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Published on: November 29, 2024
T-CaST: an implementation theory comparison and selection tool
Sarah A Birken1, Catherine L Rohweder2, Byron J Powell3
1Department of Health Policy and Management, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, 1103E McGavran-Greenberg, 135 Dauer Drive, CB #7411, Chapel Hill, NC, 27599-7411, USA. birken@unc.edu.
Background:
Theories, models, and frameworks (TMF) are foundational for generalizing implementation efforts and research findings. However, TMF and the criteria used to select them are not often described in published articles, perhaps due in part to the challenge of selecting from among the many TMF that exist in the field. The objective of this international study was to develop a user-friendly tool to help scientists and practitioners select appropriate TMF to guide their implementation projects.
Methods:
Implementation scientists across the USA, the UK, and Canada identified and rated conceptually distinct categories of criteria in a concept mapping exercise. We then used the concept mapping results to develop a tool to help users select appropriate TMF for their projects. We assessed the tool's usefulness through expert consensus and cognitive and semi-structured interviews with implementation scientists.
Results:
Thirty-seven implementation scientists (19 researchers and 18 practitioners) identified four criteria domains: usability, testability, applicability, and familiarity. We then developed a prototype of the tool that included a list of 25 criteria organized by domain, definitions of the criteria, and a case example illustrating an application of the tool. Results of cognitive and semi-structured interviews highlighted the need for the tool to (1) be as succinct as possible; (2) have separate versions to meet the unique needs of researchers versus practitioners; (3) include easily understood terms; (4) include an introduction that clearly describes the tool's purpose and benefits; (5) provide space for noting project information, comparing and scoring TMF, and accommodating contributions from multiple team members; and (6) include more case examples illustrating its application. Interview participants agreed that the tool (1) offered them a way to select from among candidate TMF, (2) helped them be explicit about the criteria that they used to select a TMF, and (3) enabled them to compare, select from among, and/or consider the usefulness of combining multiple TMF. These revisions resulted in the Theory Comparison and Selection Tool (T-CaST), a paper and web-enabled tool that includes 16 specific criteria that can be used to consider and justify the selection of TMF for a given project. Criteria are organized within four categories: applicability, usability, testability, and acceptability.
Conclusions:
T-CaST is a user-friendly tool to help scientists and practitioners select appropriate TMF to guide implementation projects. Additionally, T-CaST has the potential to promote transparent reporting of criteria used to select TMF within and beyond the field of implementation science.
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