1. Primary documents (transcripts, notes) were analyzed; all adaptations found were enumerated.
Allowed us to find all adaptations to the implementation process described
2. Adaptations were entered into a spreadsheet, and each FRAME component was described.
Allowed us to be able to break down and review reasons why adaptations occurred and their intended consequences
3. Adaptations within each practice and data source were de-duplicated.
Quantitizing adaptations allowed us to gather information on how often certain adaptation components occurred and grouped together. Since adaptations were collected through qualitative methods, there was inherent inconsistency in how much any adaptation was identified within data sources. De-duplication removed the issue of conflating number of mentions with number of adaptations as certain interviews could mention the same adaptation multiple times. Keeping de-duplication within each data source allowed us to understand how adaptations occur in each source.
4. Adaptations were compared between data sources.
Allowed us to make recommendations on which types of data collection to use and for what scenarios and intended outcomes
5. Adaptations and their components were enumerated across data sources.
Allowed us to see raw numbers of adaptations/adaptation components discovered in the data
6. Adaptation components were compared using three approaches: co-occurrence, k-means clustering, and taxonomic analysis.
Allowed us to see groupings of adaptations and adaptation components in order to be able to tell an implementation story