Assessing qualitative data richness and thickness: development of an
evidence-based tool for use in qualitative evidence synthesis Short
running title: A data thickness/richness assessment tool
Abstract
This paper introduces version one of an assessment tool developed to
address the challenges posed by the assessment of data thickness and
richness in primary qualitative studies for Qualitative Evidence
Syntheses (QES). The tool has been in development since 2014. Three
pilot versions from three review teams have been used in six Cochrane
reviews. Key members from the original three review teams came together
to create a consensus-based definitive version 1 of the tool for
publication. Four review authors piloted the version 1 tool. The
definitive version 1 assessment tool consists of two components:
assessing the thickness of contextual data and assessing the richness of
conceptual data. A sliding scale with four points is used to rate these
aspects, offering nuanced and qualitative judgments. The accompanying
guidance emphasizes the importance of assessing data that addresses the
review question. Paragraph locked by Heather Melanie R Ames The paper
provides guidance on how to apply the tool, emphasizing the importance
of reaching a consensus among review authors, and fostering a shared
understanding of what constitutes rich and thick data in the context of
the review. The potential challenges related to the time and resource
constraints of this additional review process are acknowledged. Version
1 of the data thickness/richness assessment tool represents a
significant development in QES methodology, filling a critical gap in
tools for evaluating the richness of conceptual data and the level of
contextual detail in primary qualitative studies. It enhances the
transparency and rigor of the sampling process and offers valuable
insights for assessing the thickness and richness of data in primary
qualitative studies that addresses the review requestion, objectives and
context as specified in the review protocol. The authors invite feedback
from the research community to further test, refine and improve this
tool based on wider user experiences.