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Recommendations From the Twitter Hashtag #DoctorsAreDickheads: Qualitative Analysis
BACKGROUND: The social media site Twitter has 145 million daily active users worldwide and has become a popular forum for users to communicate their health care concerns and experiences as patients. In the fall of 2018, a hashtag titled #DoctorsAreDickheads emerged, with almost 40,000 posts calling...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652212/ https://www.ncbi.nlm.nih.gov/pubmed/33112246 http://dx.doi.org/10.2196/17595 |
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author | Sharma, Anjana Estelle Mann, Ziva Cherian, Roy Del Rosario, Jan Bing Yang, Janine Sarkar, Urmimala |
author_facet | Sharma, Anjana Estelle Mann, Ziva Cherian, Roy Del Rosario, Jan Bing Yang, Janine Sarkar, Urmimala |
author_sort | Sharma, Anjana Estelle |
collection | PubMed |
description | BACKGROUND: The social media site Twitter has 145 million daily active users worldwide and has become a popular forum for users to communicate their health care concerns and experiences as patients. In the fall of 2018, a hashtag titled #DoctorsAreDickheads emerged, with almost 40,000 posts calling attention to health care experiences. OBJECTIVE: This study aims to identify common health care conditions and conceptual themes represented within the phenomenon of this viral Twitter hashtag. METHODS: We analyzed a random sample of 5.67% (500/8818) available tweets for qualitative analysis between October 15 and December 31, 2018, when the hashtag was the most active. Team coders reviewed the same 20.0% (100/500) tweets and the remainder individually. We abstracted the user’s health care role and clinical conditions from the tweet and user profile, and used phenomenological content analysis to identify prevalent conceptual themes through sequential open coding, memoing, and discussion of concepts until an agreement was reached. RESULTS: Our final sample comprised 491 tweets and unique Twitter users. Of this sample, 50.5% (248/491) were from patients or patient advocates, 9.6% (47/491) from health care professionals, 4.3% (21/491) from caregivers, 3.7% (18/491) from academics or researchers, 1.0% (5/491) from journalists or media, and 31.6% (155/491) from non–health care individuals or other. The most commonly mentioned clinical conditions were chronic pain, mental health, and musculoskeletal conditions (mainly Ehlers-Danlos syndrome). We identified 3 major themes: disbelief in patients’ experience and knowledge that contributes to medical errors and harm, the power inequity between patients and providers, and metacommentary on the meaning and impact of the #DoctorsAreDickheads hashtag. CONCLUSIONS: People publicly disclose personal and often troubling health care experiences on Twitter. This adds new accountability for the patient-provider interaction, highlights how harmful communication affects diagnostic safety, and shapes the public’s viewpoint of how clinicians behave. Hashtags such as this offer valuable opportunities to learn from patient experiences. Recommendations include developing best practices for providers to improve communication, supporting patients through challenging diagnoses, and promoting patient engagement. |
format | Online Article Text |
id | pubmed-7652212 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-76522122020-11-13 Recommendations From the Twitter Hashtag #DoctorsAreDickheads: Qualitative Analysis Sharma, Anjana Estelle Mann, Ziva Cherian, Roy Del Rosario, Jan Bing Yang, Janine Sarkar, Urmimala J Med Internet Res Original Paper BACKGROUND: The social media site Twitter has 145 million daily active users worldwide and has become a popular forum for users to communicate their health care concerns and experiences as patients. In the fall of 2018, a hashtag titled #DoctorsAreDickheads emerged, with almost 40,000 posts calling attention to health care experiences. OBJECTIVE: This study aims to identify common health care conditions and conceptual themes represented within the phenomenon of this viral Twitter hashtag. METHODS: We analyzed a random sample of 5.67% (500/8818) available tweets for qualitative analysis between October 15 and December 31, 2018, when the hashtag was the most active. Team coders reviewed the same 20.0% (100/500) tweets and the remainder individually. We abstracted the user’s health care role and clinical conditions from the tweet and user profile, and used phenomenological content analysis to identify prevalent conceptual themes through sequential open coding, memoing, and discussion of concepts until an agreement was reached. RESULTS: Our final sample comprised 491 tweets and unique Twitter users. Of this sample, 50.5% (248/491) were from patients or patient advocates, 9.6% (47/491) from health care professionals, 4.3% (21/491) from caregivers, 3.7% (18/491) from academics or researchers, 1.0% (5/491) from journalists or media, and 31.6% (155/491) from non–health care individuals or other. The most commonly mentioned clinical conditions were chronic pain, mental health, and musculoskeletal conditions (mainly Ehlers-Danlos syndrome). We identified 3 major themes: disbelief in patients’ experience and knowledge that contributes to medical errors and harm, the power inequity between patients and providers, and metacommentary on the meaning and impact of the #DoctorsAreDickheads hashtag. CONCLUSIONS: People publicly disclose personal and often troubling health care experiences on Twitter. This adds new accountability for the patient-provider interaction, highlights how harmful communication affects diagnostic safety, and shapes the public’s viewpoint of how clinicians behave. Hashtags such as this offer valuable opportunities to learn from patient experiences. Recommendations include developing best practices for providers to improve communication, supporting patients through challenging diagnoses, and promoting patient engagement. JMIR Publications 2020-10-28 /pmc/articles/PMC7652212/ /pubmed/33112246 http://dx.doi.org/10.2196/17595 Text en ©Anjana Estelle Sharma, Ziva Mann, Roy Cherian, Jan Bing Del Rosario, Janine Yang, Urmimala Sarkar. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 28.10.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Sharma, Anjana Estelle Mann, Ziva Cherian, Roy Del Rosario, Jan Bing Yang, Janine Sarkar, Urmimala Recommendations From the Twitter Hashtag #DoctorsAreDickheads: Qualitative Analysis |
title | Recommendations From the Twitter Hashtag #DoctorsAreDickheads: Qualitative Analysis |
title_full | Recommendations From the Twitter Hashtag #DoctorsAreDickheads: Qualitative Analysis |
title_fullStr | Recommendations From the Twitter Hashtag #DoctorsAreDickheads: Qualitative Analysis |
title_full_unstemmed | Recommendations From the Twitter Hashtag #DoctorsAreDickheads: Qualitative Analysis |
title_short | Recommendations From the Twitter Hashtag #DoctorsAreDickheads: Qualitative Analysis |
title_sort | recommendations from the twitter hashtag #doctorsaredickheads: qualitative analysis |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652212/ https://www.ncbi.nlm.nih.gov/pubmed/33112246 http://dx.doi.org/10.2196/17595 |
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