An extended briefing and debriefing technique to enhance data quality in cross-national/language mixed-method research

S. Chereni*, R.V. Sliuzas, J. Flacke

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)
241 Downloads (Pure)


Mixed methods surveys using multilingual assistants in areas without clear pre-defined sampling units are often difficult to manage and unpredictable, thereby threatening data quality. More so when such surveys are executed in unfamiliar territories where cultural and language barriers prevent direct communication between the principal researcher and the respondents, and field assistants act as cultural/language brokers. This paper provides a method to enhance data quality in such contexts through a reflection on the research design and data collection experience in our study on flood damage mitigation processes among households and businesses in Kampala. Associated field challenges included different disciplinary and language skills levels of assistants, their multiple positionalities when translating concepts from the inquiry language to the source language and vice-versa, low settlement permeability/accessibility, multiple households per sampling unit, and socio-psychological issues among respondents and research assistants. The available literature lacks comprehensive systematic methods to address the challenges above, using detailed research fieldwork management experiences in which data collection is outsourced from field assistants. Our application of an extended version of the briefing and debriefing technique closes this gap. As a guide to apply this approach, we conceptualize social science research into four inter-related dimensions – paradigm, people, process, and presentation.
Original languageEnglish
Pages (from-to)661-675
Number of pages15
JournalInternational Journal of Social Research Methodology: Theory and Practice
Issue number6
Early online date25 Feb 2020
Publication statusPublished - 1 Nov 2020


  • UT-Hybrid-D
  • data quality
  • multilingual assistants
  • multiple positionalities
  • language research
  • briefing and Debriefing
  • Cross-national


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