Movie dialogues as discourse data in the study of forecasting mechanisms in the delivery of medical bad news


  • Mei-hui Tsai National Cheng Kung University



bad news delivery, difficult communication, forecasting mechanism, macro discourse mechanism, natural discourse, scripted dialogue


Understanding the communication skills for delivering bad news, an important daily task for medical professionals, presents a challenge for most discourse researchers due to methodological and ethical dilemmas. Movie dialogues, in which difficult communication of life-and-death issues are fundamental ingredients in creating dramatic effects, are often adopted in medical education and thus potential data for study. By applying the concept of ‘forecasting mechanism’ in bad news delivery (Schegloff 1988 and Maynard 2003), this study examines bad news delivery events depicted in three movie clips. My analysis demonstrates (1) how forecasting, as a ‘macro conversation mechanism,’ is observed in both natural and artificial discourses; (2) what two subtypes of forecasting are identified in movie dialogues: forecasting that directs the interaction to a ‘recipient-leading-the-telling’ pattern, and forecasting that constructs the delivery as one with shared agency; and (3) how the two subtypes may facilitate the deliverers’ task by minimizing the conflicting perspectives with the recipients, ensuring the recipients’ orientation to the bad news, and freeing the deliverers from the pressure of being blamed. These findings implicate the possibility of applying movie clips in discourse research and medical education in regarding to conversational strategies for difficult communication.

Author Biography

Mei-hui Tsai, National Cheng Kung University

Mei-hui Tsai is an associate professor at National Cheng Kung University, Taiwan. Her research interests include medical discourse, Taiwanese for medical purposes, and the application of her research to medical education in Taiwan.



How to Cite

Tsai, M.- hui. (2014). Movie dialogues as discourse data in the study of forecasting mechanisms in the delivery of medical bad news. Communication and Medicine, 10(2), 165-175.




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