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Using Social Network Analysis to Investigate Positive EOL Communication.
Journal of Pain and Symptom Management 2018 August
CONTEXT: End-of-life (EOL) communication is a complex process involving the whole family and multiple care providers. Applications of analysis techniques that account for communication beyond the patient and patient/provider will improve clinical understanding of EOL communication.
OBJECTIVES: The objectives of the study were to introduce the use of social network analysis to EOL communication data and to provide an example of applying social network analysis to home hospice interactions.
METHODS: We provide a description of social network analysis to model communication patterns during home hospice nursing visits. We describe three social network attributes (i.e., magnitude, directionality, and reciprocity) in the expression of positive emotion among hospice nurses, family caregivers, and hospice cancer patients. Differences in communication structure by primary family caregiver across gender and time were also examined.
RESULTS: Magnitude (frequency) in the expression of positive emotion occurred most often between nurses and caregivers or between nurses and patients. Female caregivers directed more positive emotion to nurses, and nurses directed more positive emotion to other family caregivers when the primary family caregiver was male. Reciprocity (mutuality) in positive emotion declined toward day of death but increased on day of actual patient death. There was a variation in reciprocity by the type of positive emotion expressed.
CONCLUSION: Our example demonstrates that social network analysis can be used to better understand the process of EOL communication. Social network analysis can be expanded to other areas of EOL research, such as EOL decision making and health care teamwork.
OBJECTIVES: The objectives of the study were to introduce the use of social network analysis to EOL communication data and to provide an example of applying social network analysis to home hospice interactions.
METHODS: We provide a description of social network analysis to model communication patterns during home hospice nursing visits. We describe three social network attributes (i.e., magnitude, directionality, and reciprocity) in the expression of positive emotion among hospice nurses, family caregivers, and hospice cancer patients. Differences in communication structure by primary family caregiver across gender and time were also examined.
RESULTS: Magnitude (frequency) in the expression of positive emotion occurred most often between nurses and caregivers or between nurses and patients. Female caregivers directed more positive emotion to nurses, and nurses directed more positive emotion to other family caregivers when the primary family caregiver was male. Reciprocity (mutuality) in positive emotion declined toward day of death but increased on day of actual patient death. There was a variation in reciprocity by the type of positive emotion expressed.
CONCLUSION: Our example demonstrates that social network analysis can be used to better understand the process of EOL communication. Social network analysis can be expanded to other areas of EOL research, such as EOL decision making and health care teamwork.
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