1754 A thematic analysis of Twitter posts pre and post-publication of CRASH-3 trial results using Blooms Digital Taxonomy. Examining how social media theories impact knowledge translation
Conclusion Eight overarching themes emerging from the pre-publication phase: emotion and feeling (90.21%), hashtagging (40.21%), tagging (26.09%), education-related information (10.87%), research-related information (9.78%), conference (7.61%), statement (3.26%) and poll (2.17%). 16 overarching themes emerged from the post-publication phase: hashtagging (56.06%), tagging (36.79%), article posting (23.05%), emotion and feeling (21.83%), education-related information (19.54%), summarising (14.42%), notification of results (9.57%), media outlook (7.01%), conference (6.74%), commenting (6.06%), open questions (5.26%), judging (4.99%), research-related information (4.04%), recommending (1.75%), quoting (1.48%) and comparing trials (0.40%). Some tweets applied to more than one category of themes. There was an increase in HOTS during the post-publication phase, signifying an increase in the cognitive dimensions of learning and the subjective internalisation of information. This was likely due to the increase in social media activity and information sharing following the release of trial outcomes. These findings support the role of Twitter, through the social capital model, in facilitating higher-order learning.