A general model of conversational dynamics and an example application in serious illness communication

Autor: Margaret J. Eppstein, Laurence A. Clarfeld, Donna M. Rizzo, Robert Gramling
Rok vydání: 2021
Předmět:
FOS: Computer and information sciences
Palliative care
Computer science
Emotions
Social Sciences
Anger
Psychological Distress
Mathematical and Statistical Techniques
0302 clinical medicine
Sociology
Human–computer interaction
Medicine and Health Sciences
Psychology
030212 general & internal medicine
Function (engineering)
media_common
Verbal Communication
Computer Science - Computation and Language
Multidisciplinary
Mathematical Models
Communication
Palliative Care
Fear
Exchange of information
Dynamics (music)
030220 oncology & carcinogenesis
Physical Sciences
Medicine
Computation and Language (cs.CL)
Research Article
Markov Models
Critical Illness
Science
media_common.quotation_subject
Research and Analysis Methods
Markov model
03 medical and health sciences
Humans
Speech
Conversation
Behavior
Verbal Behavior
Biology and Life Sciences
Information flow
Models
Theoretical
Probability Theory
Probability Distribution
Communications
Health Care
Normative
Mathematics
Zdroj: PLoS ONE, Vol 16, Iss 7, p e0253124 (2021)
PLoS ONE
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0253124
Popis: Conversation has been a primary means for the exchange of information since ancient times. Understanding patterns of information flow in conversations is a critical step in assessing and improving communication quality. In this paper, we describe COnversational DYnamics Model (CODYM) analysis, a novel approach for studying patterns of information flow in conversations. CODYMs are Markov Models that capture sequential dependencies in the lengths of speaker turns. The proposed method is automated and scalable, and preserves the privacy of the conversational participants. The primary function of CODYM analysis is to quantify and visualize patterns of information flow, concisely summarized over sequential turns from one or more conversations. Our approach is general and complements existing methods, providing a new tool for use in the analysis of any type of conversation. As an important first application, we demonstrate the model on transcribed conversations between palliative care clinicians and seriously ill patients. These conversations are dynamic and complex, taking place amidst heavy emotions, and include difficult topics such as end-of-life preferences and patient values. We perform a versatile set of CODYM analyses that (a) establish the validity of the model by confirming known patterns of conversational turn-taking and word usage, (b) identify normative patterns of information flow in serious illness conversations, and (c) show how these patterns vary across narrative time and differ under expressions of anger, fear and sadness. Potential applications of CODYMs range from assessment and training of effective healthcare communication to comparing conversational dynamics across language and culture, with the prospect of identifying universal similarities and unique "fingerprints" of information flow.
Comment: 34 pages, 20 figures, submitted to PLOS One (in review)
Databáze: OpenAIRE
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