In the previous post we learned that qualitative studies can be reported in ways to ensure research design, measurement, data analysis and data itself are made transparent. Economics researchers Aguinis and Solarino conducted a literature search and developed 12 criteria for research transparency, covering research design, measurement, data analysis and data disclosure. They emphasize that transparency exists on a continuum. Not all criteria apply to all studies, but the more criteria a study satisfies, the more trustworthy and reproducible it becomes.

The authors make recommendations on what to include to satisfy the criteria. While the criteria can seem a little general, the authors list examples of characteristics that would satisfy the criteria, and cite a reference that addressed the criterion well. Here is their summary table:

Fig 1. Summary of recommendations for transparency and replicability in qualitative research, and examples of how each criterion can be implemented (Article licensed: CC BY 4.0)

In the Discussion, Auginis and Solarino also recommend that journal editors and reviewers use transparency criteria to judge and enhance research transparency in manuscripts. For example, assessments of research transparency could be easily added to existing reviewer evaluation forms. Detailed descriptions of procedures and choices in qualitative research allow readers to interpret results and conclusions correctly.

We hope that highlighting these criteria will help enhance and improve transparency of reporting in qualitative research.

Reference

Aguinis H and Solarino AM (2017) Transparency and replicability in qualitative research: The case of interviews with elite informants. Strat Mgmt J 40:1291-1315.