it. Self-reflexivity approach is significant for researcher to be transparent. Researcher must reflect on the overall procedure of research and his/her own involvement in the research. Agreeing with Michael S. Jeffress, i would say self-reflexivity is essential in qualitative research.
Single case study design can be used to either solve a context-bound problem or generate a theory about some phenomenon. In both the cases, researchers need to make sure that two conditions are met: one, that the phenomenon under study is complex and two, that multiple sources of data are available that can be used for understanding and drawing theoritical abstrations.
You can use sequential explanatory designs to further validate your qualitative results. Photovoice technique is a good way too.
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