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From Silence into Language: Questioning the Power of Physician Illness Narratives

Overview of attention for article published in The AMA Journal of Ethic, May 2017
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82 tweeters

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24 Mendeley
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Title
From Silence into Language: Questioning the Power of Physician Illness Narratives
Published in
The AMA Journal of Ethic, May 2017
DOI 10.1001/journalofethics.2017.19.5.imhl1-1705
Pubmed ID
Abstract

Physicians' narratives of their own experiences of illness can be a kind of empathic bridge across the divide between a professional healer and a sick patient. This essay considers ways in which physicians' narratives of their own and family members' experiences of cancer shape encounters with patients and patients' experiences of illness. It analyzes ethical dimensions of physicians' narratives (such as those by Atul Gawande, Siddhartha Mukherjee, and Paul Kalanithi) and of reflective writing in medical education. It also compares illness narratives written by physicians-turned-patients to those written by patients without medical training in order to explore questions of who ultimately benefits from these narratives and whether these narratives can engender greater empathy between clinicians and patients.

Twitter Demographics

The data shown below were collected from the profiles of 82 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 7 29%
Student > Master 5 21%
Student > Doctoral Student 3 13%
Librarian 2 8%
Researcher 1 4%
Other 0 0%
Unknown 6 25%
Readers by discipline Count As %
Medicine and Dentistry 9 38%
Arts and Humanities 4 17%
Biochemistry, Genetics and Molecular Biology 1 4%
Social Sciences 1 4%
Nursing and Health Professions 1 4%
Other 0 0%
Unknown 8 33%