Use of Twitter to Assess Viewer Reactions to the Medical Drama, Code Black. Issue 3 (4th March 2018) - Hoffman, Beth L.; Rosenthal, Erica L.; Colditz, Jason B.; Mcgarry, Ryan; Primack, Brian A.
Abstract : Fictional medical television programs are popular with viewers and have been shown to influence health-related outcomes. We sought to systematically analyze real-time viewer discourse on Twitter related to the new medical drama, Code Black . We retrieved all Twitter posts (tweets) and metadata around the time of the airing of Code Black for four consecutive weeks. We developed a codebook using both content assessment of Twitter messages (tweets) and theory-based variables used in entertainment education analyses. We coded all tweets that occurred during the Eastern Standard Time (EST) airing of the program. Tweets that fell into at least one coding category were further analyzed by two independent researchers. We collected a total of 19, 369 tweets, with 54% of total tweets originating during the EST airing of the program. There were 1, 888 tweets that fit into one or more of six broad coding categories. Qualitative analysis revealed several key themes including real-life motivation to pursue health sciences careers based on the program, engagement regarding medical accuracy, and respect for the nursing profession. Examination of tweets related to Code Black provides insight into viewer discourse and suggests that Twitter may provide a vehicle for leveraging program engagement into real-life discussion and inquiry.