Difference between revisions of "Pecanac2018"
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|Author(s)=Kristen E. Pecanac | |Author(s)=Kristen E. Pecanac | ||
|Title=Combining conversation analysis and event sequencing to study health communication | |Title=Combining conversation analysis and event sequencing to study health communication | ||
− | |Tag(s)=EMCA | + | |Tag(s)=EMCA; Nursing; Health communication; Intensive care unit; Mixed methods |
|Key=Pecanac2018 | |Key=Pecanac2018 | ||
|Year=2018 | |Year=2018 | ||
|Language=English | |Language=English | ||
|Journal=Research in Nursing & Health | |Journal=Research in Nursing & Health | ||
+ | |Volume=41 | ||
+ | |Number=3 | ||
+ | |Pages=312–319 | ||
|URL=https://onlinelibrary.wiley.com/doi/abs/10.1002/nur.21863 | |URL=https://onlinelibrary.wiley.com/doi/abs/10.1002/nur.21863 | ||
|DOI=https://doi.org/10.1002/nur.21863 | |DOI=https://doi.org/10.1002/nur.21863 | ||
|Abstract=Good communication is essential in patient‐centered care. The purpose of this paper is to describe conversation analysis and event sequencing and explain how integrating these methods strengthened the analysis in a study of communication between clinicians and surrogate decision makers in an intensive care unit. Conversation analysis was first used to determine how clinicians introduced the need for decision‐making regarding life‐sustaining treatment and how surrogate decision makers responded. Event sequence analysis then was used to determine the transitional probability (probability of one event leading to another in the interaction) that a given type of clinician introduction would lead to surrogate resistance or alignment. Conversation analysis provides a detailed analysis of the interaction between participants in a conversation. When combined with a quantitative analysis of the patterns of communication in an interaction, these data add information on the communication strategies that produce positive outcomes. Researchers can apply this mixed‐methods approach to identify beneficial conversational practices and design interventions to improve health communication. | |Abstract=Good communication is essential in patient‐centered care. The purpose of this paper is to describe conversation analysis and event sequencing and explain how integrating these methods strengthened the analysis in a study of communication between clinicians and surrogate decision makers in an intensive care unit. Conversation analysis was first used to determine how clinicians introduced the need for decision‐making regarding life‐sustaining treatment and how surrogate decision makers responded. Event sequence analysis then was used to determine the transitional probability (probability of one event leading to another in the interaction) that a given type of clinician introduction would lead to surrogate resistance or alignment. Conversation analysis provides a detailed analysis of the interaction between participants in a conversation. When combined with a quantitative analysis of the patterns of communication in an interaction, these data add information on the communication strategies that produce positive outcomes. Researchers can apply this mixed‐methods approach to identify beneficial conversational practices and design interventions to improve health communication. | ||
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Latest revision as of 02:29, 4 October 2019
Pecanac2018 | |
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BibType | ARTICLE |
Key | Pecanac2018 |
Author(s) | Kristen E. Pecanac |
Title | Combining conversation analysis and event sequencing to study health communication |
Editor(s) | |
Tag(s) | EMCA, Nursing, Health communication, Intensive care unit, Mixed methods |
Publisher | |
Year | 2018 |
Language | English |
City | |
Month | |
Journal | Research in Nursing & Health |
Volume | 41 |
Number | 3 |
Pages | 312–319 |
URL | Link |
DOI | https://doi.org/10.1002/nur.21863 |
ISBN | |
Organization | |
Institution | |
School | |
Type | |
Edition | |
Series | |
Howpublished | |
Book title | |
Chapter |
Abstract
Good communication is essential in patient‐centered care. The purpose of this paper is to describe conversation analysis and event sequencing and explain how integrating these methods strengthened the analysis in a study of communication between clinicians and surrogate decision makers in an intensive care unit. Conversation analysis was first used to determine how clinicians introduced the need for decision‐making regarding life‐sustaining treatment and how surrogate decision makers responded. Event sequence analysis then was used to determine the transitional probability (probability of one event leading to another in the interaction) that a given type of clinician introduction would lead to surrogate resistance or alignment. Conversation analysis provides a detailed analysis of the interaction between participants in a conversation. When combined with a quantitative analysis of the patterns of communication in an interaction, these data add information on the communication strategies that produce positive outcomes. Researchers can apply this mixed‐methods approach to identify beneficial conversational practices and design interventions to improve health communication.
Notes