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Language and rigour in qualitative research: problems and principles in analyzing data collected in Mandarin
Helen J Smith1, Jing Chen, Xiaoyun Liu
1International Health Group, Liverpool School of Tropical Medicine, Liverpool, UK. cjdhel@liv.ac.uk
BMC Medical Research Methodology
|July 12, 2008
Summary
Collaborative qualitative research in Asia faces language barriers during data analysis. This study offers practical solutions for maintaining data rigor and analytical openness when working with local languages.
Area of Science:
- Qualitative Research Methods
- Cross-cultural Research
- Public Health Research
Background:
- Qualitative research in Asia often involves data collection in national languages, presenting significant analytical challenges.
- Translation of transcripts is time-consuming, costly, and risks losing data meaning and validity.
- Language barriers can impact the depth, detail, and interpretation of qualitative data.
Purpose of the Study:
- To highlight the influence of language on the rigor of qualitative research processes in Asia.
- To propose practical solutions for overcoming language-related challenges in collaborative qualitative research.
- To share methods developed from public health research conducted in mainland China.
Main Methods:
- Drawing on published examples from public health research in mainland China.
- Analyzing challenges encountered in collecting, managing, and interpreting qualitative data in Mandarin.
- Suggesting solutions based on methods used in a specific research project in China.
Main Results:
- Identified challenges include achieving data depth, selecting data collection languages, managing Mandarin data, and language's influence on interpretation.
- Proposed methods aim to maintain analytical openness in collaborative qualitative research.
- Developed methods specifically for Mandarin data in mainland China.
Conclusions:
- Language presents significant challenges in collaborative qualitative research in Asia.
- The proposed methods offer potential solutions for maintaining data rigor and analytical openness.
- Further testing in diverse linguistic contexts and collaboration with other researchers are needed.
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