Annex A. Data Analysis: Content Analysis Approach
In brief, the process of content analysis began with a review of the whole of transcription data to gain a general understanding of the whole of the data content, which was then divided into smaller parts, or ‘meaning units’ which indicate concise ideas, actions, impacts, attitudes, context etc. These meaning units were then coded with descriptive labels based on themes that emerge from a review of all the ‘meaning units’. Connections between different codes were identified. Based on these connections, codes were then organised into larger categories, under which codes will pertain to the same issue fall. Categories can be further abstracted into themes. This method of analysis was used because it allows for both broad and specific findings to emerge through the analytic comparison at the coding, categorisation, and thematic grouping stage. Categories and themes were cross-referenced, which was important for this multisite project as nuanced differences arose within one theme/category from site to site. This analytical approach also protects against distortion and bias, as themes and codes are identified in consideration of all data collected, and therefore do not privilege any particular subgroup of participants. Finally, it allows for a close consideration of meaning units or codes which run across multiple themes, or fall outside the broader category and theme groupings, or are less closely related to the research questions.
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