Edited by Fergus Lyon, Guido Möllering and Mark N.K. Saunders
Chapter 26: A voice is worth a thousand words: the implications of the micro-coding of social signals in speech for trust research
While self-report measures are often highly reliable for field research on trust (Mayer and Davis, 1999; McEvily and Tortoriello, 2011), subjects often cannot complete surveys during real time interactions. In contrast, the social signals that are embedded in the non-linguistic elements of conversations can be captured in real time and extracted with the assistance of computer coding. This chapter seeks to understand how computer-coded social signals are related to interpersonal trust. Self-report measures of trust reflect an important and often reliable tool for researchers interested in trust (Gillespie, Chapter 20 in this volume; Lewicki and Brinsfield, Chapter 4 in this volume; Mayer and Davis, 1999; McEvily and Tortoriello, 2011). However, self-report measures require subjects to stop and think about how much they trust others or are trusted by others. Researchers are not able to use these methods when subjects cannot stop to fill out surveys in real time. In our setting, medical conversations or handoffs, one member of the pair must quickly receive critical information about a patient’s current medical condition and then immediately begin caring for that patient. The rushed and technical nature of these conversations also makes qualitative research difficult because most of the social signals embedded in these conversations are non-verbal. During a transition in care, such as those we observed, medical personnel rarely stopped to relay social information verbally, making transcripts of their conversations useless for retrieving social content.
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